Use of a hydrodynamic model to

forecast floods of Kalu River in Sri Lanka

K D W NandalalUniversity of PeradeniyaSri 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

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

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

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

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

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

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

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

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

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

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

Kalu River Study Reach and Geometric Database

Study reach extends from Ratnapura to Kalutara

about 79 km

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

River bed profile

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

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

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3

4

5

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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

Steady flow Model Outputs

3 D view of river

from station 79140 to 77090 (about 2 km)

Water level (river profile) along the river

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

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

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

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

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

Thank you