Journal of Indian Water Resources Society - IWRSiwrs.org.in/journal/jul2011/jul_11.pdf · J. Indian Water Resour. Soc., Vol. 31, No.3-4, July-Oct, 2011 42 International Workshop on

Journal ofIndian Water Resources Society

ISSN O970-6984

Volume 31 Number 3-4 July-Oct. 2011

MESSAGE FROM PRESIDENT'S DESKDear colleague,

It is indeed a great pleasure to be once again associatedwith the Indian Water Resources Society as President, IWRS.I am sure that with the support of Executive Committee andmembers of the society the IWRS will achieve all heights.

The expected impact of publications in advocatingeffectively the key messages of IWRS became an importantissue. With the accelerating pace of country's economy,improving life style of the people and increasing awarenesswithin the country and around it, the water sector isexperiencing tremendous pressure which is further likely to increase due toimpacts of climate change on the sector. The professionals from differentstreams, including planners, engineers, academicians, scientists, economists,sociologists are required to take up the challenges and work in-tandem inorder to fulfill the needs of the society at various levels.

Indian Water Resources Society (IWRS), founded in 1980, is one such openplatform which provides opportunity to all, who are interested in water sector,for healthy and meaningful discussion to fulfill its main objective of advancementof knowledge in technical and policy aspects of water resources developmentand management. Although IWRS is an NGO, we believe that co-operationwith the Government agencies, and not confrontation, is the key to making adifference in the water resources sector. With nearly 7000 strong members, 33Institutional members and 21 active local centres spread all through the country,the IWRS is a well respected force in the water sector. Further strengthening ofthe Society, by inducting more members, would certainly help the cause of thesector.

A society like IWRS in a large country like ours can be effective only whenactivities are handled not only centrally but also through respective LocalCenters which are distributed throughout the country. Many of our recognizedLocal Centres do not communicate to the Executive Office about their activities.I suggest that these could be sent to Secretary, IWRS. This would enable us toreflect briefly and highlight some, depending on the space availability.

I look forward to your personal efforts in encouraging more IWRS membership.The membership subscription forms are attached to the Journals. LocalCentres, which are desirous of membership forms, can write to the ExecutiveOffice who would supply them supporting your actions to enhance themembership. The membership application form may be downloaded fromSociety's website www.iwrs.org.in.

A feel back on your satisfaction level on the Journal, its contents and areas orscope for an improvement would help the team to strive harder and achievebetter.

With the best wishes and season's greetings,Yours faithfully,

R. C. JhaChairman, CWC & President, IWRS

President

Er. R. C. JhaChairman, Central Water Commission,New Delhi

Editor

Prof. S.K. MishraDeptt. of WRD & MIndian Institute of Technology RoorkeeRoorkee - 247 667

Joint Editor

Er. Omkar SinghScientist E-2National Institute of HydrologyRoorkee - 247 667

IWRS as a body accepts no responsibility for thestatements made by the individu als/authors

Futher. views expressed by authors need notnecessary be the views of the organisation towhich they belong.

Reprints of any portion of this publication may bemade, provided that reference thereto is quoted.

The Journal is for private circulation only.

Principal Office at :

Deptt. of Water ResourcesDevelopment & ManagementIndian Institute of Technology RoorkeeROORKEE - 247 667Uttarakhand, India

J. Indian Water Resour. Soc., Vol. 31, No.3-4, July-Oct, 2011

41

Journal ofIndian Water Resources Society

Volume 31 Number 3-4 July-Oct., 2011

CONTENTS

Page1. Geomorphology Based Nash Model for Watersheds in Sonar River Basin (M.P.)

R.K., Jaiswal, T., Thomas, R.V. Galkate and N.C. Ghosh 1

2. Application of a Groundwater Model to Basin BM-58- 59 of Purandar Taluka,Pune District, Maharashtra for the Augmentation of Water Resources by ArtificialRecharge Measures - A Case StudyK. Venugopal and B.S. Sundar Lal 8

3. Morphometric Analysis and Prioritization of Sub-watersheds in the Loni Watershed,Uttar Pradesh Using Spatial Information TechnologyRajat Agarwal, R. D. Garg and P. K. Garg 19

4. Use of Geographical Information System in Hypsometric Analysis of WatershedS.K. Sharma, N.K. Seth, S. Tignath and R.P. Pandey 28

5. Identification of Significant Environmental Aspects and Factors AffectingWetland Dynamics and Ecological Characters of Deepor beel Wetland UsingGeoinformatic TechniquesMd. Surabuddin Mondal and Padma Sharma 33


42

International Workshop

on

“PIANO KEY WEIR FOR IN-STREAM STORAGEAND DAM SAFETY”

(PKWISD-2012)

India Habitat Centre, Lodhi Road, New Delhi, India

May 30 - June 1, 2012

Indian Water Resources Society, Roorkee; Department of Water ResourcesDevelopment & Management (WRD&M), IIT Roorkee and Dept. of CivilEngineering and Environmental Science, University of Petroleum Energyand Study, Dehradun are Jointly Organizing an International Workshop on“PIANO KEY WEIR FOR IN-STREAM STORAGE AND DAM SAFETY”(PKWISD-2012)during May 30- June 1, 2012 at India Habitat Centre,Lodhi Road, New Delhi, India. For more information please visit ourwebsite : www.iwrs.org.in

All the Members of IWRS family are requested to register for theworkshop.


1

GEOMORPHOLOGY BASED NASH MODEL FOR WATERSHEDS IN SONARRIVER BASIN (M.P.)

R.K. Jaiswal1*, T. Thomas1, R.V. Galkate1 and N.C. Ghosh2

ABSTRACT

The design of small water storage structures in watersheds require accurate flood estimates, howeverunder paucity of requisite data one needs to use empirical formulae which may give erroneous results.In the study, an attempt has been made to use Nash model using geomorphology for Tumri watershed ofMadhya Pradesh. The Nash model is a two-parameter model in which a unit rainfall is routed throughn numbers of linear reservoirs arranged serially. The scale parameter (n) and shape parameter (k) ofNash model have been estimated using geomorphological parameters and a relationship betweenrainfall intensity (i) and equilibrium velocity (Ve) developed for Tumri small watershed by observationof discharge and short interval rainfall. The equilibrium velocity (Ve) is the characteristics velocitywhich can be considered as constant throughout the basin at any moment of time, changes throughoutas the storm progresses. The response of Nash model have been found comparable with the observedvalues as the efficiency of geomorphology based Nash model varies from 60.7% to 99.93% and relativeerror in peak ranges between -0.16 and 0.53 for Tumri small watershed and hence this model with sameVe-i relationship has been applied at the outlet of Tumri main watershed. Relationships have beendeveloped to estimate k of Nash model using peak rainfall intensity (ip) considering equilibrium stateof watershed. It may be concluded that the Nash model application using geomorphologicalparameters may provide an easy way for event based rainfall-runoff modeling of un-gaugedwatersheds in the region.

Key words: Nash Model, Scale Parameters, Shape Parameter, Rainfall Excess, Equilibrium Velocity,Peak Velocity, Root Mean Square Error, Spatial Correlation Coefficient, Efficiency

INTRODUCTION

The rainfall-runoff modeling using unit hydrographtheory has been considered the most importantdevelopment in the field of hydrology. The theory ofunit hydrograph proposed by Sherman (1932) as theresponse of a catchment in terms of direct surfacerunoff (DSRO) resulting from unit rainfall excessdistributed over the waterashed for the entire durationof occurance was the first major step in thedevelopemnt of relationship between rainfall andrunoff. Nash (1957) proposed a conceptual modelbased on a cascade of equal linear reservoir forderivation of IUH for a natural watershed. Nash (1957)and Dooge (1959) suggested a two-parameter gama

type model in which respons of instantaneous unitrainfall was represented by gama function of nnumbers of identical linear reservoirs. Considering theimportance of rainfall-runoff modelling for ungaugedor partially gauged watersheds, Rodriguez and Valdes(1979) introduced the geomorphological instantaneousunit hydrograph (GIUH) used geomorhologicalparameters of the watershed for development of IUHwhich was further elaborated by Gupta et al (1980).

Nash (1957,1958, 1959, 1960) proposed a cascadeof n number of identical linear reservoirs as a modelon which to base the derivation of IUH's for naturalwatersheds. The linear reservoir assumed in Nashmodel are fictious reservoirs in which the storage isdirectly proportional to the outflow from it. Using theconvolution equation and the impulse responsefunction for linear reservoirs, the IUH correspondingto the Nash Model can be easily obtained as follows :

1. Scientist, GPSRC, National Institute of Hydrology, 567, ManoramaColony, Sagar (M.P.)

2. Scientist, National Institute of Hydrology, Jal Vigyan Bhavan, Roorkee(Uttarakhand)* E-mail of corresponding author: [email protected] No. 1246

Journal of Indian Water ResourcesSociety, Vol. 31, No.3-4, July-Oct, 2011


4

equilibrium discharge (Qe) in m3/sec can be computedwith the help of the following equation

(8)

Using different pairs of Ve and i, the coefficient aand exponent b can be computed using least squaremethod. For an un-gauged basin, bed slope,geometric properties of gauging section and Manning'sroughness coefficient are used to determine differentpairs of Ve using Manning's equation and Qe atdifferent depths of gauging section. Graphs may beplotted between depth v/s area of cross-section anddepth v/s discharge. The Qe for a known value ofrainfall excess is estimated using eq. (8). Thecorresponding depth and area of cross-section may beobtained using graphs between depth v/s area ofcross-section and depth v/s discharge. Knowingcross-sectional areas, the Ve for different values of ican be computed and a relation in the form of may bedeveloped.

After determining the values of n and k, the IUHcan be calculated using eq. (1) and the ordinates (Ui)of corresponding UH by the following equation.

(9)

The φ method has been utilized for computationof excess rainfall from rainfall hyetographs andstraight-line method for determination of DSRO fromflood hydrograph in case of Tumri small watershed.The performance of the Nash model has beenevaluated in comparison to the observed runoff datausing spatial correlation coefficient (SC), integralsquare error (ISE), relative mean absolute error(RMAE), root mean square error (RMSE), relativeerror in peak (REP) and efficiency (EFF). The SCgives the measure of the degree to which twovariables are linearly related and varies between -1and 1. The high value of SC indicates strongcorrelation. The ISE is a measure of systemperformance formed by integrating the square of thesystem error over a fixed interval of time; smaller theISE value closer is the match. The RMAE is a measureindicating how close forecasts or predictions are tothe eventual outcomes and the RMSE is the squareroot of the mean-squared-error. The RMAE and RMSEranges from 0 to infinity, with 0 corresponding to theideal. The REP is the measure of deviation in two peaksand efficiency depicts how well the computed datamatched with observed data.

AQ

i e

2778.0=

( )[ ]11501−+−− ++++= iniinii u......................uuu.

nU

RESULTS AND DISCUSSIONIn the present study, the methodology of gauged

catchment has been applied for determination ofcoefficient (a) & exponent (b) of Ve-i relationship forTumri small watershed. A SRRG in Tumri village anda G/D site at the outlet of Tumri small watershed havebeen installed to obtain rainfall intensity and pointobservation of discharges. The following relationshipbetween i and Ve has been obtained and applied forestimation of peak velocities.

(10)

The relationship between rainfall intensity (i) andequilibrium velocity (Ve) for Tumri small watershedhas been presented in Fig 2. For application of Nashmodel, the ordinates of excess rainfall for selectedstorms have been computed using φ -index method.The peak velocity for peak rainfall intensity of eachevent has been estimated using eq. (10). The Nashmodel has been applied to compute the ordinates ofIUH and this computed IUH has been used to obtainUH and corresponding DSRO for these storms. Theparameters including ip, n, Vp, k, Qp and Tp of Nashmodel for few selected storms in Tumri smallwatershed has been presented in Table 2. From theobserved point observations of computed discharge,smoothened flood hydrograph has been prepared andstraight line base flow separation technique was usedto compute DSRO from the flood hydrograph. Thecomputed and observed DSRO for few known stormsof Tumri small watershed have been presented in Fig.3 and it can be observed that computed DSRO exhibita close resemblance with the observed data. Thestatistical correlations between the observed and thecomputed values of the DSRO's representing, SC, ISE,RMAE, RMSE, REP and EFF are given in Table 3 andit may be observed that spatial correlation varies from0.60 to 0.99 and ISE from 0.05 to 0.36 which imply aclose match of observed and modeled data.

565.0*899.0 iVe =

Fig. 2: Relationship between rainfall intensity (i) andEq. velocity (Ve)


7

7. Nash, JE. 1959. Systematic determination of unithydrograph parameters, J. Geophys. Res., 64(1),111-115.

8. Nash, JE. 1960. A unit hydrograph study withparticular reference to British catchments, Proc.Inst. Civil Engg., 17, 249-282.

9. Patil S, and Bardossy A, 2006, Regionalization ofrunoff coefficient and parameters of an event basedNash-cascade model for predictions in ungaugedbasins, J. Geophys Res Abstr, 8-74.

10. Rodriguez-Iturbe, I and Valdes, JB. 1979. Thegeomorphologic structure of hydrologic response.J. WRR, 20(7), 914-920.

11. Rodriguez-Iturbe, I, Devoto, G. and Valdes, JB.1979. Discharge response analysis and hydrologicsimilarity: The interrelation between the GIUH andthe storm characteristics, J. Water ResourcesResearch, 16(6), 1435-1444.

12. Rodriguez-Iturbe, I, Gonzalez-Sanabria and Brass,RL, 1982a. A geomorphoclimatic theory of

instantenous unit hydrograph, Water Reso. Res.,18(4), 877-886.

13. Rodriguez-Iturbe, I, Gonzalez-Sanabria and Brass,RL, 1982b. On the climatic dependence of the IUH:a rainfall-runoff analysis of the Nash model andthe geomorphoclimatic theory, WRR, 18(4), 887903.

14. Roso, R. 1984. Nash model relation to Hortonorder ratios, J. WRR, 20(7), 914-920.

15. Sherman, L. 1932. Stream flow from rainfall byunit-graph method, Engineering News Record,108(14), 501-505.

16. Sahoo, B, Chatterjee, C, Narendra, S, Raghuvansi,S, Singh, R and Kumar, R, 2006. Flood estimationby GIUH based Clark & Nash Model, J. Hydrol.Engg: doi: 10.1061/(ASCE) 1084-0699(2006)11:6(515).

17. Zelazinski J, 1986. Application of thegeomorphological instantaneous unit hydrographtheory to development of forecasting models inPoland, Hydrol Sci 31(2):263-270.


8

APPLICATION OF A GROUNDWATER MODEL TO BASIN BM 58- 59 OFPURANDAR TALUKA, PUNE DISTRICT, MAHARSHTRA FOR THE

AUGMENTATION OF WATER RESOURCES BY ARTIFICIAL RECHARGEMEASURES - A CASE STUDYK. Venugopal1 and B.S. Sundar Lal2

ABSTRACT

In order to avert the adverse effects of ground water over exploitation and also for developing theground water resource potential, it is necessary to augment the ground water resource by someartificial means. Provision of percolation tanks in the ground water basin is one of the best methods ofartificial recharge. Numerical groundwater model is a tool that can aid in studying groundwaterproblems and can help in understanding the groundwater system. In the present study, a finite elementbased digital simulation model of a ground water basin is used for assessing the performance ofpercolation tanks for artificial recharge in a hard rock aquifer basin BM 58-59, of Puranadar Taluka inMaharashtra for augmentation of groundwater resource. The feasibility, performance of theselected artificial recharge site has been assessed by considering the aquifer parameters, hydrogeological and hydrometeorological characteristics of the basin. The application of the model for theartificial recharge studies in the hard rock aquifer basin and the findings from the study are presentedas a case study. The importance and the use of artificial recharge studies through a numerical model inorder to minimize the project cost is emphasized in the present paper.

Key words: Numerical Model, Percolation Tanks, Artificial Recharge, Hard Rock Basin.

INTRODUCTION

Numerical Groundwater Model is a tool that canaid in studying ground water problem and can help inunderstanding the groundwater system. In India, thereare areas where groundwater development forirrigation and industries has reached critical stages dueto over exploitation and the adverse effects areeminent. In order to avert the adverse effects of groundwater over exploitation, it is necessary to augment theground water resource by some artificial means.Necessity of stabilizing agricultural production inIndia where one-third of the area is drought-prone,require speedy development of groundwater resources.

Artificial recharge of groundwater basins is auseful solution for augmenting the groundwaterresource. Provision of percolation tanks in thegroundwater basin is one of the best methods ofartificial recharge. Some areas in the states havetraditionally deep ground water levels without beingsubjected to over draft, and also the ground water

levels experience continuous decline over successivedeficit rainfall years in chronically drought-pronedistricts. Especially in hard rock areas the injectionrates are low due to the poor transmitivity values bywhich one can't have a good idea regarding theimplementation of artificial recharge programmes.Hence before taking up any artificial rechargeprogrammes such as percolation tanks in hard rock aswell as drought- prone areas, now a days, it hasbecome necessary to ascertain the performance ofthose artificial recharge structures/percolation tankswell in advance through some numerical modellingtechniques, which will reduce unnecessary expendi-ture on the implementation of those projects. Thelatest advancement to achieve this is digital simula-tion of the regional aquifer by considering the naturalfield conditions in the mathematical model developedfor assessing the performance of those artificialrecharge structures.

Finite element based Numerical Ground Watermodel for has been applied to the Ground WaterBasin BM58-59 of Purandar Taluka of Maharashtra,India, to simulate the water levels assessing theperformance of percolation tank for artificial recharge

1. Chief Research Officer2. Assistant Research Officer

Central Water and Power Research Station, Pune - 411 024Email : [email protected] No. 1258



10

element and proceed with the assembly of theelements. The discretised elements may be of variousgeometrical shapes such as triangular, quadrilateral etc.After the discretisation of the region is over the finiteelement algorithm involves development of basisfunctions to transform the local coordinates intoglobal coordinates and to relate the required head at aparticular point with the unknown heads at thevertices of the element. Further it involves thedevelopment of element matrices, generating globalmatrices, and implementing the time integration andsolving the linear simultaneous equations throughsome iterative technique after implementing the ini-tial and boundary conditions suitably. (Variationalformulation is adopted in the present study). Themethod and its application in water resourcesengineering in general and subsurface flow inparticular have been well documented in the referencebooks published by Pinder and Gray (1977) Huyakornand Heinrich (1977), Zeinkeiwicz (1971) Prickett(1975) and others. Sreenivasulu (1980) extended themethod for parameter identification ingroundwater problems. The method is not explainedin detail in this paper due to space constraint.

STUDY AREA

The study area is situated in Purandar taluk of dist.Pune in central western part of Maharashtra state,India between North latitude 18o 32' and Eastlongitude. 74o 04'. The area extends South-east wardsover a distance of approximately 40 km., whichconstitutes the maximum length of the basin and has

Fig. 1 : Location Map of the Basin

scheme, normalisation scheme and time integration.In the normalisation scheme the equation (1) isnormalised to convert into dimensionless form usingthe relations tN = t x D/(TL)2 XN = X/TL YN = Y/TL hN = (Elevation - Datum level) / TL where TL =Total length of the basin, (9786 m), hN = Non

north-south width of about 12 km. The geographicalarea is 540.04 sq.km in the hard rock basaltic terrain.BM 55/57 bound the area on the west BM 52/51 onthe north BM 60/70 on the east and BM 72/73 on thesouth. For the scientific study the areas of bothBM-58 and BM-59 have been considered together asone unit since they are contiguous to each other with atributary stream of river Khanhar at the centre. Thelocation map of the basin is shown in Figure 1. Themean annual rainfall in the basin is 542.6 mm during1992-2001. The basin topographic boundary coincideswith the groundwater divide of the basin and thus form-ing a closed groundwater basin. Groundwater occursin water table conditions in weathered fractured aqui-fer system. There are 5 observation wells in the basinwhich are monitored regularly by Maharashtra stateGround water Department for water levels which in-clude domestic wells, irrigation wells and bore wells.

APPLICATION OF THE MODEL TO THEGROUND WATER BASIN

The step wise procedure for the application of themodel to the study area comprises of discretization


11

dimensionalised head. The normalised form of theequation is employed in the simulation of the model.As regard to time integration, implicit finitedifference scheme is adopted for approximating thetime derivative to integrate the global matrixequations. The discrete dimensionless time step `tN'corresponding to one month, as taken in the presentproblem can be obtained as tN = t x D / (TL)2 . Thetime steps are fixed as 13 so that the first time stepzero corresponds to initial steady state values and theremaining time steps being for one year with the abovenormalised time increment with one month time

interval. The discretisation scheme of the basin isdescribed below.

Discretisation Scheme

The aquifer area is descritised in to eighty twotriangular elements containing 54 Nodes as shown inFig.2. This is done such that the Nodes coincide withthe observation wells. At places where theobservation wells are not available, the nodes are madeto fall on the abandoned wells where observations arenot available.

Fig. 2 : Discretisation Scheme of BM 58- 59

Input Data and Data Processing

The various inputs used in the model are explainedhere with. The model coordinates are measured withsome reference origin and are normalized by themaximum length of the basin. The initial heads usedin the model for steady state calibration are of May1992, for which the observations are available for 13wells and for the remaining wells where data is notavailable, the water levels are obtained byinterpolating the values from the water level contourmap for the same year.

The evapotranspration values are calculated byusing Penman-Monteith method as described in FAO,sIrrigation and drainage paper No. 56 obtained ETvalues are shown in Table-1. The recharge factors areobtained by dividing the monthly recharge values withthe corresponding rainfall values. The obtainedrecharge factors are given in Table - 2. The diffusivityvalues are obtained from the Transmitivity andStorage Coefficient values evaluated by an AquiferPerformance Tests, on observation wells in the areaas given in Table-3. For those nodes, where thesevalues are not available, the same have been obtainedthrough model calibration and are used throughout thesimulation process.


13

Simulation of water levels is carried out byprescribing the initial and boundary conditions andsupplementing data necessary for suitable changes innet nodal fluxes such as recharges, seepages due toirrigation and abstractions or pumpages which areassumed to be equal to evapotranspiration over all thenodes in the present study. Suitable modifications aremade to bring the simulated water levels close to theobserved water levels. Simulation of water levels iscarried out by considering May 1993 water levels asinitials and in monthly time steps for one year. If anydifference is seen in the May 1993 values at the known

Table 4 : Calibrated Water Levels

Table 5 : Simulated Water Levels (1993)

observation wells, the known observed water levelsare included in the data for initial water levels andkeeping the remaining water levels as they wereobtained in validation stage. Simulation process isdone keeping in view that the water levels at nodesshould not fall below certain critical draft level. Simu-lation of water levels is carried out till October 1999after updating the data at every simulation run. Simu-lated water levels for some months for the year 1999are shown in Table - 6. The same model is used forprediction of future water levels by changing the timesteps suitably. Future water levels are projected forthe years 2006 AD and 2025 AD (Table - 7).

NODE NO

OB. WELL

NO

JULY 1993 AUG 1993 SEPT 1993 OCT 1993

OBS SIM OBS SIM OBS SIM OBS SIM 13 123 661.20 66100 662.00 662.00 662.50 662.00 663.30 663.00 28 64 686.20 685.90 686.45 686.00 686.60 686.00 686.75 686.0

25 38 725.95 726.60 727.50 725.60 727.00 726.70 727.45 727.00 36 30 778.50 780.00 779.00 779.00 780.50 779.00 781.50 781.00 32 13 766.80 768.00 768.30 767.20 771.00 770.00 773.00 772.40 38 10 811.80 813.70 812.40 813.00 814.00 812.50 816.00 815.20 33 6 812.00 814.20 812.60 813.50 813.80 813.60 815.90 815.00 35 1 855.30 856.30 856.80 855.80 857.40 855.70 858.40 858.00 31 76 867.00 868.00 868.00 867.50 869.00 868.50 870.70 870.00 29 5 841.00 840.50 841.60 841.00 842.00 840.80 843.00 842.20 27 79 846.00 845.00 847.00 845.20 847.50 846.20 848.50 848.00 16 104 729.70 728.20 731.00 730.60 731.90 730.80 732.70 731.50 24 94 712.40 712.00 714.50 714.00 716.00 715.00 717.10 717.00

o..

Node No

May

Ob. Well No

JUNE 1992 SEPT. 1992 DEC. 1992 MAY 1993 OBS SIM OBS SIM OBS SIM OBS SIM

13 660 123 661.20 661.20 662.00 662.00 663.00 663.10 663.00 662.90 28 685 64 686.00 685.88 687.30 687.00 688.10 687.90 686.4 686.2 25 725 38 725.80 725.40 727.50 727.1 728.65 728.40 728.00 727.8 36 777 30 778.10 777.80 779.00 778.80 781.10 780.60 780.00 780.2 32 767.1 13 767.20 768.00 768.30 668.00 769.10 669.00 768.50 668.00 38 810 10 811.00 810.60 812.40 812.00 813.10 813.00 812.00 811.2 33 810 6 811.40 811.00 812.60 811.60 813.10 812.50 812.50 811.8 35 854 1 855.50 855.00 856.80 857.00 857.10 856.60 856.90 856.00 31 868 76 868.80 867.20 869.50 868.70 871.10 86.50 870.20 869.5 29 840 5 840.80 840.20 841.60 840.80 842.70 841.80 843.10 842.5 27 904 79 904.10 904.20 906.00 905.50 907.10 906.60 906.50 905.8 16 728 104 728.10 727.50 728.20 727.3 728.40 728.00 728.30 728.1 24 795 94 796.60 796.00 797.30 796.90 798.10 797.90 797.80 797.1

. .


14

NECESSITY OF THE MODEL STUDIESFOR ARTIFICIAL RECHARGE PROGRAMMESIN BM-58 AND BM-59

The scarcity of groundwater in the area of studyrequires measures for artificial recharge in it. Thescope for construction of artificial recharge structures

such as percolation tanks and its performance if takenup can be easily studied with the aid of numericalmodel developed for the groundwater basin.

In order to study the aspects of artificial rechargestructures comprehensively with in a limited time withdue regard to the hydrological, hydro geological,

NODE NO

OB. WELL

NO

JULY 1999 AUG 1999 SEPT 1999 OCT 1999

OBS SIM OBS SIM OBS SIM OBS SIM

13 123 659.4 659.30 660.1 660.30 660.9 660.90 661.50 661.30 28 64 684.1 684.00 684.3 684.10 684.7 684.50 684.95 684.45 25 38 724.4 724.40 724.8 724.60 725.0 725.20 725.65 725035 36 30 777.1 777.00 777.9 778.00 778.5 778.60 779.70 779.70 32 13 767.1 767.30 769.2 769.50 770.8 770.8 771.20 771.20 38 10 811.1 811.30 813.3 813.20 813.9 813.80 814.20 814.10 33 6 824.30 824.10 849.6 849.80 850.4 850.4 814.10 814.30 35 1 854.2 854.50 854.8 834.70 855.2 855.50 856.60 856.30 31 76 867.8 867.60 868.0 868.20 868.1 868.00 868.90 868.90 29 5 839.9 839.80 840.1 840.30 840.9 840.80 841.20 841.10 27 79 844.8 844.60 845.6 845.50 846.0 846.20 846.70 846.60 16 104 724.3 724.20 726.8 726.8 728.1 728.00 730.90 730.50 24 94 711.2 711.10 713.8 714.0 714.2 714.2 715.30 715.20

Table 6 : Simulated Water Levels (1999)

Table 7 : Predicted Water Levels

.

NODE NO. OB.WELL MAY 2006 MAY 2011 MAY

2016 MAY 2020 MAY 2025

13 123 661.0 662.0 662.75 663.75 665.00 28 64 686.0 687.0 687.75 688.75 690.00 25 38 726.0 727.0 727.75 728.75 729.00 36 30 778.0 779.0 779.75 780.75 781.80 32 13 768.0 768.5 768.25 769.75 770.00 38 10 811.0 812.0 812.75 813.75 815.00 33 6 811.0 812.0 812.75 813.75 814.00 35 1 855.0 856.0 857.0 858.0 860.20 31 76 867.0 868.0 868.75 869.75 872.80 29 5 841.0 842.0 842.75 843.75 844.80 27 79 905.0 906.0 906.75 907.75 909.10 16 104 729.0 730.0 730.75 731.75 732.20 24 94 796.0 797.0 797.75 798.75 800.00

.


15

geo-hydrological conditions of the area, groundwaterexploitation with reference to the availablegroundwater resources which are time consuming.Numerical model studies are very useful which willgive a better understanding of the performance ofartificial recharge structures in advance, beforetaking up the project. This will avoid unnecessaryexpenditure on those projects, if implemented.

METHODOLOGY ADOPTED FORFEASIBILITY AND PERFORMANCESTUDY OF PERCOLATION TANKS

The source program of digital simulation modelis modified in such a way that one can put thepercolation tank or give the artificial recharge at anytime at the required node and the required quantity asinput as all these are kept as variables while writingthe program. As the same model can predict futurewater level it would be possible to test the effect ofartificial recharge at various sites and at various timeintervals and to decide the location and time ofsupplementing the artificial recharge. After identifyingthe site for artificial recharge hypothetical

percolation tank is located at that particular location/node and the performance of the site for artificialrecharge is studied by comparing the initial andpredicted future water levels surrounding that node/location, after taking into consideration the aquifer pa-rameters, ground water abstraction, hydrogeological and hydro meteorological characteristicsof the basin. The increase in water levels surroundingthe node and including the node itself indicates thesuitability of the site for the location of apercolation tank and its performance may beconsidered as satisfactory.

In the modified digital simulation model forartificial recharge as explained above ,by addition ofsome arbitrary recharge to the ground water system ata particular site/node, it is possible to decide weatherthe selected sites are suitable for construction ofartificial recharge structures such as percolation tanks.In the present case some higher arbitrary recharge valueis given at node no's 25&31 and the waterlevels surrounding the nodes have been observed. Therise in the water levels in the influence zone indicatesthe suitability of the site for percolation tank(Table- 8 to 11).

Table 8Percolation tank at node no. 31; time July 1998




NODE NO BEFORE P.T AFTER P.T 27 844.9 849.5 35 854.1 858.5 33 810.3 815.3 43 852.5 856.5 39 860.5 865.5 30 815.0 820

NODE NO BEFORE P.T AFTER P.T 27 844.2 846.5 35 854.2 856.3 33 824.3 828.5 43 860.0 865.5 39 862.0 866.5 30 863.0 867.0

NODE NO BEFORE P.T AFTER P.T 16 724.3 728.8 17 726.4 734.4 26 724.4 726.4 37 779.5 780.5 36 771.1 776.1 21 720.6 725.6

NODE NO BEFORE P.T AFTER P.T

16 728.4 732.9 17 730.4 734.4 26 726.2 727.2 37 767.3 768.8 36 777.6 782.6 21 715.8 720.8

.

. .

.


16

RESULTS AND DISCUSSION

The results of the study are shown in the form ofobserved and simulated water levels for thirteenobservation wells for different years.

From the tables of simulation of water levels, it isseen that the simulated water levels are coinciding withthe observed ones at almost all the nodes and if thereis any difference between them, it is within theassumed critical draft level and the reasons for thedifference may be attributed to the variation in rechargefactors and E.T factors.

The same model can be used to predict futurewater levels. In case of prediction of future waterlevels, it is assumed that the conditions prevailed atthe time of initial water levels would be the same forfuture also. So the predicted water levels may not berealistic but may represent some values near to thefield situation with some error. So these values maybe treated as initial status on the aquifer in the comingyears and precautionary measures can be enunciated,if necessary.

The same Ground water model with slightadditions in the source program is used for the studyof artificial recharge programme in the aquifer basin.By observing the performance of the percolation tankthrough digital simulation, it is found that there is asignificant change in the water levels surrounding thenode at the end of a given time period. The perfor-mance of the percolation tank is studied from theobserved water levels under the same pumping condi-tions with the passage of time The initial and realizedwater levels before and after locating the percolationtanks at node numbers 25 and 31. From these tables itcan be observed that the water levels in the influencezone of the percolation tanks have increased by 2 to 3m., which indicates that there is a definite impact ofpercolation tanks in the groundwater basin.

By observing the performance of percolation tanksthrough digital simulated model, it is found that thereis a significant change in the water levels at the end ofa given time in the influence zone of the percolationtank. The increase in the water levels in the influencezone indicates the suitability of the sites for locatingpercolation tanks thereby infers that there is a definite

impact and influence of providing percolation tank inthe ground water basin to augment the ground waterresource. From the study it is felt necessary that theperformance of the percolation tanks constructed inthe groundwater basins be monitored at representa-tive locations, as the collected information/data willbe useful as a guidance for future use so that thecriteria for formation of percolation tanks can be further rationalised and the benefits quantified.

Indiscriminate formation of artificial rechargestructures without due regard to the hydrological,geo-hydrological and hydro-geological conditions ofthe area, the present stage of groundwater exploita-tion with reference to the available ground waterresources in the area and the prevailing ground waterregime, in general, may result in many adverse effectslike rendering the area water logged, salination of theground water and the soils, low performance efficiencyof the structure constructed and avoidable in fructuousinvestment. Detailed scientific and integratedhydrological, geo-hydrological and hydro-geologicalinvestigations should invariably precede finalisationof sites for formation of artificial ground waterrecharge structures. Such a study will greatly aid inascertaining the feasibility and economic viability ofthe proposed sites for accomplishing artificialrecharge. The storage capacity of the each of the arti-ficial recharge structures should be carefully decidedbased on catchment yields and with due considerationto the hydro geological conditions at the sites withspecial reference to the extent of the influence zone,the capability of the aquifers in the influence zone toaccommodate the augmented recharge, the demand ofthe existing wells, scope for further intensification ofground water exploitation etc. Ignoring the above as-pects will lead to avoidable wasteful investment andalso depriving the downstream users of the surfacewater so wasted from such improper design.

In order to study all the above aspects comprehen-sively with in a limited time, numerical model studiesare very useful, which will give a better understandingof the performance of the artificial recharge structuresin advance, before taking up the project. This willavoid unnecessary expenditure on these projects ifimplemented.


17

CONCLUSION

• Percolation tanks may be formed in the commandarea of major projects to maintain ground waterlevels.

• Identification of sites for constructing artificialrecharge structures such as percolation tanks is ofutmost importance and their performance shouldbe known well in advance before taking up suchprojects through numerical model studies whichwill avoid/minimise the wasteful expenditure onthose projects if implemented.

• From the study it is found that the numerical modelfor digital simulation of regional aquifer proves tobe a powerful tool for the performance study ofpercolation tanks.

• By the results obtained from the application of theGround water model to basin BM 58- 59 ofPurandar Taluka of Maharashtra, it is can beconcluded that the model can be effectively usedor real time simulation as well as for real timeforecasting of groundwater levels.

• From the performance study of percolation tanksin the basin BM 58 - 59 it has been found that themean water table indicated a rise of 2 to 3 m dueto the artificial recharge through the percolationtanks which shows a definite impact and influenceof percolation tanks in the basin.

• As Irrigation development is the top most priorityin the study area it is observed from the modelresults that there is further scope for artificialrecharge programmes in the basin .Artificial recharge measures may be taken up, for which thesame Ground water model can be used for the feaibility studies. However detailed geological, hydrological studies are required to be carried out atsite before taking up such programmes.

• It is felt that the field agencies such as StateGround Water Departments and researchorganizations should take up such numericalmodel studies and the findings from the studyshould be implemented in the ground waterbasins/command areas and the performance ofartificial recharge sites should be monitored and

the feed back from the field should be recorded asguidance for future use so that the criteria forformation of percolation tanks can be furtherrationalised and the benefits quantified.

ACKNOWLEDGEMENT

The authors are thankful to Dr. I.D. Gupta, Direc-tor, Shri R.S. Ramteke, Joint Diector, Central Waterand Power Research Station, Pune, for their consentand kind permission to publish this paper. The authorsare thankful to Prof. Dr. P.T. Naidu & Dr. M. Y. A.Baig, Geology Department,Sri Venkateswara Univer-sity, Tirupati, A.P, for guiding the project and for thesuggestions offered during the project work. The au-thors are also grateful to Groundwater Department,Govt of Maharashtra for providing the data.

REFERENCES

American Society for Testing and Materials, 1993.Standard guide for application of a ground water flowmodel to a site-specific problem. ASTM Standard D5447-93, West Conshohocken, PA, 6 p.

http:// www.kimberly.uidaho.edu/ref-et/fao56.pdfIrrigation and Drainage Paper FAO 56.

1. Heinrich J.C., Huyakorn P.S., Zeinkiewicz O.C.and Mitchell A.R. 1977. "An Upwind FiniteElement Scheme for Two-Dimensional ConvectiveTransport Equation", International Journal ofNumerical Method in Engineering, Vol. 11.

2. Kumar, C.P., 2001. Common groundwatermodelling errors and remediation. Jr. of IWRS,Vol.21, No.4, Oct. 2001.

3. Madan K.J., Chikamori. K and Nakarai. Y 1996."Numerical Simulations for artificial recharge ofTakaoka groundwater basin, Tosa city, Japan", Jr.of Rural and Environmental Engg., 31 (8),105-124.

4. Pinder G.F. and Gray W.G. 1977. "FiniteElement Simulation in Surface and Sub-surfaceHydrology", Academic Press, New York.

5. Prickett T.A. 1975. "Modelling Techniques forGroundwater Evaluation", Advances in HydroScience, Vol. 10, Academic Press, New York,


18

6. Sreenivasulu P 1979. "MathematicalModelling for Inverse Problems in Non-Homogenous Aquifer", Ph.D Thesis, I.I.T.,Kharagpur.

7. Sreenivasulu P 1982. "Finite Element in Groundwater Systems", Lecture Notes, Vol. I & II, ISTESummer School, R.E.C. Warangal.

8. Todd D.K. 1980. "Groundwater Hydrology", Atext book, Published by John Wiley and Sons

9. Venugopal. K 2003. "Hydrogeologicalinvestigations with some Geo Engineering aspectsfor Water resources Development and Manage-ment in the Basaltic terrain of Punedistrict, Maharashtra,India", a Ph.D Thesis withSri Venkateswara University,Tirupati,A.P,India

10. Zienkiewcz O.C. 1971. "The Finite ElementMethod in Engineering Science" A text bookpublished by McGraw-Hill Publishing & Co.,London.


19

MORPHOMETRIC ANALYSIS AND PRIORITIZATION OF SUB-WATERSHEDSIN THE LONI WATERSHED, UTTAR PRADESH USING SPATIAL

INFORMATION TECHNOLOGY

Rajat Agarwal1, R. D. Garg*2 and P. K. Garg3

ABSTRACT

Spatial Information Technology has been adopted for the identification of morphological features andanalyzing their properties using Landsat ETM+ images, in the study the morphometric parametersconsidered for analysis are stream length, bifurcation ratio, drainage density, stream frequency,texture ratio, form factor, circularity ratio, elongation ratio, length of overland flow, compactnesscoefficient and constant of channel maintenance which have been computed in each sub-watershedusing GIS software ArcMap 9.3. The drainage network shows that the terrain exhibits dendritic tosub-dendritic drainage pattern. Stream orders ranges from fourth to fifth order. The mean bifurcationratio varies from 1.65-2.61 Km and falls under normal basin category. Drainage density variesbetween 0.17-0.82 km/km2. It indicates that the watershed has highly permeable subsoil and thickvegetative cover, with a very coarse to coarse drainage texture. The compound parameter values arecalculated and prioritization rating done for seven sub-watersheds in Loni watershed of Uttar Pradesh.The sub-watershed SW6 has a minimum compound parameter value of 2.2, and is likely to be subjectedto maximum soil erosion, hence it should be provided with immediate soil conservation measure.

Key words : Morphometry, Loni Watershed, Spatial Information Technology

INTRODUCTION

Growing population and industrialization hassqueezed the availability of natural resources, such aswater, which is depleting day by day in quantity andquality. Therefore, planning and management of suchresources is essential, but immense geospatial data isrequired for proper scientific planning andmanagement of water resources. Geomorphologicalcharacteristics of a watershed are commonly used fordeveloping the regional hydrological models to solvethe various hydrological problems of ungaugedwatershed or inadequate data situations (Sharma et al.,2010). An accurate understanding of the hydrologicalbehavior of watershed is important for its effectivemanagement. The morphometric analysis of watershedcan play an important role in case of inadequate dataavailability. The morphometric characteristics of awatershed represent its attributes and can be helpfulin synthesizing its hydrological behavior (Pandey et

al., 2004). It is very difficult to develop the large areain one stretch due to some geo-environmental oreconomic conditions. There is a need to prioritize thearea while applying the developmental programme.

Spatial Information Technology (SIT) i.e. RemoteSensing (RS), Geographical Information System (GIS)and Global Positioning System (GPS), has proved tobe an efficient tool in delineation of drainage patternand its prioritization as it provides effective solutionsto overcome most of the problems of land and waterresources planning and management arising due tousage of conventional methods of data collection. Theoccurrence and movement of groundwater in an areais governed by several factors, such as topography,lithology, geomorphology, structure, landuse andinterrelationship between these factors (Jaiswal et. al.,2003). The watershed morphometric characteristicshave been studied by many scientists usingconventional (Horton, 1945? Smith, 1950? Strahler,1957) and remote sensing & GIS methods (Biswas etal., 1999? Vittala et al., 2004; Narendra and NageswaraRao, 2006; Thakkar and Dhiman, 2007; Rudraiah etal., 2008). The study comprises the geomorphologi-cal characteristics of study sub-watershed which

1. Research Scholar, Geomatics Group, Dept. of Civil Engg., IndianInstitute of Technology (IIT) Roorkee, India

2. Asstt. Prof., Geomatics Group, Dept. of Civil Engg., IIT Roorkee,India.

3. Professor, Geomatics Group, Dept. of Civil Engg., IIT Roorkee, India*Corresponding author ([email protected])Manuscript No. 1296



20

Fig.: 1 : STUDY AREA

contributes to excessive erosion losses using factor andindirect methods and established relationships. In thepresent study, morphometric analysis and prioritizationof sub-watersheds are carried out of seven sub-water-sheds of Loni watershed in Unnao and RaebareliDistricts, Uttar Pradesh, using advanced remotesensing and GIS technology.

STUDY AREA

The study area comprises of 7 sub-watersheds(SW1 to SW7) ranging from 101 to 236 Km2 of Loniwatershed in Unnao and Raebareli districts. It is a partof Central Ganga Plain in Uttar Pradesh, consisting ofgeographical area of 1166 km2. It lies between lati-tude 26º4'4.34" to 26º40' N and longitude 80°25'15.39"to 81°1'38.955" E (Fig. 1.). In Loni watershed area,the maximum temperature is 450C in summer andminimum 30C in winter. It receives a normal annualrainfall of 800 to 900 mm with rainy days experiencesub-tropical climate. Geologically, it is part of the vastIndo-Gangetic alluvial plain. The alluvium formationof the area comprises of sand, silt and clay withoccasional gravel. The older alluvium called bhangar,

forms slightly elevated terraces usually above the floodlevels. The area is underlain by quaternary alluviumconsisting of clays, occasional kankar, sand ofvarious grades and gravels in different proportions.Four types of geomorphic units are identified asactive flood plain, lacustrine plain, older flood plainand varanasi plain. Active flood plain has higherwater level surface, and hence is the best landform forgroundwater.

METHODOLOGY

In the present study, morphometric analysis andprioritization of sub-watersheds in Loni watershed isbased on the integrated use of remote sensing and GIStechniques. The drainage map of 7 sub-watersheds wasdelineated using remote sensing geocoded FCC ofbands - 2, 3 & 4 of Landsat ETM+ Fused with PANdata in ERDAS Imagine software. Survey of IndiaToposheets 63A/6, 7, 10, 11, 12, 15 & 16 were usedas reference. Digitization and analysis of drainage hasbeen carried using GIS software (ArcGIS 9.3). Theattributes were assigned to create the digital data- basefor drainage layer of the Loni watershed. The map


21

SI. No. Mophometric Parameters Formula Reference 1. Stream Order Hierarchial rank Strahler (1964) 2. Stream Length (Lu) Length of the Stream Horton (1945) 3. Mean Stream Length (Lsm) Lsm = Lu/Nu Strahler (1964) 4. Stream Length Ratio (RL) RL=Lu/Lu-1 Horton (1945) 5. Bifurcation Ratio (Rb) Rb= Nu/Nu+ 1 Schumn (1956) 6. Mean Bifurcation Ratio (Rbm) Rbm = Average of bifurcation ratio of all orders Strahler (1957) 7. Total Relief (H) H = hmax - hmin 8. Relief Ratio (Rh) Rh = H / Lb Schumn (1956) 9. Drainage Density (Dd) Dd=Lu/A Horton (1932) 10. Stream Frequency (Fs) Fs = Nu/A Horton (1932) 11. Drainage Texture (Rt) Rt = Nu/P Horton (1945) 12. Elongation Ratio (Re) Re = 2 (A / Pi) / Lb Schumn (1956) 13. Circularity Ratio (Rc) Rc = 4* Pi*A/P2 Miller (1953) 14. Form Factor (Rf) Rf = A / Lb

2 Horton (1932) 15. Length of Overland Flow (Lg) Lg = 1/Dd*2 Horton (1945) 16. Compactness Coefficient (Cc) Cc = 0.2821*P/(A)0.5 Horton (1945) 17. Constant of Channel Maintenance C = 1/Dd Schumn (1956)

u = Total stream length of order 'u', Lu ‐1 = The total stream length of its next lower order, Nu = Total no. of stream segments of order 'u', Nu + 1 = Number of

egments of the next higher order, Lb = Basin length, A = Area of the Basin (km2), P = Perimeter (km) & Pi = 3.14.

Table 1 : Formulae used for computation of Morphometric Parameters

showing drainage pattern in the study area (Fig. 2.)was prepared after detailed ground check with GPSsurvey. The order was assigned stream by followingStrahler (1964) stream ordering technique. Variousmorphometric parameters, such as linear aspects ofthe drainage network: stream order (Nu), stream length(Lu), mean stream length (Lsm) stream length ratio (RL)

and bifurcation ratio (Rb), and areal aspects of thedrainage basin: drainage density (Dd), streamfrequency (Fs), drainage texture (Rt), elongation ratio(Re), circularity ratio (Rc), form factor ratio (Rf), lengthof overland flow (Lg) of the basin werecomputed using the well-known relationship aspresented in Table 1

Fig. 2 : Sub-watersheds showing stream order


22


The utility of satellite remote sensing formorphometric analysis is emphasized in the presentstudy. The results are discussed below.

Watershed Delineation

Watershed is defined as 'natural hydrologic entitythat covers a specific area expanse of landsurface from which the runoff (due to rainfall) flow todefined drain, channel, stream or river at anyparticular point'. Watershed modeling implies theproper use of all land, water and natural resource ofwatershed for optimum production with minimumhazard to natural resource, an integrated approach towatershed modeling is insisted for sustaineddevelopment of water resource. A watershed is thesurface area drained by a part or the totality of one orseveral given water courses and can be taken as anaturally occurring hydrologic unit several givenwater courses and can be taken as a naturallyoccurring hydrologic unit characterized by a set ofsimilar topographic, climatic and physical conditions.The watershed is delineating on the basis of elevationdata and drainage pattern and then watershed has beenfurther classified into 7 sub-watersheds (SW1 to SW7)on the basis of standard rules

According to Clarke (1966), morphometry is themeasurement and mathematical analysis of theconfiguration of the earth surface, shape anddimensions of its landforms. Morphometric analysisis a significant tool for prioritization of sub-watershedseven without considering the soil map (Biswas et al.,1999). The morphometric analysis involvesmeasurement of linear, areal and relief aspects of thewatershed and slope contribution (Nag andChakraborty, 2003). Morphometric analysis requiresmeasurement of the linear features, gradient ofchannel network, and contributing ground slopes ofthe drainage basin. The measurement of variousmorphometric parameters namely stream order (Nu),stream length (Lu), mean stream length (Lsm) streamlength ratio (RL), bifurcation ratio (Rb), total relief (H),relief ratio (Rh), drainage density (Dd), streamfrequency (Fs), drainage texture (Rt), elongationratio (Re), circularity ratio (Rc), form factor ratio (Rf),length of overland flow (Lg), compactness constant (Cc)and constant of channel maintenance (C) of the wa-tershed has been carried out and the result arepresented in Table 2.

Linear Aspects

The linear aspects include the stream order, streamlength, mean stream length, stream length ratio andbifurcation ratio, which were determined and resultshave been presented in Table 2.

Stream Order (Nu)

The stream order is the first step in the drainagebasin analysis. In the present study, ranking of streamshas been done according to Strahler's stream orderingsystem. According to Strahler (1964) the smallestfingertip tributaries are designated as order 1. Wheretwo first order streams join, a channel segment oforder 2 is formed? where two of orders 2 join, asegment of order 3 is formed? and so forth. The trunkstream through which all discharge of water and sedi-ment passes is therefore the stream segment ofhighest order. The study area has maximum 5th orderstream. The order-wise stream numbers, area andstream length of the 7 sub-watershed are presented inTable 2. Among all the sub-watershed the SW6 is of5th order, whereas SW3 & SW5 is of 4th order andremaining sub-watersheds are of 3rd order. Drainagepatterns of stream network from the watershed havebeen observed as mainly sub dendritic type whichindicates the homogeneity in texture and lack ofstructural control. This pattern is characterized by atree like or fernlike pattern with branches thatintersect primarily at acute angles.

Stream Length (Lu)

Stream length is measured from mouth of a riverto drainage divide with the help of ArcGIS 9.3software. This has been computed based on the lawproposed by Horton (1945) for all the sub-watershedof the study area. Usually, the total length of streamsegments is maximum in first order streams and itdecreases as the stream order increases but in thepresent case little variation from general observation(Table 2).

Mean Stream Length (Lsm)

Mean stream length is a characteristic propertyrelated to the drainage network components and itsassociated basin surfaces (Strahler, 1964). This hasbeen calculated by dividing the total stream length oforder (u) by the number of streams of segments in theorder. The mean stream length is presented in Table 2.


23

Stream Length Ratio (RL)

Stream length ratio is the ratio of the mean lengthof the one order to the next lower order of the streamsegments. The RL values are presented in Table 2. Thestream length ratio between the streams of differentorders of the study area shows a change in eachsub-watershed. This change might be attributed tovariation in slope and topography, indicating the lateyouth stage of geomorphic development in the streamsof the study area (Vittala et al., 2004).

Bifurcation Ratio (Rb)

Bifurcation ratio is also considered as an index ofrelief and dissections (Horton, 1945). According toSchumn (1956), Rb may be defined as the ratio of the

number of the stream segments of given order to thenumber of segments of the next higher orders. Strahler(1957) demonstrated that Rb shows only a smallvariation for different regions with differentenvironments except where powerful geologicalcontrol dominates. Lower Rb values are thecharacteristics of structurally less disturbed watershedswithout any distortion in drainage pattern. Low Rbvalue indicates the less structural disturbance and thedrainage patterns have not been distorted whereas highRb value indicates high structural complexity and lowpermeability of the terrain. The Rb values in thesub-watersheds of the study area range from 1.65 to2.61 indicating that the sub-watershed are fallingunder normal basin category (Strahler, 1957).

D SWSD Name

Stream Order

Basin Area (Km2)

Stream Order (Nu) Stream Length in Km (Lu) Perimeter (P)

(Km)

Basin Length (Km) I II III IV V I II III IV V

SW1 III 222.73 12 6 4 - - 18.54 9.25 24.68 - - 79.32 22.20 SW2 III 235.67 10 2 9 - - 23.97 4.28 28.65 - - 82.82 23.40 SW3 IV 204.08 38 13 17 11 - 29.60 20.90 20.42 15.1 - 82.40 23.60 SW4 III 128.18 10 4 5 - - 7.36 5.04 10.06 - - 53.20 19.34 SW5 IV 152.22 20 11 4 4 - 27.14 16.48 3.78 3.74 - 72.51 20.74 SW6 V 121.50 51 19 4 18 17 36.20 7.00 2.05 34.74 19.46 87.07 23.68 SW7 III 101.86 18 10 6 - - 22.97 13.95 7.18 - - 58.25 15.74

SWSD Name

Mean Stream Length in Km (Lsm) Stream Length Ratio (RL) Total

Relief (H) in meter

Relief Ratio (Rh)

Drainage Density

(Dd) (Km/Km2)

Stream Frequency

(Fs)

Texture Ratio (Rt) I II III IV V II/I IV/III V/IV

SW1 1.54 1.54 6.17 - - 0.50 0.76 - - 8 0.00036 0.23 0.098 0.28 SW2 2.39 2.14 3.18 - - 0.18 0.74 - - 9 0.00038 0.24 0.089 0.25 SW3 0.78 1.60 1.20 1.37 - 0.70 0.68 0.74 - 7 0.00029 0.42 0.387 0.96 SW4 0.73 1.26 2.01 - - 0.68 0.66 - - 7 0.00036 0.17 0.148 0.36 SW5 1.37 1.5 0.94 0.93 - 0.61 0.67 0.99 - 7 0.00034 0.33 0.256 0.54 SW6 0.71 0.37 0.51 1.93 1.08 0.20 0.52 16.94 1.78 6 0.00025 0.82 0.897 1.25 SW7 1.27 1.39 1.20 - - 0.61 0.72 - - 7 0.00044 0.43 0.334 0.58

D SWSD Name

Bifurcation Ratio Rb Mean Bifurcation

Ratio (Rbm)

Elongation Ratio (Re)

Circularity Ratio (R c)

Form Factor

(Rf)

Length of Overland

Flow Ratio (Lg)

Compactness Coefficient

(Cc)

Constant of Channel

Maintenance (C) (Km2/Km)

I/II II/III III/IV IV/V

SW1 2.0 1.5 - - 1.75 0.76 0.44 0.45 2.17 1.5 4.3 SW2 5.0 0.22 - - 2.61 0.74 0.43 0.43 2.08 1.52 4.16 SW3 2.92 0.76 1.54 - 1.74 0.68 0.38 0.37 1.19 1.63 2.38 SW4 2.50 0.8 - - 1.65 0.66 0.57 0.34 2.94 1.32 5.88 SW5 1.8 2.75 1 - 1.85 0.67 0.36 0.35 1.51 1.66 3.03 SW6 2.68 4.75 0.22 1.06 2.17 0.52 0.20 0.22 0.61 2.23 1.22 SW7 1.8 1.67 - - 1.73 0.72 0.38 0.41 1.16 1.63 2.32

* I, II, III, IV and V are represents drainage order

Table 2 : Morphometric Parameters of sub-watersheds of Loni watershed


24

Total Relief (H)

Total relief aspects of the sub watershed play animportant role in drainage development, surface andsub surface water flow, permeability, landformsdevelopment and erosion properties of the terrain. Theanalysis reveals that all the sub-watershed having therelief less than 20 m (Table 2). The low H valueindicates the gravity of water flow, high infiltrationand low runoff conditions.

Relief Ratio (Rh)

Relief ratio is defined as the ratio of total reliefand the basin length, the basin length is the longestdistance in the sub-watershed. It measures the overallsteepness of a drainage basin and is an indicator ofthe intensity of erosion processes operating on theslopes of the basin. In the present study, values varyfrom 0.00025 to 0.00044 shown in Table 2. Reliefaspect of the watersheds plays an important role indrainage development, surface and sub-surface waterflow, permeability, landform development andassociated features of the terrain.

Aerial Aspects

The aerial aspect, like drainage density, textureratio, stream frequency, form factor, circularity ratio,elongation ratio, length of overland flow, compactnesscoefficient and constant channel maintenance aregiven in Table 2.

Drainage Density (Dd )

Drainage density is defined as the total length ofstreams of all orders per drainage area (Table 1). Itindicates the closeness of spacing of channels. Itprovides a numerical measurement of landscapedissection and runoff potential. They range between0.17 to 0.82 km/ km2 indicating low drainage density.It is suggested that the low drainage density indicatesthe watershed is highly permeable sub-soil and thickvegetation cover.

Stream Frequency (Fs)

Stream frequency is defined as the total numberof stream segments of all orders per unit area (Table1). Stream frequency for all sub-watersheds of thestudy area is given in Table 2. It is indicative of lowrelief and high infiltration capacity of bedrock. In thepresent study, Fs exhibits positive correlation with the

drainage density values of the sub-watersheds, whichindicates increase in stream population with respectto increase in drainage density.

Drainage Texture (Rt)

Drainage texture is the total number of streamsegments of all orders per perimeter of that area(Horton, 1945) (Table 1). Rt is an important factor inthe drainage morphometric analysis which isdepending on the underlying lithology, infiltrationcapacity and relief aspect of the terrain. Smith (1950)has classified drainage density into five differenttextures. The drainage density less than 2 indicatesvery coarse, between 2 and 4 is related to coarse,between 4 and 6 is moderate, between 6 and 8 is fineand greater than 8 is very fine drainage texture. In thepresent study, the drainage density is of very coarse tocoarse drainage texture, as shown in Table 2.

Elongation Ratio (Re)

Schumm (1956) used an elongation ratio definedas the ratio of diameter of a circle of the same area asthe drainage basin to the maximum basin length. It isa very significant index in the analysis of basin shapewhich helps to give an idea about the hydrologicalcharacter of a drainage basin. Values near to 1.0 aretypical of regions of very low relief (Strahler, 1964).The value Re of the study area is ranges 0.52 to 0.76indicates that the low relief of the terrain andelongated in shape.

Circularity Ratio (Rc)

Miller (1953) defined a dimensionless circularityratio as the ratio of sub-watershed area to the area ofcircle having the same perimeter as the sub-watershed(Table 1). All of the sub-watersheds (except SW4) havethe circularity ratios less than 0.5, indicating theirelongated shape.

Form Factor Ratio (Rf)

It is the dimensionless ratio of basin area to thesquare of basin length (Horton, 1932). The value ofform factor lies in the range of 0.22 to 0.45. The lowervalues of form factor, indicates a highly elongatedshape. The elongated basin with low form factorindicates that the watershed will have a flatter peak offlow for longer duration. Flood flows of suchelongated basins are easier to manage than that of thecircular basin.


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Length of Overland Flow (Lg)

Horton (1945) defines an Lg as the length ofwater over the ground before it gets concentrated intodefinite stream channels. It relates inversely to theaverage slope of the channel. The length of overlandflow approximately equals to half of the reciprocal ofdrainage density. In the present study, computed valueof Lg for all sub-watersheds varies from 0.61 to 2.94.

Compactness Coefficient (Cc)

Horton (1945) defines a compactness coefficientis the ratio of watershed perimeter to perimeter of circleof watershed area.

Constant Channel Maintenance (C)

Schumn (1956) has used the inverse of drainagedensity as a property termed constant channelmaintenance. It tells the area of watershed surfacerequired to sustain one unit of channel length. Theconstant channel maintenance was computed for allthe sub-watersheds (Table 2). This factor depends uponnot only the rock type and permeability but also onduration of erosion and climatic history. In general,this constant will be extremely low in areas of closedissection.

Prioritization of Sub-Watersheds

The morphometric parameters i,e., bifurcationratio (Rb), compactness coefficient (Cc), drainagedensity (Dd), stream frequency (Fs), drainage texture(Rt), length of overland flow (Lg), form factor (Rf),circularity ratio (Rc), constant of channel maintenance(C) and elongation ratio (Re) also termed as erosionrisk assessment parameters, have been used forprioritizing sub-watersheds. The linear parameters,such as drainage density, stream frequency,bifurcation ratio, drainage texture, length of overlandflow have a direct relationship with erodibility, higherthe value, more is the erodibility. Hence forprioritization of sub-watersheds, the highest value oflinear parameters was rated as rank 1, second highestvalue was rated as rank 2 and so on, and the least valuewas rated last in rank. Average of all the linearparameters was then taken. Shape parameters, such aselongation ratio, compactness coefficient, circularityratio, constant of channel maintenance and formfactor have an inverse relationship with erodibility,lower the value, more is the erodibility. Thus, the

lowest value of shape parameters was rated as rank 1,next lower value was rated as rank 2 and so on and thehighest value was rated last in rank. Average of all theshape parameters was taken. Compound parameter(Cp) was computed to taking the average value oflinear as well as shape parameters. On the basis ofcompound parameters, assigned the high priority tothe lowest score and low priority to the highest scorewas assigned as shown in Table 3. The sub-watershedswere then categorized into five classes on the basis ofpriority as shown in Fig. 3.

CONCLUSION

The study reveals that remotely sensed data andGIS based approach is more appropriate than theconventional methods for the evaluation ofdrainagemorphometric parameters and their influenceon landforms, soils and eroded land characteristics atsub-watershed level. The conventional methods of

Fig. 3. Prioritization map of Loni Watershed


26

morphometric analysis are error prone, tiresome aswell as time consuming. Interpretation of multi-spectral satellite sensor data is of great help inanalysis of drainage parameters and morphometriccharacteristics which could be used for accuratedelineation of distinct geological and landform unitsand eroded lands. The result of morphometricanalysis shows that sub-watershed SW6 falls underhighest priority and therefore it is prone to relativelyhigh erosion and soil loss. Hence suitable controlmeasures are urgently required in this sub-watershedto preserve the land from further erosion.

REFERENCES

1. Biswas, S., Sudhakar, S. and Desai, V.R. 1999.Prioritization of subwatersheds based onmorphometric analysis of drainage basin: ARemote sensing and GIS approach. J. Indian Soc.Remote Sensing 27(3), 155-166.

2. Clarke J.I. 1966. Morphometry from Maps. Essaysin Geomorphology. Elsevier Publ. Co., New York,USA.

3. Horton R.E. 1932. Drainage basin characteristics.Trans. Amer. Geophys. Union, 13, 350-361.

4. Horton R.E. 1945. Erosional development ofstreams and their drainage basins: A hydrophysicalapproach to quantitative morphology. Bull. Geol.Soc. Amer., 56, 275-370.

5. Jaiswal, R.K., Mukherjee, S., Krishnamurthy, J.and Saxena, R. 2003. Role of remote sensing andGIS techniques for generation of groundwaterprospect zones towards rural development: An approach. Int. J. Remote Sensing, 24(5), 993-108.

6. Miller, V.C. 1953. A quantitative geomorphic studyof drainage basin characteristics in the ClinchMountain area, Varginia and Tennessee. ProjectNR 389042, Tech. Rept. 3.,Columbia University,Department of Geology, ONR, Geography Branch,New York.

7. Nag, S.K. and Chakraborty, S. 2003. Influence ofrock types and structures in the development ofdrainage network in hard rock are., J. Indian Soc.Remote Sensing, 31(1), 25-35.

8. Narendra, K. and Rao, K.N. 2006. Morphometryof the Mehadrigedda watershed, Visakhapatnamdistrict, Andhra Pradesh using GIS andResourcesat data. J. Indian Soc. Remote Sensing,34(2), 101-110.

9. Pandey, A., Chowdhary, V.M. and Mal, B.C. 2004.Morphological analysis and watershedmanagement using GIS. J. of hydrology, 27(3),71-84.

10. Rudraiah, M., Govindaiah, S. and Vittala, S.S.2008. Morphometry using remote sensing and gistechniques in the sub-basins of kagna river basin,Gulburga district, Karnataka, India. J. Indian Soc.Remote Sensing, 36, 351-360.

Table 3 : Priortization of sub-watersheds of Loni watershed

watersheds

Morphometric parameters Compound Parameter

Final Priority

Linear parameters Shape parameters

Dd Fs Lg Rb Rt Cp Values R c Re Rf Cc C Cp Values

SW1 0.23 (6)

0.098 (6)

2.17 (2)

1.75 (4)

0.28 (6)

4.8

0.44 (5)

0.76 (7)

0.45 (7)

1.5 (2)

4.3 (6)

5.4

5.1

5

SW2 0.24 (5)

0.089 (7)

2.08 (3)

2.61 (1)

0.25 (7)

4.6

0.43 (4)

0.74 (6)

0.43 (6)

1.52 (3)

4.16 (5)

4.8

4.7

4

SW3 0.42 (3)

0.387 (2)

1.19 (5)

1.74 (5)

0.96 (2)

3.4

0.38 (3)

0.68 (4)

0.37 (4)

1.63 (4)

2.38 (3)

3.6

3.5

2

SW4 0.17 (7)

0.148 (5)

2.94 (1)

1.65 (7)

0.36 (5)

5.0

0.57 (6)

0.66 (2)

0.34 (2)

1.32 (1)

5.88 (7)

3.6

4.3

4

SW5 0.33 (4)

0.256 (4)

1.51 (4)

1.85 (3)

0.54 (4)

3.8

0.36 (2)

0.67 (3)

0.35 (3)

1.66 (5)

3.03 (4)

3.4

3.6

2

SW6 0.82 (1)

0.897 (1)

0.61 (7)

2.17 (2)

1.25 (1)

2.4

0.20 (1)

0.52 (1)

0.22 (1)

2.23 (6)

1.22 (1)

2.0

2.2

1

SW7 0.43 (2)

0.334 (3)

1.16 (6)

1.73 (6)

0.58 (3)

4.0

0.38 (3)

0.72 (5)

0.41 (5)

1.63 (4)

2.32 (2)

3.8

3.9

3


27

11. Schumn, S.A. 1956. Evaluation of drainage systems and slopes in badlands at Perth Amboy, NewJersy, Bull. Geol. Soc. Amer., 67, 597-646.

12. Sharma, S.K., Rajput, G.S., Tignath, S.K. andPandey, R.P. 2010. Morphometric analysis andprioritization of a watershed using GIS. J. IndianWater Resource Society, 30(2), 33-39.

13. Smith, K.G. 1950. Standards for grading textureof erosional topography. American Journal ofScience 248, 655-668.

14. Strahler, A.N. 1957. Quantitative analysis ofwatershed geomorphology, AmericanGeophysical Union Transactions, 38, 913-920.

15. Strahler, A.N. 1964. Quantitative geomorphologyof drainage basins and channel networks: In.Handbook of Applied Hydrology, McGraw HillBook Company, New York.

16. Strahler, A.N. and Strahler, A.H. 2002. A Text Bookof Physical Geography, John Wiley & Sons, NewYork.

17. Vittala, S.S., Govindaiah, S. and Honne Gowda,H. 2004. Morphometric analysis of sub-watershedsin the Pawagada area of Tumkur district, SouthIndia, using remote sensing and GIS techniques.J. Indian Soc of Remote Sensing, 32(4), 351-362.


28

USE OF GEOGRAPHICAL INFORMATION SYSTEM IN HYPSOMETRICANALYSIS OF WATERSHED

S.K. Sharma1, N.K. Seth1, S. Tignath2 and R.P. Pandey3

ABSTRACT

Hypsometry of drainage basins (area-elevation analysis) has generally been used to reveal the stagesof geomorphic development (stabilized, mature and young). In the present study, Gusuru riverwatershed located in part of Panna and Satna district of Madhya Pradesh was considered as the casestudy area. The watershed was delineated into fourteen micro-watersheds and hypsometric analysiswas carried out for all of them using the digital contour map, which was generated using Arc/Info GIS.The hypsometric integral values for all of the micro-watersheds of Gusuru river ranges between 0.20and 0.71. Further, the hypsometric analysis performed on the micro-watersheds revealed that themicro-watersheds 2, 4, 9 and 11 are more prone to erosion in comparison to other micro-watersheds ofstudy area. This finding would emphasize the construction of soil and water conservation measures inthe micro-watersheds at appropriate locations for controlling further erosion, reducing the sedimentout flow and conserve water.

Key Words : GIS, Geologic Stage, Hypsometric Analysis, Watershed

INTRODUCTION

Hypsometric analysis is the relationship ofhorizontal cross-sectional drainage basin area toelevation. The hypsometric curve has been termed thedrainage basin relief graph. Hypsometric curves andhypsometric integrals are important indicators ofwatershed conditions (Ritter et al., 2002). Differencesin the shape of the curve and hypsometric integralvalues are related to the degree of disequilibria in thebalance of erosive and tectonic forces (Weissel et al.,1994). Hypsometric analysis was first time introducedby Langbein (1947) to express the overall slope andthe forms of drainage basin. The hypsometric curve isrelated to the volume of the soil mass in the basin andthe amount of erosion that had occurred in a basinagainst the remaining mass (Hurtrez et al., 1999). It isa continuous function of non-dimensional distributionof relative basin elevations with the relative area ofthe drainage basin (Strahler, 1952). This surface el-evation has been extensively used for topographiccomparisons because of its revelation of three-dimen-sional information through two-dimensional approach(Harrison et al., 1983; Rosenblatt and Pinet, 1994).1. Soil and Water Engineering Department. Agricultural Engineering

College, J.N.K.V.V., Jabalpur, M.P.-4820042. Geology Department, Government Model Science College, Jabalpur, M.P.3. National Institute of Hydrology, Roorkee, Uttarakhand, 247667

Manuscript No. 1302

Comparisons of the shape of the hypsometric curvefor different drainage basins under similar hydrologicconditions provides a relative insight into the past soilmovement of basins. Thus, the shape of thehypsometric curves explains the temporal changes inthe slope of the original basin. Strahler (1952)interpreted the shape of the hypsometric curves by ana-lyzing numerous basins and classified the basins asyoung (convex upward curves), mature (S-shapedhypsometric curves which is concave upwards at highelevations and convex downward at low elevations)and peneplain or distorted (concave upward curves).There is frequent variation in the shape of thehypsometric curve during the early geomorphic stagesof development followed by minimal variation afterthe watershed attains a stabilized or mature stage.

Hypsometric analysis is carried out to ascertainthe susceptibility of watershed to erosion andprioritize them for treatment. The slope of thehypsometric curve changes with the stage ofwatershed development, which has a greater bearingon the erosion characteristics of watershed and it, isindicative of cycle of erosion. The hypsometricintegral (Hsi) is also an indication of the 'cycle oferosion' (Strahler, 1952; Garg, 1983). The cycle oferosion is the total time required for reduction of landarea to the base level i.e. lowest level. This entire



30

Plotting of hypsometric curves (HC)

Hypsometric curve was obtained by plotting therelative area along the abscissa and relative elevationalong the ordinate. The relative area is obtained as aratio of the area above a particular contour to the totalarea of the watershed encompassing the outlet.Considering the watershed area to be bounded byvertical sides and a horizontal base plane passingthrough the outlet, the relative elevation is calculatedas the ratio of the height of a given contour (h) fromthe base plane to the maximum basin elevation (H)(up to the most remote point of the watershed fromthe outlet) (Sarangi et al., 2001; Ritter et al., 2002).This provides a measure of the distribution oflandmass volume remaining beneath or above a basalreference plane. Estimation of hypsometric integrals(Hsi)

The hypsometric integral (Hsi) was estimated us-ing the elevation relief ratio method as proposed byPike and Wilson (1971). The relationship is expressedas : Elevmean - ElevminE ≈ Hsi = ---------------------- ------------------(1) Elevmax - Elevmin

Where, E is the elevation-relief ratio equivalent tothe hypsometric integral Hsi ; Elevmean is theweighted mean elevation of the watershed estimatedfrom the identifiable contours of the delineatedwatershed ; Elevmax and Elevmin are the maximumand minimum elevations within the watershed. Thehypsometric integral is expressed in percentage units.However, this method was observed to be lesscumbersome and faster than the other methods inpractice for Hsi (Singh et al., 2008b).


The co-ordinates of the hypsometric curves of thefourteen micro-watersheds of Gusuru river watershedsas obtained were plotted and presented in Fig 3. Itwas observed from the hypsometric curves of thesemicro-watersheds that the drainage system is attain-ing the monadnock stage from the youth stage, whichis true for most of the Tons watershed (Gusuru river issub-watershed of Tons river). The comparison betweenthese curves shown in the Fig 3 indicated a marginaldifference in mass removal from the micro-watershedsof study area. It was also observed that there was acombination of convex-concavo and S-shape of the

hypsometric curves for the micro-watersheds understudy. This could be due to the soil erosion fromtheses micro-watersheds resulting from the incisionof channel beds, down slope movement of topsoil andbedrock materials, washout of the soil mass andcutting of streams banks.

1

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1a/A

h/H

2

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

3

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

4

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

5

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

6

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

7

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

8

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

9

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

10

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

11

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/Ah/

H

12

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

13

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

14

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

a/A

h/H

Fig 3: Hypsometric curves of microwatersheds ofstudy area

The hypsometric integral (Hsi) values obtained for14 micro-watersheds of study area are presented inTable 1. The Hsi values of these micro-watershedsranged between 0.20 to 0.71. It was observed fromHsi that the micro-watersheds are in the mature stageand moving toward the peneplanation or thedeteriorating stage. While comparing the standard Hsivalues of different stages, the micro-watershed 14 hasreached to monadnock stage. It was also observed fromHsi vales that the micro-watersheds 1, 10 and 13 arein late mature stage or approaching towardsmonadnock (less susceptible) stage and attributedmainly to human interventions in the form of construc-tion of roads, intensive agricultural practices and de-forestation activities. However, the micro-watersheds3, 5, 6, 7, 8 and 12 are in mature stage. The hydrologicresponse of the micro-watersheds attaining maturestages will have slow rate of erosion unless there is


31

very high intense storms leading to high runoff peaks(Ritter et al., 2002). Moreover, the micro-watershed 9yielded higher hypsometric integral value, explainingits late youthful stage which calls for suitablemeasures of soil and water conservation. Further,micro-watersheds 2, 4 and 11 have got very high value

of hypsometric integral which takes them to youngstage i.e. very susceptible to erosion. Therefore, thesemicro-watersheds are more prone to subsequenterosion activities and needs immediately appropriatesoil and water conservation measures.

Micro

watershed

No.

Area

(km2)

Maximum

elevation

(m)

Minimum

elevation

(m)

Mean

elevation

(m)

Hypsometric

integral

Geological stage

1 11.81 628.00 538.00 566.20 0.31 Late Mature or near

Monadnock

2 10.70 608.00 479.00 560.70 0.63 Young

3 11.13 606.00 478.00 541.46 0.49 Mature

4 10.50 568.00 418.00 510.53 0.61 Young

5 14.47 609.00 417.00 506.88 0.46 Mature

6 12.57 605.00 478.00 537.75 0.47 Mature

7 7.89 609.00 477.00 535.59 0.44 Mature

8 14.72 566.00 358.00 464.74 0.51 Mature

9 10.18 606.00 358.00 500.55 0.57 Late Youthful


Monadnock

11 11.07 584.00 358.00 519.07 0.71 Young

12 11.48 564.00 358.00 442.33 0.40 Mature


Monadnock

14 9.24 566.00 339.00 383.70 0.20 Monadnock

Table 1 : Micro-watershed wise Hypsometric Integral values of Gusuru river watershed

CONCLUSION

Hypsometric analysis of watershed expresses thecomplexity of denudational processes and the rate ofmorphological changes. Therefore, it is useful tocomprehend the erosion status of watersheds andprioritize them for undertaking soil and waterconservation measures. But, great care must beexercised in interpreting and comparing hypsometriccurves due to its complex nature of computation. Theresults of hypsometric integrals revealed that the

micro-watersheds 2, 4, 9 and 11 are more prone toerosion in comparison to other micro-watershedswhich would necessitate construction of soil andwater conservation structures at appropriate locationsof the micro-watersheds to arrest sediment outflowand conserve water. Further, the micro-watersheds,which are having hypsometric integral values morethan 0.5 (i.e. approaching youthful stage) needconstruction of both vegetative and mechanical soiland water conservation structures to arrest sedimentload and conserve water for integrated watershed


32

management. However, the hypsometric integralvalues less than 0.5 (i.e. approaching monadnockstage) needs minimum mechanical and vegetativemeasures to arrest sediment loss but may require morewater harvesting type structures to conserve water atappropriate locations in the watershed forconjunctive use of water.

REFERENCES

1. Biswas, S., Sudhakar, S., and Desai, V.R. 1999.Prioritization of sub watershed based onmorphometric analysis of drainage basin: ARemote sensing and GIS approach. J. Indian Soc.Remote Sensing. Vol. 22(3). PP. 155-167.

2. Garg, S.K. 1983. Geology- the Science of the earth.Khanna Publishers, New Delhi.

3. Harrison, C.G., Miskell, K.J., Brass, G.W.,Saltzman, E.S. and Sloan II, J.L. 1983. Continentalhysography. Tectonics, 2:357-377.

4. Hurtrez, J.E., Sol, C. and Lucazeau, F. 1999.Effect of drainage area on hypsometry froman analysis of small-scale drainage basins in theSiwalik hills (Central Nepal). Earth SurfaceProcesses and Lanform, 24:799-808.

5. Langbein 1947. Topographic chactristics ofdrainage basins. U.S.G.S., Water Supply Paper.968C:127-157.

6. Pandey, A., Chowdhry, V.M. and Mal, B.C. 2004.Hypsometric analysis using GeographicalInformation System. J. Soil & Water Cons. India,32: 123-127.

7. Pike, R.J. and Wilson S.E. 1971. Elevation- reliefratio hypsometric integral and geomorphicarea-altitude analysis. Geological Soc. Am. Bull.82: 1079-1084.

8. Ritter, D.F., Kochel, R.C. and Miller, J.R. 2002.Process Geomorphology. McGraw Hill, Boston.

9. Rosenblatt, P. and Pinet, P.C. 1994. Comparativehypsometric analysis of Earth and Venus. Geophys.Res. Lett., 21: 465-468.

10. Sarangi, A., Bhattacharaya, A.K., Singh, A. andSingh, A.K. 2001. Use of geographical Information System (GIS) in assessing the erosionstatus of watersheds. Indian J. Soil. Cons. 29 (3):190-195.

11. Singh, O. and Sarangi, A. 2008a. Hypsometricanalysis of the lesser Himalayan watersheds usinggeographical information system. Indian J. SoilCons. 36(3):148-154.

12. Singh, O. Sarangi, A. and Sharma, M.C. 2008b.Hypsometric integral estimation methods and itsrelevance on erosion status of north western LesserHimalayan watershed. Water Res. Mgt. 22:15451560.

13. Strahler, A.N. 1952. Hypsometric (area-altitude)analysis of erosional topography. Geologic.Soc. Am. Bull., 63: 1117-1141.

14. Weissel, J.K., Pratson, L.F. and Malinverno, A.1994. The length scaling properties of topography.J. Geophys. Res. 99: 13997-14012.


33

IDENTIFICATION OF SIGNIFICANT ENVIRONMENTAL ASPECTS ANDFACTORS AFFECTING WETLAND DYNAMICS AND ECOLOGICAL

CHARACTERS OF DEEPOR BEEL WETLAND USINGGEOINFORMATIC TECHNIQUES

Md. Surabuddin Mondal1 and Padma Sharma²

ABSTRACT

An attempt has been made in this study to identify the significant environmental aspects & factorsaffecting to the wetland dynamics as well as the ecological characters of Deepor Beel wetland. Thedynamics of aquatic vegetation and wetland water bodies has been assessed by using multi-temporalsatellite images. The major environmental aspects & factors affecting to the wetlands have beenexplored and identified using multi-temporal satellite images. This study also highlights theimportance of monitoring the physical extent of wetlands as well as identifies different environmentalaspects & factors affecting the wetlands using multi-temporal satellite imagery, as the dynamic changesin wetland nature and extent necessitate the widespread and consistent use of satellite-based remotesensors and low-cost, affordable GIS tools for effective management and monitoring.

Key words: Wetland Dynamics, Environmental Aspects and Factors Identification, Satellite Images,Remote Sensing, GIS.

INTRODUCTION

Wetlands are areas, which are permanently or sea-sonally submerged or water-saturated land, and con-sist either of shallow water areas with the water tablenear the surface (Downing, et. al 2006). Wetlands in-clude marshes, swamps, flood plains, bogs, peat lands,shallow ponds and littoral zones of large water bod-ies. The Ramsar convention (Ramsar, Iran, 1971) de-fines wetlands as areas of marsh, fen, and peat land orwater whether natural or artificial, permanent or tem-porary, with water that is static or flowing, fresh, brack-ish or, where marine, the water depth of which doesnot exceed six meters at low tides. Ramsarfurther incorporates riparian and coastal zonesadjacent to the wetlands, and islands or bodies ofmarine water. Ramsar categories wetlands into (i)estuaries, mangroves and tidal flats; (ii) flood plainsand deltas; (iii) freshwater marshes; (iv) lakes; (v) peatlands and; (vi) forested wetlands.

Wetlands are a valuable natural resource for floodcontrol and water quality improvement (Rundquist et

al. 2001). They provide a critical habitat to a largenumber of wildlife species, including manyendangered species, and support a rich biodiversity(Ozesmi and Bauer, 2002). Wetlands also play animportant role in global carbon and methane cycles,and thus could strongly feedback to, as well as beingaffected by, climate change (IPCC, 2001 ).

There are eight different categories of wetlands inIndia differentiated by region. The flood plain of theBrahmaputra (Beels) and the marshes and swamps inthe hills of the North East and the Himalayan foot hillsare such two categories (Prasad, 2002). In Assam thereare 3,512 wetlands with areas larger than 2.25 ha and1,120 smaller wetlands. In the Brahmaputra valleymost of the wetlands are oxbow lakes and hencebigger in size. During the period of 1930s and -40smany wetlands known as Beels, marshes and swampswere seen in the rural areas. These wetlands werefound to be very productive (Patar, 2005). In the fringeareas of the wetlands (the aquatic ecotones), differentspecies of plants of economic importance grew. DeeporBeel of Assam (Kamrup District) is one of the 21national wetlands, which have been declared so far.The Deepor Beel wetland is a permanent, freshwaterlake, in a former channel of the Brahmaputra River


1. Institute of Geography, Georg August University of Gottingen,Gottingen, Germany

2. Dept. of Economics, Cotton College, Guwahati, Assam, IndiaManuscript No. 1312


34

located to the south of the present main river channel,oriented to the south-west of Guwahati city. It is a largenatural wetland with great biological and environmen-tal importance besides being the only major stormwater storage basin for Guwahati city. This wetland isendowed with rich floral and faunal diversity. In addi-tion to a huge congregation of residential water birds,the Deepor Beel ecosystem houses a large number ofmigratory waterfowl each year. Deepor Beel has beendesignated as a Ramsar Site in November 2002.

Deepor Beel Wetland of Brahmaputra Valley

Deepor beel is a permanent, freshwater lake, in aformer channel of the Brahmaputra River, now to thesouth of the main river south-west of Guwahati city. Itis a large natural wetland having great biological andenvironmental importance besides being the onlymajor storm water storage basin for the Guwahati city(Deka and Goswami, 1992) (Figure 1).

Fig. 1 Location of Deepor Beel

Physical Features

The Deepor Beel is set in a unique physiographicframework and is characterized by its activehydrologic regime. Geomorphologically, its origin anddevelopment are intimately linked with the geologicand tectonic history of the region, hydrology andchannel dynamics of rivers and pattern and intensityof land use in the area. It is commonly believed thatthe beel together with those adjoining it represents anabandoned channel of the Brahmaputra system. Thebeel is located in a broad U-shaped valley rammedbetween the steep highlands on the north and south.The highlands lying immediately to the north and southof the beel are made up of gneisses and schist's of the

Archaean age, whereas the beel and its lowland fringeis underlain by recent alluvium consisting of clay, silt,sand and pebbles.

Deepor beel acts as a natural storm waterreservoir during the monsoon season for the Guwahaticity. At maximum flooding, it is about four metersdeep; during the dry season, the depth drops to aboutone meter. The main sources of water are the Basisthaand Kalmani rivers and local monsoon run-off betweenMay and September. The beel drains into theBrahmaputra River 5 km to the north, through theKhonajan channel. About half of the beel dries outduring the winter months, and at this time, the exposedshores are converted into rice paddies to a width of upto one kilometer. Humid, tropical monsoon climatewith a prolonged monsoon season from May toSeptember, a relatively cool, dry winter, and apre-monsoon period in March-May with occasionalstorms. Temperatures range from 10.60 to 32.00C.

Ecological Features (main habitats andvegetation types)

The water area of Deepor beel itself offers avariety of habitats throughout the year as the waterregime changes. During the summer, large part of thebeel is covered by aquatic vegetation, like, waterhyacinth, aquatic grasses, water lilies and otherssubmerged emergent and floating vegetation. Thehighland areas, which are completely dry duringwinter, are also covered by aquatic and semi-aquaticvegetation. The water regime touches the surround-ing boundaries, such as, edges of hilly terrain andNational Highways, etc., during peak of the monsoonseason; hence it is a part of the Deepor beelecosystem. During the winter a variety of habitat, suchas, deep open water area (hydro phase), marshy lands,mud flat, emergent vegetation, water hyacinth patches,wet-grassland patches, paddy field area, dry grasslandareas, and scattered forest areas, etc., supportmanifold habitats for migratory waterfowl,residential waterfowl and terrestrial avifauna. Thescattered forest present within the beel area supportsa large variety of lizard species. These habitatssupport specific overlapping communities. Thesecommunities are linked by feeding relationshipsforming a very complex energy transformationsystem and food web. The beel is endowed with richfloral and faunal diversity. In addition to hugecongregation of residential water birds, the Deeporbeel ecosystem harbors large number of migratory


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waterfowl each year. The special floral (Noteworthyflora) and faunal (Noteworthy fauna) value of Deeporbeel ensures its inclusion among the wetlands ofinternational importance. The huge congregation ofmigratory and residential birds at Deepor beel is wellknown. Less often highlighted is the large number ofinvertebrate, fish, reptiles and mammals which makeit a unique ecosystem.

Social and Cultural Values (e.g., fisheriesproduction, forestry, religious importance,archaeological site, etc.)

Deepor beel supports an important fishery,providing a means of livelihood for a number of localfamilies, and is used for domestic watersupply. Nymphaea nuts, flowers, etc., are harvestedfor sale in the local markets, and these constitutevaluable natural crops. The seeds of Giant waterlily - Euryale ferox, annually leased by thegovernment revenue department, are also anothermajor revenue earning source after fish. Severalcommercial species, such as, ornamental fish,aquarium plants and medicinal plant species are alsoavailable within the beel ecosystem. Orchids ofcommercial value are to be found in the neighboringforest. The neighboring forests also harbour valuabletrees, such as, Shorea robusta and many others.

Local people traditionally utilize the beel tocollect fodder for domestic cattle, natural food, suchas, vegetables, flowers, aquatic seeds, fish, mollusesand other essential requirements. Poor peopleinhabiting the vicinity of the beel ecosystem, collecttheir required protein in the form of fish and otheranimal meats. The people of southern boundarycommunicate with the city people through the beelwater by country boats.

Dynamics of Deepor Beel Wetland

For a country like India, with its vast biologicaland cultural diversity, a comprehensive use of remotesensing, GIS and related technologies is obligatory inup-to-date conservation. Classifying and mappingwetlands based on geomorphology, water quality andother biological attributes can lead to qualitativeassessment. Results obtained can be used in planning,inventorying and monitoring wetlands in the country.Due to the large extent of wetlands, the single use ofground survey methods is not a feasible approach forwetland mapping and regular monitoring (Verhoest

E.C. et. al 2008). Satellite remote sensing has manyadvantages including synoptic view, multi-spectraldata collection, multi-temporal coverage and cost-ef-fectiveness (Rundquist et al. 2001). Therefore, satel-lite remote sensing is arguably the only practical ap-proach for mapping wetlands in a convenient mannerwhen covering large areas (Pontius et al. 2009).

Significant Environmental Aspects and FactorsAffecting the Deepor Beel Dynamics andEcological Character

The past two decades have seen considerabletransformation in the ecological and social characterof Deepor Beel and nearby areas. Factors (past, presentor potential) adversely affecting the site's ecologicalcharacter, including changes in land use anddevelopment projects has been observed that naturaland anthropogenic problems include (a) at the site (b)around the site Surroundings/catchment.

At the site

Land tenure/ownership of wetland site isstate-owned, fishery Department, government ofAssam. The entire beel area is utilized as traditionalfishing ground by the inhabitants of the surroundingvillages. Apart from this, the local people areregularly using the beel water as a waterway fortransporting the villagers of the Southern boundary tothe N.H. 37. The villagers collect fodder from the beelarea for their domestic cattle and collect aquatic seedssuch as, Giant water lily, Nymphea sp. etc.

The intensive fishing activities, prevalent both byday and night, causes a considerable disturbance andalso there is heavy hunting pressure on water birds.Large numbers of water birds are netted illegallyduring the winter months (December to March) forsale in local markets. Pesticides and fertilizers arewidely used on adjacent agricultural land, and enterthe lake in runoff. The fertilizers have acceleratedeutrophication, and infestation with Echhorniacrassipes is now becoming a serious problem.

The dynamics of aquatic vegetation and wetlandwater bodies has been asses by using multi-temporalsatellite images (Figure 2, Table 1). This studyhighlights the importance of monitoring the physicalextent of wetlands using multi-temporal satelliteimagery, as the dynamic changes in wetland natureand extent necessitate the widespread and consistent


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use of satellite-based remote sensors and low-cost,affordable GIS tools for effective management andmonitoring (Sharma et al., 2011). For this purpose,IRS-1A LISS I images of 26th December of 1990,IRS-1D LISS III satellite images of 8th February of1997 & IRS-P6 LISS III images of 14th December of2007 has been digitally classified. The supervised

Fig. 2: The dynamics of Deepor beel wetland in between 1990, 1997 and 2007

Table - 1: Area statistics of Deepor beel wetland area during 1990, 1997 and 2007

Sl. No.

Class Name

1990 1997 2007 Area

(in ha) % of Area

Area (in ha)

% of Area

Area (in ha)

% of Area

Relative Change 1990– 2007 (%)

1. Wetland Ecosystem 961.7 33.5

424.3

14.77

356.3

12.4

-21.1

2. Aquatic Vegetation - - 182.0 6.33 203.3 7.0 7.0 3. Other Vegetation 144.9 5.0 506 17.61 329 11.45 6.45 4. Other Land Use 1765.7 61.5 1760 61.29 1983.7 69.15 7.65

Total 2872.3 100 2872.3 100 2872.3 100 0

maximum likelihood classifier have been used forclassify the satellite images. The overall accuracy inof the classified image is 81.91%, 83.58%, and 84.21%for 1990, 1997 and 2007, respectively. The Kappacoefficient is 0.89, 0.89 and 0.91 for 1990, 1997 and2007, respectively.


37

At the surroundings/catchment

Land tenure/ownership of wetland surroundingareas is privately owned, except for the Gorbhangareserve forest which is state-owned. The major threatsaround wetland surrounding / catchment areas aresummarized as below:

Commercial scale forest exploitation

The forests in the catchment area to the south areoften being felled illegally to supply timber for thesawmills, resulting in increased erosion, which in turns,is causing rapid siltation in the beel (Figure 3 & Table2). Settlements and permanent agriculture are steadilyencroaching on the wetland and reducing the extentof the marsh vegetation. Government proposal to diga canal from Guwahati city to the beel to dispose ofthe city's sewage would, if carried out, have disastrouseffects on the wetland ecosystem.

Disturbance from transport artery i.e.construction of railway line along thesouthern boundary of the Deepor beel

Before the start of construction work of B.G. line,there was no railway line passing through or in thevicinity of the beel except the Rangia - Guwahati B.G.lines that touch part of the Borhola beel system lyingto the north-east of the Deepor beel and originallyforming a part of it (Figure 4).The newly constructedrailway line through the southern periphery of Deeporbeel is a major threat to the ecosystem, particularly, inview of encroachments, forest destruction, erosion,noise pollution /disturbance, wildlife collisions etc.The rerouting of flow (Runoff) in the Deepor BeelWetland is attributed to the embankment of soil onwhich the Northeast Frontier Railways track lie. Theembankment of soil has prevented the natural runoffcourse into Deepor Beel, from neighboring areas suchas the Rani Reserved Forest and the up-gradient drain-age, where 18 km to the east lays the city of Guwahati.

The beel is surrounded by the National HighwayNo. 37 on the east and north-east. The PWD roadskirting the northern fringe of the Rani and GarbhangaReserve Forest on the south, the Dharapur-Kahikuchisection of the N.H. 37 on the west and theEngineering College Road on the north. Besides, a fewother minor roads and tracts also exist in the vicinityof the beel.

Fig. 3 : Forest area exploitation in between 1987, 1997and 2007


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A number of brick kilns also operate within thebeel area itself (Figure 6). The industrialists are usingthe area for producing bricks. Aerial photos show areathat have been dug out and left unreturned to pre-excavation times. These may be areas of soil cuttingor areas where the clay has been dug out for brickmaking. It is possible that they are going to use thearea for a dump or other reason. They may evenpossibly be gravel pits. None the less they are locatedon the sanctuary and should not be tolerated.

Fig. - 6: Industries and brick making factory identifiedfrom satellite images of 2007

vi) Use of wetlands as a municipal waste dump

The city of Guwahati Municipal Authority is incharge of sewer systems and solid waste. They areplanning on using part of the beel for a waste disposalarea. This can create pollution of the groundwater andsurface water making the area inhospitable to localwildlife and foul.

vii)Hunting, trapping and killing of wild birds andmammals within and in the adjoining areas ofDeepor beel

viii)Unplanned fishing practice without controllingmesh size and using water pump, etc.

CONCLUSION

To protect the wetland the railroads totally removedand rerouted but the cost benefit from this mayexceed any financial ability of the region, remove anyareas with dams and put a bridge through thoseregions to allow water to flow to the wetland andconstruct more bridges along the tracks to make itpossible for animals to cross without having to crossthe dangerous tracks. Fences or something similarwould need to be added along the tracks also to keepthe animals from crossing onto the tracks. It may justbe cheaper to reroute the tracks to a more northern

route close to the already established highway that isevident in aerial photos. It is totally unacceptable touse the wetlands as a municipal waste dump. Landdevelopers must be stopped. Any homes that are al-ready there can stay but any further development ofthe area cannot be done. If the encroachment isallowed to continue throughout the region then muchof the animal population will disappear. Some animalscan live side by side with humans but others cannot.This is true the world over. For instance the plainsand hills of North America used to harbor the GrizzlyBear, Bison, Elk, Moose, Mountain Lion, and manyother animals but these animals have since been pushedto the mountains and highland forests. If the industri-alists are going to continue to soil cut the land aroundDeepor Beel then the manner in which they cut thesoil should be done in a more natural way producing amore natural curvy wetland instead of producing largeelongated rectangular pits which are simply scars ofan industrialized society. One positive of their actionsare that they are creating more wetlands and stormcatchments but the way it is done is simplyunpleasing to the eyes and mind. If the above actionsare left unchecked then tourism would probably fallas more and more of the beel becomes filled in.

REFERENCES

1. Convention on wetlands Ramsar, Iran, 1971.strategic plan 1997-2002 adopted by the 6thMeeting of the Conference of the ContractingParties, Brisbane, Australia, 19-27 March 1996.

2. Deka, S. K., Goswami, D. C., 1992. Hydrology,Sediment characteristics and DepositionalEnvironment of Wetlands: A case study of DeeparBil, Assam. Jour. Assam Science Soc., Guwahati,v.34, pp. 62 - 84.

3. Downing, J.A., Prairie, Y.T., Cole, J.J., Duarte,C.M., Tranvik, L.J., Striegl, R.G., McDowell,W. H., Kortelainen, P., Caraco, N.F., Melack, J.M.and Middelburg, J.J., 2006. The global abundanceand size distribution of lakes, ponds, andimpoundments. Limnol. Oceanogr., 51, pp.2388-2397.

4. IPCC on , Climate Change, 2001. The ScientificBasis, Contribution of working group 1 to the thirdassessment report of the intergovernmental panelon climate changes, Cambridge University Press,New York, pp. 524.


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5. Ozesmi, S.L. and Bauer, M.E., 2002. Satelliteremote sensing of wetlands, Wetlands Ecology andManagement, v. 10, pp. 381-402.

6. Patar, K.C., 2005. Preservation of wetlands,Editorial, The Assam Tribune, Guwahati,Saturday, October 1, 2005.

7. Pontius Jr, R. G. and Connors J., 2009. Range ofcategorical associations for comparison of mapswith mixed pixels. Photogrammetric Engineering& Remote Sensing, v. 75, no. 8, pp. 963-969.

8. Prasad, S.N., Ramachandra, T.V., Ahalya, N.,Sengupta, T., Tiwari, A.K., Vijayan V.S. andVijayan L., 2002. Conservation of wetlands ofIndia-a review, Tropical Ecology, v. 43, no. 1,pp. 173-186.

9. Rundqouist, D., Narumalani, S. and Narayanan,R., 2001. A review of wetlands remote sensingand defining new considerations, RemoteSensing Reviews, v. 20, pp. 207-226.

10. Sharma N., Janauer G., Mondal M. S.,Bakimchandra O. and Garg R. D., 2011.Assessing wetland landscape dynamics in theDeepor Beel of Brahmaputra basin using geospatialtools, Asian Journal of Geoinformatics, Specialissue, in press.

11. Verhoest E.C., Miya M. H., Lievens H., BatelaanO., Thomas A., Brendonck L., and Roeck De. E.R., 2008. Remote Sensing and Wetland Ecology:a South African Case Study, Sensors, 8, pp.3542-3556.

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Journal of Indian Water Resources Society - IWRSiwrs.org.in/journal/jul2011/jul_11.pdf · J. Indian Water Resour. Soc., Vol. 31, No.3-4, July-Oct, 2011 42 International Workshop on