Influence of downscaling methods in projecting climate change impact on hydrological extremes of upper Blue Nile basin

Abstract. Methods from two statistical downscaling categories were used to investigate the impact of climate change on high rainfall and flow extremes of the upper Blue Nile basin. The main downscaling differences considered were on the rainfall variable while a generally similar method was applied for temperature. The applied downscaling methods are a stochastic weather generator, LARS-WG, and an advanced change factor method, the Quantile Perturbation Method (QPM). These were applied on 10 GCM runs and two emission scenarios (A1B and B1). The downscaled rainfall and evapotranspiration were input into a calibrated and validated lumped conceptual model. The future simulations were conducted for 2050s and 2090s horizon and were compared with 1980–2000 control period. From the results all downscaling methods agree in projecting increase in temperature for both periods. Nevertheless, the change signal on the rainfall was dependent on the climate model and the downscaling method applied. LARS weather generator was good for monthly statistics although caution has to be taken when it is applied for impact analysis dealing with extremes, as it showed a deviation from the extreme value distribution's tail shape. Contrary, the QPM method was good for extreme cases but only for good quality daily climate model data. The study showed the choice of downscaling method is an important factor to be considered and results based on one downscaling method may not give the full picture. Regardless, the projections on the extreme high flows and the mean main rainy season flow mostly showed a decreasing change signal for both periods. This is either by decreasing rainfall or increasing evapotranspiration depending on the downscaling method.