1. Practices of Downscaling
Methods for Water Resources
Management in Sri Lanka
Sewwandhi Chandrasekara
Sanjaya Rathnayake

2. Introduction
• Sri Lanka owns different types of water
resources .Click>>
• Historically Sri Lanka had great hydraulic
civilization
• Presently water resources management is
essential to Sri Lanka

3. – 103 river basins (4560 km)
(Ministry of Forestry and Environment, 1999)
– More than 20 major
wetlands
– Minor and major irrigation
systems
– Groundwater resources
– Coastal and marine
resources. Click>>
• Sri Lanka
– 2400 m3 of available per
capita water resources
– 2000 mm of average
annual RF (Ariyabandu, 2008) click>>

4. Click>>

5. Historically
• Great ancient hydraulic civilization in Sri
Lanka
– Water used for
• Irrigation
• Domestic requirements
• Urban recreations
• Small scale industries
– However
• Water was managed properly
– Sustainably
– Participatory

7. But…..
• Temporal and spatial water scarcity
• Pollution
• Agrarian demand to sectoral demand. Click>>
– Industrial demand
– Environmental demand
– Electricity demand
– Recreational demand
Sustainable water resources management is
essential… Click>>

8. Click>>

9. Why prediction is important?

10. Threats for the water management

11. Statistical Downscaling…
• Downscaling for
– Rainfall OND
• Second inter-monsoon period
• 16% of quantity
• Important to land preparations for “Maha” season
(64% of paddy cultivation)
– Temperature OND
• Average 270C

12. Using SCM….
0.2 mm wetter than the normal

13. 44% of success rate

14. Using SSE…
0.2 –0.4 mm wetter than the normal

15. 44% of success rate

16. Using MRG….
0.2 –0.8 mm wetter than the normal

17. Poor success rate

18. Using SSE….
0.2 0C warmer than normal

19. Poor success rate

20. Using MRG…
0.2 0C warmer than normal

21. 44%-55% success rate

22. Using SCM…
0.2 0C warmer than normal

23. 55% success rate

24. Conclusions
• For OND season SSE & SCM can used to
predict rainfall at 44% success rate
• For OND season SCM can used to predict
temperature at 44% success rate
Unable to predict rainfall for the next season, because the stations what
we selected were failed at screening

25. Using Dynamic Downscaling
• Software : RegCM 4
• Predicted Region : Sri Lanka
• Latitude : 5 N – 10 N
• Longitude : 75 E – 85 E
• Duration : 1998 June

26. Westerly Wind

27. Southerly Wind

28. Geo Potential Height

29. Air Temperature

30. Relative Moisture

31. Water Vapor

32. Cloud Water

33. Surface Pressure

34. Sea Level Pressure

35. Total Precipitation

36. Total Soil Water in mm H2O

37. Accumulated Infiltration

38. Conclusion
• RegCM 4.0 is very usable to predict
South-west monsoon to Sri lanka
• Because past experiences showed the
same results observed from the RegCM
4.0 for the same monsoon season

39. Further Work
• Simulate long term predictions via
RegCM3
• Upload more applicable Sri Lankan station
precipitation data for CLIK on-line
application

40. Acknowledgement
• Dr. Lareef Zubair and staff at Foundation
of Environment and Climate Technologies,
Digana. Sri Lanka.
• Organizing Committee and Lecturers
APEC Climate Center. South Korea.
• Colleagues who participated with us.

41. Thanking you!
Sewwandhi Chandrasekara APEC Climate Center
Sanjaya Ratnayake South Korea
(Sri Lanka)