Environmental aspects of the reuse of treated wastewater ... · Donatella Caniani, Environmental aspects of the reuse of treated wastewater: impact on water quality in river systems,

Workshop Wastewater REUSE

From the research to the technological transfer within the Mediterranean

Potenza, April 29-30 2013

Environmental aspects of the reuse of treated wastewater: impact on

water quality in river systems

Donatella Caniani, Salvatore Masi, Ignazio M. Mancini, Carmen Lavinia

Donatella Caniani, Environmental aspects of the reuse of treated wastewater: impact on water quality in river systems, Potenza 29-30 April 2013

Aridity affects large areas of the globe, i.e. 41% of the planet's land surface. Currently, dry regions are home to about 2.1 billion people. Recent studies show that by 2050, 2.3 billion more people than today are projected to live in river basins experiencing severe water stress (European Innovation Partnership Water, Strategic Implementation Plan).

• Moreover, the Mediterranean Region, which comprises a transition between dry-sub-humid regions of northern croplands to hyper-arid southern desert (Saharan-Arabian deserts), is recognised among those most affected by drought that can speed up land degradation.

World map of aridity zones © CRU / UEA, UNEP / DEWA


• The consequences are rapid reduction of usable arable lands, quick decrease of the land productivity, widespread ecosystem degradation and, in turn, higher risk of desertification.

• Desertification is a common threat to the Mediterranean basin. It is estimated that at least 11% of the EU population and 17% of its territory have been affected by water scarcity to date.

• Moreover, as reflected by the Blueprint to safeguard Europe's water resources, almost half of Europe’s freshwaters are at risk of not achieving good ecological status, the main objective of the EU Water Framework Directive by 2015, with adverse effects on biodiversity and public health.


• Water recycling and reuse should be considered as the core of an integrated water management approach to save costs, recover materials and demonstrate environmental stewardship.

• The use of non-conventional water resources, through recycling and reuse of water, helps to provide water in a safe, available and affordable way, reducing energy consumption, costs of treatment, and environmental impacts. The reuse of water, therefore, is an essential component in the sustainable management of water.


The main objective of the present work aims at demonstrate how the reuse of wastewater may have, among other positive effects, also the improvement of the quality of surface waters, by the subtraction of the polluting loads that do not reach surface water.

In order to achieve this objective, a scenario analysis was carried out to evaluate the water quality at the river basin scale of the main rivers of the Region of Basilicata (Southern Italy).

We developed a new methodology, valid for every kind of basin and based on three hydrological regimes, to estimate the response of the rivers, under each management scenario and so obtain the environmental water quality status for the actual river conditions and after the measures of mitigation.


At national and international level, there are interesting applications of scenario analysis by modelling. The QUAL2E model is the most widely applied by environmental agencies around the world for studying water quality and is used in different settings for different parameters (Marsili-Libelli et al., 2004; Muhammetoglu et al., 2005; Azzellino et al., 2006; Salvetti et al., 2006; Paliwal et al., 2007).

Marsili-Libelli et al. (2004) adopt the Drivers-Pressures-States-Impacts-Responses (DPSIR) model introduced by the WFD. The study proposes the construction of an integrated software tool whereby current quality data can be used to produce quality scenarios and apply the DPSIR model. The study is conducted at a river basin scale (seasonal scenarios are considered) and the MPL parameter is evaluated.

Azzellino et al. (2006) and Salvetti et al. (2006) apply the QUAL2E and the SWAT models to evaluate the source apportionment of river pollution as required from the WFD. Dry and wet scenarios are considered to evaluate river flow conditions without the analysis of the average flow period.

In the work of Azzellino et al. (2006), a sort of calibration is obtained by feeding the model with indirect estimates of input loads and by comparing simulated data of flow and water quality parameters with median trend of the measures. The calculation of median is chosen for the distribution skewness of the water quality measurements. The simulation corresponds roughly to consider the dry weather conditions and allows grossly the validation.


The QUAL2E model was calibrated for the dry season to simulate BOD and DO profiles for a stretch of the river Yamuna.Two sets of data are used for calibration and validation for the low flow period (Paliwal et al., 2007).

In the scenario analysis the identified interventions can cover point sources and diffuse sources of water pollution (Kronvang et al., 1999; Muhammetoglu et al., 2005; Kneis et al., 2006; Marsili-Libelli and Giusti, 2008) or only point sources (Marsili-Libelli et al., 2004; Xenarios and Bithas, 2007; Paliwal et al., 2007) or only diffuse sources, as in many studies that are focused on scenario analysis to evaluate different land use management alternatives (Coiner et al., 2001; Vaché et al., 2002; Kersebaum et al., 2003; Nassauer and Corry, 2004; Santelmann et al., 2004; Jessel and Jacobs, 2005; Kersebaum et al., 2006; Bongartz et al., 2007; Volk et al., 2007).


suitable to the study of stream water quality

that not correspond necessary to seasons and cover different periods of the year, in dependence on climatic conditions

Analysis applied

to five river basins

This allowed a validation of the environmental models

Evaluation for each studied river of three hydrological

conditions (low, medium and high flows)

Analysis conducted at a river basin scale


The Region of Basilicata is characterised by a complex hydrographic network focused on five main rivers called: Bradano, Basento, Cavone, Agri and Sinni, flowing into the Ionic Sea and whose basins cover about 70% of the regional territory.

Basento

Bradano

Cavone

Agri

Sinni The hydrology of Basilicata river basins ensures a good availability of water resources, which are accumulated in several reservoirs. The supply sources are able to ensure an annual availability of about 1 billion of m3. The water resource is shared by several uses: drinking, irrigation, hydroelectric and in small part industry.


It is interesting to observe the measured and actual ecological status of the rivers, as indicated by the biological indicators and macrodescriptors. The north-eastern rivers Bradano, Basento and Cavone are in the worst conditions with bad and poor ecological status

ü High ecological status üGood ecological status üModerate ecological status üPoor ecological status üBad ecological status

Basento

Bradano

Cavone

Agri

Sinni


Soil and Water Assessment Tool (SWAT) model (Di Luzio et al., 2002), which simulates the water, pollutants and sediment contributions at the basin scale and is used to estimate agricultural, livestock and tributaries loads. The SWAT model outputs were used as inputs to QUAL2K model. River water quality model QUAL2K (Chapra et al., 2006)


SWAT

The SWAT model (Neitsch et al., 2001) is a semi-distributed and continuous time model that operates on a daily time step to estimate the effects of water management and pollutant releases in stream systems.

SWAT allows modelling the entire process of the hydrological cycle, including rainfall, evapo-transpiration, water withdrawls, and groundwater recharge.

The model allows the subdivision of watersheds into smaller subwatersheds, which are then subdivided into multiple Hydrologic Response Units (HRUs) that create separate and unique combinations of soil and land cover properties in subbasins.


The Cavone basin has the modest extension of 675 km2 and is 49 km long . The morphology is hilly with the exception of the mountainous upper part and the eastern portion. Summer outflows are close to zero, due to the scarce rainfalls and the lack of wellsprings.


Input data

DEM

River network

Land cover

Pedology

Climatic time series

Hydrografic basin

HRUs definition

SWAT Database

Parametrization

Calibration RUN

SWAT Model

Output tables and graphs

Output Maps

ArcGIS


Rainfall Temperatures (max and min) Evapotranspiration Wind velocity Relative humidity Solar radiation

SWAT is provided with a weather generator that allows to simulate long periods even if not covered by observations

Terra Mont.

Cavone SS106

Craco Peschiera

Torre Accio

Tursi

Stigliano


Used to evaluate the concentrations of macrodescriptors along the river through equations that describe the development of chemical, biological and physical processes

The major hypotesis of the QUAL2K model are:

• monodimensional hydraulic network;

• steady state;

• daily heat budget;

• daily kinetics of the water quality descriptors;

• subdivision of the contaminant loads in point sources (wastewater

treatment plants)

• and diffuse sources (agricultural and livestock loads).

The outputs provided by the SWAT model were used as diffuse source of pollution inputs to the QUAL2K model

MODEL SEGMENTATION.

QUAL2K segments the system into river reaches, which, in turn, are

subdivided into discrete elements, considered as completely mixed reactors,

with uniform hydraulic, geometrical and biochemical characteristics


Mass balance

The balance is valid for every river element with the hypothesis of steady state (∂C/∂t = 0).

where: Ax is the cross-sectional area (m2) DL is the diffusion coefficient (m2/s) C is the concentration of the considered parameter (kg/m3) u is the mean flow speed (m/s) s are the sources and/or losses of the parameter due to reactions and transport mechanisms (kg/s) V is the volume (m3).

Graphical representation of the equations used in the model QUAL2K

01 )()(1 =++- ¶××¶

×¶¶¶

××¶×

Vs

dtdC

A xCuAx

xx

xCDLAx

Ax

Kinetic processes are dissolution (ds), hydrolysis (h), oxidation (ox), nitrification (n), denitrification (dn), photosynthesis (p), respiration (r), excretion (e), death (d), respiration/excretion (rx). Mass transfer processes are reaeration (re), settling (s), sediment oxygen demand (SOD), sediment exchange (se), and sediment inorganic carbon flux (cf).

K2

Dissolved oxygen

Algae

s1

a3m

a2r

P-disc

P-org

a2m

s2

s5

a4r

SOD

CBOD

K4

K1 K3

Norg s4

b3

NH4 s3

NO2

NO3

b1

b2

a5b1

a6b2

a1r

a1m

a 1(F

)

a1(1-F)

b4

Aeration



Input data to QUAL2K

Outflow

Diffuse pollutant loads

Wastewater treatment plants

Calculated with SWAT Low flow regime

High flow regime

Medium flow regime

0

50

100

150

200

250

0 50 100 150 200 250 300 350

Tempo (giorni)

Po

rtate

(m

3/s

)

=0.3 m=3.3 m

=44.9 m3/s

Flow Duration Curves or flow monthly data in the sampling stations provided by the Basin Authority of the Basilicata region (AdB, 2006) were analysed to calculate the duration of the hydrological regime in the year and the headwater characteristic flow


Diffuse pollutant loads

This loads were calculated with SWAT for each of the three hydrological regimes: - Low flow - Medium flow - High flow

Sub

CBOD Organic Ammon Nitrate Organic Inorganic Diffuse

fast N N N P P Inflow Detritus

mgO2/L mgN/L mgN/L mgN/L mgP/L mgP/L m3/s mgD/L

1 0.0000 0.0000 19.9801 0.0000 0.0000 2.8797 0.0051 0.0138

2 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0023 0.0216

3 0.0000 0.0000 19.9866 0.0000 0.0000 2.8162 0.0214 0.0125

4 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0038 0.0115

5 0.0000 0.0000 8.4742 0.0000 0.0000 1.1651 0.0269 0.0127

6 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0051 0.0095

7 0.0000 0.0000 11.8426 0.0000 0.0000 3.1884 0.0341 0.0135

8 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0067 0.0091

9 0.0000 0.0000 10.4477 0.0000 0.0000 1.2079 0.0440 0.0133

10 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0014 0.0271

11 0.0000 0.0000 0.0000 13.5184 0.0000 0.6533 0.0537 0.0186

12 0.0000 0.0000 17.9362 0.0000 0.0000 2.2984 0.0578 0.0137

13 0.0000 0.5272 40.3959 393.7232 0.6463 688.010 0.0317 0.0071

14 0.0000 0.0000 16.0839 0.0000 0.0000 1.6084 0.0910 0.0116

15 0.0000 0.5703 39.9414 399.3196 0.8544 6.3503 0.0123 0.0044

16 0.0000 0.0000 0.0000 14.1280 0.0000 1.0542 0.1065 0.0110

17 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

18 0.0000 0.0000 9.6869 0.0000 0.0000 0.9163 0.1061 0.0115

19 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0037 0.0117


SENSITIVE AREAS

Sesitive areas cover about 50% of the territory. 92 WWTPs are located and dischardge in sensitive areas · There are 252 · WWTPs. The inputs loads for a wastewater treatment plant are evaluated considering a per capita contribution equal to: •150 gr/Ehs d for chemical oxygen demand (COD); •13 gr/Ehs d for total nitrogen; •2 gr/Ehs d for total phosphorus.


The following reduction percentages for pollutants were considered: : 90% BOD 95% COD 50% TN 25% TP

Actual situation

WWTPs


Simulation from the 1st of January 1996 to the 31st of December 2006

Calibration period From the 1st of January 2001 To the 31st of December 2004

Validation period From the 1st of January 2005 To the 31st of December 2006

-50

0

50

100

150

200

250

300

10/1/2000 4/19/2001 11/5/2001 5/24/2002 12/10/2002 6/28/2003 1/14/2004 8/1/2004 2/17/2005 9/5/2005

Tempo (giorni)

Port

ata

(mc/

s)

Deflussi osservatiDeflussi simulati

observed simulated


DO_magra

0

2

4

6

8

10

12

14

020406080

Km

DO_m

g/l

curva_taratura

misura+intervallo_confidenza_CVRR01


DO

0

2

4

6

8

10

12

0102030405060708090 km

BO

D_m

g/l

curva_taratura



BOD

0

500

1000

1500

2000

2500

3000

0102030405060708090 km

NH

4_m

icro

g/l

curva_taratura



0

2000

4000

6000

8000

10000

12000

0102030405060708090 km

NO

3_m

icro

g/l

curva_taratura



0

200

400

600

800

1000

1200

1400

0102030405060708090 km

Ptot

_mic

rog/

l

curva_taratura



NH4 NO3 TP

The QUAL2K model was calibrated for the actual scenario and the low flow regime varying the coefficients that regulate chemical variables so that the daily mean trend of the macro-descriptors interpolates the mean value of monthly samplings regarding the low flow, in the quality monitoring stations of ARPAB. In addition to the mean sampling value, the confidence interval expressed as standard deviation from the mean value is reported


The validation procedure of the model was made considering the actual scenario and the average and high flow conditions.

DO_piena

0

2

4

6

8

10

12

14

020406080Km

DO_m

g/l

curva_taratura



BOD_piena

0

1

2

3

4

5

6

7

0102030405060708090 km

BO

D_m

g/l

curva_taratura



NH4_piena

0

200

400

600

800

1000

1200

1400

0102030405060708090 km

NH

4_m

icro

g/l

curva_taratura



Ptot_piena

0

100

200

300

400

500

600

700

020406080 kmPt

ot_m

icro

g/l

curva_taratura




A set of management scenarios was defined for each river basin. The “zero option” represents the actual situation. The SWAT and the QUAL2K models were used to simulate the system’s response for each scenario, during the low flow, medium flow and high flow regimes.

Cavone basin

Flow regime low, medium

Scenario 1 all wastewater treatment plants work and imposition of concentration limit for BOD, (plants with EHs >2000)

Scenario 2 validity of scenario 1 and addition of a consortium plant that includes the wastewater treatment plants of Accettura, San Mauro Forte, Stigliano and Oliveto Lucano and imposition of concentration limit for BOD of the consortium plant

Scenario 3 validity of scenarios 1 and 2 and TWW reuse for the plants with EHs>2000 (included consortium plant)

Scenario 4 validity of scenarios 1 and 2 and 3 and addition of a consortium plant for Garaguso and reuse of its TWW

Flow regime high

Scenario 1 all wastewater treatment plants work and imposition of concentration limit for BOD, (plants with EHs >2000)

Scenario 2 validity of scenario 1 and addition of a consortium plant that includes the wastewater treatment plants of Accettura, San Mauro Forte, Stigliano and Oliveto Lucano and imposition of concentration limit for BOD of consortium plant and addition of a consortium plant for Garaguso


The graphs show an example of the outputs obtained along the river from the QUAL2K model for 5 different scenarios, during low flow regime, and for BOD5, NO3, Ammonium. The fourth scenario involves the reuse of all wastewater during periods of low flow. The same procedure was repeated for all watersheds and all flow regimes.

BOD_MAGRA

0

2

4

6

8

10

12

020406080x

(Km)

BOD (mg/l) limite_stato_buonoscenario_attualescenario_1scenario_2scenario_3scenario_4

BOD (low flow) NO3_MAGRA

0

1000

2000

3000

4000

5000

6000

0102030405060708090x

(Km)

NO3 (mg/l)

limite_stato_buonoscenario_attualescenario_1scenario_2scenario_3scenario_4

NO3 (low flow) NH4_MAGRA

0

500

1000

1500

2000

2500

3000

020406080x

(Km)

NH4 (mg/l) limite_stato_buonoscenario_attualescenario_1scenario_2scenario_3scenario_4

NH4 (low flow)


In order to select the best scenario, the following model of multi-criteria analysis has been developed. The main challenge in ranking management scenarios is the bias preservation. In order to achieve this, it is necessary to obtain the criteria weighs in an unbiased way, before multi-criteria analysis is performed.

The fundamental elements of the proposed method are: • the decision matrix, • the entropy based method used to weight criteria • the technique used to select the best scenario


nmnnn

m

m

m

m

rrrS

rrrSrrrSCCCwww

M

........

..

..

..)..(

21

222212

112111

21

21

=

S = scenarios C = criteria (environmental impact indices of the river water quality) w = weighs of criteria rij = scores obtained by the scenarios with respect to the different criteria n is the number of criteria and m is the number of scenarios


In literature, there are several useful criteria, such as “law criteria”, that enable to evaluate the concentration shift of the river water quality parameters from the threshold values, criteria that concern the shift of the maximum or the mean value, criteria based on the law threshold level shift, etc. Weaknesses: These indexes do not take into account the cases in which all or some of the simulations produce output values always lower than the values of legislation. They also do not take into account the duration and, therefore, the extent of the episode.


0

100

200

300

400

500

600

700

020406080 km

Ptot

_mic

rog/

l

curva_taratura



In order to take into account the entity and the duration of the possible water quality alteration, integral indexes have been developed. The integral indexes can be obtained by calculating the area under the curve that represents the evolution of the water quality parameters concentration along the river. Therefore, this environmental impact indicators have a double role: measuring the effects of scenarios and serving as criteria for ranking scenarios in the multi-criteria analysis.


Entropy is generally considered as an uncertainty measure. Considering the scores of the scenarios as emitters of information about the relative importance of each criterion, the entropic method allows the evaluation of each information source and the assessment of criteria weighs (w1, w2, …, wm).

nirrxn

kkjijij ,...2,1,

1

1=ú

û

ùêë

é=

-

=å

additive normalization nmnn

m

m

xxx

xxxxxx

X

............

..

..

21

22221

11211

=


Information contained in the matrix X is considered to be the emission power of each criterion and it can be used to estimate the entropy value ej:

mjxxken

iijijij ,...2,1,ln

1=-= å

=

Entropy

where the constant, k = 1/ln(m), guarantees that:

10 ££ je


The divergence of information of each criterion can be calculated using the following equation:

.,...,2,1,1 mjef jj =-=

Degree of divergence

It implies that the higher is the divergence, fj the more important is the relative criterion for the analyzed problem. Therefore, if all alternatives will obtain similar scores for a given criterion, this criterion will have less weight.


An additive normalization will give the final weights of all criteria

.,...,2,1,1

1mjffw

m

kkjj =úû

ùêë

é=

-

=å

Weights of criteria

The entropy method can be defined as an objective method, since the weighs of criteria are obtained from the decision matrix. The procedure used for retrieving the best scenario is as ‘ideal-point’ method that consists in defining it as the one that shows the shortest distance from the “ideal” solution and the longest distance from the “negative ideal” solution.


Cavone basin Best scenario

Flow regime low, medium

Scenario 4 imposition of concentration limit for BOD, addition of a consortium plant that includes the wastewater treatment plants of Accettura, San Mauro Forte, Stigliano and Oliveto Lucano, TWW reuse for the plants with EHs>2000 (included consortium plant) and addition of a consortium plant for Garaguso and reuse of its TWW

Flow regime high

Scenario 2 imposition of concentration limit for BOD and addition of a consortium plant that includes the wastewater treatment plants of Accettura, San Mauro Forte, Stigliano and Oliveto Lucano and imposition of concentration limit for BOD of consortium plant and addition of a consortium plant for Garaguso


•The worst qualitative conditions emerge for Bradano basin, Cavone and Basento river basins, Agri is in an intermediate condition, Sinni basin has the best situation. •Concerning the actual condition, on all basins, the macro-descriptor which has the worst environmental status is ammonia-N then total phosphorus and dissolved oxygen, BOD has the best condition. •Bradano is far from natural conditions especially with regard to ammonia-N, total phosphorus and BOD, although BOD reaches the good status for medium and high flow. Dissolved oxygen has, in general, the better condition with the prevalence of the moderate status. •Cavone river shows the greater problems related to ammonia-N and total phosphorus, BOD follows. Dissolved oxygen shows the favourite conditions with the attainment of the good environmental status for medium and high flow. •The Sinni river presents a satisfactory condition with the achievement of environmental quality objective for BOD along all the river, dissolved oxygen, ammonia-N and total phosphorus.


•The multi-criteria analysis allowed us to highlight which integral index is the most important criterion • NH4 integral index appears to be moderately important in all the river flow regimes and for all the rivers. •In the case of low flow regimes, for Bradano river, DO is the most important parameter, with the highest weight. While, for the Sinni river, the most important criteria are BOD and DO respectively. •In the case of medium flow regimes, the Cavone river has the same behavior, while for Bradano the most important criterion is BOD. •For the Basento river, for medium and high flow regimes, the NH4 integral index appears to be the most important criterion. For the low flow regime, the weights of all the criteria are similar.


•The suggested interventions for Agri basin are: the operation of all wastewater treatment plants, the enforcement of discharge limits in sensitive areas, the application of the code of good agricultural practice, the wastewater reuse and the release of a greater flow downstream of the dams. •To improve the qualitative and quantitative conditions of Bradano it is necessary that all the wastewater treatment plants work correctly, the TWW reuse, the respect of agricultural good practice and the release of greater flow by dams. •In the Cavone basin it is necessary that all wastewater treatment plants work in order to obtain concentrations of BOD below the threshold values for WWTPs, the wastewater reuse, the construction of consortium plants that achieve the reduction of management costs and depurative efficiencies unreachable with small plants. •For Sinni it is necessary that all wastewater treatment plants work and upstream the TWW reuse. •By establishing a scale of priorities, rivers that require protection interventions more urgent are in order: Bradano, Basento, Cavone, Agri and Sinni.


•For each river the different behaviour of water quality parameters in dependence on hydrological regime emerged. Therefore, the regime distinction was crucial for understanding the preliminary river environmental quality status. •In general for Basilicata basins the greater pollution is produced from ammonia-N. BOD meets the environmental quality objective several times, changing hydrological regimes. •The results demonstrate how the reuse of wastewater helps the improvement of the quality of surface waters, by the subtraction of the polluting loads that do not reach surface water.



( )å=

----+=t

igwseepasurfdayt QwEQRSWSW

10

SWt : contenuto finale di acqua nel suolo [mm H2O]

SWo :contenuto iniziale di acqua nel suolo giornaliero [mm H2O]

T : tempo [giorni]

Rday : ammontare della precipitazione nel giorno i-esimo [mm H2O]

Qsurf : ammontare del deflusso superficiale nel giorno i-esimo [mm H2O]

Ea : ammontare dell'evapotraspirazione nel giorno i-esimo [mm H2O]

Wseep : ammontare di acqua entrata nella zona vadosa dal profilo del suolo nel giorno i-esimo

[mm H2O]

Qgw :ammontare del flusso di ritorno nel giorno i-esimo [mm H2O]


( )( )SIR

IRQ

aday

adaysurf +-

-=

2 procedimento del Curve Number dell’SCS (Soil Conservation Service)

S

TERMINE DESCRIZIONE DIMENSIONE

Qsurf Ammontare del deflusso o

eccesso di pioggia mm H2O

Rday Altezza di pioggia giornaliera mm H2O

Ia

sottrazione iniziale che include: immagazzinamento superf., intercezione, e infiltrazione

prima del deflusso

mm H2O

S parametro di ritenzione

÷øö

çèæ -×= 1010004,25

CNS


• Introduction • Objective • Materials and Methods: Scenario analysis at

river basin scale • Entropic method of multicriteria analysis • Results • Conslusion


Bradano basin Best scenario

Upstream

Flow regime low

Scenario 3 TWW reuse for all wastewater treatment plants

Flow regime medium

Scenario 3 TWW reuse for all wastewater treatment plants

Flow regime high

Scenario 1 all wastewater treatment plants working

Downstream

Flow regime low

Scenario 2 TWW reusefor all wastewater treatment plants

Flow regime average

Scenario 2 for all wastewater treatment plants

Flow regime high

Scenario 1 all wastewater treatment plants working

Documents

Environmental aspects of the reuse of treated wastewater ... · Donatella Caniani, Environmental aspects of the reuse of treated wastewater: impact on water quality in river systems,