Investigating climate change impact on extreme rainfall events Case study: Chenar-Rahdar basin, Fars, Iran

In this research, the impact of climate change on extreme rainfall events in the 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 an a2 emission scenario. in summary, hadcm3 (for three downscaling methods) projected an increasing trend (of up to 21.8%) in extreme rainfall events for the period of 2011-2040, 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 the sdsm method resulted in an increasing trend (up to 3.6%) for recurrence periods of 20 and 25 years and a very small decreasing trend (down to -2%) for recurring periods of 50 and 100 years. relatively low correlation coefficients in multiple regressions obtained for both aogcms reect the limitations of sdsm in downscaling precipitation data in the study area. comparing the 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.