Use of a hydrodynamic model to forecast floods of Kalu River in Sri Lanka K D W Nandalal University...
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![Page 1: Use of a hydrodynamic model to forecast floods of Kalu River in Sri Lanka K D W Nandalal University of Peradeniya Sri Lanka.](https://reader036.fdocuments.net/reader036/viewer/2022062423/56649c995503460f94955999/html5/thumbnails/1.jpg)
Use of a hydrodynamic model to
forecast floods of Kalu River in Sri Lanka
K D W NandalalUniversity of PeradeniyaSri Lanka
![Page 2: Use of a hydrodynamic model to forecast floods of Kalu River in Sri Lanka K D W Nandalal University of Peradeniya Sri Lanka.](https://reader036.fdocuments.net/reader036/viewer/2022062423/56649c995503460f94955999/html5/thumbnails/2.jpg)
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![Page 3: Use of a hydrodynamic model to forecast floods of Kalu River in Sri Lanka K D W Nandalal University of Peradeniya Sri Lanka.](https://reader036.fdocuments.net/reader036/viewer/2022062423/56649c995503460f94955999/html5/thumbnails/3.jpg)
![Page 4: Use of a hydrodynamic model to forecast floods of Kalu River in Sri Lanka K D W Nandalal University of Peradeniya Sri Lanka.](https://reader036.fdocuments.net/reader036/viewer/2022062423/56649c995503460f94955999/html5/thumbnails/4.jpg)
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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![Page 5: Use of a hydrodynamic model to forecast floods of Kalu River in Sri Lanka K D W Nandalal University of Peradeniya Sri Lanka.](https://reader036.fdocuments.net/reader036/viewer/2022062423/56649c995503460f94955999/html5/thumbnails/5.jpg)
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
Year Annual Flood Damages
Ratnapura
Kalutara 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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The HEC-RAS system contains three one dimensional analysis components for;
(1) steady flow water surface profile computations;
(2) unsteady flow simulation; and
(3) 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
General Philosophy of the Modeling System
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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 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)
Energy losses are evaluated by friction (Manning's equation) and contraction/expansion (coefficient multiplied by the change in velocity head)
The basic computational procedure is based on the solution of the one-dimensional energy equation
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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 nBy 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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Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Galatara Oya 18 28 44 40 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 25
NiriElla River 69 109 170 250 350
Yatipawa Oya 4 6 10 10 10
Ratnapura
0
5
10
15
20
25
0 1 2 3 4 5 6Profile
Wat
er le
vel (
MA
SL)
Observed
Model
Ellagaw a
0
2
4
6
8
10
12
14
0 1 2 3 4 5 6Profile
Wat
er le
vel (
MA
SL)
Observed
Model
Putupaula
0
1
2
3
4
5
6
7
0 1 2 3 4 5 6Profile
Wat
er le
vel (
MA
SL)
Observed
Model
observed and model computed water levels
Flows upstream of Kalu River and its six tributaries in m3/s
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Steady flow Model Outputs
3 D view of river
from station 79140 to 77090 (about 2 km)
Water level (river profile) along the river
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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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![Page 25: Use of a hydrodynamic model to forecast floods of Kalu River in Sri Lanka K D W Nandalal University of Peradeniya Sri Lanka.](https://reader036.fdocuments.net/reader036/viewer/2022062423/56649c995503460f94955999/html5/thumbnails/25.jpg)
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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 % 100 % 93 % 50 %
20.0 100 % 92 % 83 % 46 %
19.5 100 % 86 % 76 % 41 %
19.0 100 % 86 % 76 % 41 %
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