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Abstract Simulated soil moisture is increasingly used to characterize agricultural droughts but its parametric uncertainty, which essentially affects all hydrological fluxes and state variables, is rarely considered for identifying major drought events. In this study, a high-resolution, 200-member ensemble of land surface hydrology simulations obtained with the mesoscale Hydrologic Model is used to investigate the effects of the parametric uncertainty on drought statistics such as duration, extension, and severity. Simulated daily soil moisture fields over Germany at the spatial resolution of 4 × 4 km2 from 1950 to 2010 are used to derive a hydrologically consistent soil moisture index (SMI) representing the monthly soil water quantile at every grid cell. This index allows a quantification of major drought events in Germany. Results of this study indicated that the large parametric uncertainty inherent to the model did not allow discriminating major drought events without a significant classification error. The parametric uncertainty of simulated soil moisture exhibited a strong spatiotemporal variability, which significantly affects all derived drought statistics. Drought statistics of events occurring in summer with at most 6 months duration were found to be more uncertain than those occurring in winter. Based on the ensemble drought statistics, the event from 1971 to 1974 appeared to have a 67% probability of being the longest and most severe drought event since 1950. Results of this study emphasize the importance of accounting for the parametric uncertainty for identifying benchmark drought events as well as the fact that using a single model simulation would very likely lead to inconclusive results.
Samaniego et al. (Fri,) studied this question.