Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

Abstract

Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP). For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity), drought propagation features (pooling, attenuation, lag, lengthening), and hydrological drought typology (<i>classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought</i>). <br><br> Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of <i>classical rainfall deficit droughts</i>, and an underestimation of <i>wet-to-dry-season droughts</i> and snow-related droughts. Furthermore, almost no <i>composite droughts</i> were simulated for slowly responding areas, while many multi-year drought events were expected in these systems. <br><br> We conclude that most drought propagation processes are reasonably well reproduced by the ensemble mean of large-scale models in contrasting catchments in Europe. Challenges, however, remain in catchments with cold and semi-arid climates and catchments with large storage in aquifers or lakes. This leads to a high uncertainty in hydrological drought simulation at large scales. Improvement of drought simulation in large-scale models should focus on a better representation of hydrological processes that are important for drought development, such as evapotranspiration, snow accumulation and melt, and especially storage. Besides the more explicit inclusion of storage in large-scale models, also parametrisation of storage processes requires attention, for example through a global-scale dataset on aquifer characteristics, improved large-scale datasets on other land characteristics (e.g. soils, land cover), and calibration/evaluation of the models against observations of storage (e.g. in snow, groundwater).