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Universität Potsdam (2021)

Drought modeling and forecasting from local to global scales

Samaniego Luis

Titre : Drought modeling and forecasting from local to global scales

Auteur : Samaniego Luis

Université de soutenance : Universität Potsdam

Grade : Habilitation Thesis 2021

Over millennia, droughts could not be understood or defined but rather were associated with mystical connotations. To understand this natural hazards, we first needed to understand the laws of physics and then develop plausible explanations of inner workings of the hydrological cycle. Consequently, modeling and predicting droughts was out of the scope of mankind until the end of the last century. In recent studies, it is estimated that this natural hazard has caused billions of dollars in losses since 1900 and that droughts have affected 2.2 billion people worldwide between 1950 and 2014.

For these reasons, droughts have been identified by the IPCC as the trigger of a web of impacts across many sectors leading to land degradation, migration and substantial socio-economic costs. This thesis summarizes a decade of research carried out at the Helmholtz Centre for Environmental Research on the subject of drought monitoring, modeling, and forecasting, from local to continental scales. The overarching objectives of this study, systematically addressed in the twelve previous chapters, are : 1) Create the capability to seamless monitor and predict water fluxes at various spatial resolutions and temporal scales varying from days to centuries ; 2) Develop and test a modeling chain for monitoring, forecasting and predicting drought events and related characteristics at national and continental scales ; and 3) Develop drought indices and impact indicators that are useful for end-users. Key outputs of this study are : the development of the open source model mHM, the German Drought Monitor System, the proof of concept for an European multi-model for improving water managent from local to continental scales, and the prototype of a crop-yield drought impact model for less

Mots clés  : Drought ; Forecast ; Hydrological modeling


Page publiée le 19 novembre 2021