Assessment of Climate Change Impacts on Extreme Precipitation Events in Lake Urmia Basin, Iran

Abstract

Climate change is known as one of the fundamental challenges of mankind, which has affected all aspects of human life. The present study aimed to evaluate the changes in precipitation and predict extreme precipitation in Lake Urmia basin. For this purpose, we evaluated the indices associated with changes in precipitation of eight synoptic stations of Lake Urmia basin for three time periods, namely near (2021-2040), middle (2041-2060) and far future (2061-2080), under two scenarios (RCP4.5 and RCP8.5). Using the CanESM2 model, we compared these periods to the observational period (1986-2005). To this end, after examining the capability of the SDSM model in simulating the reference period climate (1986-2005), future daily precipitation was downscaled. Subsequently, using the RClimDex, extreme precipitation indices were calculated for future periods. The results of the spatial distribution of precipitation variations showed that the average precipitation increased in the following decades, based on both scenarios. Investigation of the changes in extreme indices also revealed that percentile indices (R95p and R99p), Rx1day, SDII, and PRCPTOT rose based on both scenarios and in most future periods; meanwhile, the Rx5day, CWD, and CDD were reduced compared to the baseline period. Among the threshold indices, R10 increased based on RCP4.5 and decreased based on RCP8.5 whereas R20 and R25 did not change significantly compared to the reference period. However, in the far future, all the indices, except for CWD, had a decreasing trend. Although there is a great deal of uncertainty concerning precipitation and extreme precipitation forecasting, the results of such research can be conducive to the future policy making of a country, such as risk assessment.

Keywords

• extreme precipitation indices
• forecasting
• trend analysis
• sdsm model
• lake urmia basin