View
515
Download
0
Category
Preview:
DESCRIPTION
Citation preview
Sewwandhi Chandrasekara
Sanjaya Rathnayake
Practices of Downscaling
Methods for Water Resources
Management in Sri Lanka
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
– 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>>
Click>>
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
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>>
Click>>
Why prediction is important?
Threats for the water management
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
Using SCM….
0.2 mm wetter than the normal
44% of success rate
Using SSE…
0.2 –0.4 mm wetter than the normal
44% of success rate
Using MRG….
0.2 –0.8 mm wetter than the normal
Poor success rate
Using SSE….
0.2 0C warmer than normal
Poor success rate
Using MRG…
0.2 0C warmer than normal
44%-55% success rate
Using SCM…
0.2 0C warmer than normal
55% success rate
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
Using Dynamic Downscaling
• Software : RegCM 4
• Predicted Region : Sri Lanka
• Latitude : 5 N – 10 N
• Longitude : 75 E – 85 E
• Duration : 1998 June
Westerly Wind
Southerly Wind
Geo Potential Height
Air Temperature
Relative Moisture
Water Vapor
Cloud Water
Surface Pressure
Sea Level Pressure
Total Precipitation
Total Soil Water in mm H2O
Accumulated Infiltration
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
Further Work
• Simulate long term predictions via
RegCM3
• Upload more applicable Sri Lankan station
precipitation data for CLIK on-line
application
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.
Sewwandhi Chandrasekara
Sanjaya Ratnayake
(Sri Lanka)
APEC Climate Center
South Korea
Thanking you!
Recommended