Volume No. 8 Issue No.: 1 Page No.: 126-134 Jul-Sept. 2013

 

REGIONAL PRECIPITATION SCENARIOS USING A SPATIAL STATISTICAL DOWNSCALING APPROACH FOR KLANG WATERSHED, MALAYSIA

 

Reza Kabiri*, Ramani Bai V. and Andy Chan

Department of Civil Engineering, Faculty of Engineering, University of Nottingham, Malaysia Campus (MALAYSIA)

 

Received on : April 05, 2013

 

ABSTRACT

 

Climate change is a consequence of changing in climate on environment over the worldwide. Multi rain gauge stations have been selected to make a spatial downscaling. SDSM uses a multiregression method to link large scale climate variables as provided by Global Climate Models (GCMs) simulations with daily climatic data at local site using the SDSM. The aim of study is to assess the impact of climate changes on the future precipitation for three timeslices 2020ís, 2050ís and 2080ís under A2 IPCC scenario. To estimate rainfall trend over Klang catchment it was attempted to establish a spatial rainfall analysis of the 10 selected rainfall stations using Geo-statistical function in GIS. The watershed seems to experience increased rainfall towards the end of the century. However, the analysis indicates that there will likely be a negative trend of mean precipitation in 2020s and with no difference in 2050s. The precipitation experiences a mean annual decrease amount by 7%, 0.6% and 0.9 % for A2 scenario in 2020s, 2050s respectively and an increase by 12.4% in 2080s. It can be concluded which days with heavy precipitation will occur more frequently causing a higher frequency of high river flow events.

 

Keywords : Climate change, Statistical downscaling model, HadCM3, SDSM, GIS

 

 

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