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Abstract

Drought is a complex phenomenon due to its spatial and temporal variability, hence, the uncertainty related to its estimation is large. It is customary to use standardized drought indices to assess drought, and mostly fitting a probability distribution function is the primary step. Most studies focus on probability distribution function selection based on historical observation data, and climate projection studies use these studies as a benchmark. However, this stationary distribution assumption in drought index estimation methodologies (for future climate scenarios) might not be valid. Therefore, different distributions are tested under changing climate for estimating SPI and SPEI drought indices. Additionally, we assessed the impact of climate change on streamflow drought at Grote Nete catchment, Belgium, by forcing climate projection data on a new geohydrological model called SWAT+gwflow.The Weibull distribution is appropriate for SPI for both future scenarios (rcp 2.6 and rcp 8.5) for a 1-month accumulation period better than the gamma distribution, which is mostly preferred to fit precipitation. However, the gamma distribution remains valid for the other accumulation periods. As for SPEI, Pearson type 3 (PE3) is appropriate for fitting the water balance (difference between precipitation and potential evapotranspiration) for both shorter and longer accumulation periods. This is contrary to a previous study made using observations, which suggested Generalized extreme value distribution (GEV) for Belgium. Finally, the hydrological drought assessment on the Grote Nete watershed indicated a sharp increase in drought frequency for a one-month accumulation period, where the amount of drought events increased by a factor of 5.