This study aims to conduct a thorough investigation to compare the abilities of quantile mapping (QM) techniques as a bias correction method for the raw outputs from general circulation model (GCM)/regional climate model (RCM) combinations. The Karkheh River basin in Iran was selected as a case study, due to its diverse topographic features, to test the performances of the bias correction methods under different conditions. The outputs of two GCM/RCM combinations (ICHEC and NOAA-ESM) were acquired from the coordinated regional climate downscaling experiment (CORDEX) dataset for this study. The results indicated that the performances of the QMs varied, depending on the transformation functions, parameter sets, and topographic conditions. In some cases, the QMs' adjustments even made the GCM/RCM combinations' raw outputs worse. The result of this study suggested that apart from DIST, PTF:scale, and SSPLIN, the rest of the considered QM methods can provide relatively improved results for both rainfall and temperature variables. It should be noted that, according to the results obtained from the diverse topographic conditions of the sub-basins, the empirical quantiles (QUANT) and robust empirical quantiles (RQUANT) methods proved to be excellent options to correct the bias of rainfall data, while all bias correction methods, with the notable exceptions of performed PTF:scale and SSPLIN, performed relatively well for the temperature variable.

This paper addresses the impact of climate change on the volume of inflow to a reservoir and the volume of downstream water demand by considering three climate change scenarios in an East Azerbaijan river basin. The HadCM3 model was used to estimate possible scenarios of temperature and rainfall for the period 2026–2039 under an emission scenario (A2). A hydrological model (IHACRES) was first calibrated for the basin; and then, a monthly time series of future temperatures and rainfall were entered into IHACRES. In addition, a 14-year time series of monthly runoff was simulated for 2026–2039. Modeling results indicated that the average long-term annual runoff volume decreased by 0.7% relative to the base period (1987–2000). However, by assuming a nonchanging cultivation area, the average long-term annual water demand volume for crops increased by 16%. Both simulation and optimization models of reservoir operation were used. The simulation of reservoir performance in the delivery of water demand wa...