Drought assessment using local and large-scale forcing data in small catchments

Abstract

Drought is a natural hazard that occurs all over the world with significant impacts. For drought analysis, long time series of hydrometeorological variables are required. In many catchments around the world, insufficient hydrometeorological observations are available. Recently, global gridded re-analysis meteorological datasets with coarse spatial resolutions (0.5º × 0.5º) became available. In this study, the potential use of a largescale dataset at catchment scale was investigated by comparison of drought characteristics. A conceptual, hydrological model was forced with local and large-scale data to simulate time series of discharge, from which hydrological droughts were identified. The study was carried out in two contrasting catchments: Narsjø (Norway) and Upper-Metuje (Czech Republic). Similar results were obtained from drought analysis using either local or large-scale data. This holds for several drought characteristics. These results are encouraging for use of large-scale forcing data for drought research in small catchments with no, or limited observation