Projected Precipitation Extremes in Lake Urmia Basin under Climate Change

IntroductionClimate change has led to changes in the frequency, intensity, duration, and spatial distribution of climate extremes. During the last decade (2011-2020), the average global temperature was 0.1 ± 1.1 oC higher than in the preindustrial era. Iran and especially the Urmia Lake basin is one of the most vulnerable areas to climate change. Urmia lake basin has received the special attention of policymakers and planners since it is the location of Lake Urmia, and it also holds nearly 7% of Iran's water resources. A huge program of dam construction and irrigation networks has been started in this basin in the northwest of Iran since the late 1960s. Despite the increasing attention to Lake Urmia since 1995, the water level of this lake has decreased. During the drought of 1990-2001, Lake Urmia experienced a decrease in its level without any recovery and is decreasing at an alarming rate. Therefore, it is necessary to project the future climate of the Urmia Lake basin and especially extreme precipitation based on the latest climate change models. Materials and MethodsThe CMIP6 models were used to investigate the future projection of extreme precipitation in the Lake Urmia basin. Considering the horizontal resolution, availability of daily data, and climate sensitivity, we selected five models including GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, and UKESM1-0-LL. The horizontal resolution of all five models is 0.5o. The 25-year historical period (1990-2014) and the 25-year projection period for the near future (2026-2050) were chosen to analyze the extreme precipitation in the Urmia Lake Basin. The future projection was considered under three shared socioeconomic pathways (SSPs) scenarios. These scenarios include SSP1-2.6, SSP3-7.0, and SSP5-8.5 scenarios. Mean bias error (MBE) and Normalized Root Mean Square Error (NRMSE) were computed to evaluate the individual models and the multi-model ensemble generated by Bayesian Model Average (BMA) method. To assess extreme precipitation, we used four indices including the Number of heavy precipitation days (R10mm), the number of very heavy precipitation days (R20mm), the Maximum 1-day total precipitation (Rx1day), and the Simple Daily Intensity Index (SDII). Results and DiscussionThe performance of five CMIP6 individual models and the multi-model ensemble in the Lake Urmia basin during the period of 1990 to 2014 was evaluated against eight ground stations. The investigation of the annual precipitation sh