SlideShare a Scribd company logo
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.

More Related Content

PDF
An33233237
PDF
Status of Heavy metal pollution in Mithi river: Then and Now
PDF
EVALUATION OF IRRIGATION APPLICATION EFFICIENCY: CASE STUDY OF CHANCHAGA IRRI...
PDF
Abrha mulu article 1
PDF
Suitability Assessment of Shallow Groundwater of a Typical Coastal Aquifers f...
PDF
Assessment of Water Quality of Lakes for Drinking and Irrigation Purposes in ...
PDF
Correlation Study For the Assessment of Water Quality and Its Parameters of G...
PDF
Assessing groundwater quality with special reference to the human, agricultur...
An33233237
Status of Heavy metal pollution in Mithi river: Then and Now
EVALUATION OF IRRIGATION APPLICATION EFFICIENCY: CASE STUDY OF CHANCHAGA IRRI...
Abrha mulu article 1
Suitability Assessment of Shallow Groundwater of a Typical Coastal Aquifers f...
Assessment of Water Quality of Lakes for Drinking and Irrigation Purposes in ...
Correlation Study For the Assessment of Water Quality and Its Parameters of G...
Assessing groundwater quality with special reference to the human, agricultur...

What's hot (17)

PDF
Assessment of Canal Sediments for Agricultural Uses - JBES
PDF
Assesment of surface water quality in the vicinity of an industrial area near...
PDF
Regression models for prediction of water quality in krishna river
PDF
Simulation of Contamination of Groundwater Using Environmental Quality Model
PDF
IRJET- Assessment of Spatial Variations of Water Quality Index of Deepor Bee...
PPTX
Water pollution
PDF
Guj sw monitoring water quality fluctuation in the river sabarmati
PDF
Paper with Jutosana-IJES
PDF
Ep35806817
PDF
IRJET- Study and Analysis of Changes in Water Quality of Gomti River at diffe...
PDF
K41036370
PDF
Trace metals contamination of groundwater in and around tannery industrial ar...
PDF
Ensink et al 2009 musi water qual infrastruc ids
PDF
C04503031040
PDF
Tank model to see the effect of land use changes on runoff, infiltration and ...
PDF
G046405057
PDF
Growing Okra with Drip Fertigation- A Review
Assessment of Canal Sediments for Agricultural Uses - JBES
Assesment of surface water quality in the vicinity of an industrial area near...
Regression models for prediction of water quality in krishna river
Simulation of Contamination of Groundwater Using Environmental Quality Model
IRJET- Assessment of Spatial Variations of Water Quality Index of Deepor Bee...
Water pollution
Guj sw monitoring water quality fluctuation in the river sabarmati
Paper with Jutosana-IJES
Ep35806817
IRJET- Study and Analysis of Changes in Water Quality of Gomti River at diffe...
K41036370
Trace metals contamination of groundwater in and around tannery industrial ar...
Ensink et al 2009 musi water qual infrastruc ids
C04503031040
Tank model to see the effect of land use changes on runoff, infiltration and ...
G046405057
Growing Okra with Drip Fertigation- A Review
Ad

Viewers also liked (17)

PDF
Info swmm sustain_infoswmm_2d_and_swmm_live
PDF
Dialnet analisis espaciotemporalconsig-delruidoambientalurba-1387222
PDF
5th RNA-Seq San Francisco Agenda
PDF
TEDx Raval 3 de mar 2012 @efernandez 15min short web
PPTX
State of Blockchain Q4 2016
PPTX
The Next Generation of AI and Deep Learning - GTC17
PDF
Low impact development_coupled_with_floodplain_mitigation
PPTX
Proyecto de intervención parte 1
PPT
PRESENTACIÓN DEL PROYECTO
PDF
Clase 1 de proyectos de investigación (1)
PPTX
Defining Data Protection in the Cloud 디지탈링스
PPTX
25 Years of Thieves!
PPT
Lets learn unit 11
PDF
Voedingswaarde Check
PDF
Engage Clients Meaningfully in the Process Of Design
PPT
PPTX
UTM_SWMM_KAMAL
Info swmm sustain_infoswmm_2d_and_swmm_live
Dialnet analisis espaciotemporalconsig-delruidoambientalurba-1387222
5th RNA-Seq San Francisco Agenda
TEDx Raval 3 de mar 2012 @efernandez 15min short web
State of Blockchain Q4 2016
The Next Generation of AI and Deep Learning - GTC17
Low impact development_coupled_with_floodplain_mitigation
Proyecto de intervención parte 1
PRESENTACIÓN DEL PROYECTO
Clase 1 de proyectos de investigación (1)
Defining Data Protection in the Cloud 디지탈링스
25 Years of Thieves!
Lets learn unit 11
Voedingswaarde Check
Engage Clients Meaningfully in the Process Of Design
UTM_SWMM_KAMAL
Ad

Similar to Using Hydrologic and Hydraulic Modeling Water Flow Simulation in Metamorphic Urban Watershed (20)

PDF
Cimahi river benchmarking flood analysis based on threshold of total rainfall
PDF
ASSESSMENT OF FLOOD MITIGATION MEASURE FOR MITHI RIVER – A CASE STUDY
PDF
Regression models for prediction of water quality in krishna river
PDF
Assessment of the Upstream Water Quality of a Narrow River using Numerical Mo...
PDF
HYDROLOGICAL AND WATER QUALITY MODELLING USING SWAT FOR DONI RIVER
PDF
A REVIEW ARTICLE ON IMPACT OF URBANIZATION ON HYDROLOGICAL PARAMETERS
PDF
Best Fit and Selection of Probability Distribution Models for Frequency Analy...
PDF
POLLUTION ABATEMENT OF MEENACHIL RIVER IN KOTTAYAM DISTRICT
PPTX
Coupling of Surface water and Groundwater Models
PDF
IRJET- Rainfall-Runoff Analysis of the Watershed for River AIE
PDF
Assessing Anthropogenic Impact on Water Quality in the Musi River: A Study of...
PDF
IRJET- Hydrodynamic Integrated Modelling of Basic Water Quality and Nutrient ...
PDF
Morphometric Analysis of Indrayani River Basin using Remote Sensing and GIS T...
PDF
IRJET-Water Quality of River Basin Context in Maharashtra Region
PDF
Performance evaluation of sprinkler irrigation system in Matimba irrigation s...
PDF
An33233237
PDF
ASSESSING THE EFFECTS OF SPATIAL INTERPOLATION OF RAINFALL ON THE STREAMFLOW ...
PDF
IRJET- GIS based Quantitative Morphometric Analysis of Warna Watershed, Mahar...
PDF
Pollution Status of Mithi River
Cimahi river benchmarking flood analysis based on threshold of total rainfall
ASSESSMENT OF FLOOD MITIGATION MEASURE FOR MITHI RIVER – A CASE STUDY
Regression models for prediction of water quality in krishna river
Assessment of the Upstream Water Quality of a Narrow River using Numerical Mo...
HYDROLOGICAL AND WATER QUALITY MODELLING USING SWAT FOR DONI RIVER
A REVIEW ARTICLE ON IMPACT OF URBANIZATION ON HYDROLOGICAL PARAMETERS
Best Fit and Selection of Probability Distribution Models for Frequency Analy...
POLLUTION ABATEMENT OF MEENACHIL RIVER IN KOTTAYAM DISTRICT
Coupling of Surface water and Groundwater Models
IRJET- Rainfall-Runoff Analysis of the Watershed for River AIE
Assessing Anthropogenic Impact on Water Quality in the Musi River: A Study of...
IRJET- Hydrodynamic Integrated Modelling of Basic Water Quality and Nutrient ...
Morphometric Analysis of Indrayani River Basin using Remote Sensing and GIS T...
IRJET-Water Quality of River Basin Context in Maharashtra Region
Performance evaluation of sprinkler irrigation system in Matimba irrigation s...
An33233237
ASSESSING THE EFFECTS OF SPATIAL INTERPOLATION OF RAINFALL ON THE STREAMFLOW ...
IRJET- GIS based Quantitative Morphometric Analysis of Warna Watershed, Mahar...
Pollution Status of Mithi River

More from AM Publications (20)

PDF
DEVELOPMENT OF TODDLER FAMILY CADRE TRAINING BASED ON ANDROID APPLICATIONS IN...
PDF
TESTING OF COMPOSITE ON DROP-WEIGHT IMPACT TESTING AND DAMAGE IDENTIFICATION ...
PDF
THE USE OF FRACTAL GEOMETRY IN TILING MOTIF DESIGN
PDF
TWO-DIMENSIONAL INVERSION FINITE ELEMENT MODELING OF MAGNETOTELLURIC DATA: CA...
PDF
USING THE GENETIC ALGORITHM TO OPTIMIZE LASER WELDING PARAMETERS FOR MARTENSI...
PDF
ANALYSIS AND DESIGN E-MARKETPLACE FOR MICRO, SMALL AND MEDIUM ENTERPRISES
PDF
REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS
PDF
EVALUATE THE STRAIN ENERGY ERROR FOR THE LASER WELD BY THE H-REFINEMENT OF TH...
PDF
HMM APPLICATION IN ISOLATED WORD SPEECH RECOGNITION
PDF
PEDESTRIAN DETECTION IN LOW RESOLUTION VIDEOS USING A MULTI-FRAME HOG-BASED D...
PDF
INTELLIGENT BLIND STICK
PDF
EFFECT OF SILICON - RUBBER (SR) SHEETS AS AN ALTERNATIVE FILTER ON HIGH AND L...
PDF
UTILIZATION OF IMMUNIZATION SERVICES AMONG CHILDREN UNDER FIVE YEARS OF AGE I...
PDF
REPRESENTATION OF THE BLOCK DATA ENCRYPTION ALGORITHM IN AN ANALYTICAL FORM F...
PDF
OPTICAL CHARACTER RECOGNITION USING RBFNN
PDF
DETECTION OF MOVING OBJECT
PDF
SIMULATION OF ATMOSPHERIC POLLUTANTS DISPERSION IN AN URBAN ENVIRONMENT
PDF
PREPARATION AND EVALUATION OF WOOL KERATIN BASED CHITOSAN NANOFIBERS FOR AIR ...
PDF
ANALYSIS ON LOAD BALANCING ALGORITHMS IMPLEMENTATION ON CLOUD COMPUTING ENVIR...
PDF
A MODEL BASED APPROACH FOR IMPLEMENTING WLAN SECURITY
DEVELOPMENT OF TODDLER FAMILY CADRE TRAINING BASED ON ANDROID APPLICATIONS IN...
TESTING OF COMPOSITE ON DROP-WEIGHT IMPACT TESTING AND DAMAGE IDENTIFICATION ...
THE USE OF FRACTAL GEOMETRY IN TILING MOTIF DESIGN
TWO-DIMENSIONAL INVERSION FINITE ELEMENT MODELING OF MAGNETOTELLURIC DATA: CA...
USING THE GENETIC ALGORITHM TO OPTIMIZE LASER WELDING PARAMETERS FOR MARTENSI...
ANALYSIS AND DESIGN E-MARKETPLACE FOR MICRO, SMALL AND MEDIUM ENTERPRISES
REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS
EVALUATE THE STRAIN ENERGY ERROR FOR THE LASER WELD BY THE H-REFINEMENT OF TH...
HMM APPLICATION IN ISOLATED WORD SPEECH RECOGNITION
PEDESTRIAN DETECTION IN LOW RESOLUTION VIDEOS USING A MULTI-FRAME HOG-BASED D...
INTELLIGENT BLIND STICK
EFFECT OF SILICON - RUBBER (SR) SHEETS AS AN ALTERNATIVE FILTER ON HIGH AND L...
UTILIZATION OF IMMUNIZATION SERVICES AMONG CHILDREN UNDER FIVE YEARS OF AGE I...
REPRESENTATION OF THE BLOCK DATA ENCRYPTION ALGORITHM IN AN ANALYTICAL FORM F...
OPTICAL CHARACTER RECOGNITION USING RBFNN
DETECTION OF MOVING OBJECT
SIMULATION OF ATMOSPHERIC POLLUTANTS DISPERSION IN AN URBAN ENVIRONMENT
PREPARATION AND EVALUATION OF WOOL KERATIN BASED CHITOSAN NANOFIBERS FOR AIR ...
ANALYSIS ON LOAD BALANCING ALGORITHMS IMPLEMENTATION ON CLOUD COMPUTING ENVIR...
A MODEL BASED APPROACH FOR IMPLEMENTING WLAN SECURITY

Recently uploaded (20)

PDF
R24 SURVEYING LAB MANUAL for civil enggi
PPTX
6ME3A-Unit-II-Sensors and Actuators_Handouts.pptx
PDF
Categorization of Factors Affecting Classification Algorithms Selection
PDF
Abrasive, erosive and cavitation wear.pdf
PPTX
UNIT 4 Total Quality Management .pptx
PPTX
UNIT - 3 Total quality Management .pptx
PPT
A5_DistSysCh1.ppt_INTRODUCTION TO DISTRIBUTED SYSTEMS
PDF
BIO-INSPIRED HORMONAL MODULATION AND ADAPTIVE ORCHESTRATION IN S-AI-GPT
PDF
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
PPTX
Information Storage and Retrieval Techniques Unit III
PDF
UNIT no 1 INTRODUCTION TO DBMS NOTES.pdf
PDF
EXPLORING LEARNING ENGAGEMENT FACTORS INFLUENCING BEHAVIORAL, COGNITIVE, AND ...
PDF
III.4.1.2_The_Space_Environment.p pdffdf
PDF
Integrating Fractal Dimension and Time Series Analysis for Optimized Hyperspe...
PDF
PREDICTION OF DIABETES FROM ELECTRONIC HEALTH RECORDS
PDF
COURSE DESCRIPTOR OF SURVEYING R24 SYLLABUS
PPTX
Fundamentals of safety and accident prevention -final (1).pptx
PDF
86236642-Electric-Loco-Shed.pdf jfkduklg
PPTX
Current and future trends in Computer Vision.pptx
PDF
null (2) bgfbg bfgb bfgb fbfg bfbgf b.pdf
R24 SURVEYING LAB MANUAL for civil enggi
6ME3A-Unit-II-Sensors and Actuators_Handouts.pptx
Categorization of Factors Affecting Classification Algorithms Selection
Abrasive, erosive and cavitation wear.pdf
UNIT 4 Total Quality Management .pptx
UNIT - 3 Total quality Management .pptx
A5_DistSysCh1.ppt_INTRODUCTION TO DISTRIBUTED SYSTEMS
BIO-INSPIRED HORMONAL MODULATION AND ADAPTIVE ORCHESTRATION IN S-AI-GPT
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
Information Storage and Retrieval Techniques Unit III
UNIT no 1 INTRODUCTION TO DBMS NOTES.pdf
EXPLORING LEARNING ENGAGEMENT FACTORS INFLUENCING BEHAVIORAL, COGNITIVE, AND ...
III.4.1.2_The_Space_Environment.p pdffdf
Integrating Fractal Dimension and Time Series Analysis for Optimized Hyperspe...
PREDICTION OF DIABETES FROM ELECTRONIC HEALTH RECORDS
COURSE DESCRIPTOR OF SURVEYING R24 SYLLABUS
Fundamentals of safety and accident prevention -final (1).pptx
86236642-Electric-Loco-Shed.pdf jfkduklg
Current and future trends in Computer Vision.pptx
null (2) bgfbg bfgb bfgb fbfg bfbgf b.pdf

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.