J. Water Resource and Protection

J. Water Resource and Protection, 2010, 2, 1-92 Published Online January 2010 in SciRes (http://www.SciRP.org/journal/jwarp/).

Copyright © 2010 SciRes. JWARP

TABLE OF CONTENTS

Volume 2 Number 1 January 2010 Steady Rheological Properties of Rotating Biological Contactor (RBC) Sludge

B. ABU-JDAYIL, F. BANAT, M. AL-SAMERAIY……………………………………………………………………………….1

Groundwater Solution Techniques: Environmental Applications

S. M. PRAVEENA, M. H. ABDULLAH, A. Z. ARIS, K. BIDIN……………………………………………………………………8

The Combined Approach When Assessing and Mapping Groundwater Vulnerability to Contamination

M. V. CIVITA………………………………………………………………………………………………………………………14

Numerical Simulation of Pesticide Transport and Fate for Water Management in the Fucino Plain, Italy

M. PETITTA, M. A. MARIÑO……………………………………………………………………………………………………..29

Sublethal Antimony (III) Exposure of Freshwater Swamp Shrimp (Macrobrachium Nipponense): Effects on Oxygen Consumption and Hepatopancreatic Histology

J. L. YANG, T. J. HU, H. Y. LEE…………………………………………………………………………………………………42

Studying Heavy Metals in Sediments Layers along Selected Sites on the Lebanese Coast

N. NASSIF, Z. SAADE……………………………………………………………………………………………………………..48

The Challenges of Integrated Management of Mekong River Basin in Terms of People’s Livelihood

A. A. BELAY, S. M. A. HAQ, V. Q. CHIEN, B. ARAFAT..............................................................................................................61

The Analysis of Spring Precipitation in Semi-Arid Regions: Case Study in Iran

H. A. HASANIHA, M. MEGHDADI.................................................................................................................................................69

Colour Removal from Aqueous Solutions of the Reactive Azo Dye Remazol Black B Using the Immobilised

Cells (Shewanella Strain J18 143) – Cellulose-g.co-Monomer System

T. LI, J. T. GUTHRIE......................................................................................................................................................................77

Water Quality Parameters and Fish Biodiversity Indices as Measures of Ecological Degradation: A Case Study in Two Floodplain Lakes of India

D. K. MONDAL, A. KAVIRAJ, S. SAHA………………………………………………………………………………………….85

Journal of Water Resource and Protection (JWARP)

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J. Water Resource and Protection, 2010, 2, 1-7 10.4236/jwarp.2010.21001 Published Online January 2010 (http://www.scirp.org/journal/jwarp)


1

Steady Rheological Properties of Rotating Biological Contactor (RBC) Sludge

Basim ABU-JDAYIL1, Fawzi BANAT2, Mukheled AL-SAMERAIY2 1Department of Chemical & Petroleum Engineering, U.A.E. University, Al-Ain, U.A.E.

2Department of Chemical Engineering, Jordan University of Science and Technology, Irbid, Jordan E-mail: [email protected]

Received October 11, 2009; revised October 23, 2009; accepted December 8, 2009

Abstract The rheological characterization of sewage sludge at different steps of wastewater treatment is important since it allows predicting and estimating sludge behavior when submitted to almost all treatment and disposal operations. Rotating biological contactor (RBC) is being widely used for wastewater treatment, which is a biological treatment process following primary treatment. The rheological characterization of RBC sludge at different solid contents (TSS = 32.2 g/L–50.2 g/L) and temperatures (5–40 C) was carried out using a rota-tional viscometer. The RBC sludge showed a shear-thinning behavior, where the apparent viscosity de-creased rapidly with the shear rate reaching the limiting viscosity ( ) at the infinite shear rate. An exponen-tial relationship described the evolution of the limiting viscosity with the sludge TSS content. In addition, a dramatic increase in the limiting viscosity beyond a TSS concentration of 42.4 g/L has been observed. On the other hand, Bingham model described well the non-Newtonian behavior of sludge suspensions. It was clear that the yield stress is more sensitive than the Bingham viscosity for the variation in temperature and solid content. However, the rheological results revealed that both the limiting and Bingham viscosities have the same behavior with the TSS content and with the temperature. Keywords: Sludge Rheology, Activated Sludge, RBC Sludge, Bingham Fluid, Limiting Viscosity

1. Introduction Wastewater treatment process generates significant quantities of sludge from suspended solid in the feed, biomass generated by biological operations, and precipi-tates from added chemicals. Since solid concentration is often below 5%, large volumes of sludge must be han-dled. Sludge handling and disposal typically constitute 25 to 40% of the total cost of wastewater treatment plant [1]. Raw sludge is an unstable solids suspension that must be subjected to specific and complex treatment be-fore an environmentally acceptable product is obtained for final disposal. In a conventional activated sludge wastewater treatment plant, raw sludge is normally a mixture of the primary sludge and the excess biological sludge. In general, raw sludge has about 3-5% by weight total solids, among which about 70-80% is organic mat-ter. Due to its high organic solids content, raw sludge must be stabilized by digestion processes in order to ob-

tain a stable product that is easier to handle and to dis-pose. During the anaerobic digestion, heterotrophic bac-teria reduce about 40-50% of the organic compounds, especially those less complex and readily biodegradable. These compounds are normally insoluble and of colloidal form and may be classified as a complex mixture of nutri-ents, proteins, carbohydrates and organic acids. The bio-logical assimilation of these solids reduces slightly the total solid concentration of the sludge but certainly changes the rheological properties of the digested sludge [2].

The rheological characterization of sewage sludge at different steps of wastewater treatment is important since it allows predicting and estimating sludge behavior when submitted to almost all treatment and disposal operations. In reality, the knowledge of rheological properties helps in the selection of the most proper equipment and pro-cedure to be adopted. Rheological parameters are very important in sludge management, not only as designing parameters in transporting, storing, landfill and spreading

A-J. BASIM ET AL. 2 operations, but also as controlling ones in many treat-ments, such as stabilization and dewatering [3].

At the moment, rheological parameters are essentially used in sludges conditioning or for optimizing sludge consistency for the storage, spreading [4–6] and as indi-cators of sludge quality in aeration tanks [7]. In addition, Hasar et al. [8] have pointed out that the activated sludge viscosity has a major impact on pressure loss in pipes, transport phenomena near the membrane and sludge conditioning in next step.

The rheological characteristics of sludge depend on many factors such as source, solid concentration, tem-perature, and sludge treatment method [3,8,9] showed that rheological parameters are strongly dependent on the sludge type and total solid content. Battistoni et al. [10] has also observed that sludge rheology is strongly de-pendent on feed characteristics and conditions applied. Rotating Biological Contactor (RBC) is being widely used for wastewater treatment but there is an apparent lack of knowledge about the rheological properties of the produced sludge. A rotating biological contactor or RBC is a biological treatment process used in the treatment of wastewater following primary treatment, which removes the grit and other solids through a screening process fol-lowed by a period of settlement. The RBC process in-volves allowing the wastewater to come in contact with a biological medium at the rotating biological cofactors in order to remove pollutants from the wastewater. A rotat-ing biological contactor consists of a series of closely spaced, parallel discs mounted on a rotating shaft which is supported just above the surface of the waste water. Microorganisms grow on the surface of the discs where biological degradation of the wastewater pollutants takes place. The constant rotation of the disc causes mixing of the liquid, while the rotating disc surface alternately comes into contact between air and wastewater and thus acts as an aeration device for wastewater treatment. However, the basis of the practical use of the RBC is that the dissolved oxygen in the reactor did not have signifi-cance on treatment efficiency because sufficient amount of oxygen could be supplied during the air exposure cy-cle [11].

The objective of this work was to study the rheological characteristics of sewage sludge generated from Rotating Biological Contactors (RBC) technology. The effects of the temperature and the solid content on the rheological parameters of RBC sludge were investigated. Since the sludge samples were collected from the sludge tank that comes after the RBC unit, the rheological characteriza-tion presented here can be used to improve the storage and transportation system of the RBC sludge and the conditioning process.

2. Materials and Methods 2.1. Sludge Sample and Treatment Plant The Sludge samples were collected from a wastewater treatment plant located in the campus of Jordan Univer-sity of Science and Technology (JUST) and thereafter they were stored in a refrigerator at a temperature of 8 oC be-fore being used in the tests. The sludge samples were col-lected from the sludge tank that comes after the RBC unit.

Wastewater from the General Services Buildings, King Abdullah Hospital, Student and Staff Housing are collected and treated at the JUST wastewater treatment plant. The average biological oxygen demand (BOD) of wastewater is about 400 mg/L. The BOD of the treated wastewater is no more than 10 mg/L. Wastewater passed through several steps of treatment, including physical as well as biological steps. Six rotating biological contac-tors (RBC) are used in the bio-treatment step. The RBC contactors are made from plastic discs supported on a shaft passing perpendicularly through the center of each disc. The discs are slowly rotated at 1.25 rpm in a con-tour-bottomed tank containing the wastewater. As the surfaces of the discs are alternately exposed to the wastewater and air, biological growth forms these sur-faces. The biological growth will adsorb and assimilate the organic materials in solution. Air is also supplied to the wastewater in the tank to further increase the growth of bacteria. Excess biomass is sloughed off by shearing as the growth passes through the liquid and is kept in suspension by the mixing of the discs. The treated wastewater flows out of the tank into a clarifier to re-move the suspended solids. The clarified wastewater was chlorinated before being pumped to the university lake to be used for irrigation purposes. The remaining solids and water in the clarifier, i.e. sludge, is pumped to the sludge tank as shown in Figure 1. Sludge samples tested in this work were collected from the bottom of the sludge tank.

Figure 1. Block diagram for JUST wastewater treatment plant.

Bar Screen Pen Stock Fine Screen

RBC

Humus Tank

Sludge Tank

Solids RBC Sludge

1 2

1 Characterization Tank 2 Irrigation Tank

To the Univ.lake

Future Drying Beds


A-J. BASIM ET AL.


3

2.2. Viscometer The steady rheological properties of RBC sludge were measured using a concentric cylinder viscometer (Haake VT 500, MV1-system), which composed of an inner cylinder rotating in a stationary outer cylinder. The ra-dius of the rotating cylinder is 20.04 mm, the length of the cylinder is 60 mm, and the gap width is 0.96 mm. For every point on the flow curves a constant shear rate was used. After attaining a constant the shear-stress signal, which required about 30 seconds, the values of shear stress and viscosity were recorded. The viscometer was thermostatically controlled with a water circulator (Ha-ake D8) at the desired temperature.

Experiments were performed to characterize the rheological behavior of RBC sludge using flow curve meas-urements. A fresh sample was loaded into the annular gap of the concentric cylinder viscometer. The apparent viscosity of RBC sludge as a function of shear rate was measured.

3. Results and Discussions 3.1. Effect of Total Suspended Solids The rheological properties of sludge material can be sig-nificantly affected by variables such as shear rate, tem-perature and total solids. In many cases, solid concentra-tion was the most important parameter affecting the sludge rheology [8,12,13]. Sewage contains solid materi-als like bones, stones, wood, rages, etc, which make pumping of sewage difficult. The percentage of solids in sewage gives an indication of the concentration and physical state of its principal constitutes. The combina-tion of inorganic and organic solids is called “total sus-pended solids” [14]. In this work, the effects of total suspended solids (TSS=32.2 g/L-50.2 g/L) and temperature (5-45 oC) on the rheological behavior of RBC sludge were investigated.

200 600 10000 400 800 1200

Shear rate (1/s)

10000

30000

0

20000

40000

She

ar S

tres

s (m

Pa)

100

300

0

200

400

App

aren

t Vis

cosi

ty (

mP

a s)

T = 25 CTSS= 50.2 g/L

Shear stress

Apparent viscosity

limiting viscosity

Figure 2. Typical rheological behavior of RBC sludge at TSS of 50.2 g/L and T of 25 C.

Figure 2 shows the typical rheological behavior of RBC sludge at TSS = 50.2 g/L and temperature of 25 C. The shear stress ( ) was measured as the shear rate ( )

was increased from 11.7 to 1169 1s . As illustrated in Figure 2, the RBC sludge showed a shear-thinning be-havior, where the apparent viscosity ( /app ) de-

creased rapidly as the shear rate was increased, and be-came constant at higher shear rate reaching the limiting viscosity ( ) at the infinite shear rate. The limiting

viscosity was associated with the optimal orientation of the sludge in the direction of flow [12].

The limiting viscosity has been widely used as a pa-rameter for characterizing sludge rheology [9,12,15]. The properties of suspended solids, such as particle size, shape and density, particle-particle interaction, floccula-tion ability, etc, all have effects on the rheological prop-erties of sludge [12,15]. Figure 3 shows that the limiting viscosity was greatly affected by the TSS content of the RBC sludge, which is in agreement with several other types of biological sludges [9,12,15]. An exponential relationship always describes the evolution of the limit-ing viscosity (rheological parameter) with the sludge TSS content, as also observed in this study. It has been indicted that the increase of the limiting viscosity of ac-tivated sludge was due to the increased interactions be-tween the flocs at increased TSS content [9]. Figure 3 also shows a dramatic increase in the limiting viscosity beyond a TSS concentration of 42.4 g/L. In this case two different exponential equations were needed to describe the dependence of the limiting viscosity on the whole range of TSS content. The point of the strongest viscos-ity increase can be determined from the intersection of the two regression lines for low and high ranges of sludge solid content. This point is shown in Figure 3 as critical TSS.

34 38 42 46 5032 36 40 44 48 52

TSS (g/L)

10

30

50

0

20

40

60

Lim

iting

Vis

cosi

ty (

mP

a s)

Critical TSS

T = 5 C

T = 25 C

T = 45 C

Exponential model

Figure 3. Limiting viscosity as a function of TSS for different temperatures.

A-J. BASIM ET AL. 4

275 285 295 305 315270 280 290 300 310 320

Temprature (K)

10

30

50

0

20

40

60

Lim

iting

Vis

cosi

ty (

mP

a s)

TSS = 32.2 g/L

TSS= 37.3 g/L

TSS = 42.4 g/L

TSS = 47.5 g/L

TSS = 50.2 g/L

Arrhenius equation

Figure 4. Limiting viscosity of RBC sludge as a function of temperature for different TSS. 3.2. Effect of Temperature Moreover, temperature is another important factor af-fecting the limiting viscosity of RBC sludge. Figure 4 shows that the limiting viscosity decreased by increasing the temperature. The thermal motion of particles is more violent at higher temperature, and then the network strength between the particles is weekend, resulting in a decrease in viscosity [12]. The influence of temperature on the limiting viscosity can be described well by an Arrhenius type equation (see Figure 4):

aE

RTKe (1)

where is the limiting viscosity, K is pre-exponential

constant, T the absolute temperature, R is the universal gas constant and is the limiting viscosity activation

energy. Table 1 shows the regressed values of K and

at different TSS content. It is clear that there is small increase in with increasing the total solids. The low

value of activation energy (0.094-0.127 ) sug-gested low dependence of limiting viscosity of the RBC sludge on the temperature. The high regression coeffi-cients of the above equation, which varied from 0.982 to 0.997, suggested that the Arrhenius equation was able adequately to describe the relationships between the rheology of RBC sludges and temperature.

aE

aE

aE

molJ /

3.3. Rheological Modeling Figure 5 illustrates the flow curves of RBC sludge at different TSS values. For all investigated TSS and tem-peratures, the sludge samples showed shear-thinning behavior with a yield stress. Bingham model (Equation 2) has been used to describe the non-Newtonian behavior of sludge suspensions [3,12,13]:

o B (2)

2 3 4 5 6 7 8 9 2 3 4 5 6 7 8 9 210 100 1000

Shear rate (1/s)

10

30

0

20

40

She

ar S

tres

s (P

a)

T = 25 C

TSS=32.2 g/L

TSS=37.3 g/L

TSS=42.4 g/L

TSS=47.5 g/L

TSS=50.2 g/L

Bingham model

Figure 5. Flow curves of RBC sludge at different TSS.

Table 1. Regressed parameters of Equation 1.

TSS ( /g L ) K ( ) .mPa s aER ( K ) 2R

32.2 292 0.0113 0.997

37.3 442 0.0118 0.996

42.4 554 0.0119 0.983

47.5 1730 0.0141 0.982

50.5 3267 0.0153 0.995

where is the shear stress, o is the yield stress; B

is the Bingham viscosity and is the shear rate. In the

sludge samples the yield stress must be reached before flow starts. Its presence is due to the resistance solid par-ticles oppose to deformation, until the applied stress ex-ceed the yield strength of the solid phase and that the sludge show flow. It is commonly admitted that the yield stress of suspensions is linked to the existence of an in-terconnected three dimensional network of flocs. The value of the yield stress corresponds to the stress needed to be applied to overcome the cohesion Van der-Waals forces and induce the flow of the suspension [15].

Figure 5 also shows the flow curves of RBC sludge for different values of TSS fitted to the Bingham model; while the model parameters obtained by non-linear re-gression for different TSS and temperatures are reported in Table 2. The high regressions coefficients (around 0.99) indicated that the Bingham model describe ade-quately the rheological behavior of RBC sludges under different conditions. As shown in Table 2, both the yield stress and Bingham viscosity decreased as the tempera-ture was increased from 5 to 45 oC. However, at a given temperature when the solid content was increased the Bingham parameters ( o , B ) were found to increase

accordingly. The obtained yield stress increased signifi-cantly from 59 mPa at TSS=32.2 g/L and T=45 oC to 5520 mPa at TSS=50.2 glL and T=5 oC. On the other hand, the Bingham viscosity exhibited less pronounced


A-J. BASIM ET AL.


5

Table 2. Regressed parameter values of Bingham model used to describe the rheological data for different tempera-tures and total solid content.

TSS ( /g L ) Temperature

( K )

o

( ) mPaB

( mPa s )

278.15 1527 11.0

288.15 1094 10.2

298.15 697 9.6

308.15 332 8.7

32.2

318.15 59 7.8

278.15 2552 14.0

288.15 2123 12.9

298.15 1674 11.2

308.15 1235 10.4

37.3

318.15 929 9.4

278.15 3579 18.1

288.15 3031 15.5

298.15 2630 13.5

308.15 2199 11.9

42.3

318.15 1701 11.4

278.15 5033 29.7

288.15 4432 27.7

298.15 3794 22.0

308.15 3351 20.0

47.5

318.15 2980 17.3

278.15 5520 43.0

288.15 4864 35.9

298.15 4354 30.0

308.15 3865 26.3

50.5

318.15 3302 23.5

34 38 42 46 5032 36 40 44 48 52

TSS (g/L)

1000

3000

5000

0

2000

4000

6000

Yie

ld S

tres

s (m

Pa)

T = 5 C

T = 15 C

T =25 C

T = 35 C

Exponential model

Figure 6. Dependence of the yield stress on TSS content.

Table 3. Exponential parameters of the correlation between the yield stress and the sludge TSS content.

Temperature (C) A B 2R

278.15 167.45 0.071 0.982

288.15 89.58 0.082 0.970

298.15 35.55 0.098 0.952

308.15 7.00 0.130 0.921

318.15 0.19 0.204 0.835


TSS ( /g L ) C ( ) mPa yER ( K ) 2R

32.2 124.3 10 0.077 0.887

37.3 63.2 10 0.025 0.991

42.4 55.6 10 0.018 0.987

47.5 52.0 10 0.013 0.998

50.5 51.8 10 0.013 0.996

evolution, where it increased from 7.8 mPa s at TSS

=32.2 g/L and T=45 oC to 43 at TSS=50.2 glL and T=5 oC. It is clear that the yield stress is more sensi-tive than the Bingham viscosity for the variation in tem-perature and solid content.

smPa

An exponential law (Equation 3) can describe the rela-tionship between the yield stress and the TSS content on the entire range of TSS investigated, see Figure 6:

( [ ])B TSSo Ae (3)

Table 3 shows the values obtained form the applica-tion of the exponential model for different sludge tem-peratures. It is clear that the deviation from the exponen-tial behavior increased with increasing the temperature.

In addition, the effect of temperature on the yield stress of the RBC sludge can be also well described by the Arrhenius equation type, see Figure 7:

yE

RTo Ce (4)

where C is the pre-exponential constant, and is the

yield stress activation energy. Table 4 shows the re-gressed parameters of Equation 4.

yE

The evolution of the Bingham viscosity ( B ) with the

TSS content followed the same trend of the limiting vis-cosity, where a dramatic increase in the Bingham viscos-ity beyond a TSS concentration of 42.4 g/L was observed, see Figure 8. Several authors [16,17] have shown that on a weak TSS variation range (about 4 g/L of variation),

A-J. BASIM ET AL. 6 the evolution of Bingham parameters can be described by a linear law. The particle-particle interactions increase with TSS content and thus increase drastically the Bing-ham viscosity as well as the rheological properties of sludge [16].

On the other hand, the Arrhenius type equation well cor-related the relationship between the Bingham viscosity

275 285 295 305 315270 280 290 300 310 320

Temprature (K)

0

1000

2000

3000

4000

5000

6000

7000

Yie

ld S

tres

s (m

Pa)

TSS = 32.2 g/L

TSS= 37.3 g/L

TSS = 42.4 g/L

TSS = 47.5 g/L

TSS = 50.2 g/L

Exponential model

Figure 7. Dependence of the yield stress on the temperature.

34 38 42 46 5032 36 40 44 48 52

TSS (g/L)

10

30

50

0

20

40

Bin

gham

Vis

cosi

ty (

mP

a s)

TSS-critical

T = 5 C

T = 25 C

T = 45 C

Exponential model

Figure 8. Dependence of the Bingham viscosity of the TSS content.

275 285 295 305 315270 280 290 300 310 320

Temprature (K)

10

30

50

0

20

40

60

Bin

gham

Vis

cosi

ty (

mP

a s)

TSS = 32.2 g/L

TSS= 37.3 g/L

TSS = 42.4 g/L

TSS = 47.5 g/L

TSS = 50.2 g/L

Exponential model

Figure 9. Dependence of the Bingham viscosity of the temperature.


TSS ( /g L ) D ( mPa s ) BER ( K ) 2R

32.2 117 0.008 0.987

37.3 234 0.010 0.992

42.4 480 0.012 0.969

47.5 1512 0.014 0.977

50.5 2870 0.015 0.989

and the temperature, see Figure 9:

BE

RTB De (5)

where D is the pre-exponential constant, and is the

Bingham viscosity activation energy. Table 5 shows the regressed parameters of Equation 5. As evident from Tables 4 and 5, the activation energy for yield stress de-creased with solid content, in contrast, the activation energy of Bingham viscosity increased. However, the activation energies of both parameters were equal at TSS content above the TSS-critical.

BE

The results here comply with those of several authors who have shown an exponential [17–20] or power [10] law between sludge TSS content and Bingham parameters.

On the other hand, the activation energy of the Bing-ham viscosity varied between 0.0665 /J mol at TSS= 32.2 g/L and 0.125 /J mol at TSS=50.2 g/L, which was approximately similar to the activation energy of the limiting viscosity. Results revealed that both the limiting and Bingham viscosities have the same behavior with the TSS content and with the temperature. 4. Conclusions In this work, the dependence of rheological properties of RBC sludge on solid content (TSS) and temperature has been experimentally investigated. Results revealed that the RBC sludge behaved like a Bingham fluid. The lim-iting viscosity and the Bingham parameters have been used to characterize the RBC sludge. An exponential relationship was employed to describe the evolution of the limiting viscosity with the sludge TSS content, and the dramatic increase in the limiting viscosity beyond a TSS concentration of 42.4 g/L. The influence of tem-perature on the limiting viscosity has been well described by an Arrhenius type equation. It has been found that both the yield stress and Bingham viscosity decreased as the temperature was increased from 5 to 45 oC. However, at a given temperature when the solid content was in-creased the Bingham parameters ( o , B ) found to in-

crease accordingly. It was clear that the yield stress was more sensitive than the Bingham viscosity for the varia-tion in temperature and solid content.


A-J. BASIM ET AL.


7 5. References [1] D. Sundstorm and H. Klei, “Wastewater Treatment,”

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[15] I. Seyssiecq, J. H. Ferrasse, and N. Roche, “State-of-the- art: Rheological characterization of wastewater treatment sludge,” Biochemical Engineering Journal, Vol. 16, pp. 41–56, 2003.

[16] C. F. Forster, “The rheological and physico-chemical characteristics of sewage sludges,” Enzyme Microbial Technol, Vol. 30, pp. 340–345, 2002.

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J. Water Resource and Protection, 2010, 2, 8-13 doi:10.4236/jwarp.2010.21002 Published Online January 2010 (http://www.scirp.org/journal/jwarp)


Groundwater Solution Techniques: Environmental Applications

Sarva Mangala PRAVEENA1*, Mohd Harun ABDULLAH1, Ahmad Zaharin ARIS2, Kawi BIDIN1 1School of Science and Technology, Universiti Malaysia Sabah, Kota Kinabalu, Sabah, Malaysia.

2Department of Environmental Sciences, Universiti Putra Malaysia, Selangor, Malaysia E-mail: [email protected]

Received September 29, 2009; revised October 29, 2009; accepted November 14, 2009

Abstract Groundwater models provide a scientific tool for various groundwater studies which include groundwater flow, solute transport, heat transport and deformation. However, without a good understanding of a model, modeling studies are not well designed or the model does not represent the natural system which being mod-eled long term effects may results. Thus, this review has focused and reviewed the types of solution tech-niques in terms of advantages and limitations. The findings are vital to improve the model conceptualization and understanding of the uncertainty in model results. On the same hand, it acts as guide and reference to groundwater modeler, reduces the time spent in understanding the solution technique and complexity of groundwater models, as well as focus ways to address the groundwater problems and deliver modeling out-put more efficiently. Keywords: Groundwater Models, Solution Techniques, Advantages, Limitations

1. Introduction According to [1], groundwater modeling covers dif-ferent aspects of the system behavior. Groundwater modeling studies have four potential relevance proc-esses which include groundwater flow, solute transport, heat transport and deformation. According [2,3], groundwater modeling has turn out to be a crucial tool in decision making and planning in environmental management. Decision making and planning processes in environmental management are associated with wa-ter resource allocation, complex development and re-quiring multidisciplinary information for evaluating their effects on a social, economic and environmental level [4]. Generally, most of the groundwater modeling studies are conducted using either deterministic models, based on precise description of cause-and-effect or stochastic models based on the probabilistic nature of a groundwater system [5,6]. The main components of groundwater modeling are selecting the natural sys-tem which the model is designed, creating the concep-tual representing the natural system, models represent-ing the controlling mechanism, solution of the model, calibration and validation of the model along with simulation [7,8].

There are enormous amount of groundwater models

to study the cause and effect or the probabilistic nature of a groundwater system. It is an ad-vantage to classify them in groups based on criterias such as aquifer type, techniques used, type of aquifer simulated and the di-mension of the problem [9]. [10] stated that the classi-fication of groundwater models can be done based on model objectives, processed modeled, physical system characteristics modeled and mathematical approaches. According to International Ground Water Modeling Center (IGWMC), there are many various manners in groundwater models classifications (flow, media, transport, temperature, phases, chemical reaction, disper-sion, thermodynamics, fractured rock, vapor transport, variable saturated, saturated) that a specific and sys-tematic classification cannot be developed. A detailed explanation of these classifications can be found in [10].

Various solution techniques are a crucial component in groundwater models [6]. Solution techniques in groundwater modeling activities are to follow a multi- level approach. Multi-level approach involves data collection of groundwater flow and mass, contaminant transport and advection-dispersion equations, evalua-tion of the data and final decision to select the model. An understanding of various solution techniques is vital due to complexity in groundwater modeling and

S. M. PRAVEENA ET AL. 9 universal importance perspective. Era of numerous groundwater models development has been stimulated by high advance of computer technology and pro-gramming techniques. Yet the current numerous model development and groundwater complexity often leave those involve in groundwater studies spend a lot of time in understanding the solution techniques. This increased time resulted in less time spent in under-standing the system. Thus, there are many gaps in our understanding of groundwater modeling which limits our capacity. Various groundwater models develop-ment have exposed with many reviews on the favors and disfavors of these models [6,8,11]. However, there are limited reviews on the solution techniques of these groundwater models although they are crucial compo-nents utilized in groundwater modeling. While a num-ber of these solution techniques are focused on the types of models and applications in real world [11–14], a lack of quantitative information on the advantages and limitations of these tools impedes the use of these tools for real-world applications.

An understanding of various solution techniques is crucial due to complexity in groundwater modeling. This work was intended primarily as a guide and ref-erence for the practitioner who is trying to simulate groundwater in their site of interest. This attempt is a way to lessen the time spent in understanding the solu-tion technique and complexity of groundwater models, as well as focus ways to address the groundwater problems to render modeling output more effectively. The conceptual framework of the review was based on the types of solution techniques available in ground-water studies. An assessment of mutual understanding, advantages and limitations of all the solution tech-niques is applied to all kind of groundwater modeling studies and not limited to any particular purpose or equations. It is an attempt to reduce the time spent in understanding the solution technique and complexity of groundwater models and represent focus ways to address the groundwater problems and render modeling output more effectively. 2. Various Solution Techniques Assessment According to [8], the term model has different meanings. Combinations of all model components are suitable for groundwater model. However, term model is also used in a part of various solution techniques. Thus, the term model will also be used in a part of solution technique in this review. Numerous sophisticated solution techniques or model are currently available to overweigh the accu-racy of the groundwater system representation [15]. The groundwater solution techniques comprise from simple to complex [6]. According to [2] until early 1970s, physical and analog models were widely used as mathe-

matical models solving groundwater problems. As groundwater modeling techniques boosted with extensive computer programmings, various solution techniques have been developed to solve the systems of mathemati-cal equations. The simplest classification was done by [12] and [14], where the solution techniques are divided into two broad groups namely physical models and mathematical or numerical models. Solution techniques grouping done by [11] listed that groundwater models are divided into four broad groups which are porous me-dia, analog, electric analog and digital models. Along with the advent of computers, groundwater modeling has focused on the numerical models expressing the groundwater flow and transport studies. However, these models (analytical, physical, analog, porous, empirical and mass balance) are still needed to investigate and validate new models. The requirements are to examine and analyze whether certain assumptions underlie the new models are valid. The conceptual framework of this review was based on the types of solution techniques listed by [8] as showed in Figure 1. 3. Solution Techniques Evaluations It is very important to have strong understanding with a model in order to know the advantages and limitations of each solution techniques. Perspectives of advantages and limitations of the solution techniques were evaluated in this review. 3.1. Analytical Models Analytical models are the rapid way to analyze physical characteristics and conceptual behavior of groundwater system compare to other models. This is because it uses an exact analytical solution for specific field applications. On the other hand, analytical models are only limited to steady and uniform groundwater problems involving

Figure 1. Types of groundwater models.


S. M. PRAVEENA ET AL.


10

small parts of study area and bulky to transport problems. Table 1 presents other points of advantages and limita-tions of analytical models. 3.2. Porous Media Models Porous media or bench-scale models belong to the group of hydraulic models which has been widely used in hy-draulic engineering. Porous media models are suitable to use at any dimensionality, any type of groundwater flow and transport problems (variable saturated, heterogeneity, anisotropy, phreatic, steady, unsteady, advection, disper-sion, sorption, decay and reactions). Information about porous media is presented in Table 2. 3.3. Analog Models In terms of demonstration and education tools, analog models are still widely used for groundwater studies. Analog models (viscous fluid, membrane and lumped models) are not suitable for groundwater transport. The models have limited capability to involve with advection, dispersion, sorption, decay and reactions studies in

Table 1. Applicability of analytical models.

Model type Analytical model

Advantages

Simple [6,16] Economical/ inexpensive [2,3,6] Rapid way to analyze physical characteristics of

groundwater [2,3,20] More efficient than other models [6,9,16] Can form useful complements to any numerical

models [25,26] Can used either for verification or being part of

numerical models [16,17] An important and useful tool for estimating fate

and transport parameters from field or laboratory data [16,17]

Provide more insight into conceptual behavior of the groundwater system [3]

Does not introduce errors due to the numerical diffusion and approximation by the finite differ-ence model [12]

Limitations

An exact analytical solution may outweighed by the errors introduced by simplifying assumptions of complex field environment [9,10]

Complex and cumbersome in transport problems [2]

Limited to cases with steady and uniform flow problems [2]

Relatively simple initial and assumptions in boundary conditions. Hydrogeological boundary conditions must be idealized to fit the model [2]

Professional judgment and experience in field application are needed to apply the analytical model [2]

Suitable to solve groundwater problems involving small parts of aquifer systems or small area extent [9,18]

Could not handle spatial/temporal variations in groundwater system [18]

groundwater. The views on advantages and disadvan-tages of analog models are detailed in Table 3. 3.4. Empirical Models Empirical models are useful to use when detailed site specific data are lacking or impractical situation to simu-late fine-scale processes. Lack of understanding in the

Table 2. Applicability of porous media models.

Model type Porous media model

Advantages

Relatively straightforward and simple [19, 20]

Allow the study of special aspects of groundwater flow and transport under al-most natural condition [19,20]

Useful to enhance site characterization and features [9]

Good demonstration and education tools for students [4,7,20]

Obeys laws that govern other physical systems including laminar flow of fluids and heat [4,6,7]

Good starting point for groundwater mod-eling beginners [4]

Limitations

Capillary rise takes place in such models is far larger than that which actually occurs in a real field situation [13]

Difficult to visual and identify the water table [7,13]

Time consuming and prohibitively costly [5]

Table 3. Applicability of analog models.

Model type Analog model

Advantages

Illustrative and still widely used for demon-stration purposes of groundwater flow [4,21]

Versatility and can readily study a variety of aquifer conditions [8]

True for groundwater flow without natural recharge if the weight of the membrane is small [4]

Inexpensive tools to use to visualize groundwater stress [4]

Useful tool to help the inexperienced earth scientist to understand about groundwater hydraulics [4]

Solves problems concerning the phreatic surface for transient and steady flow con-ditions[4,7,21]

Limitations

A good care is required in the model con-struction because flow rate varies with the cube width [4,7]

Temperature is also another factor need to be focused [4,5]

Limitation on applications involving nonlinear conditions of varying transmis-sivity in unconfined aquifers and two-fluid flow problems [7,13]

Also limited applications in groundwater lowering in construction field [21]

Electric potential is unaffected by gravity, therefore it requires adjustments [22]

S. M. PRAVEENA ET AL. 11 processes involve in study area, these models can be misused or misunderstood as the models are easy to em-ploy as well as lumping process together will mask the disadvantages of these models. Table 4 summarizes the information on empirical models. 3.5. Mass Balance Models Mass balance model is also known as the black box or single-cell model. It is also a numerical model in its sim-plest form. In mass balance models, the averaging of an entire area is a crude approximation. Evaluation of field data is only involves in and out fluxes. Table 5 details the information of mass balance models.

Table 4. Applicability of empirical model.

Model type Empirical model

Advantages

Impact the accuracy of the model predictions [23,24]

Suitable to use when detailed site specific data are lacking and appropriate when it is imprac-tical to simulate fine-scale processes [4]

Representing an entire groundwater problem employs a series of physical laws, empirical laws and conservative assumptions to represent the problem of interest [1,4,23,24]

A good alternative method [23,24] Provide useful predictions without the costly

calibration time [23,24]

Limitations

Lack of understanding of process involved and only a temporary solution to assist analysis [7, 24]

Can be misused and misunderstood because they are easy to employ [4]

Lumping processes together will mask the limitations of these models [7]

Table 5. Applicability of mass balance model.

Model type Mass balance model

Advantages

The simplest form of numerical model. The best fitted in numerical modeling [4,14]

Very useful which leads to an examination of the global mass balance [14]

Easy to use [4,14] Efficiently aid in the analysis of the impact of

the management options [14] Suitable to use when detailed site-specific data

are lacking or impractical situation to simulate fine-scale processes [14]

An important part in more complexes of nu-merical models [8]

Limitations

Lack of understanding of the processes in-volved [4]

Acts as a temporary solution to aid analysis [4,14]

Can be misused or misunderstood because they are easy to use [25]

Applicable only in limited circumstances and masked by lumping process together [10,14]

3.6. Numerical Models Among of the solution techniques assessment, numerical models were found to have more advantages over other solution techniques. They are such as it solves both sim-ple and complex groundwater problems, capable to used almost of any type of groundwater system and impose no restrictions on the initial conditions, boundary types as well as characteristics of the groundwater. The most ad-vantage in numerical models is that the models utilize the latest advances in computer technology without writing any computer codes. Numerical models which employ the latest computer technology also have limitations in terms of accuracy, errors and codes. Accuracy of nu-merical output mainly depends on the availability of soil hydraulic information, errors in numerical dispersion are hard to be identified as well as special codes are need for specific groundwater problem (Table 6).

Table 6. Applicability of numerical model.

Model type Numerical model

Advantages

Employed with the latest and recent advances in computer technology [4,5,11,13]

Solves both simple and complex groundwater problems [4,7,13,26,27]

Dominated the complex study of groundwater problems as it solves both simple and complex one, two or three dimensional problems [4,7,13, 15]

Capable to simulate almost any type of ground-water situation [5,7,17]

Well suited to exploring hypothetical scenarios [15,27]

Can easily handle spatial or temporal variations of groundwater system [6,11]

Impose no restrictions on the initial conditions, boundary types, characteristics of the ground-water or investigated solute [5,10]

Computer programs for most groundwater problems are available easily and the users can apply relevant computer programs without writ-ing any computer code [4,7,13,26,27]

Limitations

Time consuming for data collection and input [4,7,11,13]

Require much information to characterize the system [28]

Expensive models [28] Special codes are required for specific problems,

such as density-dependent flow and coupled saturated unsaturated flow [15,27]

Accuracy of the results of numerical models mainly depends on the availability of informa-tion about the hydraulic properties of the subsoil [28]

Errors in numerical dispersion [28] Uncertainty of the model predictions is hard to

quantify [28]




12

4. Conclusions This review has focused and reviewed the types of solu-tion techniques available in groundwater modeling stud-ies. Assessment of six solution techniques namely ana-lytical, porous media, analog, empirical, mass balance and numerical models was done to give a clear under-standing of each solution techniques. Advantages and limitations of all the solution techniques were listed and analyzed. Analytical, porous media and mass balance models are simple and appropriate to use in groundwater modeling studies. In terms of demonstration and educa-tion tools, porous media and analog models are still widely used for groundwater studies. Empirical and mass balance models are useful to use when detailed site spe-cific data are lacking or impractical situation to simulate fine-scale processes. The most benefit of numerical models is it utilizes the latest advances in computer technology without writing any computer codes as well as solves both simple and complex of any groundwater problems. On the other hand, limitations of analytical models are only limited to steady and uniform ground-water problem involving small parts of study area. Po-rous media and numerical models face time consuming for data collection and expensive as their constraints in the applications. Empirical and mass balance models face lack of understanding in the processes involve in study area and can be misused or misunderstood. In the view of analog models, they are not suitable for ground-water transport. Moreover, errors in numerical dispersion are hard to be identified as well as special codes are need for specific groundwater problems. As a final note, it is important to point out that a good understanding of vari-ous solution techniques act as guide and reference to groundwater modeler. Besides, it reduces the time spent in understanding the solution technique and complexity of groundwater models, as well as focus ways to address the groundwater problems and render modeling output more effectively. 5. Acknowledgement The first author gratefully acknowledges the support by National Science Fellowship (NSF) Scholarship under sponsorship of Ministry of Science, Technology and In-novation (MOSTI), Malaysia for her doctoral study. Sincere appreciation is also extended to the reviewers for their helpful comments and suggestions which have im-proved the quality of this paper. 6. References [1] L. W. Canter, D. M. Fairchild, and R. C. Knox, “Ground

water quality protection,” CRC Press, Boca Raton, Flor-

ida, 1988.

[2] J. Bear, M. S. Beljin, and R. R. Ross, “Fundamentals of groundwater modeling,” United States Environmental Protection Agency, 1992.

[3] P. K. M. van der Heijde, “Quality assurance in computer simulations of groundwater contamination,” Environ-mental Software, Vol. 2, pp. 19–25, 1987.

[4] E. Manoli, P. Katsiardi, G. Arampatzis, and D. Assima-copoulos, “Comprehensive Water Management Scenarios for Strategic Planning,” Global NEST Journal, Vol. 7, pp. 369–378, 2005.

[5] S. M. Praveena, M. H. Abdullah, A. Z. Aris, and L.C. Yik, “A brush up on seawater intrusion models,” in the Pro-ceeding of Third Regional Symposium on Environment and Natural Resources, Kuala Lumpur, pp. 313–324, 2008.

[6] C. P. Kumar, “Pitfalls and sensitivities in groundwater modeling,” Civil Engineering, Vol. 84, pp. 116–120, 2003.

[7] V. S. Singh and C. P. Gupta, “Groundwater in a coral is-land,” Environmental Geology, Vol. 37, pp. 72–77, 1999.

[8] K. Spitz and J. Moreno, “A practical guide to groundwa-ter and solute transport modeling,” John Wiley and Sons, New York, 1996.

[9] M. E. Thangarajan, “Resource evaluation, augmentation, contamination, restoration, modeling and management,” Capital Publishing Company, 2007.

[10] J. R. Boulding and J. S. Ginn, “Practical handbook of soil, vadose zone, and ground-water contamination: Assess-ment, prevention and remediation,” Lewis Publishers, Boca Raton, Florida, 2004.

[11] D. K. Todd, “Groundwater hydrology,” Second Edition. John Wiley & Sons, New York, 1980.

[12] M. P. Anderson and W. W. Woessner, “Applied ground-water modeling: Simulation of flow and advective trans-port,” Academic Press, Inc., San Diego, 2002.

[13] N. Krešić, “Hydrogeology and groundwater modeling,” CRC Press, Boca Raton, Florida, 2006.

[14] W. C. Walton, “Groundwater resource evaluation,” McGraw-Hill Education, 1976.

[15] K. McGillicuddy and T. Sovich, “Strategies for operation of orange county water district Talbert seawater intrusion barrier, California,” ASCE, New York, 1996.

[16] A. M. M. Elfeki, G. J. M. Uffink, and F. B. J. Barends, “Groundwater contaminant transport: Impact of hetero-geneous characterization: A new view on dispersion,” Taylor & Francis, 1997.

[17] N. Emekli, N. Karahanoglu, H. Yazicigil, and V. Doy-uran. “Numerical simulation of saltwater intrusion in a groundwater Basin,” Water Environment Research, Vol. 68, pp. 855–866, 1996.

[18] L. F. Konikow and T. E. Reilly, “Groundwater model-ing,” In: The Handbook of Groundwater Engineering, CRC Press, Boca Raton, Florida, 1995.

[19] L. Konikow and J. Mercer, “Groundwater flow and transport modelling,” Journal of Hydrology, Vol. 100, pp.



13

379–409, 1988.

[20] J. J. Fried, “Groundwater pollution: Theory, methodology, modelling, and practical rules,” Elsevier Scientific Pub-lishing Company; Amsterdam-Oxford-New York, 1975.

[21] R. Bowen, “Groundwater,” Springer; London, 1986.

[22] J. Wainwright and M. Mulligan, “Environmental model-ing: finding simplicity in complexity,” John Wiley and Sons, New York, 2004.

[23] K. R. Rushton, “Groundwater hydrology: Conceptual and computational models,” John Wiley & Sons, New York, 2003.

[24] Environmental Protection Agency, “Models and com-puters in ground-water investigations,” 1991, http://www.

cepis.ops-oms.org/muwww/fulltext/repind46/models/models.html.

[25] V. Batu, “Applied flow and solute transport modeling in aquifers: fundamental principles and analytical and nu-merical methods,” CRC Press, Boca Raton, Florida, 2006.

[26] G. B. Maxey, W. Back, and D. A. Stephenson “Contem-porary hydrogeology,” The George Burke Maxey memo-rial volume, Elsevier, 1979.

[27] M. Kasenow, “Determination of hydraulic conductivity from grain size analysis,” Water Resources Publication, 2002.

[28] E. Holzbecher, “Modelling density-driven flow in porous media,” Springer Publisher, Heidelberg, 1998.



The Combined Approach When Assessing and Mapping Groundwater Vulnerability to Contamination

Massimo V. CIVITA

Applied Hydrogeology at the Poltecnicodi Torino, Torino, Italy E-mai: [email protected]

Received October 12, 2009; revised November 11, 2009; accepted December 4, 2009

Abstract In early 1980’s, the Italian scientific community, together with a number of institutional decision-makers, realized how urgent it was to protect natural and environmental resources. They agreed that an adequate level of scientifically organized knowledge allows the accurate planning and development of environment systems through the management and direction of the effective development process, but without stopping it. Since the special VAZAR1 project was first set up in 1984, as part of the GNDCI-CNR2 scientific context it has been the cardinal center point of Research National Program “Aquifer Vulnerability Assessment”. The prob-lem of groundwater contamination was examined in this program for the very first time in Italy in an organic and extensive manner as a key for forecasting and prevention purposes. The Italian approaches to assessing and mapping groundwater vulnerability to contamination are essentially based on two main methodologies: 1) the GNDCI Basic Method [1,2] a HCS type approach that can be used for any type of Italian hydrogeologic situation, even where there is a limited number of data. A unified legend and symbols are also defined for each hydrogeologic level. 2) The SINTACS method [2,3], a PCSM developed for use prevalently in areas with a good data base coverage. The methodological approaches described in this paper now make up the Italian standard which has been dealt with in the recent very important Italian Law (152/993) and which are now ratified in the national guidelines [4] produced by ANPA, the Italian National Agency for Environment Protection. The methods, besides Italy [5] have been applied in several other Countries [6–10] and others. Keywords: Groundwater Vulnerability, Contamination, GIS, SINTACS R5, Basic Method

1. Introduction The intrinsic (i.e. natural) vulnerability of aquifers to contamination is “the specific susceptibility of aquifer systems, in their various parts and in the various geomet-ric and hydrodynamic settings, to ingest and diffuse fluid and/or hydro-vectored contaminants, the impact of which, on the groundwater quality, is a function of space and time” [11]. The intrinsic vulnerability depends on three main factors:

1) The ingestion process and the time of travel of wa-ter (and/or a fluid contaminant) through an unsaturated

zone down to the underlying saturated zone of the aqui-fer system;

2) The groundwater (and/or a fluid contaminant) flow dynamics in the saturated zone;

3) The residual concentration of the contaminant as it reaches the saturated zone, compared to the original concentration, which indicates the aquifer attenuation capacity of the contaminant impact.

The previously mentioned factors in turn depend on the different possible synergies of several parameters of a hydrogeologic and anthropic nature, and which are therefore subject to change in each area.

The attenuation process that takes place inside an aq-uifer system (i.e. soil + unsaturated zone + saturated zone) as it receives a contaminant (fluid and/or water vectored) depends on the properties and primary concen-tration of each contaminant but also on the reactivity of the system, which can be reduced or, in the long term, completely depleted in time. Thus, when a CSC4 impact

1The acronym stands for “Vulnerability of Aquifers in High Risk Zones”. 2GNDCI-CNR stands for National Group for the Defence against Hy-drogeologic Disasters of the Italian National Council of Research. 3Law Decree n. 152, May 11 1999 “Orders on the protection of water against contamination” and acknowledgement of the 91/271/CEE Di-rective regarding the treatment of urban wastewater and the 91/676/CEE Directive regarding the protection of water against contamination by nitrates from agricultural sources.

M. V. CIVITA


15

persists for a long time or if a contaminant is persistent and mobile, the attenuation capacity of the soil dwindles and vulnerability increases in time. In these cases, groundwater protection is only aided by the time of travel, that is, by the thickness of the unsaturated zone; it is also inversely related to the ingestion capacity, vertical percolation velocity and to the mechanical dispersion that are typical of the medium. During the travelling, many interactions take place between a soil, subsoil, groundwater and the contaminants, the overall result being an attenuation of the contaminant impact. A further and surely not negligible dampening effect takes place as the residual concentration of the contaminant dilutes, in the saturation zone, to a lower degree, due to the flow velocity, unit flow rate and hydrodynamic dispersion. The evaluation of the specific vulnerability of an aq-uifer should be made case by case, taking into account all the chemical and physical features of each single con-taminant that is present (or of a group of similar con-taminants), the type of source (punctual or diffused), quantity, means and rates of contaminant applications [12–14]. This approach, although scientifically valuable and adequate for the case of the evaluation of a potential contamination [15] of a CSC in small areas, is quite im-practicable where the goal is the assessment of aquifer vulnerability for large areas or when it is carried out as part of contamination prevention and aquifer protection planning.

1.1. Advantage and Disadvantage of the Various

Methods In the last 30 years, a number of techniques have been developed for the general treatment of data (Table 1). These techniques vary considerably, according to the physiography of the tested areas [16,17] to the quantity and quality of the data, and to the aim of the study. Be-cause of the limited space available for this contribution, the reader can refer to Civita [2,18], for an exhaustive discussion of the previously mentioned methods and a complete reference list.

A division into two distinct classes is therefore impor-tant: use for any physiographic scenario, or use for a par-ticular area. For the sake of simplicity, the terms univer-sal and local are proposed. However, these two classes can also be subdivided into three basic groups:

1) Homogeneous area zoning (hydrogeologic complex and setting assessment-HCS);

2) Parametric system assessment (i.e. Matrix Systems [MS]; Rating Systems [RS]; Point Count System Models [PCSM];

3) Analogical relation (AR) and numerical model as-sessment.

As has been widely verified from a comparison of

several different approaches applied to the same sam-ple-area [2], the choice of the method that is most suit-able to build a vulnerability map for a certain area should initially depend on a strictly realistic evaluation of the number, distribution and reliability of the avail-able (and/or researchable) data. It should therefore be underlined that an aquifer vulnerability map is an envi-ronment planning document. The map must be an inte-grant part of a land planning scheme for any order and degree of the administrative territory: it cannot depend on the morphology as it must cover a wide mixture of plain, hilly and mountain areas, as can be found throughout a lot of country worldwide.

Considering the recent experience gathered in Italy5, it is possible to indicate the correlation between the three main factors that are necessary when mapping vulnerability, namely the density of surveyed points, the amount of information secured for any point and the scale denominator (SD) at which the map can be con-structed. It must be pointed out that only when there are a great number of information points per unit area (for any of which a variety of ground data are attainable) can complex, low SD models be applied; for a medium information point density with a fair distribution, a more complex or less complex parametric system (de-pending on the number of data available per point) can be used; if the specific basic information is inadequate and/or scarce and scattered throughout the area, as is often the case, an HCS method fitted to a medium-large SD must be used.

A very important consideration that must be made when choosing a method for vulnerability assessment is the reliability of the basic data, as the inadequate reliability of data can give rise to a false precision. Even worse, it can completely falsify the results, making them quite useless.

The reliability of data, moreover, can vary widely with a mean elevation of the investigated area. A sharp de-crease in the reliability of results is above a compara-tively low altitude (300-400 m a.s.l.) due to the increas-ing scarcity of data in mountainous areas, a problem which cannot be resolved through the use of extrapola-tion techniques. This is true for hydrogeologic and hy-drostructural data (piezometric levels, unsaturated zone, flow directions, hydraulic conductivity, aquifer geome-try), but no less so for pedological and climatological data (rainfall, evapotranspiration, wind, temperatures, etc.). In mountainous regions and in most hilly areas, however, it may be necessary to avoid the more complex techniques, using HCS or MS systems coupled to me-dium-high SD mapping, instead of the more sophisti-cated parametric systems. The validity of these is greater

5The Italian National Research Programme has produced, between 1984 and 2005, about 150 vulnerability maps using various methods, covering all the hydrogeologic scenarios of the Country (see Civita & De Maio, 2002). 4CSC=Contamination Spreading Centre.

M. V. CIVITA


16

in plain areas with high data density and reliability, but they are also suited to adequately low SD mapping.

On the basis of this consideration, it was realized that it is impossible to elaborate an aquifer vulnerability map using one single method, particularly when the target is

assessing vulnerability in less developed countries, where the worse experience of developed countries might be a spur to a prevention protecting policy.

It is necessary to point out advantage and disadvantage of the various methods reported in Table 1:

Table 1. Methods of assessing the aquifer vulnerability to pollution and the relative basic information.

Methodology Basic Information

Characteristics of Soil

Reference and/or name

Type

Pre

cipi

tati

on R

ate

& C

hem

cal

Com

posi

tion

Top

ogra

phic

Sur

face

& S

lope

V

aria

bili

ty

Sur

fici

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Albinet & Margat (1970)BRGM (1970) HCS

Vrana (1968)Olmer & Rezac (1974) HCS Fenge (1976) RS

Josopait &Swerdtfeger (1976) HCS

Vierhuff, Wagner & Aust (1980) HCS

Zampetti (1983)Fried (1987) AR

Villumsen, Jacobsen & Sonderskov (1983) RS

Haertle' (1983) MS

Vrana (1984) HCS

Subirana, Asturias & Casas Ponsati (1984) HCS

Engelen (1985) MS

Zaporozec (edit., 1985) RS

Breeuwsma et al. (1986) HCS

Sotornikova & Vrba (1987) RS

Ostry et al. (1987) HCS

Minstr. Flemish Comm (1986) Goossens & Van Damme (1987)

MS

Carter et al. (1987) Palmer (1988) MS

Marcolongo & Pretto (1987) method. 1 RS

Marcolongo & Pretto (1987) method. 2 AR

GOD Foster (1987, 1988) RS

Schmidt (1987) RS

Troyan & Perry (1988) PCSM

GNDCI BASIC (Civita, 1990) HCS

DRASTIC Aller et al. (1985 - 1987) PCSM

SINTACS (Civita, 1991; Civita & De Maio, 1997, 2000)

PCSM

ISIS (De Regibus,1994) PCSM

For a complete list of the above noted works, see Civita M.V. (1994 ) and Vrba & Zaporozec (1995).

M. V. CIVITA


17

w

Several methods are applicable only to the restrict zone where they had been performed:

1) Some of the methodologies consider only the action of the soil and not that of the whole system;

2) Some of most evolutes PCSM (e.g. DRASTIC [19], GOD [13]) not contemplate the climatic factors and the exchange with the surficial watercourse;

3) None method is built up for using GIS data treat-ment, so, derived maps may illustrate only a situation “crystallized” in the time and not updatable to provide the situation in real time;

4) Without the census of pollution producer and their hazard level is not possible to use vulnerability maps for planning and contamination prevention.

With the target to built out standard methods usable all country wide, since the ninety the Italian Scientific Pro-gram began to realize two methodologies usable one in hilly and mountain areas and the other in plain area. Since 2000, a new approach (named combined approach) was studied and tested, for use in any part of the Italian6 territory, which was based on the overlapping of the two different GIS ready methodologies:

1) A parametric method (a highly advanced PCSM- i.e. SINTACS Release 5 [3]), which has been improved for plain and pedhilly areas, where the amount and reliability of data, measurements, tests and analysis can be consid-ered to be sufficient for the mapping scale;

2) Homogeneous areas zoning, based on the survey of hydrogeologic complexes, characteristics and settings (HCS), to be used in mountainous and hilly areas where a scarcity or lack of underground information is normal (GNDCI-CNR Basic Method). 1.2. Brief Description of the Methods The vulnerability of a groundwater body is a function of several parameters, the most important of which are lithology, structure, geometry of the hydrogeologic sys-tem, the type of overburden, the recharge-discharge process, the interaction of the physical and hydrochemic processes that regulates the quality of the groundwater, and the fate of the contaminants that impact the system.

Where the data base is complete and the frequency of the available information is adequate, the factors that are used to assess the aquifer vulnerability to contamination are selected; a subdivision into value intervals and/or declared types is applied to each selected factor; a pro-gressive rating (P, ranging from 1-10) is given to each interval as a function of the importance in the final as-sessment (Table 2); the selected ratings of each factor must be multiplied for a choice of weight (W) strings,

which are used in parallel and not in series (Table 3), each one describing a hydrogeologic and impact setting that emphasizes the action of each parameter.

The acronym SINTACS comes from the Italian names of the factors that are used, i.e. Soggicenza (depth to groundwater); Infiltrazione (effective infiltration); Non saturo (unsaturated zone attenuation capacity); Tipologia della copertura (soil/overburden attenuation capacity); Acquifero (saturated zone characteristics); Conducibilità (hydraulic conductivity); Superficie topografica (topog-raphic surface slope). A vulnerability index is calculated for each cell of a discretisation grid that is overlaid on the basic map of the considered zone:

7

SINTACS J JJ=1

=I p (1)

The types of basic information, the necessary elabora-tions to transform them in SINTACS factors and the definition of the hydrogeologic and impact settings used to select the weight strings can be found in [2,3], to-gether with a number of application tests. 1.3. GNDCI-CNR Basic Method This method [1] is based on a standard in which a num-ber (about 20, see Table 4) of hydrogeologic settings that can be found in the Mediterranean countries is collected and the intrinsic vulnerability characteristics of the aqui-fer are identified. This method is highly flexible and can be adapted, if necessary, to other situations that are not dealt with in the standard. The lithologic, structural, pie-zometric and hydrodynamic indexes are not rigorously quantified. Starting from a complete examination of the main Italian hydrogeologic settings, the representative sites were extracted from those that best define the set-tings, e.g. the Po river Plain, the carbonatic massifs of the Apennine ridge, the karst settings of Apulia and Tri-este, the volcanic terrain of central Italy, the ancient basement of the Alps, and so on. The main factors of the aquifer vulnerability (e.g. depth to groundwater, porosity, fracturing index, karst index, linkage between stream and aquifer, and so on) were identified for each representa-tive site. Bearing in mind the dynamics and frequency of the contamination cases that were collected and previous similar experience at an international level, the settings were distributed over the 6 degrees of intrinsic vulner-ability (i.e. contamination potential) that form the synop-tic legend of the maps. 1.4. The Combined Approach From what has been seen, in many areas where it is nec-essary to cover vast areas identified by administrative (i.e. Municipalities, Provinces, Regions) or physical bounda-ries (interregional watershed) with a Vulnerability Map,

6The choices that are made, as known, are based on over 13 years of research and experiments in the field, carried out by researchers who have taken part in the GNDCI-CNR Research Programme Aquifer Vulnerability Assessment (about 100 researchers within 21 Research Units all Country wide).

M. V. CIVITA


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Table 2. Description of the parameters and related rating graphs for PCSM SINTACS.

Description Rating Definition

Depth to groundwater: is defined as the depth of the piezometric level (both for confined or unconfined aquifers) with reference to the ground surface and it was a great impact on the vulnerability because its absolute value, together with the unsaturated zone character-istics, determine the time of travel (TOT) of a hydro-vectored or fluid contaminant and the duration of the attenuation process of the unsaturated thickness, in particular the oxi-dation process due to atmospheric O2. The SINTACS rating of depth-to-groundwater therefore decreases with an increase of the depth, i.e. with an increase of the thickness of the unsaturated zone within the range 10 1.

S

Effective infiltration action: The role that the effective infiltration plays in aquifer vul-nerability assessment is very significant because of the dragging down surface of the pollutant but also their dilution, first during the travel through the unsaturated zone and then within the saturated zone. Direct infiltration is the only or widely prevalent compo-nent of the net recharge in all the areas where there are no interflow linking aquifers or surficial water bodies or no irrigation practices using large water volumes.

I

Unsaturated zone attenuation capacity: The unsaturated zone is the “second defense line” of the hydrogeologic system against fluids or hydro-vectored contaminants. A four di-mension7 process takes place inside the unsaturated thickness in which physical and chemical factors synergically work to promote the contaminant attenuation. The unsatu-rated zone attenuation capacity is assessed starting from the hydro-lithologic features (texture, mineral composition, grain size, fracturing, karst development, etc.).

N

Soil/overburden attenuation capacity This is the “first defense line” of the hydrogeologic system: several important processes take place inside the soil that built up the attenuation capacity of a contaminant travelling inside a hydrogeologic system and therefore in aqui-fer vulnerability assessment and mapping. Soil is identified as an open, three-phase, ac-cumulator and transformer of matter and an energy sub-system which develops through the physical, chemical and biological alterations of the bottom lithotypes and of the or-ganic matter that it is made up of.

T

A

Hydrogeologic characteristics of the aquifer: In vulnerability assessment models, the aquifer characteristics describe the process that takes place below the piezometric level when a contaminant is mixed with groundwater with a loss of a small or more relevant part of its original concentration during the travelling through the soil and the unsaturated thickness. Basically these processes are: molecular and cinematic dispersion, dilution, sorption and chemical reactions between the rock and the contaminants.

7The time has to add to the normal 3 dimensions that describe the volume and, in this particular case, the TOT should also be added.

M. V. CIVITA


19

Hydraulic conductivity range of the aquifer: Hydraulic conductivity represents the capac-ity of the groundwater to move inside the saturated media, thus the mobility potential of a hydro-vectored contaminant which as a density and viscosity almost the same as the groundwater. In the SINTACS assessment context, the hydraulic gradient and the flux cross section being equal, this parameter determines, the aquifer unit yield and flow ve-locity that go toward the effluences or the tapping work that indicates the of risk targets.

C

S

Hydrologic role of the topographic slope: The topographic slope is an important factor in vulnerability assessment because it determines the amount of surface runoff that is pro-duced, the precipitation rate and displacement velocity of the water (or a fluid and/or hydro-vectorable contaminant) over the surface being equal. A high rating is assigned to slight slopes i.e. to surface zones where a pollutant may be less displaced under gravity action or even stop in the outlet place favoring percolation. The slope may be a genetic factor due to the type of soil and its thickness, and can indirectly determine the attenua-tion potential of the hydrogeologic system.

Table 3. Strings of multiplier weights given for SINTACS.

Pa-rameter

Normal I

Severe I

Seep-age

Karst Fis-

suredNitrates

S 5 5 4 2 3 5

I 4 5 4 5 3 5

N 5 4 4 1 3 4

T 3 5 2 3 4 5

A 3 3 5 5 4 2

C 3 2 5 5 5 2

S 3 2 2 5 4 3

the parametric models that have been set up cannot be applied due a lack of data at those points where the ter-rain changes from a plain morphology to a hilly or mountainous area. In these situations, in the past, a sim-ple method was chosen that was able to perform a less refined and detailed evaluation, but which however was applied to many land and environmental problems con-nected to the contamination of aquifers with good results.

The solution that has been found for this problem and which has been tested, is the combined approach. This approach allows the GNDCI-CNR Basic method to be combined with the PCSM SINTACS method without continuity solutions: the latter in areas where the data that are necessary and sufficient to apply a parametric model exist; the first in areas where the great depth to water, the hydrolithologic and hydrostructural complex-ity and the lack of certain data on the terrains, the hy-draulic conductibility and active recharge do not allow details to be obtained that can be compared with those that can be obtained using SINTACS. The experience

gained over recent years has led to a reconsideration of the methodological problem: why renounce the detail that can be offered by point and weight parametric mod-els [1,2] in areas with moderate relief where the majority of the CSCs and the DCSs8 and many of the supply springs are concentrated (that is, the subjects at risk - SAR)? On the other hand, how can we carry out the evaluation of vulnerability and the risk to contamination for areas with great depth to water, areas that can be de-scribed in less detail on the basis of hydrogeologic situa-tions and complexes?

The necessary connection, whether conceptual or car-tographic, between adjacent areas where different meth-odologies should be applied, is supplied by the paramet-ric evaluations. In practice, for those complex ones where a parametric evaluation already exists, the same degrees of vulnerability are applied but the changed slope and water table conditions are also taken into ac-count. All this is possible thanks to the fact that the cali-bration with SINTACS was carried out by comparing and crossing, as already mentioned, the SINTACS evaluation with that obtained with the GNDCI-CNR Basic method, on over 600 test-sites distributed throughout the different Italian areas and territories. The division of the numerical index into 6 degrees of vulnerability, the same as those used for the Basic Method, makes the two methods comparable and the results optimally combinable.

The application of the combined approach has given excellent results in the Tanaro Project area [20] and led to a complete covering being obtained without any loss of basic information or accuracy of synthesis. The same numbers of cartographic examples of the vulnerability carried out using the combined approach of the two methods are shown in Figure 1. The thick black line in 8DCS=Diffused Contamination Sources.

M. V. CIVITA


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Table 4. Standards of Italian hydrogeologic settings (GNDCI- CNR basic method).

Vulnerability degrees

Hydrogeologic complexes and setting features

Extremely high

Unconfined (water table) aquifer in alluvial depos-its: streams that freely recharge the groundwater body; well or multiple well systems that drawdown the water table to under the stream level (forced recharge). Aquifer in carbonate (and sulphate) rocks affected by completely developed karst phenomena (holo-karst with high karst index [KI]).

Very high

Unconfined (water-table) aquifer in coarse to me-dium-grained alluvial deposits, without any surficial protecting layer. Aquifer in highly fractured (high fracturing index [FI]) limestone with low or null KI and depth to water <50m.

High

Confined, semiconfined (leaky) and unconfined aquifer with impervious (aquaculture) or semi-pervious (aquitard) superficial protecting layer.Aquifer in highly fractured (high fracturing index) limestone with low or null KI and depth to water >50m.Aquifer in highly fractured (but not cataclastic) dolomite with low or null KI and depth to water <50m.Aquifer in highly clivated volcanic rocks and non- weathered plutonic igneous rocks with high FI.

Medium

Aquifer in highly fractured (but not cataclastic) dolomite with low or null KI and depth to water >50m. Aquifer in medium to fine-grained sand. Aquifer in glacial till and prevalently coarse-grained moraines.

Medium - Low

Strip aquifers in bedded sedimentary sequences (shale-limestone-sandstone flysch) with layer by layer highly variable diffusion rates. Multi-layered aquifer in pyroclastic non indurated rocks (tuffs, ash, etc.): different diffusion degrees layer by layer close to the change in grain size.

Low

Aquifer in fissured sandstone or/and non carbonatic cemented conglomerate. Aquifer in fissured plutonic igneous rocks. Aquifer in glacial till and prevalently fine-grained moraines.Fracture network aquifer in medium to high meta-morphism rock complexes.

Very low or null

Practically impermeable (aquifuge) marl and clay sedimentary complexes (also marly flysch): con-tamination directly reaches the surface waters. Practically impermeable (aquifuge) Fine-grained sedimentary complexes (clay, silt, peat, etc.) con-tamination directly reaches the surface waters. Meta-sediment complexes or poorly fissured highly tectonized clayey complexes low metamorphism complexes, almost aquifuge: contamination directly reaches the surface waters.

the figure represents the dividing line between the areas treated with the two methods. The homogenization that the approach involves can clearly be seen. 2. A Case Study 2.1. Generality The study of vulnerability to contamination of the aqui-fers in the Tanaro Valley, Piedmont (Italy) was initially

Figure 1. Vulnerability map: (Red) extremely elevate degree; (Orange) elevated degree; (Yellow) high degree; (Green) medium degree; and (Cyan) low extremely degree of vul-nerability. set up and planned on a very large territorial basis. It was considered that not only the areas that were directly in-volved by the 1994 flood event should be considered, but also the remaining territory belonging to the Municipali-ties that were involved in the catastrophe, which were subject to the direct and derived consequences of the flood.

The case-study landscape is a part of the territory of the Alessandria Province-Piedmont, Italy (Figure 2.) and its hydrogeologic layout is synthesized in Table 5.

However, detailed data were not available for the ex-ternal areas on the depth to water, the hydraulic conduc-tivity, the soil characteristics, etc.

The vulnerability map of aquifers is a planning docu-ment and cannot therefore be limited to only the parts of the territory that were involved. Given, however, the cover conditions-data that has previously been illustrated - it was not possible to carry out an elaboration of the Vulnerability map with a uniform method. It therefore proved necessary to appropriately use the SINTACS R5 method together with the Basic GNDCI-CNR method applied in a combined approach.

2.2. Databases and Monoparametric SINTACS

Maps 2.2.1. Depth to Water The SINTACS points relative to this parameter decrease with an increase of the depth, that is, with an increase of the thickness of the unsaturated area, and they take on values between 10 and 1.

Therefore, when selecting the data to use in SINTACS it was necessary to consider the minimum depth to water value that was revealed from the survey campaign, in order to be in the most cautionary conditions possible when evaluating the vulnerability, the value of which, in all cases, is inversely proportional to the time of travel

M. V. CIVITA


21

Table 5. Hydrogeologic characteristics of the complexes.

Hydrogeologic Com-plexes

Subcomplexes Age Thickness

(M) Lithology Relative K Hydrogeologic Role

Actual alluvial Holocene 16 Coarse gravel with sandy matrixes

EE Secondary unconfined aquifer

Main plain Holocene 550 Gravel with sandy matrix, clayey gravel, sands and extended clay bodies

M Main unconfined aquifer

Intermediate terraces

Pleistocene 550 Gravel with sandy matrixes, clayey gravel, sands and extended clay bodies

M Main unconfined aquifer Gravely-clayey allu-

vial

High terraces Pleistocene 550 Gravel with clayey matrixes, gravel and clayey sands and clay lenses

M Main unconfined aquifer

Gravely-clayey Prevalently

clayey Upper Plio-

cene 150 Important clayey bodies with gravel and sand horizons

L Secondary aquifer under pressure

Sands Middle lower

Pliocene 3050 Coarse sand, silty sand with silty-clayey horizons

M Unconfined aquifer under pressure

Sandy-gravely

Gravel Middle lower

Pliocene 30100 Locally cemented gravel and sand and silty horizons

M - E Aquifer under pressure

Marly-sandy Lower Plio-

cene 100200 Prevailingly marl and silty sand horizons

I - M Limits of permeability (aquifer locally under pressure)

Clayey-sandy-conglomerate

Lower Plio-

cene 100200

Important clay bodies with sand horizons, prevalently sand and arenaceous-conglomerate bodies (varying from zone to zone)

I - M Limits of permeability (aquifer locally under pressure)

Terri-genous-evaporitic

Messinian 20100

Chalk lenses, arenaceous-conglomerate horizons, important clayey bodies (varying from zone to zone)

I - E Limits of permeability (unconfined aquifer and under pressure)

Calcare-ous-arenaceous-clayey

Palaeocene, Eocene, Oli-gocene, Mio-

cene

100

Minute conglomerates and sandstone, calcareous and arenaceous thin layers, marl, marlsandstones, marlclays and multicoloured clays

I - L Permeability sill

Clayey Tortonian 200300 Important succession of marls and marlyclays

I Impermeable, limits of permeability

Figure 2. Geographical sketch of the case study.

M. V. CIVITA


22

P

(TOT). The raw depth to water data were elaborated in an ARC/INFO ambient, first to obtain a satisfactory and descriptive territorialisation9, while taking into consid-eration the limits of the system and the georeferenced position of the 0 depth to water descriptions. Then the spaces were reclassified on the basis of the SINTACS points and cartography was obtained relative to the S parameter, which was plotted on a raster basis (Regional Technical Map) at a 1:100,000 scale.

The depth to water map was obtained automatically from subtractions of the height grids of the topographic surfaces and from the piezometric surface height grid. The topographic surface was obtained using the DTM (Digital Terrain Model) of the Regione Piemonte. This is not compatible with ARC/INFO: this led to specific software being prepared in the DOS environment to transform the original files into ASCII files which are instead compatible with ARC/INFO with the Gauss- Boaga coordinates (x, y, z) of the points that make up the DTM. The thus obtained file was imported and appropri-ately elaborated (Figure 3) so as to obtain a covering of the quoted points on which to apply the 50 m side grid, GRID 1 was obtained in this manner.

The piezometric surface was obtained from the sur-veyed point piezometric data. The Isopiezometric Map (∆h=1m) was generated from these data through linear interpolation using a traditional method. It was digitised in ARCVIEW and imported into ARC/INFO as a shape file. The creation of the topology made it possible to at-tribute the mean height of the piezometric level to the iso-value areas. GRID2 was obtained from the thus ob-tained cover.

The DTM has an accurate precision and the extraordi-nary potentialities of a GIS make it possible to use it in a great number of territorial applications (planning of in-frastructures at a mean denominator scale, the study of landslide phenomena, etc.).

The elaboration that was made also constitutes a re-markable innovation of the traditional techniques used for the drawing up of depth to water maps. These tradi-tional techniques do not supply great precision, even in the case of situations with moderate variability, and, above all, the automatic elaboration makes it possible to obtain maps almost in real time.

The thus obtained depth to water map was then reclas-sified using the RECLASS command of GRID in the intervals foreseen by the SINTACS method. This allowed a grid with the depth to water parameter points to be obtained. 2.2.2. Infiltration The evaluation and territorialisation method of this pa-rameter in the latest SINTACS versions (R5) [21] is based on the inverse hydrogeologic balance technique.

Figure 3. Flow chart of the depth to water map.

The parameter is calculated from the effective rainfall territorialized using a grid square numerical model and from the surface hydrogeologic conditions that are in-corporated in the infiltration index ().

In the case under examination, the historical series registered in 28 pluviometric stations and 11 thermomet-ric stations distributed over the area under examination and in the vicinity were examined for the periods 1931- 1941 and 1954-1964. Five homogeneous areas were iden-tified on the basis of the mean rainfall/elevation ratio; four homogeneous areas were identified on the basis of the mean corrected temperature/elevation ratio.

On the basis of the points obtained from the DTM, of the mesh defined for the studied area, from cover of the performed for the entire studied area and constructed in ARCVIEW as a polygonal shape file, through an AML script in the ARC/INFO GRID ambient, the following data are automatically calculated for each cell:

1) The specific rainfall (

);

2) The specific corrected temperature ( c

Er

Q

T );

3) The specific evapotranspiration ( );

4) The specific effective rainfall ( );

5) The specific active (infiltration) charge ( I );

6) The specific surface run off ( R ).

9Territorialization means the method, geostatistically based, that allows the punctual value of a opportunely surveyed parameter to be assigned to a territorial frame.

Grid of the depth to water values (GRID1 and GRID2)

Grid of the SINTACS depth to water points

ASCII file x,y,z co-ordinates

TINgeneration

Regione Pie- monte DTM

Creation of a Coverage of the quoted points

Isopiezometric Map (linear interpolation, h=1m)

Preparation of the shapefile

Importation in ARC/INFO(iso-height areas with h=1m)

Topographic surface GRID1

GRID2 of the piezometric surfaces (1 m resolution)

M. V. CIVITA


23

Once the value of the potential infiltration had been calculated for each grid element, a reclassification is made according to the point intervals defined by the method and with the redrawing up of the Map for pa-rameter I, in a 1:100.000 scale on a RASTER basis.

2.2.3. Effect of the Auto-Depuration of the Unsaturated Zone

The values of parameter N were obtained from a point elaboration of the stratigraphies of about 700 wells and surveys under examination in the area.

Once the depth to water is known, it is possible to make an initial sub division into unsaturated or saturated for each item of point information. Once the unsaturated thickness and the relative lithologic variations deduced from the reference stratigraphy are known, it is possible to proceed with the elaboration of the pondered mean of the SINTACS N point for each measurement point.

A heterogeneous substance with N parameter values of between 1 and 9 is indicated in the Alessandria sector, with a dominance of point 4 in the plain south of the Alessandria-Spinetta-Tortona alignment.

As expected, a value N =8 was assigned to the recent alluvial complex (prevalently gravel).

The lowest value, equal to 3, was assigned to the prevalently insistent clay complex west of the sector un-der examination. The Map relative to the autodepuration effect of the unsaturated zone was obtained using tradi-tional mapping of the data derived from the hydro-geologic survey and from the many drillings that were available. The data relative to the subsoil on which the parameterisation of the unsaturated zone is based almost all derive from the drilling of water wells and from ge-ognostic and geophysics investigations.

The different items of point information, which were placed in a specific database that contains about 15.000 data, were subjected to cross-checking and homogen isation in order to construct the greatest possible number of hydrogeologic profiles, so as to obtain a correct zon-ing of the hydrolithologic information.

The next step consisted in importing the previously treated data into the ARCVIEW ambient, where the points foreseen by the SINTACS method for the unsatu-rated thickness of heterogeneous composition were at-tributed to homogeneous areas. The information relative to the N parameter was reclassified according to the foreseen points and the Map relative to the 1:100.000 scales was redrawn on a raster basis. This elaboration was then imported into ARC/INFO. The normal mesh was applied to this cover and the grid of the SINTACS points for the unsaturated zone was obtained. 2.2.4. Typology of the Cover The values of the SINTACS T parameter were obtained from an analysis of 106 samples of the soil obtained from the 1998 sampling campaign that was carried out in

the province of Alessandria through a correlation dia-gram of the T parameter and the contents in the soil of organic substances (SO) and fine mud-clayey particles (AL) [3,22]. Given the remarkable extension of the area under examination (1042 km2), recourse was made to the Map of the Capacity of use of the Soils and their limita-tions [23] to have an adequate pedologic knowledge of the entire area, and the entire area under examination was then pedologically zoned thanks to this map and that of the hydrogeologic complexes. The entire zoning was defined according to parameter T of the studied area through the use of the correlation diagram between the textural characteristics of the soils and the relative points for the evaluation of the mitigating action of the con-taminants [24]. The dominant value of point T in the Alessandria plain area was 6, while in the hilly areas south and south east of the Alessandria sector, a T value equal to 7 was obtained. A higher value of 8 was only found in a plain area close to the Pontecurone village at the extreme south west of the area close to Cassine.

The thematic Map was obtained using traditional methods. The elaboration that was obtained was acquired as a polygonal ARCVIEW shape file in which the rela-tive points were assigned according to the reference abacuses of the SINTACS method. The shape file was then imported into ARC/INFO where the usual 50 metre side grid was applied. 2.2.5. Hydrogeologic Characteristics of the Aquifer The elaboration of the data relative to the SINTACS A parameter followed the same course as the elaboration for parameter N. Given the partial heterogeneity of the saturated zone, which also occurred for the analysis of the unsaturated zone, it was decided to apply the mean pondered technique (with respect to the thicknesses) of the value assigned to the point datum so that this totally reflected the real typology of the saturated zone.

The Alessandria sector is dominated by high values (7-8-9) of the A parameter, an indication of an elevated permeability type aquifer; a limited central zone diverges from this analysis with a SINTACS point equal to 5; a second zone central-east of Alessandria; a third zone to the extreme east of the Province, till the valley bottom of the Scrivia river.

The Map of the hydrogeologic characteristics of the aquifer was obtained by attributing the SINTACS points, according to the abacuses reported for the same method. The Grid in ARC/INFO, relative to the Map of the char-acteristics of the aquifer, was obtained through simple applications to the overall area. 2.2.6. Hydraulic Conductivity The determination of the SINTACS C parameter was mainly based on the elaboration of the hydraulic conduc-tivity data obtained from in situ tests (Slug test, recovery test, Lefranc test) and from the use of the QSPEC soft-

M. V. CIVITA


24

ware [25] using the input data extracted from the strati-graphies of wells for the entire area under study and where the data were insufficient, the correspondence between the hydraulic conductivity intervals of the main aquifer complexes and the corresponding C parameter points was taken into consideration.

The hydraulic conductivity of the aquifers in the Ales-sandria sector is medium-high and the values of C there-fore vary from a minimum of 5, relative to the high ter-races of the southern sector, to 6 for the intermediate cen-tral sectors of the Alessandria plain. The highest values occur in the sub-complex of the main plain and for the present alluvial complex with C=7 and C=8, respectively.

As expected, the hydraulic conductivity value in the western sector of the area, in correspondence to the gravely-clayey-prevalently Clayey sub-complex, is me-dium-low and the corresponding C value is 3.

The Hydraulic Conductivity Map of the aquifer was prepared for each area under study by attributing the hy-draulic conductivity value determined from slug tests and recovery tests and calculating the data of the specific dis-charge. The procedures for the creation of the covering of the hydraulic conductivity and the SINTACS point grid are similar to those carried out for the covering type Map.

The following tests were carried out in the studied area when there was a lack of specific data:

1) Recovery tests on agricultural wells; 2) Slug tests in observation wells; 3) Analysis of the specific discharge data, connected

to the stratigraphies of about 250 wells, with a QSPEC numerical calculation software specifically set up for the evaluation of the SINTACS C parameter.

The characterisation of the parameter in the areas that are not sufficiently covered by the aforementioned data was obtained using a protocol that is based on interna-tional statistics that allows the order of magnitude of the permeability of the different rock formations (hydro-geologic complexes) to be appraised, together with the SINTACS method. The different items of information relative to parameter C, appropriately reclassified ac-cording to the SINTACS points, have allowed the draw-ing up of the relative map, via GIS, at a 1:100.000 scale on a raster basis. 2.2.7. Slope The different classes of slope (between 0 and 30 %) were directly obtained from the Regional DTM in the ARC/ INFO ambient and were then reclassified according to the SINTACS points.

The relative Map of the S10 parameter was thus pre-pared on a raster basis.

The Map, presented in 1:100.000 scale, was com-pletely prepared in an automatic way. A grid of the

heights was generated from the DTM and the grid of the topographic surface slope was generated from this using the SLOPE command. The range of the slope classes is defined by the user through a file in which the percent-age slope intervals that one wishes to map are specified. The SINTACS method indicates the slope intervals and the points that are assigned to them. The polygonal cover of the slope from which the area of interest was cut was obtained using overlay operations with the cover of the border of the municipality area. The usual 50 metre side mesh was applied to the slope cover and the thus ob-tained grid was reclassified with the assignment of the relative SINTACS points. 2.2.8. Selection and Cartography of the Weight

Strings As known, the structure of the SINTACS method was thought up in order to be able to use various weight strings to attribute to parameters in function of different hydrogeologic and impact situations. In the present case, the conditions to apply 3 of the 6 strings were encoun-tered, that is:

1) Areas subject to normal impact: barren areas, un-cultivated or with spontaneous cultivations which how-ever do not require the use of plant protection products or chemical fertilisers, unless in small doses, or irrigation practices. The breeding of a few wild animals, whether permanent or seasonal, often occurs in these areas.

2) Areas subject to relevant impact: areas with cultiva-tion that foresee abundant treatments with plant protec-tion products, chemical fertilisers, applications of fert- irrigations, sewage spreading, uncontrolled dumping of waste materials, lagoons, petrol pipelines, sewage depos-its, etc.; active and abandoned industrial areas, urban areas or similar.

3) Areas subject to drainage: from surface water bod-ies and shallow aquifer; depth to water areas subject to natural and man-made drainage networks; irrigation ar-eas with large quantities of water, continuous or periodic outcropping areas of the unconfined piezometric surface.

The map and the relative grid were prepared using the standard procedures: traditional mapping, construction of the polygonal shape file in ARCVIEW and application of the usual ARC/INFO mesh.

3. Results The combined approach was used to draw up the Intrinsic Vulnerability Map. The evaluation was carried out, for the so-called restricted area, using PCSM SINTACS

where the necessary data were available. The GNDCI

Basic method, suitably calibrated for the specific hydro-geologic situation, (combined approach), was used for the so-called enlarged area (Figure 5). 10This is obviously the second “S” of the SINTACS acronym.

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Depth to water Infiltration

Effect of the auto-depuration of the unsaturated zone Typology of the cover

Hydrogeologic characteristics of the aquifer Hydraulic conductivity

Slope Weight strings

Figure 4. Lssandria plain: Parametric maps for SINTACS vulnerability map building.

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Figure 5. Light Grey: Restricted area elaborated with SINTACS; dark grey: enlarged area.

Figure 6. Vulnerability map. (Ee: extremely elevated; E: elevated; H: high; M: medium; L: low). 3.1. Vulnerability Map of the Restricted Area The implementation of the SINTACS method to a GIS foresees:

1) Importation of the basic elaborations and produc-tion of the 8 basic thematic point maps to draw up the Vulnerability Map, relative to 7 SINTACS parameters and to the hydrogeologic and impact situation;

2) Production of the vulnerability Map. 3) The vulnerability map (Figure 6) was obtained

through implementation of a cell by cell procedure in a GRID ambient that foresees the verification of the value of the cell in the hydrogeologic impact characteristic grid and identification of the relative weight strings; and ap-

plication of: 7

SINTACS J JJ=1

=I p w (1)

The value of the SINTACS index of the single cells was then normalised through the implementation of another application of the relation cell by cell procedure [2]:

Inorm=(Isintacs-26)/2.34 (2)

The Grid of the normalised intrinsic vulnerability was thus obtained and it was put on a raster basis and pro-duced in three sheets at a 1: 50.000 scale. It was neces-sary to insert a thick black line to define the border be-tween the area that was only elaborated with the SIN-TACS model and the so-called “enlarged” area which was elaborated with the Basic GNDCI-CNR Method.

3.2. Vulnerability Map of the Enlarged Area The classical method for discrete Hydrogeologic Compl- exes and Situations (HCS), which for many years was adopted for all the test sites studied as a part of the P.S. VAZAR program of GNDCI-CNR, was used for this map.

Details of this treatment can be found in the previous sections as far as the method is concerned and Table 6 shows the code that was attributed to the individual Complexes and Sub-Complexes, as far as the intrinsic vulnerability degree is concerned (Figure 7).

The congruence with the SINTACS evaluation was con-firmed with the criteria of the combined approach, in-troducing some corrections in some points that were however produced by the use of the estimation carried out with the rougher methodology.

Figure 7. Vulnerability map of the enlarged zone.

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Table 6. Hydrogeologic complexes and their vulnerability degree (Basic GNDCI-CNR method).

Vulnerability degrees Hydrogeologic complexes and setting features

Extremely High Unconfined aquifer in gravely and sandy matrixes.

Very High None

High Unconfined aquifer in gravel with sandy, clayey gravel, sands with clayey lens matrixes extended to various degrees

Medium

Unconfined aquifer in gravel with clayey, gravel and clayey sand with clay lens matrixes. Uncon-fined aquifer or under pressure in gravel and sand, coarse sand, muddy sand with silty-clayey hori-zons. Unconfined aquifer or under pressure in chalk lenses with arenaceous-conglomeratic horizons.

Low

Aquifer under local pressure in prevalently marl with sandy silty horizons; important clay bodies with sand, prevalent sand horizons and arena-ceous-conglomerate bodies. Permeability threshold in minute conglomerates and sandstone.

Very low or null

Aquifer under pressure in important clay bodies with gravel and sand horizons. Important perme-able succession of marls and clayey marls.

Figure 8. Vulnerability map of the entire zone. 4. Conclusions The method that was applied to prepare the Intrinsic vulnerability map (Figure 8) has already been fully de-scribed in the previous sections.

From this map, it is possible to note the following remarks about the Alessandria district:

1) The vast Alessandria plain is characterised, with large extensions, by a high (H) degree of vulnerability of the aquifer to contamination;

2) The degree of vulnerability is just slightly lower (medium M) in the less depressed areas (terraces) of the low Tortona area (cfr. Figure 4 for the geographic loca-tions); in the southern part of the Alessandia area; in the strip north of Solero; in the area east near Sezzadio;

3) In correspondence to the most important riverbeds and the relative floodable areas, the SINTACS index is greater than 70 (elevated vulnerability - E) and is often close to the border with the higher class (Ee - extremely elevated) for the area of Castellazzo B.-Sezzadio; to the south of the W province boundary; north east of Alessandia, next to the Tanaro river up to the convergence with the Po river;

4) All the flooded area of the Scrivia river is, likewise, in elevated (E) vulnerability conditions with some points in the higher degree (Ee) in the apical area of the fan (NW Novi Ligure): many uncontrolled waste disposal dumps of toxic and harmful materials were found in this area and structures subject to great risks are located in this area (e.g. the water intake system of the Novi Ligure aqueduct);

5) The waters from the Scrivia river derive in great part from numerous irrigation channels on the left that distribute the water from the river to areas with high to elevated vulnerability;

6) The hilly Tortonese areas, of Monferrato and the Alessandria part of the Langhe are usually characterised by a medium (M) to low (L) vulnerability degree. 5. References [1] M. V. Civita, “Legenda unificata per le Carte della vul-

nerabilità dei corpi idrici sotterranei: Unified legend for the aquifer pollution vulnerability maps,” Studi sulla Vulnerabilità degli Acquiferi, 1 (Annex), Pitagora Edit. Bologna, pp. 13, 1990.

[2] M. V. Civita, “Le carte della vulnerabilità degli acquiferi all’inquinamento: Teoria & pratica,” [Groundwater vulner-ability maps to contamination: Theory and practice] Pitagora Editrice, Bologna, pp. 325 (with bibliography), 1994.

[3] M. V. Civita and M. De Maio, “Valutazione e cartografia automatica della vulnerabilità degli acquiferi all’ inquina-mento con il sistema parametrico: SINTACS R5, a new parametric system for the assessment and automaticmap ping of groundwater vulnerability to contamination,” Pita-gora Editrice, Bologna, pp. 240, 2000.

[4] M. V. Civita and M. De Maio, “Atlante delle carte di vulnerabilità delle regioni italiane,” [Atlas of vulnerability maps of the Italian regions] DBMAP, Florence, pp. 366, 2002.

[5] M. V. Civita, M. De Maio, M. Farina, and A. Zavatti, “Linee guida per la redazione e l’uso delle carte della vulnerabilità degli acquiferi all’inquinamento,” [Guide- lines for drawing and use of the groundwater vulnerability maps to contamination] Agenzia Nazionale per la Protezione dell’Ambiente-Manuali e Linee guida, 1 CD, pp. 100, 2001.

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[6] M. V. Civita, M. De Maio, and S. Lyakhloufi, “Assess-ment of groundwater intrinsic vulnerability of the Mar-rakesh Haouz aquifer (Morocco) by PCSM SINTACS,” GEAM, Vol. 24, No. 2–3, pp. 107–114, 1999.

[7] J. Uhan, J. Pezdic, and M. V. Civita, “Assessing groundwater vulnerability by SINTACS method in the lower Savinja Valley, Slovenia,” RMZ, Vol. 55, No. 3, pp. 363–376, 2008.

[8] J. Mejia, R. Rodriguez, and J. Mata, “The role of the river beds in the evaluation of vulnerability, the Lerma River, Salamanca, Mexico,” Proc. 2nd Workshop “Aquifer Vul-nerability and Risk”, Colorno, Parma, pp. 9-10 + CD, September 21–23, 2005.

[9] S. Adelana and Y. X. Xu, “Vulnerability assessment in the cape flat aquifer, South Africa,” Proc. 2nd Workshop “Aquifer Vulnerability and Risk,” Colorno, Parma, pp. 21-22 + CD, September 21–23, 2005.

[10] D. De Ketelaer, H. Hötzl, C. Neukum, M. V. Civita, and G. Sappa, “Hazard analysis and mapping,” In: COST Ac-tion 620 “Vulnerability and Risk Mapping for the Protec-tion of Carbonate (Karst) Aquifers” (Zwahlen F. Edit.), European Commission, Directorate-General for Research, EUR 20912, pp. 86–104, 2004.

[11] M. V. Civita, “La previsione e la prevenzione del rischio di inquinamento delle acque sotterranee a livello region-ale mediante le carte di vulnerabilità,” [Forecasting and prevention of groundwater contamination risk at a re-gional level using vulnerability maps] In Proceedings Conf. Inquinamento delle acque sotterranee: Previsione e prevenzione, pp. 9–17, February 1987.

[12] L. J. Andersen and E. Gosk, “Applicability of vulnerabil-ity maps,” Int. Proceedings Conf. Vulnerab. of Soil and Groundwater to Pollutants, RIVM Proc. And Inf. Vol. 38, pp. 321–332, 1987.

[13] S. S. D. Foster and R. Hirata, “Groundwater pollution risk assessment: A methodology using available data,” Pan Ame. Cent. for Sanit. Engin. and Envir. Scien. (CEPIS) Lima, pp. 81, 1988.

[14] Y. Bachmat and M. Collin, “Mapping to assess ground-water vulnerability to pollution,” Proc. Int. Conf. Vul-nerab. of Soil and Groundwater to pollutants, RIVM Proc. And Inf. Vol. 38, pp. 297–307, 1987.

[15] M. Albinet and J. Margat, “Cartographie de la vulnerabilitè à la pollution des nappes d’eau souterraine,” Bull. BRGM Paris, Vol. 2, 3, 4, pp. 13–22 (with bibliography), 1970.

[16] M. V. Civita, “L’assetto idrogeologico del territorio ital-iano: Risorse e problematiche,”[Hydrogeological outline of the Italian territory] Quaderni S.G.I., 3, 30, pp. (edition on line) www.socgeol.it, 2008.

[17] M. V. Civita, A. Massarutto, and G. Seminara, “Groundwa-ter in Italy: A review,” EASAC Report on Ground Waters in Southern Europe Mediterranean Countries, Atti Conv. Accad. Lincei “Giornata dell’ Acqua 2008” (in print).

[18] J. Vrba and M. V. Civita, “Assessment of groundwater vulnerability,” Guidebook on mapping groundwater vul-nerability, J. Vrba & A. Zaporozec (Edit.) IAH, Int. Con-trib. to Hydrogeol, 16, Heise, Hannover, pp. 131 (with bibliography), 1995.

[19] L. Aller, T. Bennet, J. H. Lehr, R. J. Petty, and G. Hackett, “DRASTIC: A standardized system for evaluating groundwater pollution potential using hydrogeologic settings,” NWWA/EPA Ser., EPA600/287035, Vol. 455 pp. 11 Maps (with bibliography), 1987.

[20] R. Piemonte, “Relazione finale del Progetto Bacino del fiume Tanaro: Studio sui potenziali rischi dovuti all’ allu-vione del novembre 1994 e realizzazione di una rete di monitoraggio delle acque sotterranee nonché identificazi-one dei siti potenzialmente pericolosi e valutazione della vulnerabilità della falda,” [Final report of the project “Tanaro River Basin: Study of the potential hazards from disastrous flood Nov. 1994, groundwater monitoring net-work, hazardous sites and aquifer vulnerability assessing”] Torino, pp. 254 (unpublished), 2000.

[21] M. V. Civita, M. De Maio, and E. Suozzi, “Upgrading the hydrogeological potential balance method for high mountain areas,” (in print), 2009.

[22] M. V. Civita and D. Persicani, “Approccio teorico alla definizione e stima della capacità di attenuazione del suolo nei modelli parametrici di valutazione della vulnerabilità degli acquiferi all’inquinamento,” [The- oretic approach when defining and assessing of the at-tenuation capacity of soils within the parametric models of evaluation of groundwater vulnerability to contamination] GEAM, Vol. 4, pp. 209–214, 1996.

[23] IPLA, “La capacità d’uso dei suoli in Piemonte ai fini agricoli e forestali,” Regione Piemonte, Istituto per le Pi-ante da Legno e l’Ambiente, pp. 290, 3 Maps, 1982.

[24] E. Capri, M. V. Civita, A. Corniello, G. Cusimano, M. De Maio, D. Ducci, G. Fait, A. Fiorucci, S. Hauser, A. Pis-ciotta, G. Pranzini, M. Trevisan, A. Delgado Huertas, F. Ferrari, R. Frullini, B. Nisi, M. Offi, O. Vaselli, and M. Vassallo, “Assessment of nitrate contamination risk: The Italian experience,” Journal of Geochemical Exploration, pp. 1–16 (DOI:10.1016/j.gexplo.2009.02.006), 2009.

[25] M. V. Civita, “QSPEC: Software codex,” Realize 1 (in edite), 1997.



Numerical Simulation of Pesticide Transport and Fate for Water Management in the Fucino Plain, Italy

Marco PETITTA1, Miguel A. MARIÑO2 1Dipartimento Scienze della Terra, Università “La Sapienza”, Roma, Italy

2Department of Land, Air and Water Resources and Department of Civil and Environmental Engineering, University of California, Davis, CA, USA

E-mail: [email protected] Received September 23, 2009; revised October 23, 2009; accepted November 18, 2009

Abstract A three-phase pesticide transport model is used to verify by numerical simulation, the influence of different parameters on infiltration through soil and/or surface runoff processes. Simulations are performed for a typi-cal sandy loam potato field of Italy’s Fucino Plain, to explain the occurrence of measured concentrations of pesticides (mainly Linuron) in both surface waters and groundwater. Simulations take into account agricul-tural practices, climatic conditions, and soil characteristics. Results focus on the role of rainfall events and irrigation, of related infiltration amount and distribution, and of root zone thickness in influencing pesticide fate and its possible concentration increase through the years. Modeling results positively fit with the back-ground knowledge of the Plain hydrology, showing the prevalence of surface transport and a scarce possibil-ity for pesticides to reach groundwater in an average rainfall/irrigation scenario. Meanwhile, specific water management strategies are suggested to limit the occurrence of local groundwater pollution, related to high aquifer vulnerability zones, controlling inappropriate irrigation and pesticide application. Keywords: Mathematical Models, Pesticides, Unsaturated Zone, Groundwater Pollution, Italy

1. Introduction Detection of pesticides and their breakdown products in surface water and in groundwater systems is needed due to their detrimental environmental impact. Pesticides can reach surface water by runoff or by infiltration and seepage into water courses. Infiltration of rainfall and irrigation waters can leach pesticides to the water table, causing contamination of aquifers. Prevalence of one of these processes mainly depends on the amount and dis-tribution of recharge and on the hydraulic conductivity of the unsaturated zone.

The transport and fate of contaminants is a process that requires the knowledge of many parameters, such as soil physical, (bio)chemical and hydrogeological proper-ties as well as climatic conditions and agricultural prac-tices. The types of pesticide (herbicide, insecticide, fun-gicide) and crop also influence the process. Due to the high number of variables, a study of contamination by pesticides is not feasible by large-scale in situ experi-ments. A different approach is the study of entire catch-ment based on observation points [1–4], taking into ac-count both hydrogeological context and hydrodynamics

[5–7]. An easier way is represented by laboratory ex-periments [8–12], while a credible and diffused tool is the use of mathematical models to simulate the transport and fate process. Among the large number of transport models available [13–26], the integrated pesticide trans-port model (IPTM) developed by [27] is chosen for this study. Thus, this paper is an application of a well-tested and known pesticide transport model [27,28].

To compare simulation results with field data, use was made of field data collected from the agricultural area of the Fucino Plain, Central Italy, which has been studied in the last ten years from hydrological, hydrogeological, and agricultural points of view [29–32].

The Fucino Plain (200 km2 wide) was the largest lake in Central Italy (Figure 1), reclaimed in the 1800s for agricultural purposes. The fractured carbonate aquifers surrounding the Plain feed high-discharge springs and streambed springs, which ensure steady discharges even during the dry season [30]. The heterogeneous aquifer of the Plain, having a variable vertical permeability, is sup-plied by groundwater seepage and by direct infiltration from rainfall. The long-term water balance of the Plain ha 700 mm/y of rainfall, 450 mm/y of evapotranspiration, s

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Figure 1. Hydrological setting of the Fucino Plain. Main network of artificial canals is shown by black thin lines. 1: Plain aq-uifer, corresponding to the agricultural area; 2: fan and detrital deposits connecting carbonate aquifers to the Plain aquifer; 3: ancient alluvial deposits (aquitard); 4: terrigenous deposits (regional aquiclude); 5: carbonate aquifers (recharge area of springs); 6: climatic stations; 7: main springs; 8: main streambed springs; 9: public irrigation wells; 10: drinking water wells; 11: main directions of groundwater flow. and consequently 250 mm/y of water excess in the Oc-tober-March period [30]. As a consequence, crop irriga-tion was based on a sustainable use of surface water and, increasingly, groundwater through the 1980s. However, during the past 15 years, due to the concurrence of a natural decrease in spring discharge and the increase of pumping and water requirements for irrigation, a signifi-cant water shortage in the summer has been observed. Ignoring signs of water and environmental imbalance of the water-man-agriculture system, historical farm crops, mostly wheat, potato and sugar beet, were progressively and rapidly replaced by water-intensive horticultural crops [30]. This transition to an intensive agriculture has been accompanied by high water demand and by wide use of pesticides. In addition, the decreasing discharge in the canals nullifies the effect of dilution of the pollutants entering surface waters, mainly residues of fertilizers [32] and pesticides. In this framework, surveys conducted on both surface water and groundwater have shown the presence of pesticides, mainly Linuron, Dichloran, and Carbaryl, with concentrations ranging from 0.02 to 2.8 g/L in surface water and from 0.03 to 0.5 g/L in ground-water [33]. Those concentrations are frequently higher than threshold values (0.1 g/L in groundwater and sur-face water for human use) allowed by Italian laws and

European Union Directives [34–36]. There is a need to clarify how surface runoff and/or

infiltration processes allow pesticides to reach canals and/or groundwater. Because of focus on pesticide oc-currence in surface waters and groundwater, gaseous and adsorbed components of pesticide fate are not studied in detail. The IPTM-CS model [28,37] takes into account those components as functions of parameters that have been considered constant during these simulations (e.g., organic matter content for the adsorbed component). Contribution of pesticides on volatilization, adsorption, and decay has been considered as losses for water sys-tems.

The aim of this study is to verify by numerical simula-tion modeling how various parameters (agricultural prac-tices, climatic conditions, soil and vadose zone hydraulic conductivity) can affect surface runoff and infiltration, influencing pesticide transport in soil and unsaturated zone and its fate in surface water and groundwater. Iden-tification of the role of different parameters and evalua-tion of their influence on the numerical simulation results represent the methodological goal of the study. In addition, the achievement of this goal is important for water man-agement, making possible recommendations for inte-grated water-pesticide-crop management in the study area.

M. PETITTA and M. A. MARIÑO 31 2. Materials and Methods Derived from the physically-based analytical model of Hantush and Mariño [38], the adopted mathematical model, with a new Windows-based interface (IPTM-CS), is a hybrid time-continuous and space-discrete semidis-crete model, which takes advantage of both analytical and numerical methods [27,37]. The model is able to deal with physical and biochemical processes related to one-dimensional vertical water flow and three-phase pesticide transport (dissolved, volatilized, adsorbed) in the vadose zone (separated in a root zone and in a deep vadose zone), where complete mixing is assumed. The adoption of a semidiscrete solution allows the simulation for variably-saturated porous media with time- and space-variant parameters under conditions of heterogene-ous media, unsteady flow fields, and space-time-de-pendent physical and biochemical processes concerning pesticide environmental fate. A complete description of the structure of the model and various solution methods are contained in [27,37]. The model has been used in previous studies with consistent results [27,39].

The model is able to simulate pesticide transport both in plant canopy and vadose zone systems, considering different methods of irrigation (over- and under-canopy), surface runoff, and possibly of erosion. A one-dimen-sional, physically-based, compartmental model is used for simulating water flow along the soil profile, divided into surface zone, plant root zone and deep vadose zone, as schematically shown in Figure 2. The new Windows- based interface of the IPTM-CS model [27] allows easier input and data processing. The large number of tables and figures included provides specific values/ranges of the different input parameters; the reference data are adopted for lacking data or for matching with field- measured data.

In this study, several simulations on representative soil columns were conducted for different situations, starting from real data. First of all, the soil profile was discretized as follows: a) the surface layer was represented by one cell, with an assumed thickness of 0.005 m; b) the root zone was divided in 10 cells of equal thickness, consid-ering a total thickness ranging from 30 to 70 cm for dif-ferent root zones; as a result, each cell is 1/10 of the as-sumed total thickness (corresponding to 3 cm for cell when the total thickness is 30 cm, 4 cm for cell in a root zone of 40 cm, etc.); and c) the vadose zone was divided in 10 cells of 20 cm thickness each, for a total of 2 m.

This scheme allowed simulation of different thick-nesses of the root zone (from 30 to 70 cm, as field data show), fixing the same structure of the model (10 cells for the root zone), simplifying data input and output. The vadose zone was chosen to have initially a thickness of 2 m, which can be modified taking into account a water table depth ranging from 0.5 to 2.5 m below ground sur-

face. Considering the value which corresponds to the water table depth in the simulated vadose zone, the evaluation of concentration at every possible water table depth can be obtained within the same simulation.

The studied area is 10000 m2, which corresponds to an agricultural unit in the Fucino Plain; the watershed area is about 131 km2, including the entire ancient lake area. The time step adopted was one day for one entire year. Spatial discretization has been assumed appropriate with respect to the time step, considering that the IPTM-CS model does not take into account the process of molecu-lar diffusion and thus evaluation of Peclet number is not necessary. Otherwise, the mechanical dispersion is con-sidered in the simulation.

All performed simulations started on April 1, when agricultural practices including pesticide application at the start of the cropping season occurred. Daily data re-quired for simulation referred to 1989-2004, for the Fu-cino Ottomila station, located at the center of the Fucino Plain. By taking into account similar trends observed on monthly long-term data (1921-2004), the 1990-93 three- year sequence, representative of different climate regi-men, was used in all simulations. In fact, rainfall in sea-son 1990-91 was higher than the average (+29%), season 1991-92 can represent the average (-2%), and season 1992-93 the low estimate of rainfall (-33%). Tempera-ture daily data were used to calculate daily potential evapotranspiration, using the method proposed by [40].

Simulations were conducted on potato, which is the most common crop in the Plain, representing 23% of the agricultural surface in the last 15 years. Parameter ranges related to potato crops, obtained by databases and tables included in the IPTM-CS program [41–44] are shown in Table 1. Other crops, less represented in the Plain, were not considered in this paper. The crop cycle of potatoes in the Plain helped to determine the values of related parameters. In detail, because potato is cultivated from May to August, both crop coefficient and canopy inter-ception are relevant in this period, while the plant leaf

Figure 2. Scheme of the IPTM-CS model, showing proc-esses taken into account by the model (after Chu and

ariño, 2004). M




32

Table 1. Parameters used for sandy loam potato crop and Linuron pesticide.

Class Parameter Root Zone Vadose Zone

Saturated hydraulic conductivity (m/s) 6x10-6 6x10-5

Saturated water content (m3/m3) 0.41 0.43

Residual water content (m3/m3) 0.065 0.045

Field capacity (m3/m3) 0.207 0.091

Wilting point (m3/m3) 0.095 0.033

Initial water content (m3/m3) 0.16 0.35

Soil water retention parameter "n" 1.89 2.68

Soil porosity 0.453 0.437

Soil (sandy loam)

Bulk density (g/cm3) 2.6 2.6

Transpiration coefficient 0.8 0.8

Leaf area index 0-4

Crop coefficient from 0 to 1.15

Plant growing index May, June and July

Plant canopy (potato)

Canopy interception capacity 0.01-0.1

Distribution Coefficient Kd (cm3/g): 3.84 3.84

Henry's constant KH 3.089x10-6

First-order decay rate (1/d) 0.012

Longitudinal dispersivity (m) 0.76

First order decay/volatilization rate in canopy (1/d) 0.0666

Diffusion coefficient in pure water (m2/d) 0.000043

Diffusion coefficient in free air (m2/d) 0.43

Thickness of the air boundary layer (m) 0.005

Pesticide (Linuron)

Log of octanol-water partition coeff. Kow (cm3/g) 2.76

Runoff curve number for growing days 86

Runoff curve number for no-growing days 87

Ratio of init. abstraction to potential retention 0.2

Soil cover factor 0-0.5

Hydrologic parameters

Irrigation (cm/d) 1.47

area index is active during plant growth (May, June and July).

Characteristics of soils were determined by sampling of root zone soil and further laboratory analyses. The three more representative soils are sandy loam, clay loam, and silty-clay loam by the ASTM classification [45]. The granulometry, the initial water content and the bulk den-sity were laboratory-determined, whereas the saturated hydraulic conductivity was calculated by constant-head, field permeameter tests. From the analysis of soil sec-tions, it was evident that under the root zone there is a more permeable vadose zone, characterized in the sandy loam root zone by the presence of gravels and by a low percentage of silt. Direct surveys did not show fractures or preferential flowpaths in the root zone. This could have resulted in a lower hydraulic conductivity for the root zone (e.g., for sandy loam 6 x 10-6 m/s) and a higher one for the vadose zone (up to 6 x 10-4 m/s). The vertical distribution of the saturated hydraulic conductivity, from the root zone to the lower limit of the vadose zone, matched the average value obtained by in-situ per-meameter tests for the entire soil thickness (2 x 10-4 m/s).

Different values were also used for other soil parameters, resulting in different characteristics for the root zone and the deep vadose zone in these simulations. Figures and tables included by the IPTM-CS program provided val-ues for parameters which have been not measured and provide methods for the determining these parameters [23,46,47]. The soil parameterization was based on Van Genuchten’s relationships [48]. Soil parameters adopted for simulation in a sandy loam soil are shown in Table 1.

Pesticide parameters for Linuron, Dichloran, and Car-baryl were obtained from public and web databases [49] and tables attached to the IPTM-CS program [14,50,51]. Linuron is a pre- and post-emergence herbicide used to control annual and perennial broadleaf and grassy weeds on both crop and non-crop sites; it is used frequently for potatoes and carrots. Dichloran is a fungicide widely used for the pre-harvest treatment of several fruit and vegetables crops, including potatoes. Carbaryl is a com-monly used wide-spectrum carbamate insecticide of large use, which controls over 100 species of insects on several fruits and vegetables [49].

Table 1 shows values of parameters used for Linuron’s

M. PETITTA and M. A. MARIÑO 33 simulation. Use was made of results of previous surveys as targets for the simulated concentrations. In other words, measured pesticide concentrations in 2004 and 2006 in surface water and groundwater were used to de-termine if the simulated concentrations in soil and in groundwater give similar values. Data of pesticide con-centrations obtained by HPLC analysis [33] showed ab-sence of pesticides in detectable amounts in waters dur-ing winter (December 2003) and spring (early April 2004). This is in agreement with the agricultural sched-ule in which the first application of pesticides occurs approximately in mid-April. In summer 2004, Linuron was found in 30 of 35 samples, Dichloran in 6 of 35, and only one case of Carbaryl presence; in Fall 2004, Lin-uron was detected only in 7 of 35 samples, while Di-chloran was largely present in 12 of 35 samples, and Carbaryl was measured in 4 samples [52]. At the end of April 2006, a new survey was conducted in 20 sites se-lected from the previous 35 sites, where higher concen-trations were found in 2004. Linuron was found in 17 of 20 water samples and Dichloran in 7 of 20. Concentra-tions ranged from 0.03 g/L to 2.8 g/L, with relative abundance in surface waters and lower concentration in groundwater (between 0.03 and 0.5 g/L). June and Sep-tember 2006 surveys confirmed previous results, having 100% of Linuron occurrence in June (average: 1.72 g/L), while in September less than half off samples have Lin-uron, with a lower average of 0.1 g/L. Dichloran was found in only one sample in June, having major occur-rence in September 2006. In groundwater, mainly Lin-uron has been found, having the occurrence of 80% in June 2004 and 2006. Occasionally, Dichloran was found in traces (< 0.1 g/L). Samples without trace of Linuron corresponded to groundwater related to deep circulation (deep wells), while in shallow groundwater (shallow wells and springs) Linuron normally was detected, in September 2006 too. Table 2 gives concentration values measured in 2004-06 surveys for pesticides in surface waters and groundwater.

Given that the watershed under consideration is flat, simulations did not take erosion into account. Curve numbers, potential retention, and soil cover factor were evaluated by tables attached to the IPTM-CS program for potato crops and above-mentioned soils [53]. Irrigation practice information was obtained directly by farmers’ interviews and by the agricultural schedule of the Plain. For potato, under-canopy irrigation was per-formed four times between June and July with an interval of 10 days. The irrigation rate was 0.367 cm/hour, with each irrigation occurring for 4 hours resulting in an ap-plication of 1.47 cm.

Finally, pesticide applications, determined by the pre-viously mentioned farmer interviews and by the total amount of pesticides sold in the studied area, were con-sidered as follows: for Linuron, one application at the beginning of April with a rate of 0.117 g/m2; for Di-chloran, two applications every 10 days after June 1, with a rate of 0.1 g/m2; and for Carbaryl, three applica-tions every 10 days starting from June 20, with an in-creasing rate ranging from 0.05 to 0.07 g/cm2. The pesti-cide application was considered instantaneous and un-der-canopy because it was spread mainly in non-growing periods. The initial pesticide concentration entered in the simulation files was zero for the first year; for the fol-lowing years, the value of initial concentration corre-sponded to the amount obtained by simulation in the last day of the previous year, to consider possible accumula-tion processes into the soil. 3. Results Main parameters influencing dissolved pesticide fate and its concentration in waters have been identified as pesti-cide characteristics, including amount, rate, and single properties of each compound used, recharge (amount and distribution, due to both rainfall and irrigation practice), and physical soil characteristics (e.g. size, saturated hy-

Table 2. Measured pesticide concentrations in water samples (35 samples in 2004; 20 samples in 2006; n.f.= not found).

Pesticide (in g/L) 6/2004 9/2004 4/2006 6/2006 9/2006

max. 2.81 0.07 1.10 13.13 0.17

average 0.43 0.04 0.57 1.72 0.1

min. 0.03 0.03 0.21 0.3 0.07

Linuron

occurrence 86% 20% 85% 100% 44%

max. 0.65 0.14 2.33 -- 0.56

average 0.15 0.05 0.46 0.08 0.08

min. 0.02 0.02 0.03 -- 0.06

Dichloran

occurrence 17% 34% 35% 5% 38%

max. -- 0.40 n.f. n.f. n.f.

average 0.04 0.13 n.f n.f n.f

min. -- 0.04 n.f. n.f. n.f.

Carbaryl

occurrence 3% 12% -- -- --




34

Table 3. Comparison between simulated and measured Linuron concentrations in surface waters. Simulated values have been obtained considering the average runoff in 15 days (one week before and one week after sampling) (modified from Pacioni et al., 2007). Data in italics highlight periods showing significant discrepancies (April samplings).

Sampling day Runoff (g

ha-1) Total runoff

(g d-1) Discharge

(m3 d-1) Simulated pesticide con-

centration (µgL-1) Measured pesticide

concentration (µgL-1)

09/23/2006 06/15/2006 04/26/2006 09/14/2004 06/30/2004 04/20/2004 12/01/2003

0.52 0.026

2.5 0.12

0 3 0

72.6 5.72 550 26,4

0 660

0

172800 216000 259200 233280 300240 345600 328320

0.6 0.1 10 0.1 0

1.9 0

0.1 0.7 1

0.04 0.1 0 0

draulic conductivity, thickness of root and vadose zones).

To calibrate and validate the model, preliminary simulations of Linuron contribution to the runoff were com-pared with its pesticide concentrations found in surface waters during all 2004 and 2006 surveys (Table 3). Lim-ited occurrence of pesticide in groundwater did not allow a similar comparison for groundwater. Contaminant dilu-tion in the canal discharge, variability of the applied pes-ticide amount, and interference of more than one rainfall event have been considered [54]. To take into account possible shifts in the real pesticide application by farmers and the time transit of runoff waters into the Plain, an average of 15 days of the pesticide runoff obtained by simulation has been adopted, considering 7 days before and after sampling. Pesticide amount really used by farmers can not be exactly evaluated in detail for each agricultural unit. These uncertainties certainly affect the comparison between real and simulated concentration, but at the entire basin scale (130 km2) application and runoff processes can be compared, looking for the pres-ence of pesticides in surface waters in a week after the presumed date of pesticide application. Results of this comparison were oriented to highlight the role of runoff, while the specific aim of the research was to simulate pesticide fate in soil and groundwater.

Simulation results showed a significant agreement between simulated pesticide concentration due to runoff and measured concentration found in surface waters. Taking into account the difficulty to verify days and amount of pesticide application, which can locally change with respect to the assumed standard, simulation results were relatively consistent with the monitored ones. Exceptions were noted in April surveys, when the local effect of pesticide application can highly affect pesticide content in surface waters, causing outlier peaks in moni-tored surface waters (Table 3). Discrepancies between simulated and real runoff data did not affect the reliabil-ity of simulations of infiltration to groundwater, as con-firmed by specific column experiments [55-56].

The model calibration using runoff data can be ac-cepted for further simulations, taking into account the aim of this research which is to provide a preliminary evaluation of groundwater vulnerability to pollution by

pesticide at the basin scale. Considering the adopted methodology as suitable for the study area, several simulations were conducted to determine the effects of hydrological processes on pesticide fate. Firstly, simula-tions using three different soils (sandy loam, silty-clay loam, and clay loam) and for three detected pesticides were performed, to identify situations that can favor groundwater pollution. In soils with low hydraulic con-ductivity, like silty-clay and clay loams, pesticides reached the vadose zone only in undetectable concentra-tions, lower than 0.001 g/L at 0.5 m below ground sur-face. In contrast, results for pesticide applications in dif-ferent soils indicated that the runoff process is relevant during irrigation practice and natural decay is largely prevalent for pesticides having low persistence such as Dichloran and Carbaryl (half-life of few days for horti-cultural crops). For both of those pesticides, simulated concentrations at the base of the root zone were of the same order of magnitude (less than 0.001 g/L at 0.5 m below ground surface) and several orders of magnitude smaller at lower depths. Conversely, application of Lin-uron, which showed longer persistence in the system, caused highest concentration values in soil pore water. Simulation results (Figure 3) showed the variation of pesticide content with depth in the unsaturated zone. In

1,E-09

1,E-06

1,E-03

1,E+00

1,E+03

0 30 60 90 120 150 180 210 240 270 300 330 360Days

Con

cent

ratio

n (

g/L)

0,005 m0,41 m0,81 m1,01 m1,61 m2,01 m

Figure 3. Effect of depth on dissolved Linuron concentra-tion with time in a sandy loam soil (year 1990-91). The con-centrations shown are those at various depths below ground for a root zone thickness of 30 cm. Simulation period starts on April 1.

M. PETITTA and M. A. MARIÑO 35 the case of high groundwater vulnerability, as for a thin root zone (30 cm) in a sandy loam soil, dissolved Lin-uron reached 0.1 g/L at 0.5 m below ground and about 0.01 g/L at 1 m below ground (days 260-365 in Figure 3).

Considering this vulnerable scenario, additional simu-lations were performed using different values and distri-bution of the abovementioned parameters, starting from a standard scheme that simulates on a potato field the fate of Linuron, the largest occurring pesticide, in a sandy loam soil with 70 cm of root zone and 200 cm of vadose zone.

To evaluate the influence of recharge, different distri-butions of effective rainfall (rainfall minus evapotran-spiration) and irrigation were considered. When it rains in the days following the pesticide application on the ground surface, runoff can easily remove pesticide from the surface and transport it in surface waters. Simulations were conducted assuming non-rainy periods in the fol-lowing 7, 15, and 30 days since the application of the pesticide (Figure 4). Results indicated that if there is no rainfall after pesticide application, no substantial changes occur in the pesticide concentration in the soil pore water, throughout the year. In fact, the pesticide concentration trend significantly changed only in the spring and sum-mer (days 30-180 in Figure 4), when lower concentration values were registered in case of scarce rainfall. Similar results were obtained considering different years and pesticides. However, this situation which is typical of dry seasons is usually compensated by a major amount of irrigation.

Figure 5 shows a different trend in pesticide concen-tration obtained from application of higher irrigation amounts. Using as input a double irrigation time, the mobilization of the pesticide into the soil pore water oc-curred before the autumn infiltration recharge (day 200 in Figure 5), starting in the summer (day 130 in Figure 5).

1,E-06

1,E-04

1,E-02

1,E+00

0 30 60 90 120 150 180 210 240 270 300 330 360Days

Co

nce

ntr

atio

n (g

/L)

no rain 7days

no rain 15 days

no rain 30 days

real rain

Figure 4. Effects of no-rainy periods following the applica-tion (7, 15, and 30 days of no rain) on dissolved Linuron con-centration with time in a sandy loam soil (year 1990-91). The concentrations shown are those at the top of the vadose zone (10 cm below a root zone thickness of 30 cm) hence dif-ferent no-rainy periods. Simulation period starts on April 1.

1,E-03

1,E-02

1,E-01

1,E+00

0 30 60 90 120 150 180 210 240 270 300 330 360

Days

Con

cen

trat

ion

(g/

L)

real

double irrigation

double amount

two times

three times

Figure 5. Effects of different irrigation practices on dis-solved Linuron concentration with time in a sandy loam soil (year 1990-91). Double irrigation refers to a double irriga-tion rate (intensity of irrigation); double pesticide amount refers to a double mass of pesticide use during standard irrigation times; two-times and three-times refer to 8-hours and 12-hours of irrigation instead of 4 hours as standard. The concentrations shown are those at the top of the vadose zone (10 cm below a root zone thickness of 30 cm). Simula-tion period starts on April 1.

Modification in irrigation amount and time increased the pesticide concentration during the summer, according with the registered Linuron occurrence in groundwater.

By modifying the modality and quantity of pesticide application, significant changes occurred in the simula-tion results (Figure 5). Pesticide in the soil pore water showed the same trend in spring and summer, except for the concentration that is higher if a double amount of pesticide is used. Major changes were observed during autumn (days 190-220 in Figure 5), when the infiltration process begins: the larger the amount of pesticide used, the higher the pesticide concentration in the soil pore water, for doubling the pesticide for one, two, or three application times.

Several simulations indicated that infiltration from rainfall has a major influence on pesticide concentration through and at the end of the year. Because infiltration highly depends on effective rainfall, it is interesting to verify influences of real rainfall data for more than one year. The selected seasons 1990-91, 1991-92 and 1992- 93, were simulated for different root zone thicknesses of 30, 40, and 70 cm. Effective precipitation and pesticide runoff are shown in Figure 6. Spring and summer rainfall mobilized large amounts of pesticide remaining on the surface after application. Conversely, higher autumn rainfalls were not able to start a substantial Linuron run-off, because it is not largely present on the surface.

Simulation results of soil pore water for the above-mentioned three years of rainfall, at a depth of 41 cm below ground surface, below a root zone of 30 cm, are shown in Figure 7. First season with higher rainfall indi-cated a Linuron concentration above 0.1 g/L since au-tumn (day 200 in Figure 7). However, during the following




36

0

2

4

6

8

10

12

1/4/90 1/7/90 30/9/90 30/12/90 31/3/91 30/6/91 29/9/91 29/12/91 29/3/92 28/6/92 27/9/92 27/12/92 28/3/93

eff

ecti

ve

P (

cm)

-90

-70

-50

-30

-10

10

30

50

70

90

Lin

uro

n r

un

off

(g

)

effective P (cm)

Linuron runoff (g)

Figure 6. Daily effective rainfall and simulated Linuron runoff from April 1990 to March 1993.

1,E-06

1,E-04

1,E-02

1,E+00

0 30 60 90 120 150 180 210 240 270 300 330 360

Days

Co

nce

ntr

atio

n (g

/L)

90-91

91-92

92-93

1,E-06

1,E-04

1,E-02

1,E+00

0 30 60 90 120 150 180 210 240 270 300 330 360

Days

Co

nce

ntr

atio

n (g

/L)

90-91

91-92

92-93

Figure 7. Effects of different rainfall years (1990-91, 1991-92 and 1992-93) on dissolved Linuron concentration with time in a sandy loam soil. The concentrations shown are those at the top of the vadose zone (10 cm below a root zone thickness of 30 cm). Simulation period starts on April 1.

Figure 8. Effects of different rainfall years (1990-91, 1991-92 and 1992-93) on dissolved Linuron concentration with time in a sandy loam soil. The concentrations shown are those at the top of the vadose zone (10 cm below a root zone thickness of 70 cm). Simulation period starts on April 1.

season, considering the same initial pesticide application, higher concentration values were noted, not influenced by the lower total rainfall of this year. Meanwhile, sec-ondary but significant peaks were present (days 45 and 110 in Figure 7), due to high rainfall events (Figure 6). These results indicated that rainfall distribution and events affect pesticide concentration more than the total amount of rainfall. As shown for the least rainy third year, concentration values were in general lower, while the maximum value was reached in winter (day 240 in Figure 7), correlated to the rainfall observed at the end of December 2002 (Figure 6).

The influence of singular rainfall events was less evi-dent for soils having thicker root zones. Considering a 70 cm root zone (Figure 8), there were no influences of summer rainfall (as in July 1991) and the autumn peaks were less evident (day 230 in Figure 8), remaining under the limit of 0.01 g/L. During the least rainy third year, a decrease in pesticide concentration was observed at the end of the simulation (days 330-365 in Figure 8). In fact, autumn infiltration was negligible and the pesticide can not reach the vadose zone under 70 cm of root zone.

A sensitivity analysis of the results was conducted by taking into account these preliminary results, to under-

M. PETITTA and M. A. MARIÑO 37 stand the influence of several parameters known with some uncertainty, which can locally change in the Plain, such as hydraulic conductivity and root thickness. Simu-lations were conducted by varying root zone thickness from 30 to 70 cm, and using different hydraulic conduc-tivity values for root zone and vadose zone (ranging from 6 x 10-4 to 6 x 10-6 m/s). For root zone thickness of 30, 40, and 70 cm, simulations were performed for the se-lected three years (1990-93) to verify the possible in-crease of pesticide amount in soil pore water as a func-tion of time.

The process of migration of the pesticide through the soil was scarcely affected by soil saturated hydraulic conductivity (K), as it was shown by simulations per-formed changing the K value of both root and vadose zones (Figure 9), with the aim to replicate different field situations. Results using K values ranging from 6 x 10-4 to 6 x 10-6 m/s, in different combinations for root and vadose zones, indicated that pesticide concentration re-mains low, depending on the specific K value used. Dif-ferent results are observed by adopting a higher K for the root zone (10-4 m/s); in this case, the fast flow through the root zone allowed the pesticide to arrive at the vadose zone in high concentration. This situation, however, did not occur in the studied area, where the root zone was represented by a low K layer (< 10-5 m/s).

Simulation results showed that root zone thickness in-fluences time travel of pesticide after application (Figure 10), from 1-2 weeks for a thin root zone to 3-4 weeks for a thick root zone. When pesticide arrived at a fixed depth, there was a constant decrease in concentration with time. Only in October (days 190-210 in Figure 10), when ef-fective rainfall occurs, the pesticide concentration in-creased, reaching maximum values in approximately 30 days. This pattern was observed at every depth for every

1,E-03

1,E-02

1,E-01

1,E+00

0 30 60 90 120 150 180 210 240 270 300 330 360

Days

Co

nce

ntr

atio

n (g

/L)

Kr 6x10-6/Kv 6x10-5

Kr 6x10-6/Kv 6x10-6

Kr 6x10-5/Kv 6x10-5

Kr 6x10-6/Kv 6x10-4

Figure 9. Effects of saturated hydraulic conductivity, for root (Kr) and vadose (Kv) zones, on dissolved Linuron concentration with time in a sandy loam soil (year 1990-91). The concentrations shown are those at the top of the vadose zone (10 cm below a root zone thickness of 30 cm) hence different saturated hydraulic conductivities values (in m/s). Simulation period starts on April 1.

1,E-06

1,E-03

1,E+00

0 30 60 90 120 150 180 210 240 270 300 330 360

Days

Co

nce

ntr

atio

n (g

/L)

0,31 m

0,41 m

0,51 m

0,61 m

0,71 m

0,81 m

Figure 10. Effects of root zone thicknesses (from 20 to 70 cm) on dissolved Linuron concentration with time in a sandy loam soil (year 1990-91). The concentrations shown are those at the top of the vadose zone (10 cm below the root zone thickness) hence different root zone thicknesses. Simulation period starts on April 1. root zone thickness. Highest autumn concentrations, ranging from 0.5 to 0.01 g/L at the base of the root zone, decreased slightly for the rest of the year, approximately one order of magnitude less than maximum values (day 365 in Figure 10). 4. Discussion Simulated effects of different parameters on pesticide transport and fate agreed with observed data, confirming that the adopted methodology is representative for the study area. Type of pesticide was the first factor influ-encing the fate of the pesticide in the unsaturated zone. The negligible exposure levels obtained in the vadose zone for Dichloran and Carbaryl were consistent with their presence in surface waters during summer and au-tumn. Simulations suggested that runoff was responsible of their transport in surface water, by irrigation in sum-mer and by rainfall in autumn. Those pesticides quickly decayed in the root zone and when infiltration occurred in the autumn, they showed a peak in concentration, fol-lowed by a marked decrease for the natural decay. Ex-posure levels of the above-mentioned pesticides were very low in soil pore water (< 0.001 g/L) and there was scant chance to reach the water table. This hypothesis is enforced by the low hydraulic conductivity of silt and clay soils, in which infiltration is at a low rate; conse-quently, movement of water and pesticide through the vadose zone is slow.

Simulation results indicated that Linuron could reach the water in the vadose zone and the water table in con-centrations near to and over the Italian law limits, as reg-istered during surveys. Higher persistence makes this pesticide sensitive to the infiltration process in the au-tumn (days 190-200 in Figure 3), showing the highest concentration irrespective of the root zone thickness,




38

followed by steady values for the rest of the year. As a consequence, in the following year the initial concentra-tion in the soil pore water was significant, possibly higher than in previous periods. Its increase over time in groundwater occurred only after high infiltration years and in soils with limited thickness of the root zone (Ta-ble 4).

Hydraulic conductivity of the vadose zone and water table depth determine the groundwater vulnerability and consequently the possibility of contamination by pesti-cides. Soil hydraulic conductivity, both for root and va-dose zones, scarcely affected pesticide concentration, in a range of two orders of magnitude (10-4-10-6 m/s), which corresponded to the field range of saturated hydraulic conductivity of the soils. Where the water table is located no more than 1 m below ground surface, simulations showed pesticide concentrations coincident with the measured ones. This means that only shallow groundwa-ter can be contaminated by Linuron for the considered physical, chemical, and climatic conditions. Detectable concentrations are obtained only in vadose zones of high hydraulic conductivity (e.g. sandy-loam soil) (Figure 3), confirming the possibility of groundwater contamination by this pesticide.

Rainfall amount, but especially rainfall distribution and single events, largely affected the infiltration and runoff processes and, consequently, the fate of pesticides. Simulations of three real rainfall seasons (1990-93) sug-gested that high spring and summer rainfall can mobilize pesticide to surface waters. Autumn rainfall infiltrates, causing pesticide mobilization and concentration peaks in the vadose zone and in groundwater. Single events and high irrigation rate can have the same effect in summer, especially in soils with thin root zones. Increase of pesti-cide amount in soil pore water through the years is pos-sible, but not common, following high rainfall years.

Root zone thickness influenced pesticide concentration in the soil pore water. Thin root zones favored short transit time and high concentration during spring, but they have limited influence on autumn and winter con-centrations. For root zone thicknesses greater than 30 cm,

pesticide concentration was found higher during au-tumn-winter than after application. It can be asserted that where the thickness of root zone is high (> 50 cm) there is no increase of pesticides in soil pore water during low rainfall seasons.

Agricultural activities represent an additional parame-ter able to significantly influence pesticide transport and fate. If farmers apply irrigation amounts higher than crops require, as often happens in the Plain, this addi-tional water induced infiltration and subsequent mobili-zation of the pesticide to shallow groundwater. In detail, during dry seasons, farmers increased irrigation amount in spring and additional infiltration mobilized the pesti-cide into the soil pore water driving it to shallow groundwater, explaining summer occurrence of Linuron in 2004 and 2006 field surveys. Otherwise, the declared amount of irrigation did not affect pesticide concentra-tion because it did not cause infiltration and all irrigation water was consumed by plant and evapotranspiration. Application by farmers of larger amounts of pesticide than they declare (by higher quantity or additional treat-ments) caused higher concentration in the soil and groundwater in the following year, showing pesticide increase over time in the unsaturated zone and, possibly, in groundwater.

From these findings, it is possible to build a concep-tual model of pesticide fate in the Fucino Plain, related to Linuron occurrence. After April pre-treatment, a modest percentage (<15%) of the pesticide was washed off and transported into neighboring canals. Irrigation practices in early summer during drought seasons contributed to runoff and washoff to the canals too, causing peaks of pesticide in surface waters. At the same time irrigation accelerated infiltration through the soil, allowing pest-cide to reach shallow groundwater, as observed by Li-uron occurrence in summer in springs and wells. Single-rainfall events and large autumn rainfall contributed to the infiltration and enriched the soil pore water of con-taminants. In soils with a medium hydraulic conductivity (>10-5 m/s) and a thin root zone (< 50 cm), Linuron

Table 4. Linuron maximum content in the three simulated years at the surface, at the interface of the root/vadose zone, and at fixed depths (-10, -30 and -90 cm below the interface root/vadose zone), for different root zone thicknesses (30, 40 and 70 cm).

Higher Simulated Concen-tration (g/L)

Year At the

surface At the base of

root zone -10 cm inside the

vadose zone -30 inside the vadose zone

-90 inside the vadose zone

1990-91 1140 2,22 0,285 0,0587 0,00138

1991-92 1140 2,13 0,316 0,0550 0,00050 30 cm roots

(-40, -60, -120 cm) 1992-93 260 1,08 0,178 0,0236 0,00030

1990-91 1140 0,48 0,163 0,0301 0,00006

1991-92 1140 0,49 0,131 0,0044 0,00025 40 cm roots

(-50, -70, -130 cm) 1992-93 260 0,26 0,044 0,0104 0,00010

1990-91 1140 0,04 0,007 0,0008 0,000001

1991-92 1140 0,03 0,005 0,0010 0,000008 70 cm roots

(-80, -100, -160 cm) 1992-93 660 0,01 0,003 0,0005 0,000003

M. PETITTA and M. A. MARIÑO 39 reached groundwater in detectable concentrations (0.5- 0.01 g/L), locally over the legal limit of Italian law. During rainy seasons, Linuron concentration showed significant peaks in the soil pore water and could be driven to the water table in the following year, leading to groundwater contamination. 5. Conclusions The IPTM-CS model was used with a daily time step to simulate fate and transport of pesticides found in surface waters and groundwater of the agricultural region of the Fucino Plain in Central Italy, through a representative soil column. Obtained results provided a better understanding of processes of transport through soil of pesti-cides found dissolved in water. Calibration was based on comparison of simulated and measured pesticide concen-trations in surface waters during 2004 and 2006 surveys.

Conducted simulations allowed to quantify the influ-ence of each parameter on infiltration and on runoff and thus to evaluate the groundwater pollution vulnerability in different conditions in the Fucino Plain. Rainfall oc-curring immediately after pesticide spreading triggered runoff transport, explaining high concentrations of dif-ferent pesticides in surface waters at different times. In-filtration process started in fall at the end of irrigation season, due to effective rainfall; only persistent pesti-cides like Linuron were available in the vadose zone and reached the water table, causing contamination. This situation is subjected to additional constrains, like thin root zone (less than 50 cm) and high hydraulic conduc-tivity (K>10-5 m/s), related to high vulnerability zones.

This general scenario can be locally influenced by human activities, if irrigation time and/or pesticide ap-plication are increasing, enhancing the infiltration proc-ess, in agreement with the observed presence of pesti-cides at time and locations unexpected by standard simulations.

From a methodological point of view, obtained results confirm the usefulness of the IPTM-CS model in simu-lating pesticide fate in an agricultural area. This approach, which considered a limited but representative range of parameters (soil type, pesticide, crop, water table, etc.) can reduce time-expensive field surveys and lab analyses, which in a wide area can not be performed in detail for each location.

6. Acknowledgements

We thank Dr. Xuefeng Chu (North Dakota State Univer-sity) for providing the IPTM-CS software and for his support with the model. We also thank: Ezio Burri (Di-partimento Scienze Ambientali, Università dell’Aquila) coordinator of research project “Water and agriculture in the Fucino Plain”; A.R.S.S.A. local authority for agri-

cultural development; PhD students Eva Pacioni and Andrea Marchetti for field data; graduate student Maria Fanelli and Dr. Fabrizio Ruggieri for pesticide laboratory analyses; and GTA private company for pesticide and potato parameters. 7

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Sublethal Antimony (III) Exposure of Freshwater Swamp Shrimp (Macrobrachium Nipponense): Effects on Oxygen

Consumption and Hepatopancreatic Histology

Jen-Lee YANG1,2＊, Tung-Jer HU3, Hong-Yuan LEE4

1Department of Life Science, Chinese Culture University, Taipei, Taiwan, China 2Center of General Education, National Taipei College of Business, Taipei, Taiwan, China

3Department of Computer Application Engineering, Lanyang Institute of Technology, Taiwan, China 4Department of Civil Engineering, National Taiwan University, Taipei, Taiwan, China

E-mail: [email protected] Received October 28, 2009; revised November 12, 2009; accepted November 20, 2009

Abstract This study was an attempt to realize the effects of antimony on freshwater swamp shrimp (Macrobrachium nipponense). An experiment of this nature, which have not previously been carried out in this species. First, median lethal concentrations were determined in acute toxicity tests. The 96-h LC50 value was 6.748 (5.728-7.950) mg Sb/l for adult M. nipponense and 1.635 (1.271-2.103) mg Sb/l for juvenile M. nipponense. Juvenile M. nipponense were exposed to 4 different sublethal levels of antimony (0.1, 0.4, 0.8, and 1.2 mg Sb/l) over a 7-d test period and a 7-d recovery period. After 30 min (acute), there was an increase in the amount of oxygen consumed in all exposed groups. On days 3, 7, and 14, decreases in oxygen consumption were significant (p < 0.05) for the higher-exposure level groups (0.8 and 1.2 mg/l). Light microscopy inves-tigations showed histopathological alterations in the hepatopancreas which correlated with exposure concen-trations. The alterations included degenerative changes in the lumen, a reduction in the lumen volume, and injury to epithelial cells in the histoarchitecture of hepatopancreas. Keywords: Antimony, Macrobrachium Nipponense, Oxygen Consumption, Hepatopancreas

1. Introduction Antimony (Sb) compounds such as indium antimony (InSb) and gallium antimony (GaSb) are important mate-rials for the manufacture of integrated circuits and opto-electronic devices in the semiconductor industry [1]. Manufacturing processes devoted to the fabrication of GaSb-based semiconductor devices generate large vol-umes of wastes that contain the toxic metals antimony and gallium. In addition, both metals are listed as hazards by the Environmental Protection Agency in the US [2]. Previous reports indicated that mammalian exposure to trivalent forms of Sb can cause severe liver damage, hemolysis, hematuria, and circulatory disease. And an-timony trichloride (SbCl3) induced sister chromatid ex-changes (SCEs) in V79 cells and apoptosis in human fibroblasts (HFs), a human bronchial epithelial cell line (BES-6), and a Chinese hamster ovary cell line (CHO- K1) [3,4].

Industrial spills can lead to high concentrations of

toxic materials in water, affecting freshwater ecosystems with acute and chronic health effects. Toxicants may significantly damage certain physiological and bio-chemical processes when they enter the organs of fishes [5]. The liver is an important organ involved in meta-bolic processes and in detoxification of xenobiotics. In some situations, poisonous materials may accumulate in the liver to toxic levels and cause pathological alterations [6]. Histopathological alterations are recognized and commonly used diagnostic tools in aquatic toxicology studies [7]. Oxygen consumption is widely considered to be a critical factor for evaluating the physiological re-sponse and a useful variable for an early warning for monitoring aquatic organisms [8]. Like most aquatic organisms, they maintain their oxygen consumption at a constant level along a gradient of environmental oxygen concentrations, until a critical oxygen concentration is reached, and below which oxygen consumption begins to fall. Under conditions of stress, this critical oxygen con-centration is likely to increase, reflecting organisms’

J. L. YANG ET AL. 43 capacity for coping with environmental perturbations [9, 10].

Swamps are among the world’s most productive wet-land ecosystems, and they are also important as nursery grounds for many ecologically and economically impor-tant species. The freshwater swamp shrimp (Macro-brachium nipponense) is a common aquatic invertebrate widely distributed in upper and middle sections of rivers throughout the eastern Asia-Pacific area. The purposes of this study were to examine the effects of antimony on acute toxicity and the effects of sublethal antimony con-centrations on the oxygen consumption and hepatopan-creastic histology of M. nipponense, so that this evidence could then be used to evaluate possible adverse effects of this metal on the freshwater swamp shrimp. 2. Materials and Methods Juvenile and adult of the freshwater swamp shrimp (M. nipponense) were obtained from local commercial sup-pliers. Shrimp were transported to a glass aquarium in our laboratory which was equipped with a water-cycling device; dechlorinated tap water (with a pH of 7.4-8.1, dissolved oxygen (DO) of 7.0-7.7 mg/l, and hardness of 38-45 mg CaCO3/l) was used during the entire experi-ment. The temperature was maintained at 24.0 ± 0.5 ºC, and a 12-h light and 12-h dark photoperiod was used. Shrimp were acclimated for 2 weeks and fed an aquar-ium shrimp mixture every day. Juvenile (4 weeks old, 0.42 ± 0.17 cm in total length) were used for acute toxic-ity tests and oxygen consumption tests; adult (17 weeks old, 1.2 ± 0.38 cm in total length) were used for the acute toxicity tests and histological examinations in the initial experiments. Antimony trichloride (purity ≧ 99%) was purchased from Sigma (St. Louis, MO, USA). Stock so-lutions were prepared in deionized water (1000 mg/l test chemical in 0.1% nitric acid).

Laboratory static renewal tests [11] were conducted to determine the median lethal concentrations (LC50) for juvenile and adult M. nipponense. Ten shrimp of similar size were randomly sampled and placed in 10- l glass beakers. After 24 h of acclimat izat ion, the shrimp were exposed to different ant imony concent rat ions (0, 0.1, 0.2, 0.5, 1.0, 2.0, 4.0, 8.0, 12.0, 14.0, and 16.0 mg Sb/l) for 96 h or more. The cont rol and each t reatment with 4- l testing solution, and all groups were run in duplicate. Dur ing the exper iment , dead shrimp were removed, and the mortality was recorded. The LC50 of antimony and its 95% confidence limits for M. nipponense were calculated using a Basic program from the probit analy-sis described by [12].

The oxygen consumption analysis was carried out us-ing a former method with slight modification [8]. Groups of 20 juvenile M. nipponense were randomly sampled and placed in 10-l glass beakers with 4-l test ing solut ion;

triplicate shrimp were then respectively exposed to a test solution of 0.0, 0.1, 0.4, 0.8, and 1.2 mg Sb/l. Sublethal levels of antimony were equivalent to approximately 6%, 24%, 49%, and 73% of the 96-h LC50 value (1.635 mg Sb/l) according to acute toxicity tests. Twice a week, 50% of the water was renewed with standard water con-taining antimony to maintain constant environmental conditions throughout the entire experimental period. The exposure time was 1 week, followed by a 1-week recovery period in Sb-free water.

Both control and exposed samples were taken after 30 min (for acute exposure), and 3th d, 7th d, and 14th d for estimation of oxygen consumption. Oxygen consumption tests were customarily carried out by sealing two juve-nile M. nipponense in a 325-ml respiratory jar capacity with an oxygen electrode (Microprocessor Oximeter, WTW, Heidelberg, Germany). All respiratory jars con-tained up to 7 mg/l DO before the initial measurement. At each interval, two juvenile M. nipponense were put into a respiratory jar with an acclimatization time of 30 min as recorded earlier, and then the oxygen consump-tion was estimated. We allowed them to deplete the oxy-gen until death occurred, and the residual dissolved oxy-gen was measured using a multiple-range temperature and oxygen analyzer and recorder (Yokogawa, Tokyo, Japan). Oxygen consumption (QO2, mg O2/kg/h) was calculated as follows:

QO2 = Δppm × 1/BW × V × 1/t

where QO2 is the amount of oxygen (Δppm) consumed in the interval t (h) and BW is the wet body weight (kg) at the start and at the end of the test period.

Adult M. nipponense for sublethal tests were ran-domly placed in 20-l glass aquaria with 10-l test ing solut ion. Every aquarium contained 10 shrimp which were exposed to the following concentrations: 0.2, 1.0, and 4.0 mg Sb/l test solutions and a control. Sublethal levels of antimony were equivalent to approximately 3%, 15%, and 60% of the 96-h LC50 value (6.748 mg Sb/l) ac-cording to the acute toxicity tests. Twice a week, 50% of the water was renewed with standard water containing antimony to maintain constant environmental conditions throughout the entire experimental period.

Four adult M. nipponense per exposure concentration were anesthetized with MS-222 (1:6000) (Sigma, St. Louis, MO, USA) and sacrificed after 2 weeks of expo-sure. Shrimp hepatopancreases were collected, fixed in 4% buffered formalin, and routinely processed for ex-amination using standard techniques with hematoxylin and eosin (H&E).

All values of oxygen consumption assessment were performed with one-way analysis of variance (ANOVA). Duncan’s multiple-range test was used to evaluate the mean difference among individual groups at the 0.05 significance level.


J. L. YANG ET AL.


44

3. Results and Discussion According to the static renewal method for acute toxicity testing, median lethal concentrations (LC50) of antimony for swamp shrimp (M. nipponense) were calculated. The calculated 48- and 96-h LC50 values are listed in Table 1. From our investigation, juvenile M. nipponense were found to be more susceptible than adults M. nipponense to acute antimony toxicity. 96-h LC50 of antimony to juvenile zebrafish (Brachydanio rerio) was 4.65 mg Sb/l, and to juvenile common carp (Cyprinus carpio), larval tilapia (Oreochromis mos-sambicus), juvenile red seabream (Pargus major), and juvenile sheepshead minnows (Cyrinodan variegatus), were 14.05, 18.9, 12.4, and 6.2-8.3 mg Sb/l, respec-tively [2,13-16]. No toxic effect was seen at 0.2 mg Sb/l in the acute toxicity testing of juvenile M. nippo-nense, which is equivalent to 12% of the 96-h LC50 value, and is in close agreement with the concept of a safe level (one-tenth of the 96-h LC50 value) as de-scribed by [17]. Less than 0.2 mg Sb/l was proposed as a biologically safe concentration which can be used for establishing tentative water quality criteria for M. nip-ponense of this size.

The results of the oxygen consumption rates for the control and exposed juvenile M. nipponense were pre-sented in Table 2. After 30 min (acute), there was an increase in the amount of oxygen consumed in the ex-posed groups; a maximum increase of 27.3% was ob-served at the highest exposure concentration (1.2 mg Sb/l). Percentage of oxygen consumption decreased over their respective controls from acute exposure 3th d to 7th d during the exposure time. No increasing in oxygen consumption, however, was observed in the recovery period (on 14th d) compared with the respective same level groups on 7th d. In the present study, juvenile M. nipponense showed no recovery at higher exposure level groups (0.8 and 1.2 mg Sb/l) after 1-week period in Sb- free water. Former study indicated that exposure to sub-lethal toxicant concentrations increases respiratory activ-ity, resulting in increased ventilation and increased up-take of the toxin [18]. Later, cytological damage should be related to the decrease in oxygen consumption be-

cause the gills are most likely the first target of water-borne heavy metals, including thickening of branchial epithelium and deep changes in hemolymph patterns in the gills with a concomitant increase in vacuolization and reduced hemolymph spaces causing perfusion stagnation [19]. For example, an increased number of nephrocytes in gill filaments, a blackened appearance of the gills, necrosis of gill cells resulting in narrowed or obstructed hemolymphatic vessels, the appearance of a space be-tween the cuticle and the epithelial cells which contains black electron-dense material, and even fragmentation of nuclei within gill cells could be observed when P. ja-ponicus were exposed to different concentrations of Cd for 4 days [20]. A review of the responses of aquatic crustaceans in low ambient dissolved oxygen, mentioned that many crustaceans possess an excellent regulatory ability in their oxygen consumption patterns [21]. We proposed that measurements of oxygen consumption could be used to assess the effects of antimony on sub-lethal exposure levels of juvenile M. nipponense.

The controlled group and adult M. nipponense treated with 0.2 mg Sb/l showed well-developed hepatopan-creatic tubules with star-shaped lumen, and with closely arranged basal laminae surrounding each tubule (Figure 1). Alterations in the structural organization of tubules were observed after 1.0 mg Sb/l treatment. Degenerative changes in the lumen, detachment of the basal lamina, and impairment of the structural integrity were observed (Figure 2). Severe hepatopancreatic lesions were found in M. nipponense exposed to 4.0 mg Sb/l. Disorderly and disrupted hepatopancreatic tubules and reduced lumen became more prominent (Figure 3). The crustacean heap- Table 1. Median lethal concentrations (LC50) of antimony to M. nipponense.

LC50 (mgSb/L)

Life stage 48 h 96 h

Juvenile 2.240 1.635

(1.649-3.046) (1.271-2.103)

Adult 10.083 6.748

(8.736-11.378) (5.728-7.950)

Table 2. Effect of sublethal exposure to antimony on oxygen consumption (mg O2/kg/h) of juvenile M. nipponense.

Control 0.1 mgSb/L 0.4 mgSb/L 0.8 mgSb/L 1.2 mgSb/L

acute 0.653±0.043a 0.660±0.027a 0.674±0.042a 0.808±0.071b 0.831±0.064b

day 3 0.641±0.089a 0.651±0.063a 0.647±0.045a 0.507±0.065b 0.421±0.033c

day 7 0.658±0.043a 0.644±0.059a 0.628±0.071a 0.545±0.077b 0.504±0.021b

day 14 0.659±0.041a 0.652±0.050a 0.641±0.058a 0.573±0.046b 0.539±0.063b

All values are given as the mean±SD; n = 3. Values in the same row with different superscripts differ significantly at p < 0.05.

J. L. YANG ET AL. 45

Figure 1. Hepatopancreatic tissue of the adult M. nipponense in the control group. (bar = 0.1mm).

Figure 2. Hepatopancreatic tissue of the adult M. nipponense exposed to 1.0 mgSb/L for 14 d. Note the degeneration of the lu-men; impairment of structural integrity can also be seen. (bar = 0.1mm).


J. L. YANG ET AL.


46

Figure 3. Hepatopancreatic tissue of adult M. nipponense exposed to 4.0 mgSb/L for 14 d. Note the severe damage to the tu-bules, pronounced hypertrophy of the epithelia cells were also observed. (bar = 0.07mm). topancreas is assumed to be functionally equivalent to the mammalian liver and pancreas and is responsible for major metabolic events, including enzyme secretion, absorption and storage of nutrients, molting, and vitel-logenesis [22, 23]. The hepatopancreas is essentially composed of branched tubules and different types of epithelial cells (E-, R-, F-, and B-cells) lining the tubules. It is likely that exposure to a harmful chemical, such as copper sulfate, would be reflected in alterations in the structures of tubules and epithelial cells [24]. Histologi-cal alterations have been characterized in freshwater shrimp, such as M. malcolmsonii and various species of Macrobrachium. They are exposed to various chemicals, such as copper, chromium, cadmium, and zinc [25]. Several such structural alterations were noted in the hepatopancreatic tubules of treated M. nipponense that had been exposed to antimony in the present study.

nipponense to lower levels of antimony can result in such deleterious changes, and our finding suggests that anti-mony is a potential pollutant in aquatic environments, although limited knowledge on the adverse effects of antimony on aquatic animals has been reported to date. 5

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[16] L. H. Chen and J. L. Yang, “Acute toxicity of antimony

chloride (SbCl3) and its effects on oxygen consumption of common carp (Cyprinus carpio),” Bulletin of Envi-ronmental Contamination and Toxicology, Vol. 78, pp. 459–462, 2007.

[17] J. B. Sprague, “Measurement of pollutant toxicity to fish. III. Sublethal effects and safe concentrations,” Water Re-search, Vol. 5, pp. 245–266, 1971.

[18] A. S. Murty, “Toxicity of pesticides to fish,” CRC Press, 1986.

[19] S. Chinni, R. N. Khan, and P. R. Yallapragada, “Oxygen consumption, ammonia-N excretion, and metal accumu-lation in Penaeus indicus postlarvae exposed to lead,” Bulletin of Environmental Contamination and Toxicology, Vol. 64, pp. 144–151, 2000.

[20] A. Soegianto, M. Charmantier-Daures, J. P. Trilles, and G. Charmantier, “Impact of cadmium on the structure of gills and epipodites of the shrimp Penaeus japonicus,” Aquatic Living Resource, Vol. 12, pp. 57–70, 1999.

[21] B. R. McMahon, “Respiratory and circulatory compensa-tion to hypoxia in crustaceans,” Respiration Physiology, Vol. 128, pp. 349–364, 2001.

[22] R. Gibson and P. L. Barker, “The decapod hepatopan-creas,” Oceanography Marine Biol, Vol. 17, pp. 285–346, 1979.

[23] M. Chanson and D. C. Spray, “Gating and single channel properties of gapjunction channels in hepatopancreatic cells of Procambarus clarkia,” Biological Bulletin, Vol. 183, pp. 341–342, 1992.

[24] H. V. Ghate and L. Mulherkar, “Histological changes in the gills of two freshwater prawn species exposed to copper sulphate,” Indian Journal of Experimental Biology, Vol. 17, pp. 838–840, 1979.

[25] K. Vijayaraman, “Physiological responses on the fresh-water prawn, Macrobrachium malcolmsonii (Milne Ed-wards) to the heavy metals, cadmium, copper, chromium and Zinc,” Ph. D. dissertation, Bharathidasan University, India, 1993.




Studying Heavy Metals in Sediments Layers along Selected Sites on the Lebanese Coast

Nadine NASSIF, Ziad SAADE Department of Environment, Agricultural Engineer, Lebanese University, Dekwanek, Lebanon


Abstract Ensuring the environmental protection of the Lebanese coast requires a continues monitoring system. For this purpose, four heavy metals (Fe, Mn, Cu and Pb in the marine sediments along the Lebanese coast were selected for analysis Sampling was carried out from two sites: Beirut and Batroun. Thus, 1g of dried sample is used for digestion by wet mineralization in order to determine the concentration of the four heavy metals by atomic absorption spectrometry. The results showed that Beirut area is polluted, by Fe and Mn as well as the station Bat 2 of Batroun. For Cu and Pb, Batroun region is more polluted in the superficial layers. The analysis also showed significant difference between the sites except for Cu. A difference between depths and between particles size fractions are observed for all the parameters studied. There is no a significant differ-ence in layer sequence except for the Pb, and neither between the repetitions of the same sample. Results showed that the values of the four metals studied do not exceed the maximum limits at both sites, but they showed increase in comparison with the analyses obtained before July 2006 conflict, which was caused by the release of large quantity of fuel-oil from Jiyeh Power Station. Keywords: Pollution, Sediments, Heavy metals, Coast, Lebanon 1. Introduction The Lebanese coast has been threatened by a severe en-vironmental disaster in its history due to the existed con-flict in July 2006, which caused the release of 15,000 tones of fuel-oil after the destruction of oil tanks of the Jiyeh Electrical Power Station (30km south Beirut) [1].

This resulted a serious marine pollution, including a large portion of the marine ecology. This, in turn added a new aspect of pollution to the existing industrial, agri-cultural and urban ones, which cause complications on the aquatic environment that covers about 18,000 hec-tares (or 16% of the Lebanese territory), at a length of about 220km along the coast [2].

Among the contaminants brought about by human ac-tivities, heavy metals play a crucial role. Unlike most organic pollutants, heavy metals are natural constituents of the earth’s crust, which are naturally released as a re-sult of rock and soil weathering and erosion. The rapid population growth, is accompanied with several human activities, notably the industrial exploitation of natural resources, as well as sewage and refuse dumping into the sea without any treatment. They are often convoyed to the marine environment along rivers and perennial

stream. Heavy metals are at low concentrations in aquatic ecosystems where they tend to accumulate in marine sediments to reach toxic levels [3,4]. The diffi-culties in collecting valid samples for heavy metals analysis in marine water, made several researches fo-cuses primarily on marine sediments where heavy metals are located at higher concentrations. Sediment is a com-partment integrator of contaminants and can keep heavy metals among their layers and give an entire chronology of deposition mechanism.

Recent studies on marine sediments, conducted in Lebanon before the 2006 conflict, showed different heavy metal concentrations in different sites to the known concentration of heavy metals along the Mediter-ranean coasts [5,6].

In order to determine heavy metal content along the Lebanese coast, two representative sites were selected; Beirut (along the middle Lebanese coast) and Batroun to the north coastline. They are major ports, and then they contain a number of industrial activities. This study aims to evaluate the contents of four metals: lead, copper, iron and manganese. These elements are among the main elements released by industries effluents and different factories along the Lebanese coast.

N. NASSIF ET AL. 49

The study aims also to carry out a comparative analy-sis of heavy metals at different sediments depth for each site, and even a comparison between the different depths in the same site that has not been addressed in the previ-ous studies. The difference between repetitions made for the same sample (duplicate) was measured.

On the other hand, the results will help evaluating, for the first time in Lebanon, the influence of the size frac-tion to determine the most appropriate fraction contain-ing the highest concentration of metals.

According to the concentration of heavy metals found in sediments in each region, we would be able to com-pare the degree of contamination before and after the 2006 conflict and then identify which of the two regions was more influenced by pollution. 2. Methodology 2.1. Sampling The samples were selected from sediments cored from the two sites (Figure 1):

Site 1: Beirut (Ramlet el Bayda) Site 2: Batroun (Selaata region) In order to assess the detailed concentration of pollu-

tion, three stations were selected in each site. They di-verse by the depth of sediment (Table 1).

Samples were taken by carrots, made of plastic mate-rial to avoid contamination, with 40cm length and 10cm diameter, these carrots were previously washed with HCL and HNO3.

From each station, a spacing of 2 levies distant from each other by 30cm was done. The quantity of sediment samples was different from one place to another because of the granulometric so we had different amounts of sediment in the carrot (Figures 2 and 3).

Figure 1. Localization of the selected samples.

Table 1. Location and depths of each station.

Stations Coordinates of the station Depth

Beirut B 0m N=33°52.550’ E=035°28.820’

0m

Beirut B 5m N=33°52.662’ E=035°28.657’

5m

Beirut B 10m N=33°52.688’ E=035°28.458’

10m

Batroun BAT 1 N=34°15.092’ E=035°39.211’

10m

Batroun BAT 2 N=34°16.169’ E=035°39.226’

10m

Batroun BAT 3 N=34°16.709’ E=035°39.115’

5m

0 m 5 m 10 m

Rep 1 17 cm: 0-1 2-3 4-5 6-7 8-9 10-17

Rep 2 18 cm: 0-1 2-3 4-5 6-7 8-9 10-18

Rep 1 18 cm: 0-1 2-3 4-5 6-7 8-9 10-18

Rep 2 22 cm: 0-1 2-3 4-5 6-7 8-9 10-22

Rep 1 27 cm: 0-1 2-3 4-5 6-7 8-9 10-15 20-25

Rep 2 27 cm: 0-1 2-3 4-5 6-7 8-9 10-15 20-25

212 μm

125 μm

212 μm

125 μm

212 μm

125 μm

Beyrouth

Site

Depth

Carrots, repetition

and layers

Sifting

Figure 2. Schematic presentation of the sampling charac-teristics in Beirut.

Batroun

10 m 10 m (South) 5 m (North)

Rep 1 25 cm: 0-1 2-3 4-5 6-7 8-9 10-20

Rep 2 21 cm: 0-1 2-3 4-5 6-7 8-9 10-20

Rep 1 17 cm: 0-1 2-3

Rep 2 19 cm: 0-1 2-3 4-5 6-7 8-9 10-19

Rep 1 26 cm: 0-1 2-3 4-5 6-7 8-9 10-20

Rep 2 23 cm: 0-1 2-3 4-5 6-7 8-9 10-20

212 μm

125 μm

212 μm

125 μm

212 μm

125 μm

Site

Depth

Carrots, repetition

and layers

Sifting

Figure 3. Schematic presentation of the sampling charac-teristics in Batroun.

2.2. Laboratory Analysis 1) Sampling equipments used in the field or the labora-tory were maintained in safe condition and clean and had no trace of corrosion. They were handled and stored with the necessary precautions to avoid any aspect of con-tamination. All glassware used were previously soaked in 5% HCl, then 5% HNO3 for 24 hours each, and then rinsed with double deionized water. All bottles used for transport and storage of samples were of polyethylene and cap perfectly sealed.


N. NASSIF ET AL.


50

2) For the drying samples, we had cut carrots each 1 cm, and each 1cm of sediment was transferred and pre-served separately in a plastic bag placed at room tem-perature for 8 days until we had a constant mass. This step, drying samples, is essential in order to improve the efficiency of mineralization acid, because the homog-enization of dry samples is required other than wet sam-ples. Once dried, the sediment is transferred separately in containers polypropylene previously labeled.

3) Grinding of sediments was carried out to increase the homogenization of samples.

4) Sifting was also applied to study the influence of particle size on the concentration of heavy metals. Sedi-ments were sifted through sieves whose pores were re-spectively 212 μm, 125 μm and 38 μm [7].

5) Determining the size of the sample of sediments was the aim of this step to reduce the mass of an object without altering its other properties, and also to reduce the error to the least. The composition of the laboratory sample should be identical as possible to that of the ini-tial sample [8]. For that, we had chosen randomly six samples from the three regions. For each sample, we crushed a small part of the sample, and then weighed four different mass: 0.25g, 0.5g, 1g and 2.5g. Then there will be 24 solutions which to mineralize, similar to the same way to determinate their concentrations by Atomic Absorption Spectrometry (AAS).

6) Mineralization: is an essential step for the solution before analysis. To mineralize samples, the wet method was used, according to the following procedure, which was added to the test weighing, 20ml of HNO3 (65%), on a hotplate, with magnetic agitation without boiling and evaporation. After six to seven hours, 5 ml of HCl (37%) were added every 30 minutes to three times until the total digestion. The acid then evaporated and the dry residue was recovered with 50ml of HNO3, then we followed centrifuge and filtered in order to analyze them [9–11].

7) Analysis by Atomic Absorption Spectrometry al-lowed determining the levels of heavy metals by using a high temperature, the atomization, according to the case with a flame (for major elements like Fe and Mn) or an oven (for minor elements Cu and Pb). Consequently, all samples were measured with an Atomic Absorption Spectrometer (ZEEnit - 700) equipped with a system of correction Zeeman. A mixture of air-acetylene was used for (AAS) flame and argon for (AAS) oven. The curve of standard range with several known concentrations was primarily prepared. To analyze samples by (AAS), we need 1/7 dilution by HNO3 (0.5N). Each sample was passed by a beam of light wavelength and intensity de-fined (λFe=248.5 nm, λMn=279.5 nm, λCu=324.8 nm, λPb=283.3nm) to measure their absorbance, then the concentration of each sample was identified, according to the curve of range standard of the metal [9,10,12].

8) After determining the size of sediment sample;

however, all samples were mineralized, which were sifted. The mineralization was made for samples with the two fraction sizes 38-125 μm and 125-212 μm (since fraction <38μm is negligible). When the mineralization of theses samples has been done, the concentration was determined of every sample for each metal separately (for the two fraction sizes) by (AAS) with the same pro-cedure followed in the determination of the size of sedi-ment sample. 3. Results Five major findings were identified in this study, and then they were assessed to evaluate the degree of heavy metal contamination in the marine environment of Lebanon, as follows: 3.1. Percentage of Different Fraction Size in the

Sediments Samples Similar size fractions of different samples in each carrot were mixed to determine the percentages of each size fractions studied in each carrot of the two sites (Table 2). Results were plotted graphically (Figures 4 and 5).

Table 2. Percentage of size fraction.

Percentage of size fraction (%) Stations <38μm 38-125 μm 125-212 μm

B 0 m I B 0m II

0,045 0,03

10,08 8,46

89,87 91,507

B 5m I B 5 II

0,49 0,79

20,43 24,48

79,07 74,72

B 10m I B 10m II

8,86 9,322

42,4 40,13

48,738 50,54

Bat 1I Bat 1 II

0,176 0,082

4,44 3,39

95,35 96,48

Bat 2I Bat 2 II

23,04 21,06

51,984 55,06

24,97 23,87

Bat 3 I Bat 3 II

1,68 2,67

28,45 35,14

69,86 62,18

Sifting of samples sediments in Batroun

0

100

200

300

400

500

600

700

800

900

1000

B 0mI/17cm

B 0mII/18cm

B 5mI/18cm

B 5mII/ 22cm

B 10 mI/ 27cm

B 10mII/27cm

samples

weight (g)

212

125

38

Figure 4. Distribution of the three fractions size in each carrot in Beirut site.

N. NASSIF ET AL. 51

Sifting of samples sediments in Batroun

0

200

400

600

800

1000

1200

1400

BAT 1mI/ 25 cm

BAT 1mII/ 21cm

BAT 2mI/ 17cm

BAT 2mII/ 19cm

BAT 3mI/ 26 cm

BAT 3mII/23 cm

samples

Weight (g)

212

125

38

Figure 5. Distribution of the three fractions size in each carrot in Batroun site. We note, similarly, that with increasing depth in Beirut site, the size fraction 125-212 μm was declined and the proportions of fractions <38 μm and 38-125 μm gradu-ally increased. For the sample of Batroun site, the nature of rocks differs widely between depths, samples with the same depth Bat 1 and Bat 2 have a different composition. Comparing to the classification of sedimentary rocks in geology, the size fraction <38 μm is composed of silt and clay. The size fraction 38-125 μm was composed by fine sand and less silt, and the size fraction 125-212 μm was composed by fine sand and some sand. 3.2. Determination of the Size of Sediment Sample The majority of concentrations on the three tests taken: 0.25g, 0.5g and 1g, treated in the same way, were pro-portional to the increase in weight of these three tests taken. However, this proportionality would no longer be applicable for most concentrations on the test 2.5g. The test sample of 2.5g requires a long period of mineraliza-tion and a high quantity of acid. In this study we used 1g as the size of sediment sample [13]. 3.3. Concentrations of Heavy Metals It was deduced that concentrations analyzed of Fe, Mn, Cu and Pb found in sediments of the two Lebanese sites (Table 3) were below the standards [14,15], and there-fore they were acceptable, with the exception for some concentrations concerning the heavy metal Fe of the lev-ies B 0m1 and the station Bat 2, which contain several values that transcend the limit and are polluted.

It is clear that in the two sites, samples from two levies of the same depth have the same proportions for each size fractions. The repeatability of samples was acceptable. 3.3.1. Analyses of Variance (SPSS) The analyses of variance (SPSS) made for each site and for each heavy metal (Tables 4 and 5) showed a significant difference between the results for each studied setting.

Table 3. Concentrations of Fe, Mn, Cu and Pb to six ran-domly sample for 4 different sizes of sediment sample.

B 5 m I, 212μm [Fe] mg/l [Mn] mg/l [Cu] μg/l [Pb] μg/l

0.25 51.89 1.645 38.199 16.086

0.5 100.7 2.445 55.104 33.208

1 223.7 3.755 101.85 58.903

2.5 541.4 4.133 207.9 89.46

B 5m II, 212μm

0.25 48.17 1.669 19.533 22.568

0.5 92.04 2.353 34.125 28.37

1 183.5 3.305 73.01 49.595

2.5 518.4 4.2 93.03 97.37

B 5m I, 125μm

0.25 159 2.041 78.23 9.201

0.5 338.6 2.971 120.61 16.814

1 654.4 4.93 251.88 32.207

2.5 1442 8.631 453.95 144.2

Bat 1 I, 212μm

0.25 18.04 1.696 177.31 46.52

0.5 36.37 2.096 242.07 52.311

1 73.17 3.074 424.4 98.42

2.5 166.3 3.733 559.35 250.2

Bat 1 II, 212μm

0.25 16.15 1.229 44.98 18.865

0.5 33.5 2.139 168.38 33.572

1 65.86 3.408 283.29 72.05

2.5 140.2 3.998 374.55 103.81

Table 4. The effects of different settings for the Fe, Mn, Cu and Pb.

Effect Site Depth Layer Fraction Repetition

Fe Beirut + - - + -

Fe Batroun + + - + -

Mn Beirut + + - + -

Mn Batroun + + - + -

Cu Beirut - + - + -

Cu Batroun - - - + -

Pb Beirut + + - + -

Pb Batroun + + + + -

(+: Significant difference; -: no significant difference)


N. NASSIF ET AL.


52

3.3.2. Concentration of Fe Compared with the concentration of Fe samples (with a diameter <200 µm) taken from the pit of Beirut in 2004 (41.87mg/l) [13], it was found that concentrations of Fe are largely higher due the impact from the conflict of July 2006.

Figure 6(a), (b) and (c) were studying the change in the concentration of Fe, each one concerned a specific layer, between the different sampling made in the two sites and for the two size fractions selected before. In these three layers, for both studied size fractions, the station Bat 2 site was the most concentrated in Fe. The three stations of Beirut had close concentrations of Fe, lower than Bat 2, but higher than those Bat 1 and Bat 3, which had very low concentration of Fe. In the site of Beirut and for the size fraction 125-212 µm, the concen-tration of Fe in station B 10m is slightly higher than in B 5m which was in turn slightly higher than B 0m. For the size fraction 38-125 µm, the concentrations of Fe in the three depths were very close to each other.

Figure 7 shows the change in the concentration of Fe according to the different layers of a levy. The various points 0, 1, 2, 3, 4 and 5 of the y-axis represent; respec-tively the first, third, fifth, seventh, ninth and eleventh layers.

The charts in Figure 7 show that there was no signifi-cant difference between layers of the same depth, except for Bat 2, which shows some variation between layers because of the heavy concentration of Fe.

Almost all charts show that repetition did not make a significant difference for the concentration of Fe with the exception of Bat 2 for the same reason cited above. It was also observable that the samples with the finer size fraction (38-125 μm) are those who generally greater concentrations of Fe compared to the other fractions, this effect was also observable to the samples of Beirut. 3.3.3. Concentration of Mn Figure 8(a), (b) and (c) shows the change in the concen-tration of Mn, each one concerned a specific layer, be-tween the different sampling made in the two sites and for the two size fractions selected before. The results show the difference between the two sites. The station Bat 3 is the least concentrated among all others and for both size fractions. The two stations B 10m and Bat 2 are most concentrated for the two size fractions. In Beirut, B10m had the most concentrated in Mn, then B 5m and then B 0m.

The results for Mn show that samples of Beirut and Batroun did not differ significantly according to the layers.

It is obvious from Figures 8 and 9 that there was no significant difference for the repetition of the samples. Moreover, the results show that in the site of Beirut the size finer fractions contain a high concentration of Mn. While samples of Batroun did not show a difference be-

tween the two size fractions, with the exception of Bat 2, which contained a high concentration of Mn. 3.3.4. Concentration of Cu Compared with the concentration of Cu samples (sam-ples with a diameter < 200 µm) taken from the pit of Beirut in 2004 (33.67 µg/l) (13), hence, the concentration of Cu far exceeded the previous values after the conflict of July 2006. Figure 10-a, 10-b and 10-c reveals change in the concentration of Mn, each one concerned a spe-cific layer, between the different sampling made in the two sites and for the two size fractions selected before. For the size fraction 125-212 µm, results show that both sites were highly concentrated and had almost the same concentrations. While, Bat 2 and B10m presented slightly higher concentrations than the other stations.

(a)

(b)

(c)

Figure 6. Change in the concentration of Fe for the both size fractions of the first layer (a), the seventh layer (b) and the eleventh layer (c), in the d fferent levies of the two sites. i

N. NASSIF ET AL.


53

(a) (b)

(c) (d)

(e) (f)

Figure 7. Change in the concentration of Fe (mg/kg) according to the layers for both size fractions in the two sites Beirut and atroun in B 0m (a), B 5m (b), B 10m (c), Bat 1 (d), Bat 2 (e), et Bat 3 (f). B

N. NASSIF ET AL.


54

(a)

(b)

(c)

Figure 8. Change in the concentration of Mn for the both size fractions of the first layer (a), the seventh layer (b) and the eleventh layer (c), in the different levies of the two sites.

For the size fraction 38-125 µm, Figure 10 shows that the site of Batroun was most concentrated; this was the current state of contamination of the study area. In Fig-ure 10-b and 10-c, both sites were polluted, but pollution in Beirut is merely higher than in Batroun. These two figures represent the state of contamination and temporal evolution of the sites. Bat 3, B 0m and B 10m were most polluted in Cu than the other station.

Figure 11 shows the change in the concentration of Cu according to the different layers of a levy. The different figures show that there was no a large difference according to different layers. It is clear from Figure 10 and 11 that there was no significant difference for the repetition of the majorities of the samples. Samples with the size frac-tion finer (38-125 µm) had higher concentrations com-pared to the other portion size of 125-212 µm. 3.3.5. Concentration of Pb Compared with the concentration of Pb in samples taken from Jiyeh (17 μg/l) [5,6], from Zouk and Selaata (2μg/l), it was resulted that the concentration of lead has in-creased.

Figures 12(a), (b) and (c) reveal the change in the concentration of Mn, each one concerned a specific layer, between the different sampling made in the two sites and for the two size fractions selected before. Different fig ures show that Batroun site was more concentrated in Pb than Beirut site. This difference was more appreciable in the first layer, which was represented the state of a cur-rent and recent contamination. Bat 3 and B 10 and B0m were more concentrated in Pb than the other one.

Figure 13 shows the change in the concentration of Cu according to the different layers of a levy. Figures 12 and 13 show that for the site of Beirut, there was no signifi-cant difference between layers for the same depth, while for the site of Batroun, there was some difference be-tween layers of the same depth.

(a) (b)

N. NASSIF ET AL. 55

(c) (d)

(e) (f)

Figure 9. Change in the concentration of Fe (mg/kg) according to the layers for both size fractions in the two sites Beirut and Batroun in B 0m (a), B 5m (b), B 10m (c), Bat 1 (d), Bat 2 (e), et Bat 3 (f).

(a) (b)

(c)

Figure 10. Change in the concentration of Cu for the both size fractions of the first layer (a), the seventh layer (b) and the eleventh layer (c), in the different levies of the two sites.


N. NASSIF ET AL.


56

(a) (b)

(c) (d)

(e) (f)

Figure 11. Change in the concentration of Fe (mg/kg) according to the layers for both size fractions in the two sites Beirut and atroun in B 0m (a), B 5m (b), B 10m (c), Bat 1 (d), Bat 2 (e), et Bat 3 (f). B

N. NASSIF ET AL.


57

(a)

(b)

(c)

Figure 12. Change in the concentration of Cu for the both size fractions of the first layer (a), the seventh layer (b) and the eleventh layer (c), in the different levies of the two sites.

The difference between the layers in the site of Ba-troun can be attributed to the lack of disruption during the accumulation of pollutants over time, allowing mix-ing contaminants.

Almost all charts in Figure 13 show that repetition did not make a significant difference. The analyses also show that samples with finer size fraction show slightly higher concentration of Pb over the other portion size. 3.3.6. Analysis of Principal Component (A C P) All parameters in this study show that the axis F1 (which represent 45% of the variance) was mainly influenced by Fe and Mn, and the axis F2 (which represents 37% of the variance) was primarily influenced by Cu and Pb (Figure 14). This analysis also shows that Fe and Mn are per-

fectly correlated with each other positively and nega-tively with Cu and Pb, allows dividing the two heavy metal Cu and Pb one the one hand and the two other metal Fe and Mn on the other hand to evaluate the sites. This is widely visible in the table of Person correlation (Table 5). This correlation indicates the presence of a linear relationship between Fe and Mn, and another linear relationship between Cu and Pb, because Fe and Mn were considered as “Siderophile” element, but Cu and Pb were considered as “Chalcophile” element. For a long- term monitoring, the study can focus on a single pa-rameter instead of two.

A C P made on both parameters (Pb and Cu) in Figures 14 and 15 shows that the correlation between Cu and Pb is significant and there was a significant difference between the two selected sites. 4. Conclusions The comparison of the concentrations of Fe, Mn, Cu and Pb, obtained in this study, according to standards [3,15, 16] indicated that they did not exceed the maximum limit with the exception of a few values of Fe.

However, the values are far greater than those existed before the conflict of 2006, due to the release of fuel oil into the sea. The comparison with the studies done be-fore the conflict is limited since no studies have ad-dressed different layers of sediment. This is because the values given in these studies return to sediment sample with diameters of less than 63 or 80 μm [6,18].

It was noticeable that there is no correlation between Fe and Mn and between the Cu and Pb, thus the parame-ters are divided in two groups: a-Cu and Pb, b- Fe and Mn.

For Fe and Mn, sediments of Beirut site (B 10 m sta-tion is the most concentrated), are more concentrated than in Batroun site with the exception of Bat 2, which contained a high concentration of Fe and Mn. For Cu and Pb, Batroun site had higher concentration than Beirut site in the surface layers. These results are opposed to those found before the conflict of 2006. The high concentration in Beirut site is probably due to human activities and the conflict of 2006 (oil spill in the sea).

The high concentration in Batroun site was attributed to the impact of wind carried pollutants from different

Table 5. Correlation of pearson between the heavy metals studied

Cu Pb Fe Mn

Cu 1 0.474 0.091 0.028

Pb 0.474 1 -0.099 -0.145

Fe 0.091 -0.099 1 0.753 Mn 0.028 -0.145 0.753 1

The significant values are represented in bold with α=0. 05

N. NASSIF ET AL.


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(a) (b)

(c) (d)

(e) (f)

Figure 13. Change in the concentration of Fe (mg/kg) according to the layers for both size fractions in the two sites Beirut and Batroun in B 0m (a), B 5m (b), B 10m (c), Bat 1 (d), Bat 2 (e), et Bat 3 (f).

N. NASSIF ET AL.


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Variables (axes F1 and F2: 81 %)

CuPb

FeM n

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

-- axis F1 (45 %) -->

-- a

xis

F2 (37 %

) --

>

Figure 14. Analysis of principal component (ACP) to all parameters studied (in Beirut and Batroun): correlations between concentrations of different heavy elements traces in all samples studied.

Variables (axes F1 and F2: 100 %)

Pb

Cu

-1.5

-1

-0.5

0

0.5

1

1.5

-1.5 -1 -0.5 0 0.5 1 1.5

-- axis F1 (74 %) -->

-- a

xis

F2

(26

%)

-->

Figure 15. Analysis of principal component (ACP) to all parameters studied (in Beirut and Batroun) : correlations between concentrations of Cu and Pb in all samples studied.

regions, and the correlation between heavy metals and hydrocarbons, was attributed to the industry of chemical products at Selaata factory near Batroun, as well as due to the conflict of 2006.

For the investigated parameters, the effect of size frac-tion is significant, because the samples with the finer size fraction 38-125 μm had higher concentration than the other fraction 125 – 212 μm. The mineralogical compo-sition was also involved in significant proportions.

Thus, the silty clay minerals were more richer in met-als that silica sand. This is the case with stations B 10m, Bat 2 and Bat 3 which contained quantities exceeding of fine fractions, because results showed higher concentra-tions of metals (especially Fe and Mn) compared to other stations [18–20].

Variables and observations (axes F1 and F2: 100 %)

Bey-1-1-1-1-Bey-1-1-1-2-Bey-1-1-2-2-Bey-1-2-1-1-

Bey-1-2-2-1-

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Bey-1-3-1-2-

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Bey-2-1-1-2-Bey-2-1-2-1-Bey-2-1-2-2-Bey-2-2-1-1-

Bey-2-2-1-2-Bey-2-2-2-2-Bey-2-3-1-1-

Bey-2-3-1-2-Bey-2-3-2-2-

Bey-2-4-1-1-Bey-2-4-1-2-Bey-2-4-2-1-

Bey-2-5-1-1-Bey-2-5-1-2-Bey-2-5-2-2-Bey-2-6-1-1-Bey-2-6-1-2-Bey-2-6-2-2-Bey-3-1-1-1-

Bey-3-2-1-2-

Bey-3-4-1-2-Bey-3-5-1-2-

Bat -1-1-1-2-

Bat -1-1-2-1-

Bat -1-1-2-2-

Bat -1-2-1-1-Bat -1-2-1-2-

Bat -1-2-2-2-Bat -1-3-1-1-Bat -1-3-1-2-

Bat -1-3-2-1-Bat -1-3-2-2-

Bat -1-4-1-2-

Bat -1-4-2-1-Bat -1-4-2-2-

Bat -1-5-1-1-Bat -1-5-1-2-Bat -1-5-2-1-

Bat -1-5-2-2-

Bat -1-6-1-1-Bat -1-6-1-2-

Bat -2-1-1-1-

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Bat -2-2-1-2-Bat -2-2-2-2-

Bat -2-3-1-2-

Bat -2-3-2-1-Bat -2-3-2-2-

Bat -2-4-1-1-

Bat -2-4-1-2-Bat -2-4-2-1-

Bat -2-4-2-2-

Bat -2-5-1-1-

Bat -2-5-2-1-

Bat -2-5-2-2-Bat -2-6-1-1-

Bat -2-6-1-2-Bat -2-6-2-1-

Bat -3-1-1-1-Bat -3-1-1-2-

Bat -3-1-2-1-

Bat -3-1-2-2-

Bat -3-2-1-1-Bat -3-2-1-2-

Bat -3-2-2-1-

Bat -3-2-2-2-

Bat -3-3-1-1-Bat -3-3-1-2-Bat -3-3-2-1-

Bat -3-4-1-1-Bat -3-4-1-2-

Bat -3-5-1-1-

Bat -3-5-1-2-

Bat -3-5-2-2-

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Bat -3-6-1-2-Bat -3-6-2-1-

Bat -3-6-2-2-

Cu

Pb

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

-0.2 0 0.2 0.4 0.6 0.8 1

-- axis F1 (74 %) -->

-- a

xis

F2

(26

%)

-->

Figure 16. Analysis of principal component (ACP) con-cerning the concentration of Cu and Pb to all parameters studied (in Beirut and Batroun).

For all studied parameters the effect of depth wassig-nificant, and it shows that pollution is growing more; especially with depth at a distance from the coast, but also at the coast which was close to industries, traffic and various sources of pollution.

Similarly, the effect of repetition (2 levies distant from one another by 30 cm) was not significant for different studied metals; proving that for the same sample taken on the same depth, there was no difference, which also shows that the variance linked to the analysis, is void.

For the investigated parameters, there was no effect between layers except for Pb. This is in accordance with the results of the variance analysis, while in the future we can study a single layer for daily analysis in the same region.

It sought to continue this research on much more sites and on time series in order to confirm the effect of layers in other regions along the Lebanese coast. 5

. References

[1] R. Steiner, “Lebanon oil spill rapid assessment and re-sponse mission,” pp. 1–30, 2006.

[2] E. Iaurif, “Regional environmental assessment, report on the coastal zone of Lebanon,” Government of Lebanon, Council for Development and Reconstruction, pp. 46–56, 1997.

[3] R. Kantin and G. et Pergent, “Gestion des écosystemes littoraux méditérranées,” IFREMER et Université de CORSE, pp. 15–45, 2007.

[4] S. Casas, “Modélisation de la bioaccumulation de métaux traces (Hg, Cd, Pb, Cu et Zn) chez la moule Myitlis Galloprovinciallis, en milieu méditerranéen,” Sud Toulon VAR. France, pp. 10–19, 2005.

[5] K. Nakhle and Le Mercure, “le Cadmium et le Plomb dans les eaux littorales libanaises: apports et suivi au moyen de bioindicateurs quantitatifs (éponges, bivalves,

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et gastropodes),” Paris 7. France, pp. 7–14, 32–41, 99–101, 2003.

[6] N. Nassif, “Pollutions chimiques en milieu marin : Essai de modélisation et approche réglementaire,” Edition: GG/F. Janvier, Institut National Agronomique. Paris- Grignon. Paris-France. ISBN: 2–35040–000–X, pp. 9–42, 81, 203–210, annexes 13, 14, 2006.

[7] J. C. Amiard, “Les problèmes liés à l' échantillonnnage et à la détection des élements traces en écotoxicologie,” Vol. 1, pp. 172–195, 1994.

[8] M. Castrec-Rouelle, N. Nassif, and A. M. et De- Kersabiec, “Prélèvements préparation et traitement d'échantillons environnementaux: Approches statisti- ques,” Dossier Environnement, Vol. 32, pp. 23–28, 2003.

[9] C. Biney, A. T. Amuzu, D. Calamari, N. Kaba, I. L. Mbome, H. Naeve, O. Ochumba, O. Osibanjo, V. Radegonde, and M. A. H. et Saad, “Etude des métaux lourds,” Revue de la pollution dans l'environnement aquatique africain, FAO, Vol. 25, pp. 1–6, 1994.

[10] B. Boutier, D. Claisse, D. Auger, E. Rozuel, J. Breteau- deau, and I. Truquet, “Surveillance du milieu marin. Les métaux dans les sédiments du Golfe de Gascogne,” RNO (IFREMER), pp. 17–34, 2005.

[11] E. Bastarache, “Toxicologie, céramique, verrerie et métallurgie,” Smart. Conseil, 2006.

[12] PNUE, “Meilleurs méthodes de gestion pour les sources agricoles non ponctuelles de pollution,” Rapport technique du PEC, Programme pour l'environnement des caraibes, pp. 150, 1998.

[13] R. Mebazaa, “Détermination de la taille de l'échantillon des sédiments marins par étude de la variance,” L'Institut

National Agronomique Paris-Grignon - Centre National des Sciences Marines de Jounieh. Agence Universitaire de la Francophonie (AUF). Mémoire de Diplôme d'études approfondies, Contrôle et gestion de la qualité, pp. 12–22, 2004.

[14] PNUE, “Etat du milieu marin et littoral de la région méditérranéene,” MAP Technical Reports-Series, pp. 3–11, 29–48, 1996.

[15] UNEP, “Etat de l'environnement et politiques suivies de 1972 A 2002, la mer et les côtes. GEO 3,” Le passé, le présent et les perspectives d'avenir, pp. 180–209, 2002.

[16] B. Boutier and D. et Claisse, “Surveillance du milieu marin. Les contaminants chimiques dans les sédiments du littoral méditérranéen,” RNO (IFREMER), pp. 9–52, 1998.

[17] B. Boutier and D. et Claisse, Surveillance du milieu marin. Les carottes sédimentaires, mémoire de la contamination,” RNO (IFREMER) , pp. 21–40, 2001.

[18] J. F. Chiffoleau, D. Auger, B. Boutier, E. Rozuel, and I. et Truquet, “Dosage de certains métaux dans les sédiments et les matières en suspension par absorption atomique,” IFREMER, pp. 6–16. 2003.

[19] Y. Gueguen, “Réalisation d'un système expert pour le bilan de la contamination métallique du réseau hydrographique de la Seine,” Université Pierre et Marie Curie, Université Paris-Sud, et Ecole Nationale du Génie Rural des Eaux et des Forêts. France, pp. 5–6, 2003.

[20] B. Boutier, D. et Claisse, “Surveillance du milieu marin. Les métaux lourds dans les sédiments de la Baie de Seine (campagne 1993),” RNO (IFREMER), pp. 25–32, 1995.



The Challenges of Integrated Management of Mekong River Basin in Terms of People’s Livelihood

Alebel Abebe BELAY, Shah Md. Atiqul HAQ, Vuong Quoc CHIEN, Badandi ARAFAT Vrije Universiteit Brussel, Brussel, Belgium

E-mail: {abelay, satiqulh, vuong.quoc.chien}@vub.ac.be, [email protected] Received October 12, 2009; revised November 19, 2009; December 7, 2009

Abstract Mekong River Basin is a life for many people in six south East Asian countries. The river basin is very pro-ductive and has crucial activities like: fishing, agriculture, hydroelectric power, transportation, biodiversity and so on. However, due to mismanagement, political intentions and one way interest only for development, the river basin has already started experiencing complications. The major challenges found out were, huge hydroelectric dam constructions and other projects, high population pressure, lack of cooperation among ri-parian states (especially upper Mekong region and lower one), and lack of proper management system. This leads to inequitable resource use, impact on water quality, biodiversity loss, and disasters like flooding. It is a high time to make a joint venture among riparian countries for sustainable use of the resource. Multi lateral cooperation and commitment among user countries by consulting all stakeholders will benefit all to use this precious resource equitably without major ecological impacts on the river basin. Keywords: Challenges, Ecology, IWRM, Livelihood, Mekong River, Sustainability

1. Introduction Mekong River is one of the great river systems of the world draining 795,000 km2 covering a distance of 4800kms. Its Annual discharge is about 475 billion cubic meters. The river basin includes parts of China, Myan-mar and Viet Nam, nearly one third of Thailand and most of Cambodia and Lao PDR [1].

In Southeast Asia, it is the region’s largest river ba-sin and widely praised as the “Mekong Spirit”. The climate of the Lower Mekong Basin is governed by monsoons. Agriculture is a predominant economic sector in the Mekong River Basin. The large portion of water use in the river basin is for irrigation with rice as the main crop under irrigation and fisheries are a signifi-cant water user in the Mekong Basin. A large majority of the population earns their living from agriculture and fishing [2].

The great majority of the lower basin’s inhabitants are farmers and fishers, relying quite directly on the natural resource base. Integrity of the basin’s ecology is vital to their social, cultural and economic well-being [3].

The source of the river’s great productivity is its sea-sonal variation in water level, and the range of wetland habitats inundated. Wet season river levels are up to 8-10

meters higher than dry season ones, creating a rich and extensive series of wetlands in the four countries of the Lower Mekong Basin [4].

The biodiversity of the Mekong River Basin is im-mense, and of truly exceptional significance to interna-tional biodiversity conservation even in comparison with other parts of tropical Asia. The river and its numerous tributaries, backwaters, lakes, and swamps support many unique ecosystems and a wide array of globally-threatened species. The diversity of the river fauna itself is sur-passed only by that of the Amazon and the Congo, with between 500 and 1,300 species of fish inhabiting the main channels, tributaries, and associated wetlands [4].

The heavy reliance of the Mekong Basin’s inhabitants on the river, especially for agriculture and fisheries, pre-sents a number of complex, interrelated issues for trans-boundary governance and sustainable development. In the lower basin, which cuts through four countries, 70 percent of the inhabitants are subsistence farmers. Tradi-tional rice cultivation goes hand in hand with fishing and the gathering of forest products [5].

Moreover, high levels of human population and usage have led to increasing unplanned development pressures within the basin, causing many direct threats to most of the important ecosystems and endangered species for

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which the region is renowned. This poses a significant threat to biodiversity and environmental sustainability and thereby to the livelihoods of the Mekong peoples [5].

Only 1.3% of the biodiversity-rich Mekong Delta now remains in a semi-natural condition and the few remain-ing wetland species are wholly reliant on these remnant patches. Degradation of wetland habitats and hydrologi-cal regimes poses perhaps the greatest threat to the vi-ability of one of the most important freshwater fisheries in the world. Widespread hunting and over-fishing, in-flated by a massive illicit wildlife trade, has brought many species to the brink of extinction, and development of river infrastructure is believed to have caused the ex-tinction of a number of endemic fish species [5].

These problems have been exacerbated by sociopoli-tical issues, including widespread poverty, high popula-tion growth, a history of conflict and which caused by the weak governance structure. The growing need for integrated basin management to address food insecurity, rural poverty, environmental degradation, threats to bio-diversity, and tensions among multiple users makes the river basin a good choice for the Challenge Program on Water and Food [6].

Therefore, the objective of this paper is to identify the major challenges of Mekong River Basin management and evaluate its impact on biodiversity issues in particu-lar. Eventually feasible recommendations for effective and sustainable management of the river basin will be forwarded. 2. Challenges in Mekong River Basin

Management 2.1. Challenge Induced by Development Projects Tens of millions of people in the Mekong Basin rely on traditional uses of the water of the river system to pro-vide them with their primary source of nutrition and in-come for their livelihood. Yet, as population numbers increase, these traditional uses and benefits are being threatened. With a relatively low level of development the natural capacity of the river system to supply goods and services may be pushed beyond acceptable limits, as often experienced at the local level. Developing the eco-nomic potential of the Mekong system for domestic use, for hydropower, navigation, irrigation and drought man-agement is the key to fighting poverty and increasing people’s welfare [7].

Today this development is still in its early stages and the Mekong offers a high potential for balanced and sus-tainable socioeconomic development. However develop-ment must carefully take into account the environmental impacts. Independent planning should be replaced by jointly planning which based on regional cooperation and yield better management results. The challenge is not only

to attract significant investments, but also in ensuring that development avoids the risks of environmental degrada-tion, social inequity and international disagreement [7].

Economically and technologically, Mekong’s riparian states were not well-equipped to undertake large-scale exploitation of its waters so far. However, recent devel-opments in the five riparian countries’ economic and political conditions and the region’s increasing demand for energy, is bound to change this picture. This together with considerations of climate change and renewable sources of energy and the rising importance of regional trade and investment flow have stimulated a new era of hydropower development in the basin. In response to market demands, a broad range of developers are now investigating a large number of potential projects. In the last ten years, more than 100 large dams have been pro-posed on the river. Western companies and donor coun-tries are vying for contracts to build dams on the Mekong through international lending institutions with high hopes for substantial profit [8].

Hydropower generation potential and energy demand are geographically imbalanced, thus highlighting the importance of and opportunities for an emerging regional power market. This regional dimension is the driver be-hind most of the current projects with bilateral agree-ments being established for the export of electricity [8].

During construction of dams: it submerged a lot of for-est land (including cash crops), agricultural land, pastoral and waste land. A lot of people were displaced from the inundated area to the inland from river bank. Some of them were moved out to faraway places [8].

The livelihoods of these displaced were depend on agricultural cultivation. Such as: Cash crops like fruits are the main income sources of the local people. Most of the farmlands are located at the alongside of the River. This region has rich resources of water, soil and favorable climates. Depend on these unique natural resources; the people living in the region can produce enough grains for their own consumption as well as for sale. With the reform of the rural economy, the agri-culture production in this region had made great pro-gress. However, the new farmlands received by these displaced farmers because of the dam construction are less productive, some of them placed in hilly area (prone to irrigation), and some of them even didn’t get any compensation at all [8].

Hence, people who had received new lands are facing the problem of food shortages because of their low pro-ductivity cultivation. The living conditions of most of the immigrants are getting worse year by year. Many young people have moved out to work in construction sites as cheap labor. Because of poverty, children are facing the threat of dropping out of education; whereas adults are facing the threat of diseases. There are families that have broken down, with the wives and children leaving home for other provinces. To speak from the perspective of the

A. A. BELAY ET AL. 63 local people, the operation of the dam is also the begin-ning of a disaster for them. However, the company has been denominated as one of the production unit in the Chinese electricity system for five years. Only by the year 2001 the company has got annual profit of around 35 million euro [8].

When comparing the lives of local inhabitants and the benefits to the enterprise and governments, the discrep-ancy is obvious. The main reason for this gap is that in-formation in resettlement policies and decision-making was not disseminated openly enough to the public. The construction of project was started before the immigra-tion, which provide the investors and local governments an opportunity of cutting down the expenses of resettle-ment to meet the escalating construction costs. The plan of resettlement neglected the rehabilitation and devel-opment of immigrants. The estimations about the number of people need to be resettled and their property losses were severely lower than the realties [9].

The other problems being experienced by riparian countries especially by those found downstream of the Mekong River Basin due to the continued dam construc-tion and commercial navigation plan are: suffering from the Mekong’s abnormal floods, signs of such stress in erosion, siltation and changes in water currents. There is also some reduction in fishery resources, impediments to river transportation and exceptional flooding. Its impact might scale up to dry the Tonle Sap ending the famous river fishing industry and causing widespread flooding; and eventually the home of endangered fish specious would be destroyed. A study to look at the downstream impacts is urgently needed for the sustainability of re-sources management in the Mekong. Of course, some preliminary researches show that the change of flow re-gime is a critical factor in the annual flood levels that sustain the region’s fisheries, traditional livelihoods and biodiversity [9].

There was an agreement being signed among riparian countries found in the LMB (lower Mekong River Basin) in 1995 in order to utilize the river sustainably. This agreement has been hailed as a landmark achievement, adopted by the four lower riparian states in the “Spirit of Mekong Cooperation.” It seeks to promote “sustainable development in the utilization, management and conser-vation of the water and related resources of the Mekong River Basin, such as navigation, flood control, fisheries, agriculture, hydropower and environmental protection.” However, the agreement is incomplete since China and Burma didn’t sign on the document. The attempt to apply more stringent rule will normally make more difficult to secure cooperation from all the relevant states. The Agreement has also failed to attract the participation of China and Burma, and this failure is perhaps the biggest setback that stops MRC’s initiatives from becoming truly regional in scope [10].

The challenges in the field of water governance, espe-cially the implementation of water efficiency programs, its impact on people’s livelihood and the environment require a global and joint approach to resource manage-ment, organized at the natural and relevant level of local, national or cross-border river basin districts. In the Me-kong River use, It is clear that China’s participation is particularly important because not only it’s engaging in many large-scale hydropower projects on the Mekong which have important downstream trans boundary im-plications but also because of its dominant role in trade and development in the region. Therefore, the agreement theoretically needs to include all users for maximum and sustainable use of the river basin without significant deleterious effect on the environment [10].

In general, from those projects that are already ac-complished, China still intends to develop a number of big hydroelectric power plants and to make Mekong mainstream navigable from Yunnan to the South China Sea, a distance of some 2,500 kilometers. This poses unprecedented environmental and social problems for the downstream countries Myanmar, Laos, Thailand, Cam-bodia and Vietnam. Severe ecological deterioration of the Mekong River is a foregone conclusion if this plan proceeds. And of course the impacts will not be limited to the river [11].

The downstream countries will be forced to undertake exhausting and largely futile efforts to protect themselves and make up for the damage to their agriculture, fisheries, forests, and way of life. Cambodia and Vietnam, the two countries farthest downstream, will benefit little and will experience the worst negative impacts from the scheme. Particularly at risk are Cambodia’s Great Lake and Viet-nam’s Plain of Reeds and Mekong Delta. China itself will not be immune to adverse impacts. Of particular concern will be sedimentation of the Lancang hydro-power dam reservoirs. Sediment in the Lancang main-stream, already great, is likely to increase due to larger and more frequent landslides and other effects brought about by the dams and their reservoirs. The useful life-time of China’s Lancang cascade of hydropower dams is likely to be only about thirty years rather than the one hundred years foreseen by project proponents [11]. 2.2. Deforestation It is a major issue in the Mekong Basin. The impacts of deforestation on the biodiversity are obvious. Forests have the important role in stabilizing the river’s flow and protection of watershed. However, due to various reasons, forests are decreasing dramatically. In Vietnam, for example, the reasons of deforestation are inappro-priate economic development policies. In total, Viet-nam’s forest cover has declined from 67% in the 1940s to the current 26% [12].


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2.3. Challenge on Population Pressure and Institutional Management

The Mekong River Commission (MRC) has been estab-lished for the sustainable development of the Mekong River Basin to broaden the scope of cooperation in all fields of basin development and resource management, river navigation, flood control, fisheries, agriculture, power, production and environmental protection to prevent and turn the potential conflicts to a mutually beneficial coop-eration and sustainable development of the river basin among member states. And the potential area of conflict is how to ensure use and development of water and re-lated resources to be consistent with the needs to pro-tect, preserve and enhance environment and aquatic conditions, and maintenance of the ecological balance for future [2].

The 1995 agreement on the cooperation for the sus-tainable development of the Mekong River Basin has focused on the activities that must have aim for a balance between the economic, social and environmental dimen-sions of development in the basin because the aquatic and terrestrial environment of the basin supports the live-lihood of the majority of the people especially the rural poor. Use of water resources for development purposes in one country can have negative effects for other coun-tries, unless potential impacts are properly considered during planning. Obviously, environmental management and related socio-economic factors must be understood as integrated in a development process that helps to sus-tain existing livelihoods and promotes the alleviation of poverty, while reducing the risk for conflict over the use of resources within and between countries [2].

Within the riparian countries there is a challenge to in-tegrate management between government agencies both “vertically” between national, provincial and local gov-ernment levels and “horizontally” between ministries and sectors. It has been pointed out by Campbell (2005) that there is a disparity in institutional capability across the riparian countries and in countries such as Cambodia; many of the institutions are relatively undeveloped and need strengthening. And community input is an impor-tant aspect to evaluation of basin wide development strategies if management policies are suppose to reflect aspirations of communities.

The Mekong Basin has diverse social and cultural system and if community participation is to be effective then it must be carried out on a country by country basis in a transparent and flexible manner. This is a challeng-ing task and the National Mekong Committees (NMCs) are, therefore, required to play a key role to address this aspect as they are well placed in respective countries to coordinate with national organizations while still work-ing within the basin wide perspective provided by the MRC [13].

The development of a water utilization procedure and the realization of an agreement to adopt this in practice

by the basin countries involve so many complexities that a truly rational comprehensive decision making approach may be impossible. However, a significant input of re-sources is required if MRC has to achieve an outcome that is acceptable to all the MRC member countries. The implementation of comprehensive integrated resource management policies across the basin will not be possi-ble unless and until the basin wide planning is complete enough to provide a framework for action and agreement is reached on fundamental issues such as water use, sharing of resources in times of scarcity and sharing of benefits [13].

There is another big challenge of greater pressure on water resources from a growing population in Mekong River. This demands for clean and adequate water, food and energy supplies to support economic development without causing serious damage to the environment and ecological system. Integrated water resources manage-ment leading to sustainable development is yet to be achieved in the Mekong River Basin. Effective coordina-tion and management of water and related natural re-sources across the basin is yet to be instituted. Basin wide evaluation, development planning and strategy formulations are in the process. Critical challenges like the understanding of how the basin functions as a system, integrating institutional management, forging community participations and securing resources for building capa-bilities and competence are identified [13].

There is certainly a need for a systematic approach to integrated water resources management. Apart from the requirement of equitable distribution of water among the stakeholders, governance, economic performance and environmental quality are the crucial challenges facing water resources management. Water resources manage-ment must inevitably involve multi-objective tradeoffs in a multi-disciplinary decision making process. However, under the present institutional framework, several de-partments or agencies are dealing with the water re-sources development according to their own require-ments, without much integrated effort towards basin- wide planning and management. A collaborative and coordinated effort is needed among all the stakeholders involved in order to address the issues and challenges of water resources management [13].

In the past most countries did not pay attention enough to the management aspects as the resource was abundant compared to the demand and easily obtained from river, lakes, and canals and from rainfall. With the growth in demand over the years, many regions are facing short-ages of water, particularly in the dry season, and, fre-quently, excess of water during the wet season. These concerns result not only from the scarcity or excess of water, but also from the lack of appropriate water man-agement policies and institutional structures to utilize the national water resources effectively. With the promotion of the concept of integrated water resources management,

A. A. BELAY ET AL. 65 an appropriate shift in the water management paradigm is needed, considering three important elements of an enabling environment, effective institutional structure, and appropriate tools and technologies. This should be viewed as a flexible framework to be adapted within the economic, strategic and social dimensions of each coun-try concerned [13]. 2.4. Challenges Regarding Pollution and Water

Quality Water quality is one of the key factors affecting the en-vironmental health of the Mekong river system. As the livelihoods of most of the 60 million people who live in the Lower Mekong Basin (LMB) wholly or partly de-pend on aquatic resources, the environmental health of the river is a major concern to the governments of the countries in the basin. In 1985, the Mekong River Com-mission (MRC) established the Water Quality Monitor-ing Network (WQMN) to provide an ongoing record of the water quality of the river, its major tributaries, and the Mekong Delta [11].

Three main categories of water-quality indexes (WQI) were used: 1) for the protection of aquatic life (WQIai); 2) for human impact (WQIhj); and 3) for agricultural use (QWIag). Each WQI category is subdivided into classes according to the number of chemical parameters (DO, pH, etc.) that meet guideline thresholds. Based on the classifi-cation and index the quality of the river and its use for different purpose has been tried to be assessed [11].

In the mainstream and tributaries, the WQIai is mostly High Quality. However, in the Delta from the total 8 stations four are Moderate Quality, and one is Poor Quality. Signs of significant human impact on water quality are observed at stations in the uppermost part of the LMB and downstream of Phnom Penh. The lower index values at the downstream stations reflect higher population densities, particularly in the highly populated and intensively farmed Delta. In addition, one of the Delta stations of the WQIhi is classed as Severely Im-pacted. Moreover, some stations on the Cau Mau Penin-sular of the Delta were under the class of Severe Restric-tions [11]. 2.5. Major Sources of Mekong River Water

Pollution 2.5.1. Municipal Waste Water The two largest urban areas (Vientiane in the Lao PDR, and Phnom Penh in Cambodia) are of concern as they lie on the banks of the Mekong. Currently, Vientiane, a city of less than 500,000 inhabitants, discharges its municipal sewage into the That Luang Marsha wetland that dis-

charges into the Mekong River some distance down-stream of Vientiane. This discharge is small at this time and is not thought to pose any immediate risk to the mainstream of the Mekong. However development and population growth it may pose greater threats to the mainstream in the future [11].

Phnom Penh approximately with 1.7 million inhabi-tants also discharges much of its urban sewage into a series of wetlands that drain into the Bassaca tributary of the Mekong. In addition, certain industrial and municipal discharges as well as storm-water runoff discharge di-rectly into the Tonle Sapa tributary of the Mekong [11].

The MRC reports in 2007 about local pollution of an industrial nature in the Tonle Sap at Phnom Penh. There are also a number of floating villages on the Great Lake of Cambodia. These populations discharge domestic sew-age directly into the water column. However, the loading and significance of these discharges are not known. Us-ing population statistics and data on urban sanitation coverage’ for year 2000, the total discharge from urban areas was found 150,000-170,000 tones /year of BOD, 24,000-27,000 tones/year of total-N, and 7200-8100 tones/ year of total-P [ibid]. These values indicate that it is by far very strong and concentrated waste that can affect the aquatic ecosystem of the river and consequently biodi-versity and human livelihood in the long run [14]. 2.5.2. Industrial Wastewater Industrial development has the potential to increase sub-stantially the pressure on aquatic resources. For example, in the upper Mekong region especially the Yunnan Prov-ince in the People’s Republic of China, located immedi-ately upstream of the Chinese/Lao border, is reported to have inspected 1042 industrial enterprises in the basin in 2000 (CIIS, 2002). Among them the dangerous one like the Lanping Lead-Zinc Mine has been built on the banks of the Lancang (Mekong) River which could have a tre-mendous impact on the LMB. In general at present there is no much information and strong evidence available on industrial discharges to the river because of limited re-search work on this specific section [11]. 2.5.3. Agriculture Agriculture sector has also its own pollution potential in the river basin. Based on available data suggest, a loss of about 225,000 tons of Nitrogen and 37,000 tons of phos-phorus per year. There is some evidence for transboundary transmission of pollutants from the Upper Mekong Basin into the LMB. There is no sign of any significant basin- wide trends for any parameter regarding pollution status from agriculture. However, with the continuing develop-ment of both, agriculture (increased use of fertilizers, pes-ticide) and urbanization there will be a threat in the changes of water quality in some tributaries [11].


A. A. BELAY ET AL.


66

3. Principal water Quality Issues in the Lower Mekong Basin

Salinity: High salinities caused by saltwater intrusion are nearly ubiquitous in the Delta (but not on the main-streams of the Mekong and Bassac Rivers). Fifty-four of the stations analyzed have a maximum conductivity greater than the threshold of Some Restrictions in the WQIagi (for general agricultural use). For nine of these sites located in on the Ca Mau peninsula of the Delta, the WQIagi is at the level of severe restrictions [11].

Acidification: When exposed to air (oxygen) sulphate soils in the Delta produce sulphuric acid, which leaches to the canal system. The most severely affected area is the Plain of Reeds, but similar effects are recorded in some areas in Cambodia. The situation in the Plain of Reeds seems to improve in the western parts of the canal system that are close to the Mekong. Further east, there are still times of the year when extremely low pH-values are measured [11].

Eutrophication: There is a significant increase in the total-P concentrations at the mainstream stations, while no such difference is found for the tributaries. Although the concentrations of nitrogen and phosphorus generally are lower than the threshold values for WQIa1, there is a possibility of an effect on algae, and floating aquatic vegetation. In general, due to the greater discharge of Mekong River the possibility of eutrophication seems unlikely [11]. 4. Challenges on Biodiversity Biodiversity in the Mekong River Basin is fundamental to the viability of natural resource-based rural livelihoods of a population of 55 million people living in the Lower Mekong Basin-equivalent to more than 90% of the population of the entire Mekong River Basin [4].

Biodiversity loss is a major problem in Mekong River Basin. For instance, fish species diversity in the basin is currently estimated at 1200 species, and could be as high as 1700 species. The difference clearly shows there is a very rapid biodiversity loss in the river basin. Besides the anthropogenic impact on biodiversity loss the dynamic nature of floodplain ecosystems also drives fish to mi-grate, often very long distances, contributing to both ge-netic mixing and isolation of populations. Although only a fraction of migratory species have been studied, in only modest detail, to date, a high proportion of these are thought to have distinct populations within the Mekong Basin [15].

A serious decline in biodiversity is an indicator of un-sustainable development. And in this regard, the fisheries are unquestionably of paramount importance. Maintain-

ing biodiversity must be a key goal in the quest for sus-tainable development of the Mekong. Fisheries as a threat to biodiversity because of widespread over-ex-ploitation of stocks, the use of destructive fishing gears, large by-catches (killing unused species) and general mismanagement of resources which leads to biodiversity loss especially for some endangered specious [12].

But still the degree of diversity is large due to the complexity of the Mekong river ecosystem. The river and its tributaries originate high in mountainous areas and flow through a wide variety of landscapes as they wind their way to the sea. Variation in climate, geology, terrain and water flow results in river habitats of almost unlimited variety. Seasonally-flooded forest represents a type of habitat that is particular rich in life. The pressure of the riparian communities and their fishery demand is one of the big challenges for Mekong River Basin. Ac-cording to Mekong River Commission the Lower Me-kong fishery supports up to 40 million people and two third of the population of the lower Mekong Basin are actively involved at least part-time in the fisheries. The average catches per fisher, although tend to low in rivers, but participation in the fishery is very high [16].

There are a number of factors influencing the biodi-versity of the River. However, two types of activities, which frequently mentioned are over exploitation and environmental degradation. While the former considered bringing less adverse impacts to the basin, the later raises special concern of the environmental actors. Regarding the extraction of fish in the basin, the use of destructive fishing methods (explosive, poisons and electrocution) is mentioned as a big threat and need to be ban completely. Considering the environmental degradation, the expan-sion of agriculture and aquaculture are taken into account. For example, in Vietnam, inland fisheries production is expected to rise from 310,000 tons (1992) to 600,000 tons in 2000, due mainly to increased aquaculture production. This practice has resulted in the clearance of thousand hectares of forests [12].

Problem with the release of farm-raised native species are well documented in the rivers, particularly for highly migratory species (as occur in Mekong River Basin). Therefore, the determination whether a particular ani-mals are exotic to a certain area can only be made by considering diversity at the genetic level, not at the spe-cies level. However, it is not always easy to measure the change in genetic of any species in a short time. Hence, the evaluation of biodiversity at Mekong River is really a big challenge [12].

Although over exploitation is a problem in rivers, it has yet to lead to collapses of fisheries (with the excep-tion of certain vulnerable species). Environmental deg-radation is the threat instead. As nearly 75% of the re-gion population is employed in agriculture, fishery and forestry [16]. The intensification of agriculture in the Delta is reliant on increased use of agrochemicals. Un-

A. A. BELAY ET AL. 67 fortunately the management of chemical use in agricul-ture and in many other sectors is a difficult task and not always success, impact on the environment due to over use of chemical becomes uncontrollable. For instant, the Mekong Water Quality Monitoring project (1989) has found the presence of organ chlorines in water and fish tissue [12].

Rice cultivation is a good example of how agriculture activity causing the environmental degradation in the region. Regard to Vietnam case, the Mekong Delta is crucial as it’s “rice bowl”, producing half the rice and 40% of total agricultural output, making it the richest agricultural zone in the country [12]. Increased agricul-ture production has fuelled economic “renovation” or “doi moi” and the Mekong delta has been instrumental in this continuous process. And especially, Mekong Delta is considered as a main source both of food security and export income, contributing significantly to the GDP of the country. However, as mentioned earlier, rice produc-tion might be increase the risk for environmental degra-dation due to the overuse of pesticides. 5. Impact of Flooding and its Management Flooding is a way of life along the lower Mekong River in Vietnam and Cambodia. Every year between August and November, monsoon rains fill the rivers of Southeast Asia, and the Mekong River Delta broadens well past its dry season levels. The annual floods carry nutrient-rich silt to farmland around the river and provide the moisture needed to grow vast fields of rice. Vietnam is the second largest exporter of rice in the world behind Thailand, and the Mekong River Delta is one of two primary rice- growing areas in the country [17].

In Thailand, some local residents and environmental-ists told IRIN they suspected Chinese dams and the de-struction of small Mekong river islands to clear passage for Chinese cargo ships had aggravated flooding in the region. They also blamed the Mekong River Commission for failure to warn people about the flooding [18].

Due to the fact that flooding has become annually ex-pected dangerous event in the basin, the Mekong River Commission is conducting Flood Forum every year for better understanding, early preparation, forecast and mitigation. The forum provides an opportunity for man-agers, planners, practitioners and scientists from riparian states, international organizations, and civil society or-ganizations to meet and exchange experiences and in-formation addressing flood issues and to identify ways to improve flood management using a balanced regional and holistic approach [19].

In fact the Mekong floods play an important role in the development of the country as they carry and distribute fertile silt into the floodplain for agriculture production,

Figure 1. Flood inundated area, 2002 (Source:http://www. mrcmekong.org/programmes/flood.htm and 6th annual flood forum). feed the food chain for fisheries, provide water supply for people living along the river side, provide navigation routes and necessary environmental functions, but ex-treme floods usually cause severe damage and suffering, especially to people living in low lying areas. It is, therefore important to find ways how to get the maxi-mum benefits and the minimum risk or damages from floods. To achieve this more effort and commitment as well as coordination and cooperation between institu-tions and people concerned are needed. Problem regard-ing forecasting has been observed especially in Cambo-dia and needs to be strengthening in a more scientific base and more efficient technical staff for better and ac-curate flood forecasting. Not only countries found in the lower Mekong River Basin that are affected but also China has frequently been hit by floods and suffered from flood disasters [20]. 6. Conclusions and Recommendations Integrated Water Resources Management (IWRM) is a process, which promotes the coordinated development and management of water, land and related resources, in order to maximize the resultant economic and social welfare in an equitable manner without compromising the sustainability of vital ecosystems and future genera-tion. However, the management of Mekong River Basin is not following this natural balance and equity. This is due to high population pressure, development and tech-nological advancement and less political commitment and cooperation to use the resource equitably without harming the environment [13].

Management of the Mekong River Basin and its natu-ral resources need to be integrated due to the complexity of various socio-economic, cultural and environmental issues in the basin. An appropriate approach should take into account the combination between physical, biologi-cal, institutional, political, social and economic interests. At all level, the approach needs to consider the implica-tions of development in one sector on the well-being of other sectors, both on-and off-site.

Regarding the biodiversity conservation at the Me-kong Basin, in one hand, it needs to be considered in the relation with the livelihood development of the riparian communities and the development of the riparian coun-tries. On the other hand, any development policies should


A. A. BELAY ET AL.


68

take into account the adverse impact on the Mekong Ba-sin, in both sustainable use of natural resources and con-servation of biodiversity. The integrated management of Mekong Basin requires also providing of adequate knowledge on sustainable use of natural resources to various stakeholders. It also requires a closely and effectively collaboration among different stakeholders in order to share equally benefits and responsibility as well as risks in the management of the Mekong Basin.

For optimal and equitable development of the Me-kong’s water resources require collaborative planning and joint identification of investment priorities, referring to basin-wide strategies in each water-related sector.

This may also be usefully supported by multi-sect oral analysis and the simulation of various development sce-narios and their effect on the river flow regime. In con-clusion, the Mekong River Basin needs the attention of all riparian countries with full commitment and motiva-tion to use it equitably without serious impact on it. This multilateral cooperation also needs the involvement of all stakeholders to meet the need of the poor in front. Moreover, development projects needs to have impact assessment of the current and future generation and the environment as a whole. Development shouldn’t be un-der the cost of the environment. The MRC has to influ-ence the upper basin countries like China to join and sign the agreement for better utilization of the basin with common understanding among the riparian countries. 7. References [1] D. Clayton, “Challenge program on water and food,”

CGIAR, 2008, Retrieved 22:00, 11 April 2009 from: http://www.waterandfood.org/basins/mekong-river-basin.html

[2] MRC, “Strategic plan 2001-2005, Mekong River com-mission secretariat,” Phnom Penh, 2002.

[3] Philip Hirsch and Gerard Cheong, “Natural resource management in the Mekong River Basin: Perspectives for Australian development cooperation,” University of Sydney, 2000.

[4] Mekong wetlands biodiversity conservation and sustain-able use programme, 2004, Retrieved 12:20, March 16, 2009 from: http://www.mekongwetlands.org/Programme/mekong.htm

[5] Mekong wetlands biodiversity conservation and sustain-able use, Retrieved 22:00, March 22, 2009 from:

www.undp.org/gef/05/documents/writeups_doc/bio/MekongnotesBioD1.doc

[6] CGIAR, “Challenge programme on water and food, Mekong River Basin,” Retrieved 18:25, 26 march 2009 from: http://www.waterandfood.org/basins/mekong-river-basinhtml

[7] MRC work programme: Mekong river commission for sustainable development, 2007.

[8] Mekong River Commission, 2008, Retrieved 16:30, April 16, 2009 from: http://www.mrcmekong.org/programmes/ flood.htm

[9] M. Quang, P. E. Nguyen, “Hydrologic impacts of China’s upper Mekong dams on the lower Mekong River,” 2003.

[10] Tashi Tsering, “Mekong: Managing a transboundary River,” 2008, Retrieved 18:25, 26 march 2009 from: http://www.sdnpbd.org/river_basin/transboundary/document/mekong.pdf

[11] MRC Technical Paper, “An assessment of water quality in the Lower Mekong Basin, meeting the needs, keeping the balance,” No. 19, 2008.

[12] Mekong River Commission, “Biodiversity and Fisheries in Mekong River Basin,” 2003.

[13] A. D. Gupta, “Challenges and opportunities for integrated water resources management in Mekong River Basin: Role of water sciences in transboundary river basin man-agement,” Thailand, 2005.

[14] C. Marina, A. Paolo, and S. Alfredo, “Water quality con-trol in the river Arno, science direct, waster research,” Vol. 30, No. 10, pp. 2673–2680, 2002.

[15] D. Coates, A. F. Poulsen, and S. Viravong, “Governance and transboundary migratory fish stocks in the Mekong River Basin,” Presented at the MRC Third Fisheries Technical Symposium, Mekong River Commission, Phnom Penh, in press, 2000.

[16] Mekong River Commission: Annually Report, 2006.

[17] G. Halusa, “Visible earth,” 2008, Retrieved 18:25, 05 April 2009 from: http://visibleearth.nasa.gov/view_rec.php?id= 19596

[18] IRIN, 2008, Retrieved 20:00, April 16, 2009 from: http://www.alertnet.org/thenews/newsdesk/IRIN/4842e788c4ef45c66b509654ebfb6652.htm

[19] Mekong River Commission, “Regional multi-stakeholder consultation on the MRC hydropower program,” consul-tation proceedings, 2008.

[20] Integrated approaches and applicable systems for me-dium-term flood forecasting and early warning in the Mekong River Basin, 6th Annual Mekong Flood Forum, proceeding, Phnom Penh, Cambodia, 2008.

J. Water Resource and Protection, 2010, 2, 69-76 doi:10.4236/iwarp.2010.21008 Published Online January 2010 (http://www.SciRP.org/journal/jwarp/).


The Analysis of Spring Precipitation in Semi-Arid Regions: Case Study in Iran

Hossein Ali HASANIHA1, Majid MEGHDADI2

1Department of Water Resource Engineering, Faculty of Agriculture, Zanjan University, Zanjan, Iran 2Department of Compute Engineering, Faculty of Engineering, Zanjan University, Zanjan, Iran

E-mails: [email protected], [email protected] Received October 13, 2009; revised November 16, 2009; accepted November 24, 2009

Abstract

In this study, Zanjan from Iran has been chosen from among all the semi-arid regions of world, which has Synoptic station and statistical data since 1955. Spring and monthly precipitations are also provided in the period of 1956-2005. First, all data has been controlled by double mass method with the help of adjacent sta-tions, and then it was normalized by the box-cox transformations method. The global SPI index was calcu-lated for all months and spring, also drought and wet periods were determined and finally compared. In the drought category view, spring months have represented the great similarities. The moving averages are rep-resented all months and spring’s precipitations such as three years, five years, seven years and nine years are shown. Statistical period was observed and analyzed based on five periods of ten years, and results precipita-tion with more than 5mm and 10mm has gradually decreased on April. However the number of days with pre-cipitation has increased. The calculated spring precipitations and all of the atmospheric factors represented the dependence of this model to maximum average of spring temperature and relative humidity of spring and winter by the use of multi variable regression method. The predicted precipitation of spring also showed the gradual decline of precipitation in the next 30 years by the arima model. Keywords: Iran, Semi-Arid Regions, Precipitation, Drought, Box-Cox Transformations Method, Arima Model

1. Introduction The semi-arid regions involve the great part of the earth’s all arid regions. Nowadays, the study of these regions is one on the most important studies; especially in the last two decades, where there is repetitive drought as a result of shortage of precipitations [1]. These short-ages have caused some changes that tend to have influ-ence on these regions. The lack of precipitation’s time distribution is one of the features of the regions, so that there is a great degree of precipitations in the seasons other than the required seasons and can not be controlled. The shortage precipitations and repetitive drought in the last two decades made the rural people to immigrate from villages to cities. Also, the cultivating and animal husbandry has been under losses. These immigrations tend to great problems in the cities’ management. The shortage of the precipitations causes some problems in providing beverage water of cities and industries’ water. As a result of this issue stores and dams become dry and the surface of underground canals began to decline in terms of excessive use. Consequently, the study of pre-

cipitations trend and acquaintance of their condition in this period is more useful. In this study, our focus is on the spring precipitations in the semi-arid regions of the world.

Semi-arid regions’ importance is because of their ca-pacity of dry farming. Also, the great amount of these regions’ precipitations in the spring become in the form of rainstorm which is out of control. Therefore acquaint-ance with the precipitations trend of these regions, in terms of number of factors such as amount, rate, contin-uousness, recurrence, maximum, minimum degree and day of precipitations, can lead to the correct and proper planning [2]. In this respect we can have proper planning of watering and dry farming, filling of dam, saving su-perficial water sources, distributing of the flood waters, feeding groundwater tables, preventing floods, and over-flows, soil protection and watershed. 2. Materials and Methods 2.1. The Study Site A semi-arid climate or steppe climate generally described

H. A. HASANIHA ET AL.


70

Figure 1. Arid and semi-arid regions of the world.

Figure 2. Iran and the location of Zanjan. climatic regions that received low annual precipitation (250-500 mm or 10-20 in). A more precise definition was given by the Köppen climate classification that treated steppe climates (BS) as intermediates between the desert climates (BW) and humid climates in ecological charac-teristics and agricultural potential [3]. The Köppen cli-mate classification allows adjustments for temperature and for seasonality of precipitation, effectively excluding forested regions. (In the tables and figures hereafter, the statistics and information belongs to Zanjan).

In this study, we have chosen Zanjan synoptic station where is one of the semi-arid regions of the world in or-der to observe spring precipitations’ trend in these kinds of areas. Figure 1 represents the semi-arid regions of the world and Figure 2 shows Iran’s geographical map in which Zanjan is specified. Zanjan is located in the North-West of Iran which has 29, 48º longitude and 36, 47º latitude and 1663.6 m height of see surface [4].

The average precipitation in a year reached to 313.1 mm in Zanjan and its average temperature was 10º C in a year, it is necessary to say that the number of glacial days is 117 and the average of evapotranspiration reached to 1025 mm during a year.

Near to 238 million cube meter of the whole amount of Zanjan precipitation that equaled to 1157 million cube meter, was the same as 21 percent of the whole amount of precipitation of this area, in which there was no uses and even in some cases it caused to some material and

financial damages such as demolition of agricultural lands and gardens, institutions, buildings, and communi-cation means [1]. 2.2. Used Method 2.2.1. Double Mass Method One of the common graphic methods which are used for making sure of the homogeneity of data is double mass method. This method is usually used for homogenizing of data related to the precipitation and flowing waters [5].

If we had hydrologic time series data in the condition that they had any periodic and non-periodic changes, we could call those data as stationary data. There was al-ways the stationary (fixed) amount of mean and variance if some other identical data was added to them. However, in some cases where the data are not similar we should ho-mogenize them first or make sure they are homogeneous. 2.2.2. The Box-Cox Transformations Method The most commonly used symmetry-producing trans-formations are the two closely related functions;

2 ( 1) / ; 0 (1)

2 ;nL 0 (2)

Here “Spread” is some resistant measure of dispersion, such as the “Inter-Quantile range” or “Median absolute deviation”. The Hinkley is used to decide among

power transformations essentially by trial and error, by computing its value for each of a number of different choices for

d

[6].

( / ) /Spread Max Min 4 (3)

/d Average Median Spread (4)

(( ) /

)4

Average Mediand

Max Min

(5)

In the aforementioned method, data are normalized. In other words, data are not normal in %99 of cases and all of the time series of data, and central norms such as mean, median and mode have some differences however they cover one another in the vertex. To analyze data, first we should normalize them.

Normal or Gaussian distribution Law is: 2

2

( )

21

2

x

Y e

(6)

where:

π = 3.14, e = 2.72, µ = mean and σ = variance.

All normal averages are similar and bell shaped and their difference is just in the amount of µ and σ. We as-sign λ to different numbers in box-cox transformations



71

method formula and then calculate dX. The value of dX is calculated by trial and error. The value of dX is usually acceptable up to 0.01. In order to normalize the data, we do analyzing it near to 0.00 and make sure that all data are normalized %100.

2.2.3. The Standardized Precipitation Index (SPI) To calculate the SPI, a long-term precipitation record at the desired station was first fitted to the probability of distribution (e.g. gamma distribution), which was trans-formed into a normal distribution later so that the mean SPI is zero. The SPI might be computed with different time steps (e.g. 1 month, 3 months, and 24 months). Positive SPI values indicated greater than mean precipi-tation and negative values indicated less than mean pre-cipitation [7] (See table 1).

In this research, we used global SPI Index in order to study the drought, and we calculated the SPI precipitations of the months of spring. The above table represented the SPI Index for categorizing of wet and drought periods. 2.2.4. Stepwise Linear Regression Linear Regression estimated the coefficients of the linear equation, involving one or more independent variables that best predict the value of the dependent variable. Method selection allowed us to specify how independent variables were entered into the analysis. Using different methods, we could construct a variety of regression models from the same set of variables. In Stepwise Linear Regression, the independent variable not in the equation which had the smallest probability of Analysis of Vari-ance (F), was entered at each step, if that probability was sufficiently small. Variables already in the regression equation were removed if their probability of F became sufficiently large. The method terminated when no more variables were eligible for inclusion or removal [8].

This research used multi variable regression-stepwise- method that existed in SPSS software in order to reach spring precipitations’ model in terms of all the atmosph eric characteristics. 2.2.5. Arima Forcast Model Arima fitted a box-jenkins arima model to generate fore-costs. Arima stands for autoregressive integrated moving

Table 1. The standardized precipitation index values.

Category SPI

Extremely Wet Severely Wet Moderately Wet Lightly wet Lightly Drought Moderately Drought Severely Drought Extremely Drought

≥ 2,0 1,50 to 1,99 1 to 1,49 0 to 0.99

0 to -0,99 -1 to -1,49 -1,50 to -1,99

-2,0

average with each term representing steps taken in the model construction until only random noise remained [9].

In this study we used time series and arima model that is a linear model. Ochoa [10] used time series and he di-vided the method into two groups linear and non-linear models. He mentioned that results of linear models-like arima model – are very better than non-linear models [10].

Table 2. Drought category in different periods.

Year April May June Spring

1956 - S. D. - L. D. 1957 - - - - 1958 E. D. L. D. - L. D. 1959 S. D. - - - 1960 - S. D. - L. D. 1961 L. D. M. D. L. D. E. D. 1962 - - - - 1963 - - L. D. - 1964 - S. D. M. D. L. D. 1965 - L. D. - - 1966 - L. D. M. D. M. D. 1967 L. D. - M. D. - 1968 - - - - 1969 - - - - 1970 M. D. - M. D. L. D. 1971 - - M. D. - 1972 M. D. - - - 1973 L. D. L. D. M. D. M. D. 1974 - M. D. M. D. L. D. 1975 - - - - 1976 - - L. D. - 1977 L. D. - - - 1978 E. D. - - L. D. 1979 M. D. L. D. - L. D. 1980 L. D. L. D. L. D. M. D. 1981 - - - - 1982 - - L. D. - 1983 L. D. - L. D. - 1984 - - L. D. - 1985 - M. D. L. D. L. D. 1986 L. D. - - - 1987 L. D. L. D. L. D. L. D. 1988 - M. D. - L. D. 1989 M. D. L. D. L. D. E. D. 1990 - L. D. M. D. L. D. 1991 L. D. L. D. - L. D. 1992 - - - - 1993 L. D. - L. D. L. D. 1994 - L. D. M. D. - 1995 L. D. - - - 1996 - - M. D. - 1997 L. D. L. D. - L. D. 1998 L. D. L. D. - L. D. 1999 M. D. L. D. L. D. E. D. 2000 L. D. S. D. L. D. E. D. 2001 M. D. L. D. - S. D. 2002 - L. D. L. D. L. D. 2003 - - - - 2004 L. D. - - - 2005 M. D. - M. D. -

L. D. = (Light Drought), M. D. = (Moderately Drought), S. D. = (Severely Drought ), E. D. = (Extremely Drought)



72

0

2

4

6

8

10

12

14

16

18

April May June Spring Period

Dr. F

requency

Light D.

Mode. D.

Seve. D.

Extre. D.

Figure 3. Drought frequency at different periods.

Zanjan April SPI (1956-2005)

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

1956

1958

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Year

SP

I

Zanjan May SPI (1956-2005)

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

1956

1958

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Year

SPI

Zanjan June SPI (1956-2005)

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

1956

1958

1960

1962

1964

1966

1968

1970

1972

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

Year

SP

I

Zanjan Spring SPI (1956-2005)

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

1.50

2.00

195

6195

8196

0196

2196

4196

6196

8197

0197

2197

4197

6197

8198

0198

2198

4198

6198

8199

0199

2199

4199

6199

8200

0200

2200

4

Year

SPI

Figure 4. Spring precipitation SPI values in different periods.

This study was done in Zanjan synoptic station using arima model which exists in Minitab software in order to predict the spring 30 years’ precipitations. By using the past fifty year data, we predicted the coming thirty years precipitations of station.

3. Results and Discussion The opposite situations of drought categories during 1956–2005 are represented. In four periods, light drought category is replicated more than others (Table 2 and Figure 3). On June there were no intensive categories of drought and all ones were in the mean and slight catego-ries. It is necessary to mention that on May there was lack of most intensive categories; however, all of the categories existed on April.

We have drawn the SPI Index’s value on the different time periods in Figure 4. In this figure, the intense of droughts was the most one on April and the last on June. The accumulation of recurrent drought is well cleared in recent years. In [11] the authors used SPI index to inves-tigate meteorological and hydrological drought to see the surface of groundwater tables and to forecast drought. SPI index was not estimated in different time periods. This index has shown a good correlation with GRI index in which it inspects and forecast the conditions of groundwater tables.

The moving averages of precipitations for the periods of 3, 5, 7 and 9 years of April were represented (Figure 5). In the figures you could find the wet and drought pe-riods more clearly and also the gradual decrease of pre-cipitation during fifty years statistical period. As the nine years moving average represented, the amount of accu-mulated precipitation of April in Zanjan decreased from 60 mm to 40 mm.

The moving average of precipitation of 3, 5, 7 and 9 years during the statistical period has been shown in Figure 6. As the average represents, the amount of ac-cumulative precipitation during spring decreased from 110mm to 80 mm .

The graph of wet and drought periods during 50 statis-tical years for all months of spring and also for spring itself is shown in Figure 7. Among four trends of drought period’s representations, we confronted with some simi-larities between May and spring as a whole.

We analyzed the fifty years precipitation of statistical periods (1956–2005) in terms of ten years periods. Fig-ure 8 represented the change of ten years precipitation for different periods. Although all periods showed grad-ual decrease during the statistical periods, this trend be-came clearer on April.

Figure 9 represented the accumulative precipitation of different months of spring in terms of percent. As this figure shows, the amount of spring precipitation on April, May nd June are respectively %52.90, %37.85 and % 9.25. a



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Figure 7. Drought duration in different periods.

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Spring Precipitation = 1.1519 May Precipitation + 53.162,

Pearson R2 = 0.7113 Periods In Figure 10, you could find maximum precipitation of a

day (24 hours) on April during fifty-year statistical period. As figure shows, this precipitation (Maximum precipitation of a day (24 hours) on April has decreased in recent years.

The number of days with precipitation that was more than 10mm in April during the statistical period showed a regular gradual decrease during statistical period. Also you could find the number of days with precipitation of more than 5mm on April and their frequency in Figure 12.

The number of days with precipitation on April during 50 years of statistical period indicated a gradual decline of precipitation during statistical period in Figure 8. however the number of days with precipitation relatively increased.

We calculated the regression of multi variables be-tween accumulative precipitation of spring and all at-mospheric factors by Stepwise option of multi variable regression method of SPSS software. The model ex-tracted form this regression marked the dependence of accumulative precipitation of spring to factors such as average of maximum temperature and average of relative humidity.

Spring Precipitation Total = 433.732 – 11.666 spring’s Average of Max. Temperature + 3.590 spring’s Average



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Figure15. Moving average of natural spring precipitation and our forecast at different periods. of Relative Humidity (at 09 UTC.) – 2.490 winter’s Av-erage of Relative Humidity (at 03 UTC).

R = 0.772 and R2 = 0.60 We predicted the past accumulative precipitation of Zanjan by the use of 50 years statistics, and also we an-ticipated 30 years precipitation in this region during-spring by arima model and Minitab software. In Figure 14, you could find the past accumulative precipitations and predicted ones all together and also the graded de-cline of several accumulative precipitations during last 50 years statistical period and coming 30 years respec-tively.

The moving average of natural spring predicted in 3, 5, 7, and 9 accumulative precipitations during spring was

represented (Figure 15). The wet and drought periods of 80 years and the graded decline of several accumulative precipitations of 110mm to 80mm in 9 years moving aver-age is perceptible through this figure. 4. Conclusions Authors in [12] have studied region commentary and the management of superficial water sources on semi-arid areas especially it has inspected and forecasted the con-dition of meteoric – atmospheric - rainfalls. In 2050 (40 years later) meteoric rainfalls decreases up to %20 to %25 in north of Africa, some parts of Egypt, Saudi Ara-bia, Iran and Syria. Our study has gassed almost the



76

same in 30 future years to decrease %20 in semi-arid areas.

In this paper, we have addressed spring precipitation in semi-arid regions. Spring and monthly precipitations are provided in the late 50 years. Statistical period was observed and analyzed. Results show that the number of days with precipitation has increased. But precipitation with more than 5mm and 10mm has gradually decreased on April. Results represented the dependence of this model to maximum average of spring temperature and relative humidity of spring and winter by the use of Multi Vari-able Regression method. The predicted precipitation of spring also showed the gradual decline of precipitation in the next 30 years. 5. References [1] D. Khalili and A. Ganji, “Analysis of drought with simple

time series/disaggregation models, utilizing short record length,” (Persian), Preceding of First National Confer-ence on Drought Mitigation and Water Shortage, Jahad Daneshgahi Kerman and Shahid Bahonar University Pub-lication, Vol. 66, pp. 581–593, 2001.

[2] WMO (World Meteorological Organization), “World climate news,” The Challenges of Climate Adaptation, Weather Climate and Water (WCN), Vol. 33, pp. 4–11, 2008.

[3] U. Lohrnann, R. Sausen, L. Bengtssonl, U. Cubasch, J. Perlwitz, and E. Roeckner, “The Koppen climate classi-fication as a diagnostic tool for general circulation mod-els,” Climate Research. Vol. 3, pp. 181–190. 1993.

[4] WMO (World Meteorological Organization). “Climate: Into the 21st century,” Publisher: Cambridge University

press. Editors: William Burrought, Vol. 240, pp. 11–28, 2003.

[5] A. Alizadeh, Eds., “Principles of applied hydrology,” (in Persian), Astane Ghods, Bonyade Ferhengiy Rezevi Pub-lication, Meshhad, Iran. pp. 451–461, 2006.

[6] T. Takahiro and H. Yuzo, “A modified box-cox trans-formation in the multivariate arima model,” In: Journal of the Japan Statistical Society. Vol. 37, No. 1, pp. 1–28, 2007.

[7] T. B. McKee, N. J. Doesken, and J. Kleist, “The rela-tionship of drought frequency and duration to time scales,” In: Proceeding of the 8th Conference on Applied Climatology, American Meteorological Society, Califor-nia, 17–22, pp. 179–184, 1993.

[8] R. W. Simmons and P. Pongsakul, “Preliminary stepwise multiple linear regression method to predict cadmium and zinc uptake in soybean,” In Communications in Soil Sci-ence and Plant Analysis, Vol. 35, No. 13, 14, pp. 1815– 1828, 2005.

[9] P. Brockwell, J. Davis, and A. Richard (Eds), “Introduc-tion to time series and forecasting series,” Spring Texts in Statistics, 2002.

[10] J. C. Ochoa, “Prospecting droughts with stochastic artifi-cial neural networks,” Elsevier Journal of Hydrology, Vol. 352, pp. 174–180, 2008.

[11] G. Mendicino, A. Senatore, and P. Versace, “A ground-water resourceindex (GRI) for drought monitoring and forecasting in a mediterranean climate,” In Journal of Hydrology, pp. 5–15, 2008.

[12] R. Ragab and C. Prudhomme, “Climate change and water resources management in arid and semi-arid regions: Prospective and challenges for the 21st century,” In Bio systems Engineering-Soil and Water, Vol. 81, No. 1, pp. 3–34, 2001.



Colour Removal from Aqueous Solutions of the Reactive Azo Dye Remazol Black B Using the Immobilised Cells (Shewanella Strain J18 143) –Cellulose-g.co-Monomer

System

T. LI1, J. T. GUTHRIE2

1College of Light Industry and Food Sciences, South China University of Technology, Guangzhou, China 2Department of Colour Science, School of Chemistry, University of Leeds, Leeds, UK


Abstract Consideration is given here to colour removal, carried out using immobilised biological cells, Shewanella strain J18 143. In order to provide greater control of an overall colour removal process and to give a basis for the effective recovery of the cell culture species, cell immobilisation has been established on chemically modified cellulose. The modification was achieved by chemically inducing the graft copolymerisation of methacrylic acid onto cotton fabric. The immobilised cells were able to decolorise the dye. The immobilisa-tion methods, physical adsorption, “growing-in” and chemical coupling, were compared. Each of the meth-ods was effective to some extent. However, the latter two immobilisation methods provided the greater effect in decoloration. Each of these immobilised systems is relatively simple to achieve, whether by adsorption, physical interlocking or covalent coupling. The graft copolymer is able to offer versatility in use. The decol-oration was shown to be rapid under relatively simple processing conditions. Thus, compared with the estab-lished controls, complete decoloration of solutions of Remazol Black B was observed. The potential use of the graft copolymer substrate as support for a biochemical agent was confirmed. Keywords: Reactive Azo Dyes, Colour Removal, Immobilisation, Immobilised Cells

1. Introduction Reactive dyes have great use in the textile industry, due to their good fastness properties, their provision of a wide range of bright colours and the significant flexibil-ity in their application methods [1]. However, reactive dyes have been considered to be the basis of more envi-ronmental problematic compounds that arise from textile dye effluents [2]. Often, only 50–90% of the dye will react with the fabric, depending on the dye and on the application method [1,3]. As a result, the highly con-taminated wastewater produced is a considerable pollu-tion concern. Various colour removal methods for textile effluents have been extensively studied including physi-cal, chemical, physico-chemical and biological treat-ments [4].

Approaches that involve physical and/or chemical processes to remove reactive azo dyes, and hydrolysed reactive azo dyes from the aqueous wastewaters can be

costly to operate [5]. In this regard, the anaerobic reduc-tion of azo dyes using a microbial sludge can provide an effective and economic treatment process for removing colour from reactive azo-dye wastewaters [6,7]. Colour removal from industrial wastewaters by biological cells is the subject of interest of many researchers. Several papers on the transformation of organic compounds by microorganisms have been published [8,9]. A factor to be considered is that the anaerobic degradation of reactive azo dyes involves not only a reduction of the azo bond but also the production of aromatic amines. The resultant aromatic amines resist further degradation and can be even more toxic than the dyes themselves [10,11]. Be-cause of the toxic potential of the aromatic amines, fur-ther degradation of the dye compound is necessary if this toxicity potential is to be eliminated or reduced [12]. A high percentage of the intermediates of the azo dyes have been identified as carcinogens [10]. A proportion of these aromatic amines can be aerobically degraded [13]. In addition, the aromatic amines can be autoxidised to

T. LI ET AL.


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')

2 )

products that are expected to be easily removed, e.g. by attachment to flocculants that can then be easily sepa-rated [11]. A two stage mechanism for azo-reduction has been proposed, as shown below [14]:

2 2 ( ') (e H R N N R R NH NH R (1)

22 2 ( ') ( ) ( 'e H R NH NH R R NH R NH (2)

Here, it is speculated that the intermediate product of reaction (1) would be unstable and colourless. However, the azo bond can be reformed upon oxidation, regaining some of the colour. Hence, step (2) is required.

The bacterial degradation of textile dyes has been in-vestigated by a large number of researchers. Some of these studies that have been reported in the literature have been summarised and discussed by Willmott [15] and by Pearce et al. [7]. Shewanella putrefaciens are non- fermentative facultative aerobes (obligate respirers), that are capable of the dissimilatory reduction of many dif-ferent electron acceptors [16]. Shewanella strain J18 143 cells that were isolated from a textile wastewater have been shown to be capable of removing selected azo- based colorants from wastewater [15].

Colour removal from textile wastewaters using immo-bilised cells can offer many advantages over the free cells in industrial and analytical applications [17,18]. The stability of immobilised cells can be improved, relative to the stability of the non-immobilised equivalents. Bet-ter control of reduction is achievable. The immobilised cells can be easily removed from the reaction system and, under appropriate conditions, can be used repeatedly and flexibly to make the continuous processes practical. Less equipment space is required for reaction using immobi-lised cells and a high cell concentration can be intro-duced in the system. Furthermore, the immobilisation support components can provide a protective environ-ment for the cells against denaturants, proteolysis and can give reduced susceptibility to contamination, so that the cells are less affected by any fluctuations in the characteristics of their surroundings [19].

The immobilisation of the proteins, enzymes and cells onto graft copolymeric substrates, has been undertaken since substrates containing hydroxyl groups provide the basis for effectiveness [20–23]. The grafting of mono-mers or mixture of monomers can greatly increase the number of reactive groups that can be used for such im-mobilisation. The extent of incorporation of hydrophilic or hydrophobic groups can be controlled, creating a mi-croenvironment that could improve the viability and sta-bility of the biological materials that have been immobi-lised [18].

The present work relates to an investigation of the colour removal from reactive azo dye solutions brought about using biological cells that were covalently coupled to cotton cellulose graft copolymeric support systems. The cell system is that of Shewanella strain J18 143. In

this study, a grafting reaction was carried out on cotton fabric, using potassium persulphate as the initiator and methacrylic acid as the monomer. Three immobilisation methods for the cells, physical adsorption, “growing-in” and chemical coupling, were used and compared. The Remazol Black B reactive azo dye was chosen as a model for this study of the effectiveness of immobilised cells in chromophore destination. 2. Materials and Methods 2.1. Materials The reagents that were used in this study were of ana-lytical grade, obtained from Sigma-Aldrich Gillingham (Dorset, UK), unless otherwise stated.

A cellulose-g.co-monomer system was chosen as the immobilisation substrate. The cellulose used was in the form of bleached cotton fabric, supplied by Whaleys Ltd. (Bradford, UK). The cotton fabric was washed with de-tergent and then thoroughly rinsed with deionised and distilled water before being dried at 60 ºC. The dried cotton fabric was kept in a desiccator before use. Potas-sium persulphate was chosen as the initiator. The mono-mer grafted onto the cotton cellulose fabric was methacrylic acid.

Shewanella strain J18 143 cells were grown in Tryp-tone Soy Broth (TSB, Lab M, Bury, Lancashire, UK) medium. To prepare a sterile culture medium, the TSB solution was made up with distilled water and was auto-claved for 15 minutes at 121 °C. All of the decoloration work was carried out in a Phosphate Buffer Saline (PBS) medium solution in 10 cm3 glass vials. The pH of the buffer solution was adjusted to 7±0.2. Remazol Black B dye (Dystar UK Ltd., Huddersfield, UK) was used as the selected azo dye, in solution as a representative of the real textile effluents. 2.2. Graft Copolymerisation Procedures The initial swelling of the cotton cellulose was achieved by stirring the cotton fabric slivers at 28 °C in distilled water for 2 hours, followed by soaking in the system overnight.

The swollen cotton fabrics were stirred gently for 60 minutes in an aqueous solution containing potassium persulphate (0.075 mol dm-3) at 28 ºC. After one hour of impregnation of the pre-treated fabrics, purified methacrylic acid (0.5 mol dm-3) was added into the reaction system, drop wise. The treatment was allowed to proceed at 50 ºC, in a water bath, for 5 hours. At the end of the desired reaction period, the fabrics were washed repeat-edly and thoroughly with distilled water at 60 ºC in the water bath for 60 minutes, to dissolve and then remove any produced, extractable homopolymer. Then the grafted fabric was re-washed with distilled water and

T. LI ET AL 79 dried at 35 ºC in the oven until a constant weight was achieved.

The graft yield was quantified as the percentage in-crease in weight of the samples after grafting, expressed as follows

% GraftedCellulose OriginalCellulose

OriginalCellulose

W WGraftYield

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100

2.3. Immobilisation of Shewanella Strain J18 143 2.3.1. Free Cell Preparation To initiate the cell growth process, a loop of inoculum of Shewanella strain J18 143 was put into 50 cm3 of the prepared growth medium, in 250 cm3 conical flasks. The flasks were sealed and were left overnight in a water shaker bath (Grant Instruments Ltd, Cambridge, UK) and incubated at 30 °C, with shaking at 200 rpm. Then aero-bic cultures of Shewanella strain J18 143 were grown in 100 cm3 universal bottles, containing 90 cm3 of the auto-claved culture medium, sealed with butyl rubber stoppers and inoculated with 9 cm3 of the aerobic culture. To ob-tain sufficient anaerobic cell growth, the bottles were incubated for 4 hours at 35 °C, without shaking.

The cells were harvested by centrifugation at 3300 rpm for 10 minutes, using a Jouan Centrifuge C3-12 (Jouan Ltd., UK) and washed twice in PBS solution. The cells supernatant in PBS was adjusted to a consistent absorbance value at 600 nm, to ensure that the concen-tration of protein in each reduction experiment was the same (Specord S100 UV–visible spectrophotometer, Sarstedt Ltd., Leicester, UK). This prepared cell suspen-sion was used immediately. 2.3.2. Immobilisation of Shewanella Strain J18 143

onto the Substrate Three immobilisation methods were used in the study (Figure 1), a “growing-in” method, a physical adsorption method and a chemical coupling method. The immobili-sation method of “growing-in” was aimed at growing the biological cells within the texture of the cotton cellulose copolymeric substrate for immobilisation.

NaHCO3

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T.S.B. solution T.S.B. solution + grafted celluloseaerobic cell growth14 hrs

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Adsorption Coupling Figure 1. Biological cells immobilisation methods.

The method of adsorption was aimed at allowing the biological cells to be adsorbed onto the immobilisation substrate physically. The biological cells were also im-mobilised by chemical coupling [18]. The chemical cou-pling agent that was used to couple the cells onto the cotton cellulose copolymer substrate was CMC, 1-cyclo- hexy l-3-[2-morphilinyl-4-ethyl] carbodi-imidome-tho- p-toluene sulphonate.

The immobilisation methods are summarised in Figure 1. 2.4. Decoloration of Remazol Black B Dye

Solutions Using Immobilised Cells of Shewanella Strain J18 143

All of the reduction investigations were carried out in 10 cm3 vials. Each vial (Vial 2, Vial 3 and Vial 4) contained the dye solution (50 µM), sodium formate (21 mM), an-thraquinone-2,6-disulphonic acid disodium salt (AQDS, 100 µM), the prepared immobilised cells and the re-quired amounts of buffer solution to make up 9.5 cm3 in total volume, unless otherwise stated [22]. The vial nota-tions (Vial 1 etc.,) are of relevance to the images pre-sented in Figures 3 to 6.

To allow the reduction process to proceed under an-aerobic conditions, all of the vials were degassed with nitrogen after initial sealing. The samples were incubated at 30 °C, unless otherwise stated, without shaking, for 7 days. Optical density readings were taken daily at λmax of the sampling dye solutions (597 nm) using a Specord S100 UV–visible spectrophotometer. As the optical den-sity was measured, photographic representations were taken (Nikon COOLPIX2500). 2.5. Establishment of Standards To achieve a better understanding of the colour removal effect provided by the immobilised biological cells on the targeted dye solutions, several standard controls were established.

An immobilised cells standard (Vial 5) was used to establish the effect, if any, of the immobilised cells and that of the existing of the cotton cellulose copolymer immobilisation substrate on colour removal. The ab-sorbance of the prepared systems, without the addition of dye solution, was measured as one of the colour removal controls. The bacterial cells were immobilised by the three different methods. The aim of operating this control was to investigate the effect of the immobilised cells on the measurement of the adsorption of the analysed solution.

A dye solution standard, (Vial 4), for Remazol Black B, without any addition of biological cells, was prepared as the second control.

The cell growth medium used was tryptone soy broth. A cell growth medium solution standard, (Vial 6), was


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80

established using the “treated” graft cellulosic copolymer, (the graft cellulosic copolymer underwent the procedure of immobilisation by the method of “growing-in” with the absence of bacterial cells) instead of the immobilised cells, as the third control.

A control of grafted cotton cellulose copolymer stan-dard, (Vial 7), was prepared. This fourth control used the grafted cotton cellulose substrate in the decoloration system.

The effect of the planktonic Shewanella strain J18 143 cells on the colour removal of Remazol Black B dye so-lutions has been well investigated [24]. A free cell stan-dard using the prepared cell suspension (0.5 cm3) instead of the immobilised cells was established to make the fifth control. 2.6. Protein Analysis The grafted cotton cellulose was cut into pieces of 1 cm× 2 cm. These pieces then underwent the particular immo-bilisation procedures. The grafted cellulose pieces with their immobilised cells were used for protein assay pur-poses.

The protein assay was performed using 96-well micro-titre plates and an Anthos 2001 plate reader, equipped with kinetic software (Jencons Scientific Ltd., Leighton Buzzard, UK). The samples were prepared in the 96-well microtitre plate, as indicated in Table 1. In Table 1, the notation A1 to A10 refers to containers of the standard protein solution (S1 to S5 in duplicate). This approach was used to produce the calibration curve for the stan-dard protein solution. B1 to B6 contained the cellulosic substrates on which the cells were immobilised by the method of physical adsorption (GC Ad). C1 to C6 con-tained the cotton cellulose copolymer substrates on which the cells were immobilised by the method of chemical coupling (GC CC). D1 to D6 contained the cellu-losic substrates with immobilised cells that the cells were immobilised by the method of “growing-in” (GC GI). The immobilised cells (B1 to D6) were immersed in 50 µ dm-3 of PBS solution (10 mM, pH 7). 1.0 cm-3 of the mixture (bicinchoninic acid-copper sulphate solution) was added to each of the well. The 96-well plate was then left in an incubator, at 30ºC for 30 minutes. The values of the optical density of the standard protein solu- Table 1. Preparation of protein assay samples in 96-well plate.

1 2 3 4 5 6 7 8 9 10A S1 S1 S2 S2 S3 S3 S4 S4 S5 S5

B GC Ad

GC Ad

GC Ad

GC Ad

GC Ad

GC Ad

/ / / /

C GC CC

GC CC

GC CC

GC CC

GC CC

GC CC

/ / / /

D GC GI

GC GI

GC GI

GC GI

GC GI

GC GI

/ / / /

tion and of the substrates with immobilised cells, after 30 minutes of incubation at 30ºC, were obtained by the plate reader (at 570 nm).

The standard solutions identified in Table 1, contain-ing Bovine Serum Albumin (BSA) and PBS, were pre-pared in disposable cuvettes. 1 cm3 of bicinchoninic acid-copper sulphate solution (50:1) was added. The cu-vettes were left to stand at room temperature for 30 min-utes. After this time, the absorbance at 562 nm, of each of the solutions, with PBS as the reference, was measured. A calibration curve of absorbance versus protein concen-tration was produced from the absorbance of these stan-dard solutions containing known concentrations of BSA. 3. Results and Discussion The emphasis of the current paper lies in the use of graft copolymers as supports for immobilised cells that can be then be to used decolorise colored, waterborne effluents.

Three general issues are raised. These concern the na-ture of the prepared graft copolymer system, the use of these copolymers in the immobilisation of whole cells and the application of these cells in colorant destruction. The chosen grafting route is one that produces grafts, of varying chain length, randomly on the substrate back-bone, [25]. Where controlled grafting is required, alter-native methods must be used as described by Carlmark and Malmstrom [26], by Roy et al., [27] and by Sahnoun et al. [28].

For the current study, the random grafting approach was chosen so that a variety of access options could be available for the coupling and the binding of the cells of the Shewanella strain J18 143. Thus, the immobilised cells option, involving the use of a suitable graft co-polymeric substrate, based on cotton, was chosen to give flexibility in action and in processing. Other possibilities were considered. These include the approach taken by Mahmoodi et al. [29], dealing with decoloration by UV-radiation induced oxidation, in the presence of a redox catalyst system, that taken by Long et al. [30], concerned with general approaches to the anaerobic and the aerobic treatment of organic compounds and that of Xu et al. [31], who decolorised dyes using Shewanella decolorationis S12.

The results considered below can be judged alongside those presented in these earlier reports. In general, the procedures used as described in this report offer the sig-nificant advantages in effectiveness that are described below. 3.1. Colour Reduction of Remazol Black B

Solutions Using the Shewanella Strain J18 143

To evaluate the dye reduction rate, calibration curves

T. LI ET AL 81 (absorbance values at λmax against known dye concentra-tions) for Remazol Black B solutions were established, as shown in Figure 2.

Analysis of the decoloration process, using visible spectrophotometry, supported by photographic evidence, was used to monitor the colour changes taking place during the reduction treatment.

The samples used during the investigation of the de-coloration of Remazol Black B and the relative estab-lished standards were photographed, Figure 3.

In the system identified as “Vial 1” contained the stan-dard dye solution together with the immobilised cells. These cells were immobilised through the “growing-in” method within the matrix of the cotton cellulose graft copolymer in the growth medium, i.e. if the cells had become attached, they would have been fixed/immobi-lised by the method of adsorption/entrapment. The sys-tem identified as “Vial 2” contained the dye solution and the graft copolymer support, linked via chemical cou-pling of the immobilised bacterial cells. The system, “Vial 3” contained the dye solution and the grafted cot-ton cellulose with the physically adsorbed cells. The system “Vial 4” represented the control of the standard dye solution. The system “Vial 5” was made up as the standard of the immobilised cells (see Experimental).

It can be seen from the images (Figure 3) that the stan-dard of the immobilised cells (Vial 5) was yellow. The yellow coloration in the solution was due to the presence of cytochromes in the solution. The cytochromes are more likely released by a certain amount of cell lysis that occurred during the treatment [24] that was used in pre-paring the compositions. Moreover, the yellow colour of the samples disappeared when these samples were ex-posed to air, i.e. the solutions were “colourless” in the presence of air.

Figure 3 shows that all of the samples that were treated with immobilised cells were decolorised to some degree. Comparing the decoloration results of “Vial 1”, “Vial 2” and “Vial 3” visually, the cells immobilised onto the grafted cotton cellulose by the method of “growing-in” provided a fast and efficient method of colour removal. The colour of the sample that was placed with the cells that were immobilised on to the grafted cotton cellulose by adsorption (Vial 3) was not com-pletely removed. The process of decoloration by the cells that were immobilised by chemical coupling (Vial 2) was slower than that obtained with the cells that were located by “growing-in” adsorption/entrapment (Vial 1). One issue that needs to be recognised is that, although these three immobilisation processes were undertaken with the same concentration of the cell suspension and the same amounts of grafted cellulose were used, the biomasses of the immobilised cells would be unlikely to have been identical, despite the precautions that were taken. This could explain the differences described above. It should be noted that, despite these differences, effective colour

y = 29.065x + 0.0661

R2 = 0.9995

0.0

0.4

0.8

1.2

1.6

2.0

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07Concentration (g/dm

-3)

Opt

ical

Den

sity

at 5

97 n

m

Figure 2. Calibration curve of solutions of the dye Remazol Black B

Figure 3. Results from the decoloration of solutions of Re-mazol Black B. The images represent the evaluated decol-oration systems of “Vial 1”, “Vial 2” and “Vial 3”, and the standards of “Vial 4” and “Vial 5”, taken over different periods of treating time: (a) 20 minutes; (b) 24 hours; (c) 96 hours; (d) 168 hours, respectively. removal was observed. 3.1.1. Control of the Cell Growth Medium Solution The immobilisation of bacterial cells by the “growing-in” method was carried out by immersing the grafted cellu-


T. LI ET AL.


82

Figure 4. Established standard of the cellulose copolymeric substrate-contains solutions of Tryptone Soy Broth (the images of the standards that were taken in periods of time: a. 5 minutes; b. 24 hours; c. 96 hours; d. 168 hours after assembly).

Figure 5. Established standard of the cellulose copolymeric substrate (the images of the standards were taken over pe-riods of time: a. 5 minutes; b. 24 hours; c. 96 hours; d. 168 hours respectively).

Figure 6. Decoloration flow profile for the decoloration with free Shewanella cells (the images of the standards were taken after periods of incubation: a. 10 seconds after injec-tion of bacterial cells; b. 5 minutes later; c. 10 minutes later). lose samples, together with the cell culture, into a cell growth medium. There could have been a small amount of residual TSB solution in the sample, after washing. Thus, the influence, if any, of the TSB on the decolora-tion of the dye solutions of Remazol Black B needed to be considered (Figure 4). “Vial 6” related to the standard control of TSB solution in which the composition corre-sponds to the parallel control, “Vial 1”.

Figure 4 shows that the TSB solution has no effect on colour removal from the solutions of Remazol Black B. Since the TSB solution is a very rich medium that can be used for growing a wide range of bacteria, strict aseptic environments for the experiments were always used,

with careful handling during the processes. 3.1.2. Standard of Graft Cellulosic Copolymer A point needs to be considered as to whether or not the cotton cellulose-g.co-methacrylic acid immobilisation substrate had an effect on the decoloration of the Rema-zol Black B dye solution. This point was investigated by establishing the grafted cotton cellulose copolymer stan-dard, “Vial 7”.

Figure 5 shows that the immobilisation substrate, cot-ton cellulose-g.co-methacylic acid, had no influence on colour removal from the solution of Remazol Black B. 3.1.3. Free Cells Standard Shewanella strain J18 143 has the ability to remove col-our by degrading the chromophore of the reactive azo dyes [15,19,24]. In qualifying the use of immobilised biological cells, in the decoloration of reactive dye solu-tions, free cells standards were established, (Figure 6). It should be noted from “Vial 8”, that the reduction of the black dye solution was rapidly achieved by the free bio-logical cells. Actually, the colour removal process began before the nitrogen degassing was complete, as indicated in Figure 6.

The decoloration of the dye solution with free cells was much faster than that which was achieved with any of the grafted cellulose immobilised cells systems. However, the colour of the Remazol Black B dye solu-tion was removed completely by the immobilised bio-logical cells of Shewanella strain J18 143, within 24 hours of incubation. This result showed that there is a potential in using chemically modified cotton cellulose as an immobilisation substrate in decoloration systems, with the option of recycling and reuse. 3.2. The Decoloration of Remazol Black B

Solutions Using Immobilised Cells UV-visible spectophotometry was used as the main analysis support to evaluate the nature and the extent of the decoloration of the dye solutions. Figure 7 shows the absorbance versus time behaviour for the respective sys-tems.

Figure 7 shows that the colour of the dye solution is removed completely within 24 hours by the system based on the “growing-in” of the immobilised cells (Vial 1). The removal of the colour was also completed by the system based on the chemical coupling of the immobi-lised cells (Vial 2). However, the decoloration that oc-curred was slower than that of the “growing-in” immobi-lised cells. The complete decoloration took about 48 hours of incubation. There was almost no change in col-our within the first few hours in the system based on physically adsorbed cells (Vial 3). The colour was re-duced at a much slower rate. Complete decoloration was not achieved. Compared with the standard of the dye

T. LI ET AL


83

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

0 20 40 60 80 100 120 140 160 180

Time (hour)

Ab

sorb

ance

at

597

nm

Vial 1Vial 2Vial 3Vial 4Vial 5Vial 6Vial 7

y = 0.063x - 0.0438

R2 = 0.9924

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 2 4 6 8 10 1Concentration (mg cm

-3)

Opt

ical

Den

sity

at 5

62 n

2

m

Figure 7. Results from the decoloration of Remazol Black Figure 8. Calibration plot of standard protein solution assay. B dye solutions using the immobilised biological cells.

Table 2. Results from protein analysis of immobilised bacterial cells.

1 2 3 4 5 6 7 8 9 10

A S1

0.056 S1

0.081 S2

0.237 S2

0.233 S3

0.319 S3

0.319 S4

0.414 S4

0.467 S5

0.587 S5

0.582

B GC-Ad 0.099 2.275

GC-Ad 0.184 3.648

GC-Ad 0.158 3.228

GC-Ad 0.159 3.244

GC-Ad 0.139 2.291

GC-Ad 0.149 3.083

/ / / /

C GC-CC 0.273 5.087

GC-CC 0.215 4.149

GC-CC 0.238 4.521

GC-CC 0.251 4.731

GC-CC 0.218 4.198

GC-CC 0.218 4.198

/ / / /

D GC-GI 0.468 8.238

GC-GI 0.488 8.562

GC-GI 0.504 8.820

GC-GI 0.530 9.240

GC-GI 0.408 7.269

GC-GI 0.430 7.624

/ / / /

solution (Vial 4), the cellulosic graft copolymer (Vial 7) and the growth medium of the bacteria (Vial 6) had no influence on the decoloration of the Remazol Black B dye solution. 3.3. Comparison of Decoloration Effect of the

Immobilised Cells between the Three Immobilisation Methods

The results of this study have shown that using cotton cellulose-g.co-methacrylic acid as a support for biologi-cal cells immobilisation is practicable and effective in the current context. Comparisons of the decoloration efficiency between “Vial 1”, “Vial 2” and “Vial 3” were carried out via the method of protein assay. The protein assay was designed on the basis of methods that are used for the protein determination of free biological cells [22,32]. The calibration curve of the standard protein solution is shown in Figure 8. The corresponding protein assay results, by the means of measured optical density values, of Table 1 are listed in Table 2. For the data pre-sented in Table 2, the dye decoloration rate was calcu-lated from the measuring results in the first 24 hours of incubation, based on the results from the protein assay of immobilised cells. The bacteria concentration used under

each immobilisation method was an averaged value. It can be seen from Table 2 that the cells immobilised by the method of “growing-in” provided the most effective decoloration, as evaluated from both the dye reduction rate in the protein assay and the dye reduction measured by volumetric means. The cells immobilised by the method of adsorption, in the first 24 hours of incubation, show a greater reduction rate than that of the coupling immobilised cells. However, after 48 hours of incubation, the Remazol Black B was almost completely removed from the system by the cells that were immobilised by coupling but not by the cells that were immobilised by adsorption. One can conclude that all of the three differ-ent methods involving immobilised cells gave colour removal of the Remazol Black B from the investigated dye solution systems. 4. Conclusions The described decoloration systems were successful with respect to the objective of colour removal from solutions of a reactive azo dye (Remazol Black B) using immobi-lised cells. The cotton cellulose fibre-g.co-methacrylic acid copolymer system can be used as immobilisation substrate for the biological cells of Shewanella strain J18

T. LI ET AL.


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143. In this case, “growing-in” and chemical coupling were better options for the immobilisation methods.

The cellulose-MAA copolymer shows potential in use as immobilisation substrate for the bacterial cells of She-wanella strain J18 143. Optimisation of the immobilisa-tion system needs to be considered. 5

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[1] K. N. Tapley, “Dyes and pigment properties and applica-tions,” Polymer Science Lecture, Department of Colour and Polymer Chemistry, UK: University of Leeds, 2002.

[2] J. García-Montaño, N. Ruiz, I. Muñoz, X. Domènech, J. A. Gracía-Hortal, F. Torrades, and J. Peral, “Environ-mental assessment of different photo-fenton approaches for commercial reactive dye removal,” Journal of Hazardous Materials, Vol. 138, pp. 218–225, November 2006.

[3] A. J. Smith, “Colour removal from dyehouse effluents,” Ph.D. thesis, University of Sheffield, UK, 2001.

[4] Y. M. Slokar and A. M. Le Marechal, “Methods of de-coloration of textile wastewaters,” Dyes and Pigments, Vol. 37, No. 4, pp. 335–356, May 1998.

[5] C. I. Pearce, R. Christie, C. Boothman, H. Canstein, J. T. Guthrie, and J. R. Lloyd, “Reactive azo dye reduction by Shewanella strain J18 143,” Biotechnology and Bioengi-neering, Vol. 95, pp. 692–703, June 2006.

[6] T. H. Wallace, “Biological treatment of a synthetic dye water and an industrial textile wastewater containing azo dye compounds,” Masters Dissertation, Virginia Poly-technic Institute and State University, USA, 2001.

[7] C. I. Pearce, J. R. Lloyd, and J. T. Guthrie, “The removal of colour from textile wastewater using whole bacterial cells: a review,” Dyes and Pigments, Vol. 58, pp. 179– 196, September 2003.

[8] M. I. Banat, P. Nigham, D. Singh, and R. Marchant, “Mi-crobial decolorization of textile dyes containing effluents: A review,” Bioresource Technology, Vol. 58, pp. 217– 227, December 1996.

[9] A. Stolz, “Basic and applied aspects in the microbial degradation of azo dyes,” Applied Microbiology and Biotechnology, Vol. 56, No. 1–2, pp. 69–80, July 2001.

[10] M. A. Brown and S. C. De Vito, “Predicting azo dye toxicity,” Ccritical Reviews in Environmental Science and Technology, Vol. 23, No. 3, pp. 249–324, 1993.

[11] C. T. M. J. Frijters, R. H. Vos, G. Scheffer, and R. Mulder, “Decolorizing and detoxifying textile wastewater, containing both solution and insoluble dyes, in a full scale combined anaerobic/aerobic system,” Water Re-search, Vol. 40, No. 6, pp. 1249–1257, March 2006.

[12] A. Gottlieb, C. Shaw, A. Smith, A. Wheatley, and S. Forsythe, “The toxicity of textile reactive azo dyes after hydrolysis and decolorisation,” Journal of Biotechnology, Vol. 101, No. 1, pp. 49–56, February 2003.

[13] E. Razo-Flores, M. Luijten, B. A. Donlon, G. Lettinga, and J. A. Field, “Complete biodegradation of the azo dye azodisalycilate under anaerobic conditions,” Environ-mental Science and Technology, Vol. 31, No. 7, pp. 2098–2103, 1997.

[ 14] D. T. Sponza and M. Işik, “Decolorization and azo dye

degradation by anaerobic/aerobic sequential process,” Enzyme and Microbial Technology, Vol. 31, No. 1–2, pp. 102–110, July 2002.

[15] N. J. Willmott, “The use of bacteria-polymer composites for the removal of colour from reactive dye effluents,” Ph.D. thesis, University of Leeds, UK, 1997.

[16] D. A. Saffarini, T. J. DiChristina, D. Bermudes, and K. H. Nealson, “Anaerobic respiration of Shewanella putrefa-ciens requires both chromosomal and plasmid-borne genes,” FEMS Microbiology Letters, Vol. 119, No. 3, pp. 271–278, January 1994.

[17] I. Chibata and T. Tosa, “Immobilized cells: Historical background,” Applied Biochemistry Bioengineering, Vol. 4, pp. 1–9, 1983.

[18] M. H. M. Gil, “Immobilisation of proteins, enzymes and cells onto graft copolymeric substrates,” Ph.D. thesis, University of Leeds, UK, 1983.

[19] A. Kamilaki, “The removal of reactive dyes from textile effluents - a bioreactor approach employing whole bacte-rial cells,” Ph.D. thesis, University of Leeds, UK, 2000.

[20] D. Roy, S. Perrier, and J. T. Guthrie, “RAFT graft co-polymerisation of 2-(dimethylanimoethyl) methacrylate onto cellulose fibres,” Australian Journal of Chemsitry, Vol. 59, pp. 737–741, 2006.

[21] D. Roy, S. Perrier, and J. T. Guthrie, “Synthesis of natu-ral-synthetic hybrid materials from cellulose via the RAFT process,” Soft Matter, Vol. 4, pp. 145–154, 2008.

[22] T. Li, “Removal of colour from solutions of azo dyes using bacterial cells (Shewanella Strain J18 143),” Ph.D. thesis, University of Leeds, UK, 2007.

[23] D. Roy, J. Knapp, S. Perrier, and J. T. Guthrie, “Antim-icrobial cellulose fibres via RAFT surface graft polym-erisation,” Biomacromolecules, Vol. 9, pp. 91–99, 2008.

[24] C. I. Pearce, “The reduction of coloured compounds us-ing whole bacterial cells (Shewanella strain J18 143),” Ph.D. thesis, University of Leeds, UK, 2004.

[25] A. Hebeish and J. T. Guthrie, “The Chemistry and tech-nology of cellulosic copolymers,” Springer-Verlag, Hei-delberg, ISBN 3-540-10164-0, 1981.

[26] A. Carlmark and E Malmstrom, Journal of the American Chemical Society, Vol. 124, pp. 900–901, 2002.

[27] D. Roy, J. T. Guthrie, and S.Perrier, Australian Journal of Chemistry, Vol. 59, pp. 737–741, 2006.

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Water Quality Parameters and Fish Biodiversity Indices as Measures of Ecological Degradation: A Case Study in Two

Floodplain Lakes of India

Debjit Kumar MONDAL1, Anilava KAVIRAJ1, Subrata SAHA2 1Department of Zoology, University of Kalyani, Kalyani, India

2Department of Mathematics, Institute of Engineering and Management, Salt Lake, Kolkata, India E-mail: [email protected]

Received October 24, 2009; revised November 16, 2009; accepted November 23, 2009

Abstract A three year study was conducted in two floodplain lakes to evaluate changes between seasonal variation of water quality parameter and finfish diversity indices. Samples of water and fish specimens were collected every month from three different stations of each lake to determine physico-chemical parameters of water and the finfish diversity indices. Split-plot and MANOVA designs, Multiplicative decomposition method and quadratic regression analysis were used to analyze the effects of the rate of changes between the pa-rameters and sustainability of the lakes. The obtained results suggested that the impact of environmental change (e.g depth, conductivity, salinity of water etc.) on diversity indices was significant and should be taken into consideration when designing policies to increase the long-term sustainability of fishing activities in the lakes. Keywords: Baur, Finfish, Diversity Indices, Multiplicative Decomposition, Quadratic Regression

1. Introduction Floodplain lakes support a lucrative fishery in India, par-ticularly in the eastern and north-eastern states and are considered as the second most important inland fisheries resources of the country [1]. These water bodies are not only rich in finfish biodiversity, but also support a rich source of zooplankton, phytoplankton and macro- invertebrate species [2]. It is well established that the productivity of a water body depends on its ecological conditions. Productivity can be increased for obtaining maximum sustainable yield of fish and maintenance of environmental and social stability through constant monitoring of water quality. The water quality parame-ters like temperature, hardness, pH, dissolved gases (oxygen and CO2), salinity etc. must be watched regu-larly, individually or synergistically to keep the aquatic habitat favorable for existence of fish.

The present investigation was conducted to study the water quality parameters in two floodplain lakes for a period of three year from 2004 to 2006. In West Bengal, more than 150 floodplain lakes, covering an area of 42,000 ha, contribute about 22% of the total freshwater area of the state [1]. Largest share of this water resources

(8861 ha) exists in the North 24-Parganas district [3]. River Ichhamati and its branches form a large complex of floodplain lakes, locally called as “baurs”, at Bongaon region of North 24-Parganas [4]. Most of these baurs are open with a seasonal or perennial connection with the river Ichhamati and are fed with tidal ingress of saline water from the Bay of Bengal. Thus these baurs show characteristics of both lentic and lotic elements [2]. Many brackish water species of fish migrate from the mouth of this river into the baurs during breeding season and exploit the rich nutrient resources of these water bodies for spawning. We made a study on the fish as-semblage, water quality parameters and biodiversity in-dices of two such baurs. The assemblage of fish and the pattern of changes in the composition and abundance of the fish species in these two floodplain lakes during the period 2004 to 2006 had been already reported [5]. The present paper dealt with changes in physico-chemical parameters of water and its relation with the fish biodi-versity indices in these two lakes during the same period.

Fish assemblages in lakes and reservoirs are greatly influenced by water quality parameters [6]. Floodplain lakes in India have become worst victims of environ-mental degradation since last two decades. Majority of

D. K. MONDAL ET AL.


86

these water bodies are shrinking due to siltation caused by high fluvial allochthonous charges from the river meanders, discharge of organic debris from human set-tlements around the lakes, run-offs from agricultural fields, eutrophication and autochthonous production of macrophytic biomass [2,7,8]. Indiscriminate jute retting during summer months and subsequent deterioration of water quality is also a serious threat to the fish biodiver-sity and productivity of floodplain lakes in West Bengal [9]. Therefore, changes in the water quality parameters and its relation with biodiversity indices are crucial fac-tors to evaluate fish biodiversity in floodplain lakes. 2. Materials and Methods 2.1. Study Area Studies were made on two baurs, Gopalnagar and Dumar, located in the Bongaon Subdivision (23.07º N 66.82º E) in the North 24-Parganas district of West Bengal. These two ‘baurs’ were found connected to the river Ichamati throughout the year by a narrow canal. The Gopalnagar baur was smaller of the two with a length of 6 km con-taining 60 ha water area while the Dumar baur was 15 km long containing a water area of 395 ha. A map show-ing location of these two baurs along the course of the river Ichamati had been published in another paper [5]. 2.2. Sampling Three different stations were selected in each baur for sampling of fish and water. One station was located near the connection of the baur with the river (mouth), the second in the middle of the baur and the third at far end from the mouth. Samplings were done every month from January 2004 to December 2006.

For water quality analysis random samples of water were collected from three different locations of each sta-tion in the morning of the first week of every month dur-ing January 2004 to December 2006. Water samples were collected from 50 cm depth in each collection site. Depth of water, dissolved oxygen (DO), free carbon dioxide, pH, total alkalinity, hardness, salinity, conductivity, transpar-ency and surface water temperature of water were deter-mined using standard methods [10]. A Celsius ther-mometer (scale ranging from 0ºC to 100ºC) was used to measure surface water temperature of water. pH of water was measured directly in a digital electronic pH meter (Systronics) and specific conductivity of water was measured in a digital direct reading electronic conductiv-ity meter (Model 304, Systronics). Transparency was measured with the help of a Secchi disc. Dissolved oxy-gen (DO), free carbon dioxide, total alkalinity, hardness and salinity were determined by titration [10].

For determination of diversity indices random samples

of fish were taken from five nettings from each stations and pooled together to make a 500g sample of fish for each station for each month. Total number of species, total number of individuals in a sample and total number of individuals of a species were determined every month. From these data Shannon–Weaver (S-W) species diver-sity index [11], Evenness index [12] and Index of Domi-nance [13] were determined using the following equa-tions:

21

S.W. Species Diversity index H = - N / N log N / Ns

i

i i

where S is the total number of species; N is the total number of individual; Ni is the number of specimens in each species.

Evenness Index (J′ ) = ( H )/log2S.

where H is the S.W. Species Diversity Index; S is the total number of species.

Index of Dominance (ID) = ∑ (Ni/N)2

where N is the total number of individual; Ni is the num-ber of individuals in each species. 2.3. Data Analyses To determine the relative importance of year compared to age of the baur a mixed-effects analysis of variance (MANOVA and Split–plot) was conducted in which yearly variation was considered a random effect. Sig-nificance was determined at alpha = 0.05. F-ratio ob-tained from the analyses was tested for significance of difference between stations. Data indicated that there was annual and monthly variation in the various meas-ures of chemical limnology. In case of a significant variation, difference between the stations were compared with critical difference (CD) value for station and the station with greater variance was selected from each year data for further analyses. A trend cycle was estimated for each parameter from the observed data. For this purpose the data series was smoothed to reduce random variation using Multiplicative decomposition technique [14]. In order to make predictions of long term behavior of rela-tion between the water quality parameters and the diver-sity indices, best fitted parabolic curves were constructed from the three year data based on quadratic regression in the form Y=a+bx+cx2. Physically it was interpreted that, if a, b, c were all greater (positive) an increase in x would result in increase of Y and if a, b, c were all nega-tive then a reverse trend would be followed. Long term growth or decay would follow accordingly as c was posi-tive or negative. 3. Results T he results indicated a conspicuous seasonal variation of

D. K. MONDAL ET AL.


87

0 5 10 15 20 25 30 352.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

DE

PT

H

(m)

MONTH

D G

0 5 10 15 20 25 30 3520

22

24

26

28

30

32

34

D

- - - - G

TR

AN

SP

AR

EN

CY

(c

m)

MONTH

0 5 10 15 20 25 30 350.30

0.32

0.34

0.36

0.38

0.40

0.42

0.44

0.46

- - - - GD

CO

ND

UC

TIV

ITY

(m

Mho

)

MONTH

0 5 10 15 20 25 30 350.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55D

------- G

SA

LIN

ITY

(pp

t)

MONTH0 5 10 15 20 25 30 35

4.5

5.0

5.5

6.0

6.5

7.0

7.5 D- - - - G

DIS

SO

LVE

D O

XY

GE

N (

mg/

L)

MONTH

0 5 10 15 20 25 30 35

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2D

- - - - G

CO

2 (m

g/L

)MONTH

0 5 10 15 20 25 30 35

7.5

7.6

7.7

7.8

7.9

8.0

8.1

8.2

8.3 D- - - - G

pH

MONTH0 5 10 15 20 25 30 35

80

90

100

110

120

130

140

150

160

170 D- - - - G

HA

RD

NE

SS

(m

g/L)

MONTH

0 5 10 15 20 25 30 35

120

125

130

135

140

145

150

155

160

165

170

175

180

185D

- - - - G

AL

KA

LIN

ITY

(m

g/L

)

MONTH

Figure 1. Time plot of monthly observed data of physico-chemical parameters of Gopalnagar (G) and Dumar (D) baur. the

e pattern of variation was almost similar, there was e-

riod of study. The Gopalnagar baur showed continuous water quality parameters in both the baurs. Although was observed in both the baurs during the three year p

thwide difference in the level of these parameters between the two baurs except depth, pH and conductivity of water (Figure 1). Transparency of water also differed widely between the two baurs for the first year of observation; thereafter showed similarity between the two baurs. Depth of water significantly varied between the stations through out the experimental periods, while transparency, free CO2 and surface temperature of water showed sig-nificant variation between the stations for most part of the studies (Table 1). Depth decreased alarmingly during summer months and a trend of gradual decrease in depth

decrease of depth from 2004 to 2006, while Dumar baur showed a sharp decrease of depth from 2004 to 2005, but did not show a marked decrease of depth thereafter. Transparency of water also showed a trend of gradual decrease in both the baurs. Salinity of water sharply de-creased during monsoon and increased during summer. The highest value of salinity recorded in summer be-tween 2005 and 2006 was higher than the summer value recorded between 2004 and 2005. Overall salinity, pH and dissolved oxygen levels were lower in Gopalnagar baur than Dumar baur, the later showing lower level of

D. K. MONDAL ET AL.


88

from va

Table 1. F-ratio and critical difference (CD) value obtained variance analysis of the physico-chemical parameters are given below. Bold face F-ratio indicates statistically significant riation between stations.

Gopalnagar baur Dumar baur Parameters

Statistical values 2004 2005 2006 2004 2005 2006

Conductivity. 0.48 F ratio

CD 2.05 4.26 2.38

4.31 3.86 3.91 4.67 5.48

20.28 2.01 1.04

Depth F ratio

CD F ratio

142.78

1

Wate

2 2 2

Alkalinity

3.68 263.64

4.96 184.2410.86

14.15 17.78

22.83 9.54

83.73 7.01

DO

CD F ratio

9.34 6.59

4.28 5.96

1.20 9.54

46.05 3.13

4.53 9.01

40.351.42

pH

CD F ratio

10.94 1.39

6.25 1.47

13.31 0.65

14.12 2.53

2.40 0.77

4.18 1.03

Salinity

CD F ratio

0.27 3.84

34.44 2.24

4.37 2.07

0.13 3.59

1.44 1.66

1.83 2.51

r temperature

CD F ratio

7.84 1.43

0.59 1.03

13.35 .077

15.63 1.83

35.06 0.29

44.37 1.44

Transparency

CD F ratio

6.78 3.68

6.12 2.26

7.18 1.82

94.932.73

65.561.67

02.212.51

Hardness

CD F ratio

15.91 1.32

3.63 4.49

22.94 1.72

30.76 1.76

1 1.36 38.64 0.13

1.96

CD F ratio

14.98 2.43

19.30 2.67

1.50 2.83

1.77 2.93

9.82 3.81

7.11 1.54

Free CO2

CD 14.45 7.19

25.31 3.43

1.58 29.85

66.67 6.01

11.16 9.74

34.87 6.35

Table 2. Average annual diversity indices determined for three different statio Gopa nd Du ur.

Station 1 Station 2 Station 3 Overall mean

n s of ln aagar mar ba

Year Index ± SD ± SD ± SD ± SD

Gopalnagar baor

2004 SWI 3.88±0.31 3. 3. 3.

EI 0.90±0.04 0.87±0.09 0.89±0.06 0.89±0.05

005 SWI

006 SWI

Dum

004 SWI

EI 0.84±0.06 0.87±0.05 0.86±0.05 0.85±0.04

005 SWI

006 SWI

81±0.55 86±0.35 85±0.35

ID 0.08±0.00 0.10±0.04 0.08±0.02 0.09±0.03

2 3.88±0.19 4.02±0.22 3.94±0.26 3.95±0.16

EI 0.92±0.03 0.93±0.04 0.92±0.02 0.92±0.02

ID 0.08±0.01 0.08±0.02 0.08±0.02 0.08±0.01

2 3.99±0.18 3.91±0.21 3.95±0.19 3.95±0.12

EI 0.94±0.03 0.94±0.02 0.94±0.02 0.94±0.01

ID 0.08±0.02 0.08±0.01 0.07±0.01 0.08±0.01

ar baor

2 3.52±0.27 3.69±0.35 3.63±0.32 3.61±0.24

ID 0.13±0.04 0.11±0.03 0.11±0.03 0.12±0.02

2 3.66±0.26 3.72±0.28 3.77±0.33 3.72±0.24

EI 0.88±0.05 0.90±0.04 0.90±0.05 0.89±0.03

ID 0.10±0.02 0.10±0.02 0.10±0.03 0.1±0.02

2 3.84±0.2 3.86±0.18 3.83±0.18 3.84±0.12

EI 0.91±0.03 0.91±0.03 0.90±0.04 0.91±0.02

ID 0.09±0.02 0.08±0.01 0.09±0.02 0.09±0.01

SWI = Shannon-Weaver I = Eve = Ind ce

alkalinity,

Mean annual values of Shannon-Weaver index, even- 1)

di

crease of the index of dominance (ID) during the study

re 2). Both S-W index and evenness index increased sharply during October-November, while in-

related with conductivity of water (Figures 3 and 4). In

index; E nness index; ID ex of dominan

hardness and free carbon dioxide of water. period (Figu

ness index and index of dominance of fish fauna (Tabled not show any significant variation between the sam-

pling stations of the two baurs (Table 3). Multiplicative decomposition method showed a gradual increase of Shannon-Weaver index and evenness index and a de-

dex of dominance decreased during this period. While correlating the physico-chemical parameters of water with the diversity indices, it was observed that in both Gopalnagar and Dumar baur the Shannon-Weaver index was positively correlated with depth and negatively cor-

D. K. MONDAL ET AL. 89

0 5 10 15 20 25 30 35

3.5

3.6

3.7

3.8

3.9

4.0

4.1

D----- G

EA

VE

R

IND

EX

SH

AN

NO

N -

W

MONTH

0 5 10 15 20 25 30 350.82

0.84

0.86

0.88

0.90

0.92

0.94 D---- G

EV

EN

NE

SS

IN

DE

X

MONTH

0 5 10 15 20 25 30 35

0.07

0.08

0.09

0.10

0.11

0.12

0.13

D------ G

IND

EX

OF

DO

MIN

AN

CE

MONTH

Figure 2. Time plot of monthly observed data of the diversity indices of fish fauna of Gopalnagar (G) and Dumar (D) baur. Dumar baur Shannon-Weaver index was further posi-tively correlated with free CO2 of water and negatively correlated with salinity of water (Figure 4).

of each

arameter, obtained form the MANOVA table, indicated hemical parameters of the two baurs

ries purpose for the period of study

4. Discussions Conspicuous seasonal variation of the physico-chemical parameters of the two baurs reflected well defined dry and rainy seasons in the study area. Grand mean

pthat the physico-c

ere suitable for fishewundertaken. But a few parameters, such as depth and salinity, indicated a trend that could be alarming for the ecological sustainability of the baurs. A few studies on habitat structure and fish assemblages in lakes indicated that physico-chemical parameters could influence fish community structure of a lake [15,16]. But it was diffi-cult to identify the key parameters that influenced the fish community structure most. Kar et al. [17] found dissolved oxygen of water to influence fish yield in the floodplain lakes of Assam, while Vono and Barbosa [16] observed abundance of macrophyte to influence total fish abundance in natural lakes. On the other hand, Deka et al. [18] observed that depletion of fish in wetlands was af-fected most by a cluster of variables consisting of silta-tion, anthropogenic activity, encroachment, flood effect, mesh size of net, indiscriminate catch and fishing rules. The results of the present study revealed that trend cycle, obtained by smoothing of the data series after reduction of random variation by multiplicative decomposition technique, was a strong tool to predict long term effect of the water quality parameters in baurs. Thus the declining trend of depth in the baurs under study gained most sig-nificance and need for an effective control program to maintain optimum depth for sustainable fisheries in the baurs was felt necessary. Siltation from the river mean-ders, discharge of organic debris from human settlements around the lakes and run-offs from agricultural fields primarily resulted in reduction of depth of many flood-plain lakes in India [2,7,8]. Siltation and anthropogenic activities were found as the major cause of depletion of fish stocks in floodplain lakes of Assam [18]. Present results indicated that worst situation prevailed in the baurs of Bongaon subdivision (W.B., India) during summer months, when extreme reduction of depth re-sulted in increase of salinity, free CO2 and hardness of water and decrease of dissolved oxygen, pH and trans-parency of water rendering a reduction in fish diversity. Apart from continuous removal of water for irrigation purpose and heavy infestation of weeds, which primarily caused reduction of depth, wide spread use of the baurs for jute retting was found to cause a large scale degrada-tion of the water quality parameters particularly during summer months in these baurs [9]. Such ecological deg-radation was reflected in poor catch of fish [5] and de-crease of diversity index during summer months from these baurs. Since salinity of water was inversely related with the depth of water a negative relation between the salinity of water and Shannon-Weaver index (SWI) was exhibited in the baur. A general trend of decrease in depth and an increase in salinity was considered to produce serious impact on sustainability of these floodplain lakes.

The present study indicated a conspicuous seasonal fluctuation of Shannon-Weaver index and evenness in-


D. K. MONDAL ET AL.


90

om

aga

Table 3. F ratio and critical difference (CD) value obtained fr variance analysis of various diversity indices of finfish from Gopalnagar and Dumar baur.

Gopaln r baur Dumar baur Statistical Parameters

values 2004 2005 2006 2004 2005 2006

Shannon-Weaver index F ratio

CD 0.23 6.47

0.72 5.70

0.99 4.23

1.15 3.56

1.65 4.99

2.01 5.23

Evenness 1.58 0.04 1.66 0.43

Index of dominance

index F ratio

CD F ratio

4.08 1.99

0.35 2.66 0.26

2.37 0.25

5.17 1.18

0.53 4.73 0.05

3.15 0.68

CD 19.53 16.48 15.02 16.99 19.30 15.21

3.2 3.4 3.6 3.8 4.0 4.2 4.42

3

4

5

6

7

DE

PT

H

(m)

SW I

Y = 11.25 - 4.38X + 0.65 X2

3.2 3.4 3.6 3.8 4.0 4.2 4.420

22

24

26

28

30

TR

AN

SP

AR

EN

CY

(c

m)

SW I

Y=137.14 - 59.81X + 7.93X2

3.2 3.4 3.6 3.8 4.0 4.2 4.40.10

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

CO

ND

UC

TIV

ITY

(m

Mho

)

SW I

Y= 0.76 - 0.01X - 0.001X2

3.2 3.4 3.6 3.8 4.0 4.2 4.40.15

0.20

0.25

0.30

0.35

0.40

0.45

SA

LIN

ITY

( p

pt )

SW I

Y= - 1.68 + 1.10X - 0.15X2

3.2 3.4 3.6 3.8 4.0 4.2 4.43

4

5

6

7

8

DIS

SO

LVE

D

OX

YG

EN

(m

g/L

)

SW I

Y= 41.39 - 19.13X + 2.54X2

3.2 3.4 3.6 3.8 4.0 4.2 4.4

0.0

0.5

1.0

1.5

2.0

2.5

3.0C

O2

(m

g/L)

SW I

Y= -44.48 + 22.06X - 2.88X2

3.2 3.4 3.6 3.8 4.0 4.2 4.46.8

7.0

7.2

7.4

7.6

7.8

8.0

8.2

8.4

8.6

8.8

9.0

pH

SW I

Y= 16.36 - 4.49X + 0.58X2

3.2 3.4 3.6 3.8 4.0 4.2 4.4100

120

140

160

180

200

HA

RD

NE

S

(mg/

L)

SW I

Y= - 76.38 + 102.54X - 11.74X2

3.2 3.4 3.6 3.8 4.0 4.2 4.4

100

120

140

160

180

200

220

240

ALK

ALI

NIT

Y (

mg

/L)

SW I

Y= - 720.67 + 468.73X - 62.03X2

Figure 3. Quadratic relationship between physico-chemical parameters and Shannon-Weaver index (SWI) of fish fauna in Gopalnagar baur.

D. K. MONDAL ET AL. 91

3.2 3.4 3.6 3.8 4.0 4.2

3

4

5

6

7D

EP

TH

(m

)

SW I

Y= 45.15 - 24.14X + 3.59X2

3.2 3.4 3.6 3.8 4.0 4.2

18

20

22

24

26

28

30

32

34

36

TR

AN

SP

AR

EN

CY

(c

m)

SW I

Y= 358.05 - 177.60X + 23.70X2

3.2 3.4 3.6 3.8 4.0 4.2

0.20

0.25

0.30

0.35

0.40

0.45

0.50

CO

ND

UC

TIV

ITY

(m

Mo

h)

SWI

Y= 1.12 +0.41X - 0.7X2

3.2 3.4 3.6 3.8 4.0 4.20.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0.65

SA

LIN

ITY

( p

pt )

SW I

Y= -0.23 + 0.52X - 0.09X2

3.2 3.4 3.6 3.8 4.0 4.22

3

4

5

6

7

8

9

DIS

SO

LV

ED

O

XY

GE

N (

mg

/L)

SW I

Y= 23.50 - 9.68X + 1.34X2

3.2 3.4 3.6 3.8 4.0 4.2

0.0

0.5

1.0

1.5

2.0

CO

2 (

mg/

L) SW I

Y= 14.96 - 8.78X + 1.34X2

3.2 3.4 3.6 3.8 4.0 4.27.4

7.6

7.8

8.0

8.2

8.4

8.6

pH

SW I

Y= - 0.35 + 4.76X - 0.67X2

3.2 3.4 3.6 3.8 4.0 4.270

80

90

100

110

120

130

140

HA

RD

NE

SS

(m

g/L

)

SW I

Y= 1150.26 - 526.68X + 773.12X2

3.2 3.4 3.6 3.8 4.0 4.2100

110

120

130

140

150

160

170

180

ALK

ALI

NIT

Y (

mg/

L)

SW I

Y= - 533.94 + 347.25X - 44.87X2

Figure 4. Quadratic relationship between physico-chemical parameters and Shannon-Weaver index (SWI) of fish fauna in Dumar baur. dex, post monsoon period (Sept-Oct) showing the peak. Number of species and the total number of individuals of all species harvested in each sample from these two baurs fluctuated between the seasons [5]. Since both the baurs were connected with a river, many species of fish migrated from the river to breed in the baur during mon-soon (July-Aug). Species number thus increased during Sept-Oct rendering an increase in the Shannon-Weaver index. However, this study indicated that there was a trend of increase in the Shannon-Weaver index and evenness index in both the baurs. This was due to grad-

ual reduction in number of individuals of the dominant species captured in both the baurs [5], resulting in a gradual reduction of index of dominance.

Despite clear changes in species composition Carol et al. [6] found no significant effect of water quality on overall fish richness or Shannon’s diversity in some Spanish reservoirs. These reservoirs had low richness assemblages and these authors suggested that in such case species composition was a better indicator of cul-tural eutrophication of reservoirs than fish diversity. The present study however, indicated that quadratic regres-


D. K. MONDAL ET AL.


92

sion analysis was an effective tool to establish relation-ship between water quality parameters and the finfish diversity indices in the floodplain lakes. The results of the quadratic regression analysis indicated that apart from depth and salinity, conductivity and free CO2 of water also produced significant effect on Shannon-Weaver index and fluctuation of these physico-chemical parameters should be taken into consideration while pre-dicting future effects on finfish diversity of the flood-plain lakes under study. The quadratic relationship was also worked out between the physico-chemical parame-ters and the evenness index and dominance index (results not presented) and almost same picture was revealed. However, it was revealed that fluctuation of all three

e diversity and designing policies on long

Zamora, E. Navarro, J. Armengol, and E. Garcia-Berthou, “The effects of limnological features on fish assemblages of 14 Spanish reservoirs,” Ecology of Freshwater Fish , Vol. 15, pp. 66–77, 2006.

[7] M. M. Goswami, T. K. Deka, P. K. Singha, P. K. Sharma, and M. Kakati, “Studies of some wetlands of Assam with reference to the eutrophication stresses,” Journal of the Inland Fisheries Society of India, Vol. 31, pp. 39–43, 1999.

[8] V. V. Sugunan and B. K. Bhattacharjya, “Ecology and fisheries of beels in Assam,” Bulletin of Central Inland Fisheries Research Institute, No. 104, pp. 1–65, 2000.

[9] D. K. Mondal and A. Kaviraj, “Ecotoxicological effects of jute retting on the survival of two freshwate fish and

2008.

[10] APHA (American Public Heath Association), “Standard of water and waste water,”

iation, American Water Works Association and Water Pollution Control Federa-

2] E. C. Pielou, “The measurement of diversity in different gical collections,” Journal of Theoretical

, pp. 131–144, 1966.

abitat structure,” Canadian Journal of Fish-

diversity indices should be considered while evaluating the trend of th

two invertebrates,” Ecotoxicology, Vol. 17, pp. 207–211,

term sustainability of the floodplain lakes.

5. Acknowledgements Authors acknowledge the facilities of research provided by the Head, Department of Zoology, University of Kalyani and Fishermen Cooperative Society associated with Gopalnagar and Dumar baur. 6. References [1] U. Bhaumik, B. C. Jha, K. Mitra, and G. K. Vinci “Fish

yield optimization in beels: Some case studies from West Bengal,” Bulletin of Central Inland Fisheries Research Institute, Barrackpore, No. 125, pp. 43–54. 2003.

[2] R. A. Khan, “The ecology and faunal diversity of two floodplain ox-bow lakes of south eastern West Bengal,” Records of the Zoological Survey of India, No. 195, pp. 1–57, 2002.

[3] Anonymous, “Annual report 2004-2005,” Department of Fisheries, Aquaculture, Aquatic Resources and Fishing Harbours, Government of West Bengal, pp. 25–27, 2006.

[4] S. R. Das and N. C. Nandi, “Oxbow lake environment and management of Ichhamati river basin, West Bengal,” Journal of Environment and Sociobiology, Vol. 1, pp. 81–90, 2004.

[5] D. K. Mondal and A. Kaviraj, “Distribution of fish as-semblages in two floodplain lakes of North 24 - Parganas in West Bengal, India,” Journal of Fisheries and Aquatic Science, Vol. 4, pp. 12–21, 2009.

[6] J. Carol, L. Benejam, C. Alcaraj, A. Vila-Gispert, L.

r

methods for examinationAmerican Public Health Assoc

tion, Washington, DC, USA, 1995.

[11] C. E. Shannon and W. Weaver, “The mathematical theory of communication,” Urbana, University of Illinois, pp. 117–125, 1963.

[1types of bioloBiology, Vol. 13

[13] E. W. Simpson, “Measurement of diversity,” Nature, Vol. 163, pp. 688, 1949.

[14] S. Makridakis, S. C. Wheelright, and R. J. Hyndman, “Forecasting methods and applications,” 3rd edition, John Wiley & Sons, Singapore, 2003.

[15] B. J. Benson and J. Magnuson, “Spatial heterogeneity of littoral fish assemblages in lakes: Relation to species di-versity and heries and Aquatic Science, Vol. 49, pp. 1493–1500, 1992.

[16] V. Vono and F. A. R. Barbosa, “Habitat and littoral zone fish community structure of two natural lakes in southeast Brazil,” Environmental Biology of Fishes, Vol. 61, pp. 371–379, 2001.

[17] D. Kar, A. V. Nagarthana, T. V. Ramachandra, and S. C. Dey, “Fish diversity and conservation aspects in anaquatic ecosystem in northeastern India,” Zoos’Print Journal, Vol. 21, pp. 2308–2315, 2006.

[18] T. K. Deka, M. M. Goswami, and M. Kakati, “Causes of fish depletion – a factor analysis approach,” NAGA, World Fish Centre Newsletter, Vol. 28, pp. 37–42, 2005.

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