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Global multimodel analysis of drought in runoff for the second half of the twentieth century


Stacke,  Tobias
Terrestrial Hydrology, The Land in the Earth System, MPI for Meteorology, Max Planck Society;

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Van Huijgevoort, M., Hazenberg, P., Van Lanen, H., Teuling, A., Clark, D., Folwell, S., et al. (2013). Global multimodel analysis of drought in runoff for the second half of the twentieth century. Journal of Hydrometeorology, 14, 1535-1552. doi:10.1175/JHM-D-12-0186.

During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether thesemodels are suitable to capture hydrological drought, in terms of runoff, on a global scale. Amultimodel ensemble analysis was carried out to evaluate if 10 such large-scalemodels agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runofffrom 10 global hydrologicalmodels, and their ensemblemedian have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoffand smallest in regions with high runoff. In vast regions, correlation between runoffdrought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoffdrought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoffresponse to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoffresponse was partly overcome and delay in drought propagating from meteorological drought to drought in runoffwas included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures. © 2013 American Meteorological Society.