Urbanization of an area cause to increase the impervious areas in the vicinity of city area that cause to decrease the infiltration and increase the surface runoff. This cause flash floods in low land areas. Therefore stormwater management in urban areas should be done with sufficient attention.
Stormwater drainage problem in Matara Municipality area has become a major problem. This is mainly because of improper practices adopted while developments are taking place. In this context alternation made to the surface topography and permeability in property developments have created a significant impact on increasing the surface run-off rates and volume. People who live in the close proximity, change the topography to prevent the surface runoff through their land, thus, effectively changing the natural drainage paths in the urbanized areas.
This studies mainly focused to develop a stormwater model for Piladuwa area in Matara municipal council, by the use of EPA SWMM model.
Field visits to the study area were made to collect the input parameter for mathematical model development. During these field visits stakeholder surveys was done to collect the data for model verification. A Sensitivity analysis was carried out for the catchment area in order to identify the catchment parameters that affect the catchment outflow parameters. Result taking from the model used to take the engineering option for storm water management in Piladuwa area.
First and foremost, I would like to express my appreciation to Prof. N. T. S Wijesekera [Final year Research Project coordinator and my individual Research Project supervisor], for sacrificing his priceless time of heavily loaded work schedule in order to guide, direct, advise, comment, correct and criticize me and my research work.
Also there was excellent support from academic staff of the Department of Civil Engineering University of Moratuwa. I make this an opportunity to extend my humble gratitude to all the academic staff members in the Department of Civil Engineering.
Special appreciation goes to Mr.Dulanjan Wijesinghe and, Miss.Nimmi sooriyabandara for helping us in GPS survey .
I would also like to thank my research group members Miss.H.M.D.Harshani, Miss.K.S.S.Chandrasiri and my batch mates that I closely worked with during the research work, Mr. Supun rangana, Mr. Susantha Wanniarachchi and Mr.Y.A.Naotuna. Thank you very much for the eventful, wonderful and most remembered time shared with me during the final year research project.
At last but not least, I appreciate each and every person who contributes to make my research project a success.
Department of Civil Engineering
University of Moratuwa.
Table of Contents
List of Figures vi
List of Tables vii
CHAPTER 01 1
1.1 Introduction 1
1.1.1 Research background 1
1.2 Scope 2
1.3 Objectives 2
1.3.1 Overall objectives of group 2
1.3.2 Specific objective 2
1.3.3 Limitation and boundary of the research project 2
1.4 Study Methodology Flow Chart 4
1.5 Activities Executed 5
CHAPTER 02 7
2.1 Literature review 7
2.1.1 Brief History 7
2.2 Stormwater management in urbanized watersheds 7
2.2.1 Effects of urbanization on watersheds 7
2.3 Storm water modeling for urban areas 8
2.4 Different Model available for modeling 9
2.5 Typical application of SWMM 11
2.6 Engineering Guidelines 12
CHAPTER 03 15
3.1 Data Collection 15
3.1.1 General description 15
3.3 Sample calculation 17
3.3.1 Slope 17
3.3.2 Area 18
3.3.3 Width 18
3.3.4 Manning roughness: 18
3.3.5 Percentage of pervious and imperviousness 18
3.4 Field work execution 19
3.4.1 Other required data 20
CHAPTER 04 21
4.0 Modeling 21
4.1 Model selection 21
4.2 My study area 21
4.3.1 Schematic diagram for SWMM model 22
4.3.3 Notations & symbols used 23
4.2.3 Data for model 23
4.4.4 Design rainfall intensity 25
4.4.5 Input rainfall data 26
4.4.6 Catchment details 27
CHAPTER 05 29
5.0 Model results 29
5.1 Surface runoff 29
5.2 Simulation result 30
5.3 Subcacthment Runoff summary 32
5.4 Node depth summary 32
5.5 Node inflow summary 33
5.6 Node flooding summary 33
5.7 Outfall Loading Summary 34
5.8 Link flow summary 34
CHAPTER 06 36
6.1 Sensitivity Analysis 36
6.2 Sensitivity analysis for Subcatchment 06 36
6.2.1 Sensitivity of Slope of the catchment 36
6.2.2 Sensitivity of ” n”pervious 37
6.3 Sensitivity analysis for other subcatchment 39
CHPATER 07 40
7.1 Conclusion & Discussion 40
8.0 REFERENCES viii
9.0 ANNEXES viii
9.1 Annex A viii
9.2 Annex B ix
List of Figures
Figure 1 – Matara Municipal Council area 1
Figure 2 – Flood hazards 2
Figure 3 – Catchment areas 3
Figure 4 – Methodology flow chart 4
Figure 5 – Surface runoff reducing 13
Figure 6 -Pervious cathbasin 14
Figure 7 – sMap of selected area (Piladuwa) 22
Figure 8 – Divided subcatchments 22
Figure 9- SWMM model schematic diagram 23
Figure 10 notation used for SWMM 23
Figure 11 – Input parameters for the model 24
Figure 12- manning’s roughness values 24
Figure 13 -Infiltration data 25
Figure 14 – Typical Depression storage values 25
Figure 15 -Time series editor 26
Figure 16 – Time series 27
Figure 17 – Surface runoff 29
Figure 18 – Subcatchment losses 29
Figure 19 – Schematic diagram of Piladuwa 30
Figure 20 – Water elevation profile -at 1.00 hour 30
Figure 21 – Node depth Vs time 31
Figure 22 31
Figure 23 – Water elevation profile -at 15 minutes 31
Figure 24 – Water elevation profile -at 30 minutes 32
Figure 25 – Flooding area 40
List of Tables
Table 1 – Model comparison 10
Table 2 – Model comparison 10
Table 3 – Field work execution 20
Table 4 – Catchment details 28
Table 5 – Subcatchment Details 28
Table 6 – Subcacthment Runoff 32
Table 7 – Maximum node depth 32
Table 8 – Node inflow summary 33
Table 9 – Node flooding summary 33
Table 10 – Outfall Loading Summary 34
Table 11 – Link flow summary 34
Table 12 – Flooding nodes 36
Table 13 – Subcatchment slope vs peak flow 37
Table 14 – Pervious Manning’s n vs. peak out flow 38
1.1.1 Research background
When the history is considered, it can clearly see that the civilization has occurred around the f flood plains. Matara Municipal Council Area is also situated in a flood plain of Nilwala River (Figure 1) and has experiencing stormwater drainage problems,such as flash floods.
Figure 1 – Matara Municipal Council area
Matara municipality area is a very low land area and it is almost a flat terrain .Matara town rapidly growing since Matara is one of best city in southern province and it possesses leading schools and infrastructure facilities. Because of above mentioned reasons people attract to the Matara city and its population density went up and people dwell low land areas also. With respect to the population increase imperviousness, vegetation removed of the city limit this created, increase of overland flow as well as speed of the over land flow.
Nowadays Matara municipality area facing storm induced flash flood due to above mentioned reasons. This is a inconvenience for people, with flood they may have to leave their houses (Figure1) then government have to give them shelter and food and also when road are flooded transportation is become vulnerable (Figure 1)so time of people is wasted and large amount money ,properties of the country wasted productivity of the work force also affected .This problem is not only facing Matara, lot of cities in Sri Lanka facing this problem so it is advisable to manage stormwater and overcome this flooding problem.
Figure 2 – Flood hazards
The main scope of this study is to develop a mathematical model for the Matara Municipal Council Area, to provide engineering and management options to mitigate the stormwater problem.
1.3.1 Overall objectives of group
Overall object of this project is to investigate the existing stormwater related problems in Matara Municipal Council and develop a mathematical model for storm water management and find out engineering and management options, that can be implemented, in order to mitigate the stormwater problem.
1.3.2 Specific objective
1) Identify the watershed using water flow directions
2) Identify the sensitive catchment parameters which affect the outflow from the catchment to the canal system
1.3.3 Limitation and boundary of the research project
Since Matara Municipal Council area is an ungauged catchment area, no data were available about the catchment and it was found through the field survey for model calibration process. Therefore it is difficult to develop a model which generate output with higher accuracy. Therefore the developed model was calibrated produce the results within a maximum and minimum values.
1.4 Study area
Matara is located at the Southern coast of Sri Lanka. Matara is a well developed commercial centre. Nilwala River is the main fresh water body at close proximity. In Matara Municipal area there are three sample areas which were identified for detailed modeling. They are listed below.
Figure 3 – Catchment areas
1.5 Study Methodology Flow Chart
Figure 4 – Methodology flow chart
1.6 Activities Executed
> Literature survey
Literature surveys done to identify best software package to this project and also to gain knowledge what have done by other have done relating to our research project. Literature survey is very important to find manning’s roughness value, parameters for GREEN AMPT infiltration method etc….
> GPS practice
To take the GPS point, photo point and voice cut at the field. GPS points are very important to identify the path of the river , also we can check that if there is a deviation with map also and length between nodes can be measures using GPS points .
> Desk study
Desk study is done before every field visit to identify the boundaries of the area which we are going to be covered at the field and also from where to start and end the field study. After every field visit desk study done to calculate catchment slope, width of catchment etc… Data arranging was also done during this desk study time.
> Computer model practicing and identifying the parameters for the model
After choosing the software package for the modeling purpose it was needed to know familiarize with the parameters that should taken at the field work. After identifying the parameters a field book was prepared.
> Practicing a sample data collection
Before going to the field, it is important to have firsthand experience in how to take the relevant data accurately and quickly. So
> Field visit
Field visits were conducted for collect data of the subcatchment such as vegetation, ponded areas, geometry of channel, nodes etc…..
> Data arranging and summarizing
After every field visit it was necessary to arrange and summarize the collected data for future references.
> Calculation other parameters
After every field visit the collected data were entered to the model thus it was needed to calculate the catchment parameters. These parameters were calculated using Arc GIS software. Those parameters are essential to develop the model.
> Model development for catchment areas
This research is based upon the model development for subcatchment areas.After developing the model for this areas evaluation of engineering and management option can be done.
> Calibration and verification of models
Even though we develop a computer model e can’t guarantee that it would give accurate result as output . To assure reliable output from the model it is necessary to calibrate the model with the available data for rainfall data and inundation depths.
> Sensitivity analysis
Sensitivity analysis is important to identify which parameter affects mostly affect to the outflow from the catchment. After identifying those parameters engineering and management option can be given.
2.1 Literature review
2.1.1 Brief History
It is advisable to discuss the problems of existing Nilwala scheme, which was implemented in 1980 s with technical consultancy of a French company. The strategy of ‘protecting lands by embanking and evacuating storm water by pumping’ was mainly applied in this scheme. Other alternatives such as diversion, storage, temporary detention, enlarging river channel etc were not been considered. Flood warning and bypassing system had been attempted, but failed due to various socio – economic factors.
The Nilwala scheme was subjected to many controversies since the beginning. The time allocated for planning and design was very limited. The problem was not discussed widely and the stakeholders and local expertise point of view were not taken in to consideration. The scheme could not achieve the targeted benefits. Specially the first phase of the scheme, Kiralakele, was a complete failure and still abandoned after the several attempts of rectification works. (P.Hettiarachchi)
2.2 Stormwater management in urbanized watersheds
The term “stormwater management” implies a comprehensive approach to the planning, design, implementation, and operation of stormwater drainage improvements. The purpose of stormwater management approach is to develop an effective drainage systems that balance the objectives of maximizing drainage efficiency and minimizing adverse environmental impacts.
(Municipal Program Development Branch Alberta, January 1999)
2.2.1 Effects of urbanization on watersheds
Urbanization causes a change to natural systems that tends to occur in the following sequence. First, land use and land cover altered as vegetation and topsoil were removed to make the way for agriculture, or subsequently buildings, roads, and other urban infrastructure. These changes, together with and the introduction of a artificial drainage network, have alter the hydrology of the local area, such that the receiving waters in the affected watersheds experience radically different flow regimes than it was prior to urbanization. Nearly all of the associated problems result from one underlying cause: loss of the water-retaining and evapotranspirating functions of the soil and vegetation in the urban landscape. In an undeveloped area, rainfall typically infiltrates into the ground surface or is evapotranspirated by vegetation. In the urban landscape, these processes of evapotranspiration and water retention in the soil are diminished, such that stormwater flows rapidly across the land surface and arrives at the stream channel in short, concentrated bursts of high discharge. This transformation of the hydrologic regime is a wholesale reorganization of the processes of runoff generation, and it occurs throughout the developed landscape. When combined with the introduction of pollutant sources that accompany urbanization (such as lawns, motor vehicles, domesticated animals, and industries), these changes in hydrology have led to water quality and habitat degradation in virtually all urban streams. (CLAIRE WELTY, et al., 2008)
The influence of humans on the physical and biological systems of the Earth’s surface is not a recent manifestation of modern societies; instead, it is ubiquitous throughout our history. As human populations have grown, so has their footprint, such that between 30 and 50 percent of the Earth’s surface has now been transformed (Vitousek et al., 1997). Most of this land area is not covered with pavement; indeed, less than 10 percent of this transformed surface is truly “urban” (Grübler, 1994). However, urbanization causes extensive changes to the land surface beyond its immediate borders, particularly in ostensibly rural regions, through alterations by agriculture and forestry that support the urban population (Lambin et al., 2001)
2.3 Storm water modeling for urban areas
Even though storm water modeling is not much used in Sri Lanka it is widely used in many other countries. Stormwater modeling is being done very effective for obtaining management solution for urban area.
With today’s advances in computer technology, many cities in the developed countries manage local and minor flooding problems using computer based solutions. This involves building computer models of the drainage/sewer system, for instance by using software like MOUSE (Lindberg et al., 1989); Info Works (Bouteligier et al., 2001) and the SWMM
models (EPA SWMM, MIKE SWMM, and XP SWMM), (Huber and Dickinson, 1988). These types of models are used to understand the frequently complex interactions between rainfall and flooding. Once the existing conditions have been analyzed and understood, alleviation schemes can be evaluated and the optimal scheme implemented. Nevertheless, at present there are few studies on urban flooding that O. Mark et al. / Journal of Hydrology 299 (2004) 284-299 285deal with both the conditions in the surcharged pipe network and the extensive flooding on the catchment surface. Even fewer projects have dealt with modeling urban flooding in developing countries. Some of the few case studies dealing with of modelling of urban flooding which both includes the pipe system and extended surface flooding are: Bangkok (Thailand) (Boonya-Aroonnet et al., 2002); Dhaka City (Bangladesh) (Mark et al., 2001); Fukuoka and Tokyo (Japan) (Ishikawa et al., 2002); Harris Gully (USA) (Holder et al., 2002); Indore (India) (Kolskyet al., 1999) and Playa de Gandia (Spain) (Tomic?ic´ et al., 1999). These studies treated urban flooding as a one-dimensional (1D) problem. Schmitt et al. (2002) considered a 2D model as a benchmark for 1D model. A model, which dynamically couples a 1D pipe flow model with a 2D hydrodynamic surface flood is currently under development (Alam, 2003).
Many numerical models available today adopt numerical schemes to the solutions of full de Saint-Venant equations. For instance, models like SWMM-EXTRAN (Huber and Dickinson, 1988)
2.4 Different Model available for modeling
There are 8 models specially design for urban stormwater modeling They are listed below:
4. SWMM level1
6. WALLINGFORD MODEL
Table 1 – Model comparison
(Review of storm water models by Christopher zoppou)
SWMM free and it can use for planning and designing urban models.
Table 2 – Model comparison
Georgia Stormwater Management Manual
The storm water management model(SWMM) was developed for the Environmental Protection Agency in 1969 – 1971 as a singel event model for simulation of quantity and quality processes in combined sewer systems.It has since been applied to virtually every aspect of urban drainage,from routine drainage design to sophisticated hydraulic analysis to non-point source runoff quality studies, using both single event and continous simulation.Through subdeviding large catchments and flow routing down the drainage system.SWMM can be applied to catchments of almost any size ,from parking lots to subdevision section to cities. (philip B.Bedient, 1992)
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. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps.
2.5 Typical application of SWMM
Since its inception, SWMM has been used in thousands of sewer and stormwater studies throughout the world. Typical applications include
* Design and sizing of drainage system components for flood control
* Sizing of detention facilities and their appurtenances for flood control and water quality protection
* Flood plain mapping of natural channel systems
* Designing control strategies for minimizing combined sewer overflows
* Evaluating the impact of inflow and infiltration on sanitary sewer overflows
* Generating non-point source pollutant loadings for waste load allocation studies
* Evaluating the effectiveness of Best Management Practices for reducing wet weather pollutant loadings.
2.6 Engineering Guidelines
* Detained water contributes to runoff and therefore detention ponds or basins must have an outlet and outfall system . A gravity outfall should be used whenever feasible. Pumping should only be used where there is no other practical way of handling the excess runoff. (Highway Design Manual )
* Detention pond designing
Detention ponds are the most commonly used form of runoff control, Outlet facilities for ponds can consist of a concrete weir, a berm with culverts at several levels, a mid-pond draw-off, or any one of a variety of other outlet structures. Side slopes are typically grassed. However rip rap or gabion erosion protection shall be used where erosive wave action is a concern. Various edge treatments are also used to minimize onshore weed growth and maintain aesthetics. The pond side slopes are normally kept flat, typically between 5:1 (H:V) to 7:1 (H:V), to reduce the risk of slipping on wet grass and falling into the water.(Storm water management Guidelines for the Province of Alberta)
Detention refers to holding or storing stormwater and releasing it over a set period of time to avoid high peak flows in the receiving water. Generally, detention is employed through the use of excavated or constructed basins, often referred to as dry detention basins or dry basins, which drain completely between storms. Dry detention basins are effective at reducing the peak flow of stormwater from a drainage area and have the advantage of causing the least rise in temperature in the receiving water, thus helping protect temperature-sensitive aquatic species .Properly designed dry basins can be aesthetically pleasing. Some commercial office buildings have well-kept grassed detention basins that serve in dry weather as lunchtime gathering areas for employees. Pollutant removal and aesthetic qualities can be enhanced by extending the time the stormwater is held, which creates a small permanent wetland. Plants in the wet area hide the sediment and debris accumulated near the outlet. Disadvantages include moderate to high routine maintenance needs, infrequent but expensive sediment removal, and nuisance problems including weeds, odors and debris collection. Dry basins are considered unsightly at least in part because the accumulated sediment and debris are visible between rains.
* Surface runoff reducing
On-site (Lot-level) Controls
On-site (Lot-level) controls are practices that reduce the quantity of stormwater runoff and improve the water quality before the runoff reaches the conveyance system. These practices are applied at a single lot level or multiple lots in a small area.
Reduced Lot Grading
The development standards require a minimum lot grade of two per cent to ensure adequate drainage of stormwater away from the buildings. In order to avoid foundation drainage problems, grading within two to four meters of buildings should be maintained at two per cent or higher. In areas outside this envelope, grading can be flattened to 0.5 per cent. A reduction in the lot grading should be evaluated if the land is flat. In hilly areas, alterations to natural topography should be minimized. Areas outside this envelope should be graded at less than two per cent (Figure 5). Reduced lot grading can be implemented where soils have an infiltration rate of = 15 mm/h and it is applicable to all soils coarser than loam; clay soils are usually not suitable. In areas where reduced lot grading is implemented, roof leaders should extend two meters away from the building to discharge to the surface.
Figure 5 – Surface runoff reducing
* Pervious Catchbasins
Pervious catchbasins are designed to convey the road drainage and these systems have large sumps that are physically connected to an exfiltration storage medium. The storage medium is located below or beside the catchbasin. Pervious catchbasin details for road drainage are shown in Figure6
Figure 6 -Pervious cathbasin
3.1 Data Collection
3.1.1 General description
Field visits conducted to collect subcathment parameters such as vegetation, ponded areas, geometry of channel, nodes etc….. These field-collected data are very important for model calibration and verification in case of ungauged catchments. SWMM software was practiced before the field visit to familiarize with the input parameters. Before going to the field locations in Matara, a preliminary field visit was conducted at Molpe- Katubedda area to gain experience on field parameter capturing. Also a GPS survey was done in the university premises to familiarize with the instruments.
It is important to know about parameters that must be collected at the field for model development. For model calibration and verification purpose at least the upper limit and the lower limits of the water flow in conduits must be known in the case of unavailability of exact measurements.
To obtain maximum outputs from a field visit, it is important to study the area using maps. These maps were very important to identify the boundaries of the catchment areas.
Responsibilities were allocated to each person, regarding with data collecting, asking questions from stakeholders, taking relevant photographs, tabulating all data and as well as the careful looking at the instruments. Since responsibilities were changed during the field, all members practice each and every activity. At the end of each day, a small discussion was done to ensure the successful data collection.
3.2 Field data
At the field following data were collected.
> Canal geometry (shape, width etc….)
> Canal bank condition(concrete, gabion etc…)
> Position of nodes
> Length between nodes
> Maximum depth of canal at nodes
> Photos of the field
> GPS locations
> Data from stake holders
3.3 Sample calculation
After every field visit desk study was carried out to complete the calculation accordingly. The sub catchments slope, area, width, manning’s roughness and percentage areas of pervious and imperviousness, were calculated using collected data, 1:10,000 topographic sheets, and Arc GIS software. Infiltration model choose for computation was the Green-ampt model. Required data for this method can be found in SWMM help manual, provided the soil type is known.
If contours are present and we can recognize water flowing paths can be recognized then water path length and contour intervals were measured to calculate the slope.
Considering all, Final Slope = (0.07×516.38+0.044×443.31+0.0896×294.65)
Subcatchments of the study area was divided according to the contour pattern of that area. Using Arc GIS software, areas of each subcatchment were calculated by creating a polygon.
This is given by the subcatchment area divided by the maximum overland flow length. Maximum overland flow length was taken as the length of the water path that starts at the most far end of the sub catchment.
3.3.4 Manning roughness:
Values of Manning’s roughness for over land flow used as in the manual of the SWMM and checked the values with the literature available value( Applied Hydrology by Chow V.T.) Weighted average method was used to achieve a representative roughness value since land cover changes within the area.
3.3.5 Percentage of pervious and imperviousness
By observing the satellite images of the area those percentages were calculated.
* percentage of impervious area
Roof area = 192m2
Houses = 62
Total roof area = 11904m2
Galle road = 4339.37m2
Subroad1 = 1180.38m2
Subroad2 = 603.3m2
Percentage of impervious = 18027.05 x 100% = 9%
* Percentage N pervious
Marshy land area 1 = 22221.96m2
Marshy land area 2 = 7259.09m2
Areas from trees = 67263.19m2
Areas for earth soils = 5169 m2
N values for short grass = 0.15
Light under bush = 0.4
Fallow soils = 0.05
So percentage N pervious = 31585.88/200290.89=0.16
All the calculations were done as mentioned above for all sub catchment.
3.4 Field work execution
Number Date Location Work done 01 06/11/2009 Walgama Identify the main canals at the field and note down shape of the canal segments and identify the canal bank types (as concrete, gabion or vegetation) and took photos of each nodes and important places. At the nodes points maximum depth were measured. When there is a flow we used a float and found the flow velocity of the water. Also got GPS point of the path. From the peoples asked about rain and flood height and frequency and maximum flow of canal and minimum flow. 02 04/03/2010 Piladuwa ” 03 Thotamuna ” 04 13/03/2010 Thudawa ” 05 14/03/2010 Kunu Ela ” ” 06 Brownshill ”
Table 3 – Field work execution
3.4.1 Other required data
Other required data were gathered from following sources
* 1:50000 digital maps – Survey department of Sri Lanka
* 1:1000 digital maps – Survey department of Sri Lanka
* Satellite imaginary developed at 2007 – Survey department of Sri Lanka
* Runoff coefficient – Ven Ti Chow open channel hydraulics book
* Rainfall data – Irrigation Department
* Manning roughness values – SWMM help
4.1 Model selection
We used EPA SWMM software use to model the catchment in our research work because of the following reasons.
1. SWMM is dynamic rainfall-runoff model used for single event or long term (continuous) simulation of runoff quantity and quality from primarily urban areas.
2. Specially design for urban watersheds.
3. Handles drainage networks of any sizes
4. Accommodates various conduit shapes as well as irregular natural channels
5. Spatially and time varying rainfall can use in model
6. Infiltration and evaporation can be include with model
7. Can use for flood plain mapping
8. GIS point can insert to the model
4.2 My study area
Piladuwa area is I selected and it is situated very close to Nilwala River, which is a one of boundary for my catchment. This area is having bund, which was constructed in the Nilwala scheme. My study area having three major canals. Piladuwa area is highly populated area.
Figure 7 – sMap of selected area (Piladuwa)
4.3.1 Schematic diagram for SWMM model
Figure 8 – Divided subcatchments
4.3.2 Schematic of model
Figure 9- SWMM model schematic diagram
4.3.3 Notations & symbols used
There are some notations which are used to indicate the symbols in the model. Those notations can be changed by varying the default values of the model. Following are the notations which are used for this study.
S – Subcathment
C – Conduit (canal)
J – Nodes
Out – Outfall
RG – Rain gauge
Figure 10 notation used for SWMM
4.2.3 Data for model
For familiarize with EPA SWMM, installed the software and practice the tutorial given along with the software .By doing that identified the following parameters which should input to the model.
Figure 11 – Input parameters for the model
4.4 Input data for the model
4.4.1 Manning’s roughness
Figure 12- manning’s roughness values
Manning roughness for the open channel flow for a particular cannel section is in over a range. As an example for lined canals filled with vegetal, value fluctuating between 0.03 – 0.4. If the canal filled with more vegetal the roughness is selected near to the upper bound of 0.4. This is because high vegetal means disturbance to the flow is very much and the roughness vale must be high. Like that the values must have to be selected between lower bound and upper bound.
4.4.2 Infiltration data
Figure 13 -Infiltration data
4.4.3 Depression storage data
Figure 14 – Typical Depression storage values
4.4.4 Design rainfall intensity
Rainfall data were collected from the Irrigation Department. These rainfall data had been recorded at three hour intervals. If those data were input to the time series of the model, All the values will be it was taken as for one hour. So those data should be converted into one hour rainfall data.
Rainfall intensity was calculated using rainfall Intensity- Duration -Frequency relationship.
I = Intensity of rain in inches/hr
D = duration of storm in minutes
X & Y are two constants as given below.
According to the map of hydrological stations and Zones Matara is located at zone 3. Then for 10 year return period the Intensity become 0.845 inches/hr.
(Design of irrigation head works for small catchment, ponraj)
4.4.5 Input rainfall data
Figure 15 -Time series editor
Figure 16 – Time series
4.4.6 Catchment details
Catchment Area (km2) Length of the Longest Stream(km) Slope (%) Width Overall Study Area 0.568 0.36 0.003 96.8 Sub Catchment 1 0.0348 0.17 0.002 128.2 Sub Catchment 2 0.0213 0.24 0.002 47.9 Sub Catchment 3 0.0113 0.16 0.004 55.5 Sub Catchment 4 0.009 0.12 0.0028 129.6 Sub Catchment 5 0.0159 0.19 0.005 291.1 Sub Catchment 6 0.0539 0.33 0.0004 93 Sub Catchment 7 0.0307 0.45 0.002 141 Sub Catchment 8 0.063 0.16 0.0029 76.5 Sub Catchment 9 0.0121 0.25 0.0045 54.05 Sub Catchment 10 0.0136 0.26 0.0024 163.3 Sub Catchment 11 0.0426 0.24 0.0026 183.7 Sub Catchment 12 0.0437 0.36 0.0012 110 Sub Catchment 13 0.0394 0.25 0.0025 122.4 Sub Catchment 14 0.0306 0.33 0.007 130.7 Sub Catchment 15 0.0425 0.37 0.009 137.8 Sub Catchment 16 0.0509 0.3 0.002 176.6 Sub Catchment 17 0.053 0.36 0.003 1301.7
Table 4 – Catchment details
Subcatchment N-Impervious N-perv S- Imperv S-Perv %zero 1 0.0125 0.15 2.5 5 10 2 0.0125 0.15 2.5 5 10 3 0.0125 0.4 1.25 5 2 4 0.014 0.4 2.5 5 20 5 0.015 0.4 1.25 5 25 6 0.015 0.24 2.5 2.5 2 7 0.014 0.6 2.5 7.5 4 8 0.014 0.8 1.25 7.5 5 9 0.012 0.4 2.5 4.5 5 10 0.011 0.24 2.5 4 10 11 0.011 0.15 1.25 5 5 12 0.011 0.24 1.25 5 5 13 0.012 0.15 1.25 5 20 14 0.012 0.41 1.25 1.25 10 15 0.0125 0.8 1.25 7.5 10 16 0.0125 0.8 5 7.5 10 17 0.011 0.13 2.5 5 5
Table 5 – Subcatchment Details
5.0 Model results
After modeling and calibration the mathematical model, it can be use to take number of out puts such as flow simulations, subcathment runoff, infiltration etc. Some results are given below which generate for the Piladuwa (My catchment).
5.1 Surface runoff
Figure 17 – Surface runoff
Figure 18 – Subcatchment losses
5.2 Simulation result
Figure 19 – Schematic diagram of Piladuwa
Figure 20 – Water elevation profile -at 1.00 hour
From this animated results clearly shows that this canal is not going to flood with the design rainfall since it is not flooded after one hour.
Figure 21 – Node depth Vs time
Node depth vs time graph can use to identify that maximum depth of the water level at any node .
Figure 23 – Water elevation profile -at 15 minutes
Figure 24 – Water elevation profile -at 30 minutes
These animated results shows that this canal in my catchment flooded within 1st 15 minutes, so this canal system flooded with design rainfall input.
5.3 Subcacthment Runoff summary
Table 6 – Subcacthment Runoff
5.4 Node depth summary
Table 7 – Maximum node depth
5.5 Node inflow summary
Table 8 – Node inflow summary
5.6 Node flooding summary
Table 9 – Node flooding summary
5.7 Outfall Loading Summary
Table 10 – Outfall Loading Summary
5.8 Link flow summary
Table 11 – Link flow summary
From the field data ,calculated data and output from the result following maximum and minimum values can be identify.
> Largest subcatchment = 0.06 km2
> Smallest subcatchment = 0.009 km2
> Maximum slope of the catchment = 0.009 km2
> Minimum slope of the catchment = 0.0004km2
> Maximum out flow from the catchment = 0.249 m3
> Minimum out flow from the catchment = 0.029 m3
> Maximum runoff coefficient = 0.989
> Minimum runoff coefficient = 0.568
6.1 Sensitivity Analysis
At the field we identify the flooding location, from the model we got those area getting flooded, after calibration of the model. These flooding nodes as below:
Flooding Node Related subcathment J1 S6 J15 S11 J16 S14 J17 S12
Table 12 – Flooding nodes
So it is needed to do a sensitivity analysis for above mentioned subcatchments to identify sensitive parameters.
6.2 Sensitivity analysis for Subcatchment 06
6.2.1 Sensitivity of Slope of the catchment
Graph 1 – Subcatchment slope vs peak outflow
% slope % change of slope Peak runoff(m3/s) peak runoff% change 0.0025 -50 0.195 4.4 0.005 0 0.204 0 0.0075 50 0.209 2.4
Table 13 – Subcatchment slope vs peak flow
6.2.2 Sensitivity of ” n”pervious
Graph 2 – Pervious Mannig’s N vs peak out flow
Pervious Manning’s N = Manning’s roughness coefficient for pervious area
Manning’s “n” % change of “n” Peak runoff(m3/s) Peak runoff %change 0.24 0 0.204 0 0.36 50 0.194 4.9 0.48 100 0.187 8.33 0.8 233 0.176 13.7
Table 14 – Pervious Manning’s n vs. peak out flow
6.3 Sensitivity analysis for other subcatchment
7.1 Conclusion & Discussion
The output from the SWMM model and field observations are matching so SWMM can use to model this catchment area. In Piladuwa area major problem is blockage of water by the bund which was built under Nilwala scheme. This causes to flooding in the area marked in below figure. Also capacity of this canal is very much low consider to the in flow.
Figure 25 – Flooding area
From the sensitive analysis result we can conclude followings
> Subcatchment 14 is the most sensitive for the catchment slope catchment
> Subcatchment 6 is the most sensitive for the N pervious value of the catchment
> Subcatchment 14 is the most sensitive for the percentage imperviousness of the catchment
> Change of slope have high effect on out flow from the catchment.
> Manning’s roughness coefficient for pervious area and percentage of pervious area are sensitive for out flow from the catchment.
> By having thick vegetation will increase the Manning’s roughness coefficient and decrease the surface runoff.
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9.1 Annex A
Photos taken at the field
Date 08/04/2010 Location: (Piladuwa) Chainage
(m) Geometry Roughness Nodes Remarks shape No. Top Maximum L/B R/B Bed Invert Maximum barrels width(m) depth(m) level depth 0 rect. 1 0.4 0.6 conc conc conc 3.1 rect. 1 0.4 0.8 conc conc conc 6.8 rect. 1 1.0 1.0 conc conc conc 0.875 15.7 rect. 1 2.3 1.35 conc conc conc 1.46 1.23 20.4 rect. 1 2.5 1.45 conc conc conc 25.1 rect. 1 2.5 1.5 conc conc conc 1.52 1.33 33.6 rect. 1 2 1.5 conc conc conc 38.9 rect. 1 2 1.5 conc conc conc 43.2 rect. 1 2 1.8 conc conc conc 1.46 1.28 In front of hospital 54.3 rect. 1 1.8 1.8 conc conc conc 67.8 rect. 1 1.8 1.8 conc conc conc 1.61 1.42 79.1 rect. 1 1.5 1.6 conc conc conc 1.55 1.57 87.4 rect. 1 1.6 conc conc conc 98.9 rect. 1 3 1.6 conc conc conc 111.2 rect. 1 3.5 1.8 conc conc conc 2.1 1.5 120.8 rect. 1 3 1.75 conc conc Muddy 1.2 0.9 150.7 rect 1 2.5 1.8 Vege Vege Muddy 160.5 rect. 1 1.9 Vege Vege Muddy 172.7 rect. 1 3.8 1.8 Vege Vege Muddy 9.2 Annex B