Climate change impacts on the shrinkage of Lake Urmia

Abstract

The purpose of this study was to investigate the impact of climate change on the water level and shrinkage of Lake Urmia. To achieve this, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm was used to select the top 10 general circulation models (GCMs) among 23 CMIP5 GCMs in the baseline period (1951–2005). Based on the K-nearest neighbors (KNN) method, 10 GCMs were combined and their uncertainties were quantified. Also, the future period (2028–2079) data were generated by using the LARS-WG model. According to the results, the temperature increased in all seasons of the future period. Under the RCP4.5 scenario, the precipitation decreases by 10.4 and 27.8% in spring and autumn, respectively, while it increases by 18.2 and 3.4% in summer and winter, respectively. Moreover, the RCP8.5 scenario lowers the precipitation by 11.4, 22.7, and 4.8% in spring, autumn, and winter, respectively, while it rises by 26.5% in summer. Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to calculate the short-, medium- and long-term meteorological droughts of the baseline and future periods. The occurrence number and peaks of droughts increase, while their durations decrease, in the future period. In general, the SPEI has a robust relationship than the SPI with changes in the water level of Lake Urmia. HIGHLIGHTS Using TOPSIS to select superior GCMs for simulation of climatic variables.; Using the K-nearest neighbors (KNN) approach for Combining the superior GCMs.; Assessment of climate variable simulation uncertainty in combined and single GCMs.; Providing a relationship between meteorological drought and the water level of Lake Urmia.;

Keywords

• climate change
• lake urmia
• rcps
• spei
• stochastic downscaling
• topsis