Introduction to Urban Drainage Modeling Urban Drainage Modeling for (SWMM) and Data collection for Pourashavas model calibration and theRequirements three selected validation in the Coastal Region of Bangladesh
Considering Climate Change Dr. A.K.M. Saiful Islam Dr. Tarekul Islam Dr. Sujit Kumar Bala Surpiya Paul Ahsan Shopan Institute of Water and Flood Management Bangladesh University of Engineering and Technology (BUET)
Urban flooding situation in Bangladesh Dhaka gets a record rainfall in 28th July 2009 of highest oneday in 60 years
333 mm/day
Heavy downpour in Chittagong 463 mm rainfall in Chittagong on 26 June 2012
91 people killed from land slides • In that event about 91 people killed from land slides. Due to illegal destructions of hills and unplanned settlement is the root cause. primarily by illegal .
Components of Hydrological Cycle
Urban water management models
What is SWMM • SWMM is a distributed, dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas.
SWMM Storm Water Management Model
8
SWMM’s Process Models
Input Data Include… PRECIPITATION Channel Characteristics Elevations Imperviousness Slope Roughness Width (a shape factor) Depression Storage Infiltration Parameters
10
Properties of Sub catchment
11
Hydrologic Modeling Features • • • • • • • •
Spatially and time varying rainfall Evaporation of standing surface water Snow accumulation and melting Interception from depression storage Infiltration into soil layers Percolation into shallow groundwater Interflow between groundwater & channels Nonlinear routing of overland flow
12
Hydraulic Modeling Features • Handles drainage networks of any size • Accommodates various conduit shapes as well as irregular natural channels • Models pumps, regulators, storage units • Allows external inflows from runoff, groundwater, RDII, sanitary, DWF, and usersupplied time series • Uses flexible rule-based controls for pumps and regulators • Models various flow regimes, such as backwater, surcharging, reverse flow, and surface ponding
Supported cross section of conduit
Supported Hydraulic Structures Pumps (bombas) Outlets
Weirs (vertederos)
Orifices (orificios)
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Set up of urban drainage model • Sub-Catchment delineation and identification of drainage networks have been conducted using ArcGIS software. • Digital elevation model of 10m resolution the LGED Master Plan has been used. • Land use, infrastructures, water bodies maps from LGED MP and satellite images are analyzed to determine sub-catchment properties.
Pirojpur Pourashava
Sub-catchment and Drainage network
Amtali Pourashava
Sub-catchment and Drainage Network
Golachipa Pourashava
Sub-catchment and Drainage network
Calibration of model at Pirojpur Simulated water level (m)
3
(b)
2.5 2 1.5 1
y = 0.881x + 0.320 R² = 0.965
0.5 0 0
1
2
3
Observed water level(m)
DamudorVarani Junction
Simulated water level (m)
2.5
(b)
2 1.5
y = 0.955x + 0. R² = 0.933
1 0.5 0 0
1
2
DamudorShashanghat Junction
DamudorKumarKhali Junction
Simulated water level (m)
Observed water level(m)
2.5
(b)
2 1.5 1
y = 1.023x - 0.250 R² = 0.913
0.5 0 0
1
2
Observed water level(m)
Calibration at Amtali
Simulated water level (m)
Basuki Khal
4
y = 0.850x + 0.322 R² = 0.874
3 2 1 0 0
(b)
2 Observed water level(m)
4
Calibration at Golachipa Branch Khal to meet lohalia river
Simulated water level (m)
3
y = 2.801x - 2.763 R² = 0.785
2 1
0 0.5
1.5
(b)
Observed water level(m)
2.5
Issues in Calibration and Validation • Due to limited scope of the project the runoff data has been collected by using the support from the three Pourashava’s Engineers. • It is collected for a few locations for one or two storm events during 2012. • It was not possible to collect data for the whole monsoon season and for several year or locations. • However, with is limited data sets, model shows reasonable similar patters of observed data and with high level of correlation coefficient.
Design of the drainage network • Design storm has been generated by using historic rainfall data from the nearest meteorological stations. • Data of Barisal station is used for Pirojpur and Khepupara is used for both Amtali and Golachipa pourashavas. • Intensity duration curve has been generated for both long and short durational rainfall. • Hytographs has been developed by alternative block method. • 10 year 2 hours rainfall has been used as desing rainfall.
IDF Curve of Barisal and Khepupara 18
14 2-year
16
2-year
5-year
14
5-year
12
10-year
Intensity (mm/hour)
Intensity (mm/hour)
12
10-year
10
25-year
8
50-year
6
100-year
4 2
25-year
10
50-year
8
100-year
6 4 2
0 0
24
48
72
96
120
144
0
168
0
24
48
72
Duration (Hour)
200 2-year 5-year
150
Intensity (mm/hour)
Intensity (mm/hour)
175
10-year 25-year
125
50-year
100
100-year
75 50 25 0
0.0
0.5
1.0
1.5 Duration (Hour)
2.0
2.5
3.0
96
120
144
168
Duration (Hour)
500 450 400 350 300 250 200 150 100 50 0
2-year 5-year 10-year 25-year 50-year 100-year
0.0
0.5
1.0
1.5 Duration (Hour)
2.0
2.5
3.0
Estimation of Peak Discharge • Frequency analysis has been conducted to estimate the peak discharge of the surrounding rivers using Long-Normal, Extereme value Type I and Log Pearson's Type III methods and determine the most suitable methods of the fitted PDFs.
Fitted PDFs and probability plot of Baleswar River (SW 107) as example PDF 2.33 2.52 2.48 2.48 2.44 2.54
LN2 LN3 P3 LP3 EV1
20 2.85 3.16 3.16 2.93 3.12
Return period 50 2.96 3.60 3.48 3.21 3.35
Rank 100 3.03 4.01 3.72 3.44 3.52
PPCC 0.84548 0.96272 0.95404 0.96100 0.90389
5 1 3 2 4
Log Normat Type III Has been found with lowest Probability Plot Correlation Coefficient, PPCC value.
Water Level, mPWD
6.0 5.0 4.0
LN-III has been selected for generating Design water as boundary conditions.
3.0 2.0 1.0 0.0 -3
-2
-1
0
1
Standard Normal Variate
2
3
Design of Urban Drainage Network • After calibration of the SWMM model for the three selected Pourashavas, model is simulated for the design storm and boundary conditions for both present and climate change conditions.
• The depth-inundation plots considering normal and future climate change conditions have been generated for 3 Pourashavas.
Climate Change conditions • Rainfall analysis has been conducted using regional model results of future projected rainfall for two future time slices 2030s and 2050s. Extreme emission scenarios SRES A2 scenarios has been used for assess impact of climate change. • Future possible land-use and population data has been collected from LGED Master Plan which has been used for determining change of catchment properties. • Sea level rise has been added based on the available information and review of other studies.
Inundation map – Pirojpur Baseline
Climate Change, 2050
Inundation map – Amtali Baseline
Climate Change, 2050
Inundation map – Golachipa Baseline
Climate Change, 2050
Identification of flooding • Using the design storms and design water level boundary conditions, SWMM has been simulated and inundated areas within Pourashavas have been identified.
• To improve the present situation, by changing the x-sections of existing canals (considering excavation, lining or mud removing) alternative simulation have been conducted.
Improvement of the system • It has been found that in many places it is possible to avoid flooding by changing depth and slope of the x-sections. Detail analysis has been provided in the report.
• Due to limited scope of this study, it was not possible to simulated models with many other possible and plausible solutions e.g. detention ponding, pump installations etc.
Improved X-section of Damudar Khal of Pirojpur for present condition Damudor Khal
XS No. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Chainage Roughness 0 230 480 730 980 1230 1480 1730 1980 2230 2480 2730 2980 3230 3480 3630 3880 4079
0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.02 0.02 0.035 0.035 0.035 0.035
Max WL 3.18 3.13 3.08 3.00 2.95 2.93 2.90 2.85 2.60 2.55 2.55 2.55 2.58 2.60 2.63 2.65 2.68 2.73
Present Condition Baseline (Equivalent Trapezoidal XS) Bottom Width Slope Height Comment Bottom Width Overflow 1:1.5 31.50 2.60 30.80 20.25 14.30 18.15 20.40 22.65 17.80 20.55 14.95 19.00 16.50 18.10 18.40 18.35 15.75 20.65 17.85 21.90
1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5
3.57 2.77 2.90 2.71 2.51 2.41 2.59 3.05 2.98 2.64 2.94 2.69 2.74 3.20 3.25 3.13 3.09
Improvement Slope Height 1:1.5 3.15
Comment Not Required
Overflow Overflow Overflow Overflow Overflow Overflow
13.90 18.00 20.00 22.00 17.08 20.08
1:1.5 1:1.5 1:1.5 1:1.5 1:1.5 1:1.5
3.08 3.00 3.00 3.00 2.94 2.94 Not Required Not Required
16.24 18.32 18.32
1:1.5 1:1.5 1:1.5
2.82 2.76 2.76 Not Required Not Required Not Required Not Required Not Required
Improved X-section of Damudar Khal of Pirojpur for 2050s Damudor Khal XS No.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
Roughnes Chainage s Max WL
0 230 480 730 980 1230 1480 1730 1980 2230 2480 2730 2980 3230 3480 3630 3880 4079
0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.035 0.02 0.02 0.035 0.035 0.035 0.035
3.18 3.13 3.08 3.00 2.95 2.93 2.90 2.85 2.60 2.55 2.55 2.55 2.58 2.60 2.63 2.65 2.68 2.73
2050 Climate Change Condition Baseline (Equivalent Trapezoidal XS) Improvement Bottom Bottom Slope Height Comment Slope Height Width Width Overflow 1:1.5 31.50 2.60 30.07 01:01.5 3.70 1:1.5 20.25 3.57 Overflow 3.60 1:1.5 14.30 2.77 13.20 01:01.5 Overflow 3.60 1:1.5 18.15 2.90 17.20 01:01.5 Overflow 3.60 1:1.5 20.40 2.71 19.20 01:01.5 Overflow 3.60 1:1.5 22.65 2.51 21.20 01:01.5 Overflow 3.60 1:1.5 17.80 2.41 16.20 01:01.5 Overflow 3.60 1:1.5 20.55 2.59 19.20 01:01.5 3.60 1:1.5 14.95 3.05 Overflow 16.20 01:01.5 Overflow 01:01.5 1:1.5 19.00 2.98 16.40 3.45 1:1.5 16.50 2.64 Overflow 15.40 01:01.5 3.45 1:1.5 18.10 2.94 Overflow 17.40 01:01.5 3.45 1:1.5 18.40 2.69 Overflow 17.60 01:01.5 3.30 Overflow 01:01.5 1:1.5 18.35 2.74 17.60 3.30 1:1.5 15.75 3.20 Overflow 15.60 01:01.5 3.30 1:1.5 20.65 3.25 1:1.5 17.85 3.13 1:1.5 21.90 3.09
Comment Not Required
Not Required Not Required Not Required
Conclusions • It has found that SWMM can be successfully applied to assess the flow and flooding of the three coastal Pourashavas. • Model shows reasonable performance while it was calibrated with observed data. • Using the design storm conditions (10yr-2hr rainfall) flooding has been observed for many places in both baseline and climate change conditions.
Recommendations • It was found essential to conduct detail topographic survey of these Porashava areas and the surrounded catchment areas. • Rainfall-runoff data has been collected continuously for a whole year for model calibration and validation.
