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International Journal of Innovative Research in Advanced Engineering (IJIRAE)
Volume 1 Issue 2 (April 2014)
ISSN: 2278-2311 IJIRAE | http://ijirae.com
© 2014, IJIRAE – All Rights Reserved Page - 52
Using Hydrologic and Hydraulic Modeling Water Flow
Simulation in Metamorphic Urban Watershed
Patil Prashant Jaysing
Veermata Jijabai Technological Institute, Mumbai
Prashant.p9300@gmail.com
Chaudhari Pravin S.
Veermata Jijabai Technological Institute, Mumbai
pschaudhari@vjti.org.in
Abstract- Anthropogenic activities result in significantly decrease of surface water quality of aquatic systems in
watersheds. Rivers in a watershed play a major role in assimilating or carrying off municipal and industrial
wastewater and runoff from agricultural land. River inflows contribute main pollutants to most lakes in a watershed,
thereby tending to induce serious ecological and sanitary problems. The aim of this study is to model the rainfall
runoff process and assessment of anthropogenic activity in an urban basin using available software. The land use and
land cover are the most important factors in the analysis in highly urbanized catchments. The present study
concentrates on the flow simulation of Mithi River catchment. The present study simulates the flow in Mithi River
using Storm Water Management Model (SWMM.5).
Keywords: Surface water pollution, Anthropogenic activity, Watershed modeling, SWMM.5
I. INTRODUCTION
Surface water pollution with chemical, physical and biological contaminants by anthropogenic activities is of great
environmental attention all over the world. The constant discharges of domestic and industrial wastewater and seasonal
surface run-off due to the climate all have a strong effect on the river discharge and water quality. However, rivers are the
main water sources for domestic, industrial and agricultural irrigation purposes in a region, river water quality is one of
important factors directly concerning with health of human and living beings. Therefore, it is imperative and important to
have reliable information on characteristics of water quality for effective pollution control and water resource
management. There is a great need to evaluate the river water quality and it is useful in identification of possible factors
caused by natural and anthropogenic activities that influence water systems. [1] Surface water bodies are progressively
subjected to pollution due to anthropogenic activities. In this paper assessed and examined the impact of human activities
on spatial variation in the water quality of Mithi river watershed. [2]
Hence, it is essential to monitor water quality changes in the entire river, but it is tedious, time consuming and
uneconomical. The mathematical models are the alternative way to describe the relation between waste loads and
water bodies, since they allow immediate remediation before problems become prohibitively difficult to solve.
This practice has grown in popularity in recent years and is becoming a common tool for the management of
water resources.[3] For Mithi river study the EPA Storm Water Management Model (SWMM) is a dynamic rainfall-
runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from
primarily urban areas.
A. Objectives of Study
 The aim of this study is to model the rainfall runoff process and assessment of anthropogenic activity in an
urban basin using available software.
 To estimate the quality and quantity of surface flow for different land use pattern using computer model
(SWMM.5) and generate pollutograph.
II. METHODOLOGY
Rainfall runoff plays important role in surface water pollution. Rainfall runoff carries pollutant from watershed
catchment area to river channel. For this purpose rainfall runoff computation is important to know how much discharge
carries by river channel due to rainfall occurring. Due to this rainfall runoff modeling required.
International Journal of Innovative Research in Advanced Engineering (IJIRAE)
Volume 1 Issue 2 (April 2014)
ISSN: 2278-2311 IJIRAE | http://ijirae.com
© 2014, IJIRAE – All Rights Reserved Page - 53
Fig.1: Methodology adopted in the computation of runoff
III. CASE STUDY
The city Mumbai, financial capital of the state of Maharashtra, is situated on the west coast of India. Mumbai city
receives seasonal rainfall for four months, from June to September. Average rainfall is 2500 mm, of which 70 per cent is
during July and August. Mumbai is lined on the west by Arabian Sea and is intercepted by number of creeks (Mahim,
Mahul and Thane creeks), rivers (Mithi, Dahisa, Poisar and Oshiwara rivers, and their tributaries) and a complex nallah
(drain) system.
Mithi river originating at Powai, Mithi river flows through Saki Naka, Safed Pool, around Santacruz airstrip, passing
through thickly populated and industrial area like Jarimari, Bail Bazar, old airport road, Kalina (CST road), Vakola,
Bandra Kurla complex, Dharavi and ends at Mahim creek. It serves as combined sewer for the area carrying sewage as
well as storm water to sea. River bed is narrow in the initial stretch and is about 10 meters wide but at Bandra Kurla
complex it is much wider. The river passes through congested residential colonies including hutments, which let out raw
sewage in the river and also throw garbage in it. Due to this reason, the river bed is full of sludge, garbage and vegetation
growth like Hyacinth in many parts. Cattle sheds in areas like Bail bazar, Jarimari, Andheri Kurla road etc. contribute
animal waste. The do present study SWMM.5 software used for simulating models, SWMM.5 uses catchment area of
Mumbai city, under the effect of Mithi River.
A. Calibration and Validation of Model (Pre Monsoon Time)
For calibration and validation of model land pattern of Mithi river watershed is run for 14 July 2009 rainfall data
and it correlated with observed data of depth on that day. For is correlation hydrologic and hydraulic modeling of Mithi
watershed is done. Land pattern used for calibration and validation of 2013 and the depth of water checked at Pawai
station. Depth observed and simulated depth by SWMM software is correlated with each other.
Where,
x = Observed depth (m)
y = Simulated depth (m)
Correlation coefficient r = 0.87
RAINFALL
DATA
CATCHMENT DATA
CHANNEL
DATA
INFILTRATION MODEL
(GREEN AMPT)
ROUTING MODEL (KINEMATIC MODEL)
OUTPUT DATA
HYDROLIC AND HYDROLOGIC
MODELING
International Journal of Innovative Research in Advanced Engineering (IJIRAE)
Volume 1 Issue 2 (April 2014)
ISSN: 2278-2311 IJIRAE | http://ijirae.com
© 2014, IJIRAE – All Rights Reserved Page - 54
From above graph observed that the simulated and observed depth at Pawai junction is correlated with each
other with correlation coefficient 0.87 it mean that is very good result given by software and its use give good result.
Fig.2 Calibration graph
B. Water Quality Assessment for Dry Weather Flow (Post Monsoon Time)
To find the water quality in dry weather condition for this the water quality are checked at Mithi River. To
check water quality the water samples were collected at two locations, one at Morarjinagar and the other at JVLR Bridge.
Samples were collected at regular interval of one hour. At the same time the water depths were also measured to
understand flow variation in that particular day. Collected sample are checked in laboratory and 5 day BOD determined.
Using these experimental results and simulated model results are compared.
Site 1 (Morarjinagar): Morarjinagar site is first sampling point on Mithi river. From this point water sample collected at
regular interval of one hours. The input data required for simulation of SWMM software is depth of water and water
quality of water in intersected into this node into software.
Site 2 (JVLR Bridge): JVLR bridge point is second point sampling from this point water sampling and depth of water
measured at regular interval of one hour. The simulated result given by software from inserting input data of site 1 is
compare with result obtain at site 2 by field observed depth and laboratory tested BOD.
IV. RESULT AND DISCUSSION
A. Water Depth Observed and Simulated In Dry Weather Flow Condition at JVLR Bridge:
B.
Fig. 3 Result of depth observed and simulated at JVLR Bridge Site by SWMM
International Journal of Innovative Research in Advanced Engineering (IJIRAE)
Volume 1 Issue 2 (April 2014)
ISSN: 2278-2311 IJIRAE | http://ijirae.com
© 2014, IJIRAE – All Rights Reserved Page - 55
Correlation coefficient r = 0.83
C. Water Quality Observed and Simulated In Dry Weather Flow Condition at JVLR Bridge:
Fig.4 Result of BOD observed and simulated at JVLR Bridge Site by SWMM
Correlation coefficient r = 0.65
From above table and graph it is observed that the BOD value of laboratory test and simulated BOD value by
software (SWMM) is same and its result shows a good match with each other with a correlation coefficient of 0.60.
Similarly result of depth observed and depth simulated matches good with correlation coefficient of 0.83.
D. Effect of continuous discharge on BOD:
It is observed that for a continuous discharge of 3m3
/sec from Vihar Lake reduces downstream BOD by 50% at
Morarjinagar and JVLR point. Thus to reduce BOD concentration from Mithi River continues discharge from Vihar lake
is the best option.
Fig.5 Reduced BOD due to continues discharge at Murarjinagar and JVLR
V. CONCLUSION
The model has been applied to the flood simulation of Mithi river urban catchment. The model has been used for the
simulation of the different rainfall intensity, and the different land use pattern. From this model simulation, we get the
calibration and validation with correlation coefficient of 0.87. The model presented here can be effectively used to study
the effect of change in land pattern on river quality and quantity. The model is also used for studying the dry weather
flow condition. It is observed that the simulated and observed result of BOD matches with correlation coefficient 0.65
which is an indication of good result. For same condition depth simulated and observed of water in river channel matches
with good result. In dry weather flow condition it is observed that continuous constant discharge from inlet of 3m3
/sec
International Journal of Innovative Research in Advanced Engineering (IJIRAE)
Volume 1 Issue 2 (April 2014)
ISSN: 2278-2311 IJIRAE | http://ijirae.com
© 2014, IJIRAE – All Rights Reserved Page - 56
value of BOD reduced to half of the original value. Therefore, it can be said that the water quality, during dry weather,
can be improved by releasing continuous discharge from the reservoir.
REFERENCES
1. Deependra Kumar Sinha, Virendra Kumar and Anil Kumar (2013), “Physiochemical qualities of Damoder river water and
turbidity control studies in monsoon season” , Scholars Journal of Engineering and Technology (SJET), Vol. 1(2) pp no. 49-
54
2. WANG Xiao-long, LU Yong-long, HAN Jing-yi, HE Gui-zhen, WANG Tie-yu (2006), “Identification of anthropogenic
influences on water quality of rivers in Taihu watershed” Journal of Environmental Sciences, page no.475-481.
3. Basappa. B. Kori, T.Shashidhar & Shashikanth Mise (2013) Application of automated qual2kw for water quality Modeling
in the river karanja, India - G.J.B.B., VOL.2 (2) 2013 : 193 – 203 Global Journal of Bio-science and Biotechnology
4. Igor A. Shiklomanov(1998),” World water resources a new appraisal and assessment for the 21st century” UNESCO 1998.
5. V. Subramanian (2004), “Water Quality in South Asia”, Asian Journal of Water, Environment and Pollution, Vol. 1, No. 1 &
2, pp. 41-54.
6. Rakesh Kumar, R.D. Shingh, K.D. Sharma (2005), “Water resources of India” Current Science, vol.89, no.5.
7. U.S. Environmental Protection Agency's (EPA) user Manual for SWMM.5
8. Pravin S. Chaudhari, Raj Bharat. Srinivas (2011), “Evaluation of flood mitigation structure on Mithi River using AWS
rainfall and HEC-HMS Model” International Journal of Earth Sciences and Engineering, Vol.4,page no. 315-318.
9. Beling, F.A. Garcia, J.I.B. Paiva, E.M.C.D. Bastos, G.A.P. Paiva, J.B.D(2011), “Analysis of the SWMM Model
Parameters for Runoff Evaluation in Periurban Basins from Southern Brazil” 12nd International Conference on Urban
Drainage, Porto Alegre/Brazil.
10. Cambez, M.J. Pinho, David, L.M (2008). “Using SWMM 5 in the continuous modelling of storm water hydraulics and
quality” 11th International Conference on Urban Drainage, Edinburgh, Scotland, UK.
11. Chaudhari, M. Hanif. (1994). “Open Channel Flow”, Prentice-Hall, U.S.A.
12. Giuseppe De Martino, Francesco De Paola, Nicola Fontana, Gustavo Marini, Antonio Ranucci, (2011), “Pollution Reduction
in Receivers: Storm-Water Tanks” American Society of Civil Engineers.
13. Hormoz Pazwash (2011). “ Urban Storm Water Management”, CRC Press,New York.
14. Javier Temprano, Oscar Arango, Juan Cagiao, Joaquín Suárez, Inaki Tejero(2006), “Stormwater quality calibration by
SWMM: A case study in Northern Spain” Water SA Vol. 32.
15. K. Subramanya (2012). “Engineering Hydrology”, Tata McGraw-Hill, New Delhi.
16. L. Gabriel T. de Azevedo, Timothy K. Gates (2000), “Integration of water quantity and quality in strategic river basin
planning” Journalof Water Resources Planning and Management, Vol. 126, page no. 17387.
17. Ram S. Lokhande, Pravin U. Singare, Deepali S. Pimple(2011), “Study on Physico-Chemical Parameters of Waste Water
Effluents from Taloja Industrial Area of Mumbai, India” International Journal of Ecosystem.
18. S.Rocky Durrans (2003).”Stormwater conveyance modeling and design”, Haestad press, USA.
19. Steve Schreiner, Jodi Dew, Allison Brindley, Morris Perot, Nancy Roth(2006), “Storm water pollutant model for linganore
creek watershed frederick county, maryland” Frederick County Division of Public Works, Maryland.

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Using Hydrologic and Hydraulic Modeling Water Flow Simulation in Metamorphic Urban Watershed

  • 1. International Journal of Innovative Research in Advanced Engineering (IJIRAE) Volume 1 Issue 2 (April 2014) ISSN: 2278-2311 IJIRAE | http://ijirae.com © 2014, IJIRAE – All Rights Reserved Page - 52 Using Hydrologic and Hydraulic Modeling Water Flow Simulation in Metamorphic Urban Watershed Patil Prashant Jaysing Veermata Jijabai Technological Institute, Mumbai Prashant.p9300@gmail.com Chaudhari Pravin S. Veermata Jijabai Technological Institute, Mumbai pschaudhari@vjti.org.in Abstract- Anthropogenic activities result in significantly decrease of surface water quality of aquatic systems in watersheds. Rivers in a watershed play a major role in assimilating or carrying off municipal and industrial wastewater and runoff from agricultural land. River inflows contribute main pollutants to most lakes in a watershed, thereby tending to induce serious ecological and sanitary problems. The aim of this study is to model the rainfall runoff process and assessment of anthropogenic activity in an urban basin using available software. The land use and land cover are the most important factors in the analysis in highly urbanized catchments. The present study concentrates on the flow simulation of Mithi River catchment. The present study simulates the flow in Mithi River using Storm Water Management Model (SWMM.5). Keywords: Surface water pollution, Anthropogenic activity, Watershed modeling, SWMM.5 I. INTRODUCTION Surface water pollution with chemical, physical and biological contaminants by anthropogenic activities is of great environmental attention all over the world. The constant discharges of domestic and industrial wastewater and seasonal surface run-off due to the climate all have a strong effect on the river discharge and water quality. However, rivers are the main water sources for domestic, industrial and agricultural irrigation purposes in a region, river water quality is one of important factors directly concerning with health of human and living beings. Therefore, it is imperative and important to have reliable information on characteristics of water quality for effective pollution control and water resource management. There is a great need to evaluate the river water quality and it is useful in identification of possible factors caused by natural and anthropogenic activities that influence water systems. [1] Surface water bodies are progressively subjected to pollution due to anthropogenic activities. In this paper assessed and examined the impact of human activities on spatial variation in the water quality of Mithi river watershed. [2] Hence, it is essential to monitor water quality changes in the entire river, but it is tedious, time consuming and uneconomical. The mathematical models are the alternative way to describe the relation between waste loads and water bodies, since they allow immediate remediation before problems become prohibitively difficult to solve. This practice has grown in popularity in recent years and is becoming a common tool for the management of water resources.[3] For Mithi river study the EPA Storm Water Management Model (SWMM) is a dynamic rainfall- runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. A. Objectives of Study  The aim of this study is to model the rainfall runoff process and assessment of anthropogenic activity in an urban basin using available software.  To estimate the quality and quantity of surface flow for different land use pattern using computer model (SWMM.5) and generate pollutograph. II. METHODOLOGY Rainfall runoff plays important role in surface water pollution. Rainfall runoff carries pollutant from watershed catchment area to river channel. For this purpose rainfall runoff computation is important to know how much discharge carries by river channel due to rainfall occurring. Due to this rainfall runoff modeling required.
  • 2. International Journal of Innovative Research in Advanced Engineering (IJIRAE) Volume 1 Issue 2 (April 2014) ISSN: 2278-2311 IJIRAE | http://ijirae.com © 2014, IJIRAE – All Rights Reserved Page - 53 Fig.1: Methodology adopted in the computation of runoff III. CASE STUDY The city Mumbai, financial capital of the state of Maharashtra, is situated on the west coast of India. Mumbai city receives seasonal rainfall for four months, from June to September. Average rainfall is 2500 mm, of which 70 per cent is during July and August. Mumbai is lined on the west by Arabian Sea and is intercepted by number of creeks (Mahim, Mahul and Thane creeks), rivers (Mithi, Dahisa, Poisar and Oshiwara rivers, and their tributaries) and a complex nallah (drain) system. Mithi river originating at Powai, Mithi river flows through Saki Naka, Safed Pool, around Santacruz airstrip, passing through thickly populated and industrial area like Jarimari, Bail Bazar, old airport road, Kalina (CST road), Vakola, Bandra Kurla complex, Dharavi and ends at Mahim creek. It serves as combined sewer for the area carrying sewage as well as storm water to sea. River bed is narrow in the initial stretch and is about 10 meters wide but at Bandra Kurla complex it is much wider. The river passes through congested residential colonies including hutments, which let out raw sewage in the river and also throw garbage in it. Due to this reason, the river bed is full of sludge, garbage and vegetation growth like Hyacinth in many parts. Cattle sheds in areas like Bail bazar, Jarimari, Andheri Kurla road etc. contribute animal waste. The do present study SWMM.5 software used for simulating models, SWMM.5 uses catchment area of Mumbai city, under the effect of Mithi River. A. Calibration and Validation of Model (Pre Monsoon Time) For calibration and validation of model land pattern of Mithi river watershed is run for 14 July 2009 rainfall data and it correlated with observed data of depth on that day. For is correlation hydrologic and hydraulic modeling of Mithi watershed is done. Land pattern used for calibration and validation of 2013 and the depth of water checked at Pawai station. Depth observed and simulated depth by SWMM software is correlated with each other. Where, x = Observed depth (m) y = Simulated depth (m) Correlation coefficient r = 0.87 RAINFALL DATA CATCHMENT DATA CHANNEL DATA INFILTRATION MODEL (GREEN AMPT) ROUTING MODEL (KINEMATIC MODEL) OUTPUT DATA HYDROLIC AND HYDROLOGIC MODELING
  • 3. International Journal of Innovative Research in Advanced Engineering (IJIRAE) Volume 1 Issue 2 (April 2014) ISSN: 2278-2311 IJIRAE | http://ijirae.com © 2014, IJIRAE – All Rights Reserved Page - 54 From above graph observed that the simulated and observed depth at Pawai junction is correlated with each other with correlation coefficient 0.87 it mean that is very good result given by software and its use give good result. Fig.2 Calibration graph B. Water Quality Assessment for Dry Weather Flow (Post Monsoon Time) To find the water quality in dry weather condition for this the water quality are checked at Mithi River. To check water quality the water samples were collected at two locations, one at Morarjinagar and the other at JVLR Bridge. Samples were collected at regular interval of one hour. At the same time the water depths were also measured to understand flow variation in that particular day. Collected sample are checked in laboratory and 5 day BOD determined. Using these experimental results and simulated model results are compared. Site 1 (Morarjinagar): Morarjinagar site is first sampling point on Mithi river. From this point water sample collected at regular interval of one hours. The input data required for simulation of SWMM software is depth of water and water quality of water in intersected into this node into software. Site 2 (JVLR Bridge): JVLR bridge point is second point sampling from this point water sampling and depth of water measured at regular interval of one hour. The simulated result given by software from inserting input data of site 1 is compare with result obtain at site 2 by field observed depth and laboratory tested BOD. IV. RESULT AND DISCUSSION A. Water Depth Observed and Simulated In Dry Weather Flow Condition at JVLR Bridge: B. Fig. 3 Result of depth observed and simulated at JVLR Bridge Site by SWMM
  • 4. International Journal of Innovative Research in Advanced Engineering (IJIRAE) Volume 1 Issue 2 (April 2014) ISSN: 2278-2311 IJIRAE | http://ijirae.com © 2014, IJIRAE – All Rights Reserved Page - 55 Correlation coefficient r = 0.83 C. Water Quality Observed and Simulated In Dry Weather Flow Condition at JVLR Bridge: Fig.4 Result of BOD observed and simulated at JVLR Bridge Site by SWMM Correlation coefficient r = 0.65 From above table and graph it is observed that the BOD value of laboratory test and simulated BOD value by software (SWMM) is same and its result shows a good match with each other with a correlation coefficient of 0.60. Similarly result of depth observed and depth simulated matches good with correlation coefficient of 0.83. D. Effect of continuous discharge on BOD: It is observed that for a continuous discharge of 3m3 /sec from Vihar Lake reduces downstream BOD by 50% at Morarjinagar and JVLR point. Thus to reduce BOD concentration from Mithi River continues discharge from Vihar lake is the best option. Fig.5 Reduced BOD due to continues discharge at Murarjinagar and JVLR V. CONCLUSION The model has been applied to the flood simulation of Mithi river urban catchment. The model has been used for the simulation of the different rainfall intensity, and the different land use pattern. From this model simulation, we get the calibration and validation with correlation coefficient of 0.87. The model presented here can be effectively used to study the effect of change in land pattern on river quality and quantity. The model is also used for studying the dry weather flow condition. It is observed that the simulated and observed result of BOD matches with correlation coefficient 0.65 which is an indication of good result. For same condition depth simulated and observed of water in river channel matches with good result. In dry weather flow condition it is observed that continuous constant discharge from inlet of 3m3 /sec
  • 5. International Journal of Innovative Research in Advanced Engineering (IJIRAE) Volume 1 Issue 2 (April 2014) ISSN: 2278-2311 IJIRAE | http://ijirae.com © 2014, IJIRAE – All Rights Reserved Page - 56 value of BOD reduced to half of the original value. Therefore, it can be said that the water quality, during dry weather, can be improved by releasing continuous discharge from the reservoir. REFERENCES 1. Deependra Kumar Sinha, Virendra Kumar and Anil Kumar (2013), “Physiochemical qualities of Damoder river water and turbidity control studies in monsoon season” , Scholars Journal of Engineering and Technology (SJET), Vol. 1(2) pp no. 49- 54 2. WANG Xiao-long, LU Yong-long, HAN Jing-yi, HE Gui-zhen, WANG Tie-yu (2006), “Identification of anthropogenic influences on water quality of rivers in Taihu watershed” Journal of Environmental Sciences, page no.475-481. 3. Basappa. B. Kori, T.Shashidhar & Shashikanth Mise (2013) Application of automated qual2kw for water quality Modeling in the river karanja, India - G.J.B.B., VOL.2 (2) 2013 : 193 – 203 Global Journal of Bio-science and Biotechnology 4. Igor A. Shiklomanov(1998),” World water resources a new appraisal and assessment for the 21st century” UNESCO 1998. 5. V. Subramanian (2004), “Water Quality in South Asia”, Asian Journal of Water, Environment and Pollution, Vol. 1, No. 1 & 2, pp. 41-54. 6. Rakesh Kumar, R.D. Shingh, K.D. Sharma (2005), “Water resources of India” Current Science, vol.89, no.5. 7. U.S. Environmental Protection Agency's (EPA) user Manual for SWMM.5 8. Pravin S. Chaudhari, Raj Bharat. Srinivas (2011), “Evaluation of flood mitigation structure on Mithi River using AWS rainfall and HEC-HMS Model” International Journal of Earth Sciences and Engineering, Vol.4,page no. 315-318. 9. Beling, F.A. Garcia, J.I.B. Paiva, E.M.C.D. Bastos, G.A.P. Paiva, J.B.D(2011), “Analysis of the SWMM Model Parameters for Runoff Evaluation in Periurban Basins from Southern Brazil” 12nd International Conference on Urban Drainage, Porto Alegre/Brazil. 10. Cambez, M.J. Pinho, David, L.M (2008). “Using SWMM 5 in the continuous modelling of storm water hydraulics and quality” 11th International Conference on Urban Drainage, Edinburgh, Scotland, UK. 11. Chaudhari, M. Hanif. (1994). “Open Channel Flow”, Prentice-Hall, U.S.A. 12. Giuseppe De Martino, Francesco De Paola, Nicola Fontana, Gustavo Marini, Antonio Ranucci, (2011), “Pollution Reduction in Receivers: Storm-Water Tanks” American Society of Civil Engineers. 13. Hormoz Pazwash (2011). “ Urban Storm Water Management”, CRC Press,New York. 14. Javier Temprano, Oscar Arango, Juan Cagiao, Joaquín Suárez, Inaki Tejero(2006), “Stormwater quality calibration by SWMM: A case study in Northern Spain” Water SA Vol. 32. 15. K. Subramanya (2012). “Engineering Hydrology”, Tata McGraw-Hill, New Delhi. 16. L. Gabriel T. de Azevedo, Timothy K. Gates (2000), “Integration of water quantity and quality in strategic river basin planning” Journalof Water Resources Planning and Management, Vol. 126, page no. 17387. 17. Ram S. Lokhande, Pravin U. Singare, Deepali S. Pimple(2011), “Study on Physico-Chemical Parameters of Waste Water Effluents from Taloja Industrial Area of Mumbai, India” International Journal of Ecosystem. 18. S.Rocky Durrans (2003).”Stormwater conveyance modeling and design”, Haestad press, USA. 19. Steve Schreiner, Jodi Dew, Allison Brindley, Morris Perot, Nancy Roth(2006), “Storm water pollutant model for linganore creek watershed frederick county, maryland” Frederick County Division of Public Works, Maryland.