Civil and Environmental Engineering Department, School of Engineering, Shiraz University, Zand Blvd., Shiraz, 7134851156, Iran
In this research,the impact of climate change on extreme rainfall events in Chenar-Rahdar Basin, Shiraz, Iran, was investigated utilizing three statistical downscaling methods; namely change factor, LARS-WG, and SDSM. Daily precipitations with different recurrence periods were projected for the future period of 2011-2040 (2020s) based on two AOGCM output data (HadCM3 and CGCM3) under A2 emission scenario.In summary, HadCM3 (for three downscaling methods) projected an increasing trend (of up to 21.8%) in extreme rainfall events for 2011-2040 period with respect to the base period. On the other hand, CGCM3 showed an increasing trend for extreme rainfall events for the first two methods (up to 24.7%), while SDSM method resulted in an increasing trend (up to 3.6%) for recurrence periods of 20- and 25-yr and a very small decreasing trend (down to -2%) for recurrence periods of 50- and 100-yr. Relatively low correlation coefficients in multiple regressions obtained for both AOGCMs reflect limitations of SDSM in downscaling precipitation data in the study area. Comparing three downscaling techniques utilized in this study, it is concluded that using change factor or LARS-WG downscaling methods would be conservative enough in climate change impact assessment for the next 30 years.