An Extreme Value Mixture model to assess drought hazard in West Africa

Abdoulaye Sy, Catherine Araujo-Bonjean, Marie-Eliette Dury (), Nourddine Azzaoui () and Arnaud Guillin
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Abdoulaye Sy: CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne
Catherine Araujo-Bonjean: CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne
Marie-Eliette Dury: CERDI - Centre d'Études et de Recherches sur le Développement International - IRD - Institut de Recherche pour le Développement - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne
Nourddine Azzaoui: LMBP - Laboratoire de Mathématiques Blaise Pascal - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne
Arnaud Guillin: LMBP - Laboratoire de Mathématiques Blaise Pascal - CNRS - Centre National de la Recherche Scientifique - UCA - Université Clermont Auvergne

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Abstract: A critical stage in drought hazard assessment is the definition of a drought event, and the measure of its intensity. Actually, the classical approach imposes to all climatic region the same set of thresholds for drought severity classification, hence resulting in a loss of information on rare events in the distribution tails, which are precisely the most important to catch in risk analysis. In order to better assess extreme events, we resort to an extreme value mixture model with a normal distribution for the bulk and a Generalized Pareto distribution for the upper and lower tails, to estimate the intensity of extreme droughts and their occurrence probability. Compare to the standard approach to drought hazard, which relies on a standardized precipitation index and a classification of drought intensity established from the cumulative standard normal distribution function, our approach allows the drought threshold and the occurrence probability of drought to depend on the specific characteristics of each precipitation distribution. An application to the West Africa region shows that the accuracy of our mixture model is higher than that of the standard model. The mixture performs better at modelling the lowest percentiles and specifically the return level of the centennial drought, which is generally overestimated in the standard approach.

Keywords: Mixture model; Generalized pareto distribution; Drought; Extreme value theory (search for similar items in EconPapers)
Date: 2021-07
New Economics Papers: this item is included in nep-agr, nep-isf and nep-rmg
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