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Investigating the interactions between data assimilation and post-processing in hydrological ensemble forecasting

Abstract : We investigate how data assimilation and post-processing contribute, either separately or together, to the skill of a hydrological ensemble forecasting system. Based on a large catchment set, we compare four forecasting options: without data assimilation and post-processing, without data assimilation but with post-processing, with data assimilation but without post-processing, and with both data assimilation and post-processing. Our results clearly indicate that both strategies have complementary effects. Data assimilation has mainly a very positive effect on forecast accuracy. Its impact however decreases with increasing lead time. Post-processing, by accounting specifically for hydrological uncertainty, has a very positive and longer lasting effect on forecast reliability. As a consequence, the use of both techniques is recommended in hydrological ensemble forecasting.
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https://hal.inrae.fr/hal-02600032
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Submitted on : Tuesday, December 1, 2020 - 8:56:48 AM
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F. Bourgin, M.H. Ramos, G. Thirel, V. Andreassian. Investigating the interactions between data assimilation and post-processing in hydrological ensemble forecasting. Journal of Hydrology, Elsevier, 2014, 519 (Part D), pp.2775-2784. ⟨10.1016/j.jhydrol.2014.07.054⟩. ⟨hal-02600032⟩

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