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Some Actions for Sustainable Development – Sri Lanka

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Some Actions for Sustainable Development – Sri Lanka Water-centric Inter-linkages Some Case Studies in Sri Lanka S.B Weerakoon1 - Water with Floods, Climate, Energy Cho Thanda Nyunt2 - Water with Climate Change Yoshimitsu Tajima3 - Water with Coastal Environment 1University of Peradeniya, Sri Lanka 2University of Tokyo, Japan 3University of Tokyo, Japan Rainfall Forecasting and Flood Inundation along the Lower Reach of Kelani River Basin under Changing Climate S.B Weerakoon1, Srikantha Herath2 , Gouri De Silva1 1Department of Civil Engineering, University of Peradeniya, Peradeniya, Sri Lanka 2United Nations University, Shibuya-ku, Tokyo, Japan Elevation distribution Flood inundation in Colombo(DEM) and suburbs create heavy economic damages 4 Kelani River Basin Region – Wet Zone Total Basin Area – 2,230 km2 Uppermost Elevation – 2,250 m Length of the River – 192 km Average Annual Rainfall – 2,400 mm Peak flow – 800-1500 m3/s Vegetation cover Upper basin – Tea, rubber, grass and forest Lower basin – heavily urbanized 1. Weather forecasting for flood warning Rainfall forecasting using downscaling of 72 hr climate model data by Weather Research and Forecasting (WRF) model - to provide early warning on rainfall and floods Application of Weather Research and Forecasting model (WRF model) Nesting option – 135/45/15/5 (4050 ×4050 / 1530 ×1395 / 465 ×465 / 245 ×260 ) with푘푚 input resolution푘 푚of 10 minutes 푘푚 푘푚 푘푚 Input data downloaded from NCAR web site WRF – short term rainfall forecasting Calibration – 21st November 2005 Validation – 27th and 28th April 2008, and 30th, 31st May and 1st June 2008 Justification Mean Absolute Model Error percentage % = × 푺푺푺푺푺푺푺푺푺 푹푺푺푹푹� − 푶푶푶푺푶푶 푹푺푺푹푹� 푴푴푴푴 ퟏퟏퟏퟏ 푶푶푶푺푶푶 푹푺푺푹푹� Calibration and validation Calibration Difference between WRF predictions and observed rainfall for the date 21st November 2005 Validation Difference between WRF predictions and observed rainfall for the date 27th April 2008 Validation Difference between WRF predictions and observed rainfall for the date 31st May 2008 Difference between WRF predictions and observed rainfall for the date 1st June 2008 2. Flood inundation analysis under changing climate • Climate pattern up to 2099 under A2 and B2 Emission Scenarios of AR4 by – Statistical Downscaling Model • Inundation modeling in the lower Kelani basin using FLO-2D model Study area for rainfall analysis (about 2200 km2) Study area for rainfall – runoff simulation (about 1700 km2) Study area for flood analysis (about 500 km2) Hanwella Source: Department of Irrigation, Sri Lanka Meteorological data Hydrological data Data collection Topographic data Rainfall forecast for future under both A2 and B2 scenarios (SDSM) Calibration and Analyze forecasted verification of rainfall data HEC-HMS Generate inflow at the upstream for future (FLO-2D) Forecasting future flood conditions according to future rainfall 14 Flood inundation model (FLO-2D) Grid size – 250 m Parameters Channel and catchment characteristics such as, Infiltration Manning’s coefficient Channel roughness GridManning'sElevation and boundary Distribution coefficient of accordingcatchment (DEM) to land use Channel shape and dimensions 3 day rainfall for upper basin 3 day rainfall / Return (mm) Period / (yr) A 2 B 2 50 391 383 100 429 420 Daily rainfall for lower basin Daily rainfall / Return (mm) Period / (yr) A 2 B 2 50 425 377 100 476 417 Calibration and validation – with respect to discharge hydrograph at the D/S gauging station (Nagalagam Street) and flood inundation maps Justification Normalized Objective Function (NOF) 2 Nash – Sutcliffe efficiency R NS Percentage bias (δb) Fraction of the domain classified correctly by the simulations (F) = × 100 푆표표표 ∩ 푆푚표푚 퐹 17 푆표표표 ∪ 푆푚표푚 Calibration Observed and simulated flow during 2005 flood 18 Validation Observed and simulated flow at during April-May 2008 flood Event 2 November 2005 푁푁0.09퐹 푅0.98푁푆 6.98%훿푏 April-May 2008 0.14 0.97 10.37% 19 Validation HEC–HMS was used to compute inflow into the lower basin at the upstream Time series of observed and simulated flow at the D/S gauging station during May 2010 flood F = 73% Observed Inundation extent (from DMC data) Simulated Inundation extent Results Inundation extents due to 50 year Inundation extent correspond to 50 year return period rainfall under A2 scenario return period rainfall under B2 scenario Inundation extents due to 100 year Inundation extent correspond to 100 year return period rainfall under A2 scenario return period rainfall under B2 scenario Water Resources in Sri Lanka 2012 MahaweliBasin Kelani Basin Source: CEB Source: CEB in kt eq. CO2/TWh About 140 MHPs with 1000 974 778 350MW capacity at present 800 778 contribute 6.2% 600 400 200 15 Goal- Renewable energy to 1 0 supply 10% by 2016 S1 Coal Diesel Reservoir River Hydro with Heavy Oil Hydro Run-of- Source: CEB Run-of-river MHP/SHP provides lowest contribution during dry period Operation of multi-purpose large reservoirs has great impact on energy generation For the Kelani River Basin Forecasting of weather for early warning systems Inundation extents and high risk areas of inundation by rainfalls of 50, 100 year return periods under both A2 and B2 scenarios in Colombo were investigated For hydro-energy Integrated water management under changing climate is important. Devon waterfall ( Upper Kotmale Subbasin) 7th July 2008, Weerakoon Adaptation strategies Levee and detention basin • A levee of 1.0 m height and 10 km long from the downstream • Detention reservoirs; several marshy lands were identified from land use maps and converted in to detention reservoirs. 10km long Levee Developed marshy lands as detention reservoirs Results – Inundation extents under (c) 50 year return period rainfall under A2 scenario Reduces average risk about 65% 50 year return period rainfall under B2 scenario Reduces the average risk about 40% Results – Inundation extents under (c) 100 year return period rainfall under A2 scenario Reduces the average risk about 32% 100 year return period rainfall under B2 scenario Reduces the average risk about 25% .
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