Bias correction of regional climate model simulation for hydrological climate change over Bouregrag watershed in Morocco

General and regional climate models (GCMs/RCMs) exhibit many systematic biases, which affects the simulation accuracy of the real precipitation patterns and consequently the associated hydrological changes. The common approach used to reduce errors in the climate model output is to apply bias correction methods (BCMs) which attempt to adjust the climate simulation by its observation counterpart. In this study, we applied BCM on simulated rainfall over the Bouregrag basin (Morocco) from CanRCM4 CORDEX RCM using linear SCALING method (SCALING), gamma quantile mapping (GQM) and empirical quantile mapping (EQM). Owing to its high performance compared to the others, we applied the EQM method on climate projections under the RCP4.5 scenario. Results showed a decrease up to -50% in the monthly rainfall for the period 2041-2060 with the exception of August and December exhibiting an increase between +20% and +78%. This study supports the need to bias correct climate data before their use in hydrological models where the bias could be irreversible.