1. P B Hunukumbura1 S B Weerakoon1
Application of physically based hydrological model to the Upper Kotmale basin
P B Hunukumbura1
S B Weerakoon1
University of Peradeniya, Sri Lanka
20th December 2004 – SLAAS , Colombo

2. Objective of study
SLAAS
Develop a physically based hydrological model for stream flow prediction in the Upper Kotmale basin
Compare the performance of the Similar Hydrological Element Response model (SHER) with different types of basin distribution

3. Introduction Water Resources in Sri Lanka Rainfall Surface water
SLAAS
Water Resources in Sri Lanka
Rainfall
Southwest monsoon – May to Sep.
Northeast monsoon – Dec. to Feb.
Inter monsoon – Mar.to Apr & Oct. to Nov.
Surface water
Sri Lanka has 103 river basins and their sizes vary from 10 km2 to km2

4. Study area Basin area = 304 km2 Elevation = 1200m to 2500m
SLAAS
Study area
Basin area = 304 km2
Elevation = 1200m
to 2500m
Annual rainfall = 2200 mm
to 2600 mm
The Upper Kotmale Basin

5. Land use map Tea 44% Forest 36% Built up Land 7%| Grass 5%
SLAAS
Tea 44%
Forest 36%
Built up Land 7%|
Grass 5%
Cash Crops 5%

6. Preparation of GIS maps
Slope map
SLAAS
Preparation of GIS maps
The area and slope of each block was estimated by using a GIS database. The 1: scale digital maps prepared by the Survey Department were used in this study. A TIN model was first created by using the contour map and then the elevation GRID was created using the TIN model and corrected using the stream network. The slope grid of the basin was then derived.

7. Soil type map
SLAAS

8. The SHER model
SLAAS
The Similar Hydrological Element Response model (SHER) is a lumped physically based model developed in the Extend simulation environment incorporating the physical processors to represent basin heterogeneity
The basin is distributed by considering the basin stream network, soil distribution and slope variation.

9. Criteria for dividing the basin for SHER model application
SLAAS
In this study, three models were developed and performance of each model predictions were compared
SHER 1
The basin was divided into three regions based on three main soil series. Each region was modeled using soil moisture block.

10. SLAAS
Block diagram for SHER 1
Soil NE
Basin
Soil HOR
Soil MAT

11. Cont..
SLAAS
SHER 2
The basin was divided into three regions based on three main soil series.
Each soil series was again subdivided into two slope groups

12. Block diagram for SHER 2 % of the area with Slope 0-20 >20 Block 3
SLAAS
Block diagram for SHER 2
% of the area with Slope
0-20
>20
Block 3
Block 1
Block 2
Block 6
Block 4
Block 5
Soil NE
Basin
Soil HOR
Soil MAT

13. Cont..
SLAAS
SHER 3
The basin was divided into three regions based on three main soil series.
Each region was divided to two sub regions. The area that lies within 0.5 km from perennial streams is taken as one sub region and the rest as the other region.
The latter is subdivided into two regions according to the slopes

14. Block diagram for SHER 3 Block 6 Block 4 Block 5 Block 7 Block 8
SLAAS
Block diagram for SHER 3
Block 6
Block 4
Block 5
Block 7
Block 8
Block 2
Block 1
Block 3
% of the area with Slope
0-20
>20
Block 9
Soil NE
Basin
Soil HOR
Soil MAT
Other
Near Stream
Near Stream

15. Data Stream flow Evaporation Rainfall 1987 to 1993
SLAAS
Stream flow
Daily Stream flow data at Thalawakele flow gauge was used
Evaporation
Daily pan evaporation data at Kotmale was used
Rainfall
Daily rainfall data at six stations were used
1987 to 1993

16. Model evaluation Calibration period - 1987 to 1988
SLAAS
Calibration period to 1988
Verification period to 1993
Two statistical indices were used to compare the model predictions
Nash Sutcliffe coefficient,
Root mean square error,

17. Results
SLAAS
Calibration Period

18. Results Cont..
SLAAS
Verification Period

19. Simulated mean flow/(mm/day) 2.39 2.33 3.36 3.1 2.91
Parameter
1987 to Calibration
1989 to 1993 – Verification
SHER 1
SHER 2
SHER 3
SHER1
SHER2
SHER3 Nc
0.47
0.57
0.64
0.54
0.63
0.65
RMSE
1.84
1.66
1.53
2.82
2.53
2.46
Simulated mean flow/(mm/day)
2.39
2.33
3.36
3.1
2.91
Standard deviation of simulated flow
2.18
1.74
1.95
3.8
3.2
Observed mean flow/(mm/day)
2.85
Standard deviation observed flow
4.15

20. Conclusion
SLAAS
Physically based model (SHER ) was developed and calibrated for the Upper Kotmale basin to predict the stream flow at the basin outlet.
The third type SHER 3 where the basin was distributed considering the soil type, stream network, and the basin slope, gives the highest Nc value of 0.65 and the lowest RMSE value of 2.46 in the verification period. It is found that the Nc value increases by 0.1 when the SHER 1 distributed further corresponding to SHER 2
The accuracy of the model predictions increases with the distribution the basin according to slope

21. Thank You