Assessment of climate change impact on surface runoff, statistical downscaling and hydrological modeling

In this study, using the Statistical downscaling model (SDSM), the data of CanESM2 Canadian general circulation model (GCM) was downscaled under the Representative Concentration Pathway (RCP) 2.6, RCP4.5, and RCP8.5. In order to study the climate change, the artificial neural network (ANN) and IHACRES models were used over the period of 2010-2040. The study results showed that the temperature is increased in the upcoming period of 2006-2100 (0.8 to 5.6 C°), and the highest temperature changes are related to winter and summer. The precipitation in the upcoming period shows an increasing trend on the annual average, but, in general, it can be said that the 4-55% precipitation shows an increasing trend. The runoff in the upcoming period of 2010-2040 under RCP2.6, RCP4.5 and RCP8.5 is -4, 26 and -2 percent in the ANN model and 26, 28 and 33 percent in the IHACRES model, respectively.
Source: Physics and Chemistry of the Earth, Parts ABC - Category: Science Source Type: research