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Use of a hydrodynamic model to
forecast floods of Kalu River in Sri Lanka K D W Nandalal University of Peradeniya Sri Lanka
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Kalu Ganga is the third largest river in Sri Lanka
Catchment area is 2690 km2 River basin lies entirely within wet zone Source located 2250 m MSL and traverses about 100 km, before it enters the sea at Kalutara
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Average annual rainfall is 4000 mm.
It ranges from2750 mm from coastal areas to 5250 mm in mountains Discharges the largest volume of water to the sea Annual flow volume is more than 7300 x 106 m3
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Catchment upto Ratnapura is 615 km2
River bed elevation at Ratnapura is 13.7 m MSL Ratnapura Town subjects to flood when river level rises to 20 m MSL Flooding of Ratnapura Town had been a frequent occurrence These floods flow along the river inundating low level areas Finally Kalutara is affected by floods
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Year Annual Flood Damages Ratnapura Kalutara 1984 0.37 0.27 1994 3.01 2.19 1985 0.22 0.16 1995 5.64 1.31 1986 1.10 0.80 1996 N.A. 0.55 1987 0.05 0.03 1997 2.18 0.42 1988 0.23 0.17 1998 0.46 3.34 1989 3.94 2.88 1999 7.69 8.70 1990 3.11 2.27 2000 2.72 1.17 1991 6.34 462 2001 0.08 0.74 1992 12.42 9.06 2002 0.25 1.63 1993 2.41 1.76 2003 50.6 21.76
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HEC RAS Hydrologic Engineering Center - River Analysis System
Developed by; US Army Corps of Engineers The HEC RAS is comprised of a graphical user interface (GUI), Separate hydraulic analysis components, data storage and management capabilities, graphics and reporting facilities
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General Philosophy of the Modeling System
The HEC-RAS system contains three one dimensional analysis components for; steady flow water surface profile computations; unsteady flow simulation; and movable boundary sediment transport computations A key element is that all three components will use a common geometric data representation and common geometric and hydraulic computation routines
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Overview of Hydraulic Capabilities
HEC-RAS is designed to perform one-dimensional hydraulic calculations for a full network of natural and constructed channels User Interface File management Data entry and editing Hydraulic analysis Tabulation and graphical display of input and output data Reporting facilities On-line help
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Steady Flow Water Surface Profiles
This component is intended for calculating water surface profiles for steady gradually varied flow Can handle a full network of channels, a dendritic system or a single river reach Capable of modeling subcritical, supercritical and mixed flow regime water surface profiles
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The basic computational procedure is based on the solution of the one-dimensional energy equation
Energy losses are evaluated by friction (Manning's equation) and contraction/expansion (coefficient multiplied by the change in velocity head) The momentum equation is utilized in situations where the water surface profile is rapidly varied These situations include mixed flow regime calculations (i.e., hydraulic jumps), hydraulics of bridges, and evaluating profiles at river confluences (stream junctions)
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Unsteady Flow Simulation
This component is capable of simulating one-dimensional unsteady flow through a full network of open channels Model can perform mixed flow regime (subcritical, supercritical, hydraulic jumps, and drawdowns) calculations
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Graphics and Reporting
Graphics include X-Y plots of the river system schematic, cross-sections, profiles, rating curves, hydrographs, and many other hydraulic variables A three-dimensional plot of multiple cross-sections is also provided Tabular output is available Users can select from pre-defined tables or develop their own customized tables
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DEVELOPMENT OF THE MODEL
The Kalu River reach from Ratnapura to Kalutara was modeled using HEC-RAS (version 3.1.3) flood simulation package The model requires the plan and cross sections of the river, upstream and downstream boundary conditions, details of in-line structures along the river, hydraulic properties of the river and discharge scenarios
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Kalu River Study Reach and Geometric Database
Study reach extends from Ratnapura to Kalutara about 79 km
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River from Ratnapura to Kalutara in the model
86 surveyed cross section details were used Six major tributaries join the Kalu River NiriElla River, Kuru River, Galatara Oya, Yatipawa Ela, Morawak Oya, Kuda River
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River bed profile
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Model Calibration Calibration parameter is channel resistance; Manning’s n By trial and error, the most suitable values for the Manning’s n were found Water level and discharge data at three locations, Ratnapura, Ellagawa and Putupaula, were used to calibrate the model
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Flows upstream of Kalu River and its six tributaries in m3/s
Scenario 1 Scenario 2 Scenario 3 Scenario 4 Scenario 5 Galatara Oya 18 28 44 40 Kalu River 100 158 249 400 550 Kuda River 122 192 303 300 200 Kuru River 54 85 134 175 150 Mawak Oya 11 17 27 25 NiriElla River 69 109 170 250 350 Yatipawa Oya 4 6 10 Flows upstream of Kalu River and its six tributaries in m3/s observed and model computed water levels
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Steady flow Model Outputs
Water level (river profile) along the river 3 D view of river from station to (about 2 km)
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Unsteady flow Simulation
When a flood wave moves down a river, the shape/magnitude of the flood wave gets modified Calibrated model for the Kalu River can be used to study the movement of floods along it
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Fifty different floods were created and their movement was simulated
Ratnapura water level greater than (masl) Putupaula water level greater than (masl) 4.0 4.5 5.0 5.5 20.5 100 % 93 % 50 % 20.0 92 % 83 % 46 % 19.5 86 % 76 % 41 % 19.0 Similar tables could be developed for any station along the river and such information could be used to warn people of possible floods with the aim of minimizing flood damages
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People in the rural areas (less developed) with very low technical knowledge could be able to read and understand such tables A set of similar tables for a few locations were developed to predict flood levels based on upstream observations and were given to rural communities along the river
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CONCLUSIONS Model developed can be used to predict water level along the river stretch from Ratnapura to Kalutara for different water flows in the river Model provides the extent of inundation on both banks along the river. The model uses river cross section details at 86 locations along the river obtained from a field survey and the flood plain elevations read from 1:10,000 topo-sheets. The accuracy of the results depends on the accuracies expressed by these data
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Probability that the water level at a downstream location rises above a certain level for different water levels observed at an upstream location can be obtained from the model This result can be used to warn people in downstream areas by upstream communities based on the floods that they experience
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Thank you
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