On the Benefits of Bias Correction Techniques for Streamflow Simulation in Complex Terrain Catchments: A Case-Study for the Chitral River Basin in Pakistan

This work evaluates the suitability of linear scaling (LS) and empirical quantile mapping (EQM) bias correction methods to generate present future hydrometeorological variables (precipitation, temperature, streamflow) over Chitral River Basin, in Hindukush region Pakistan. In particular, LS EQM are applied correct high-resolution statistically downscaled dataset, NEX-GDDP, which comprises 21 state-of-the-art general circulation models (GCMs) from coupled model intercomparison project phase 5 (CMIP5). Raw bias-corrected NEX-GDDP simulations used force (previously calibrated validated) HBV-light hydrological long-term (up 2100) streamflow projections catchment. Our results indicate that using raw leads substantial errors (as compared observations) mean extreme regimes. Nevertheless, application solves these problems, yielding much more realistic plausible for XXI century.