Evaluating climatic change effects on EC and runoff in the near future (2020–2059) and far future (2060–2099) in arid and semi-arid watersheds

Abstract

This study investigates the effect of climate change on the runoff and electrical conductivity (EC) of the Marun watershed. It used 35 general circulation models (GCMs) and the identification of unit hydrographs and component flows from rainfall, evaporation and streamflow data (IHACRES) rainfall-runoff model for the hydrological simulation. Moreover, a non-parametric regression model based on the multivariate adaptive regression splines (MARS) was utilized to estimate the EC under representative concentration pathway RCP4.5 and RCP8.5 scenarios in the near future F1 (2020–2059) and far future F2 (2060–2099) periods. Also, it used the technique for order of preference by similarity to ideal solution (TOPSIS) method to determine the best GCMs for each region and the k-nearest neighbors (KNN) technique to combine the temperature (Tmean) and precipitation (PCP) outputs and reduce the GCM uncertainty in each cell. According to the results, the highest increase of EC relative to the historical period (1966–2005) that will occur in the F1 period under the RCP4.5 and RCP8.5 scenarios is 17.43% and 15.6%, and for the F2 period is 18.46% and 11.2%, respectively, during autumn. The changes of annual Tmean, PCP, runoff, and EC in F1 period are 8.6%, 2.1%, − 10.7%, and − 11%, respectively, under the RCP4.5 scenario and 10.5%, 5.9%, − 3.5%, and − 12.2%, respectively, under the RCP8.5 scenario. The same values for the F2 period are 12.9%, − 0.1%, − 14.9%, and − 10%, respectively, under the RCP4.5 scenario and 22.6%, 5.2%, 1.2%, and − 12.8%, respectively, under the RCP8.5 scenario relative to the historical period.