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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/nhess-2017-352
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Research article
24 Oct 2017
Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Natural Hazards and Earth System Sciences (NHESS).
Intensity-Duration-Frequency (IDF) rainfall curves in Senegal
Youssouph Sane1, Geremy Panthou2, Ansoumana Bodian3, Theo Vischel2, Thierry Lebel2, Honore Dacosta4, Guillaume Quantin2, Catherine Wilcox2, Ousmane Ndiaye1, Aida Diongue-Niang1, and Marianne Diop Kane1 1Agence Nationale de l’Aviation Civile et de la Météorologie (ANACIM), Dakar, Sénégal
2Univ. Grenoble Alpes, IRD, CNRS, Grenoble INP, IGE, 38000 Grenoble, France
3Laboratoire Leidi, Université Gaston Berger, Saint Louis, Sénégal
4Département de Géographie, Université Cheikh Anta Diop, Dakar, Sénégal
Abstract. Urbanization resulting from a sharply increasing demographic pressure and the development of infrastructures have made the populations of many tropical areas more vulnerable to extreme rainfall hazards. Characterizing extreme rainfall distribution in a coherent way in space and time is thus becoming an overarching need that requires using appropriate models of IDF curves. Using 14 series of 5-min rainfall records (aggregated at a basis time-step of 1 h) collected in Senegal, a comparison of two GEV&scaling models is carried out, leading to adopt the most parsimonious one, built around four parameters. A bootstrap approach is proposed to compute the uncertainty associated with the estimation of these 4 parameters and of the related rainfall return levels for durations ranging from 1 h to 24 h. This study confirms previous works showing that simple scaling holds for characterizing the time-space structure of extreme rainfall in tropical regions such as sub-Saharan Africa. It further provides confidence intervals for the parameter estimates, and shows that the uncertainty linked to the estimation of the GEV parameters, is 3 to 4 times larger than the uncertainty linked to the inference of the scaling parameter. From this model, maps of IDF parameters over Senegal are produced, providing a spatial vision of their organization over the country, with a North to South gradient for the location and scale parameters of the GEV. An influence of the distance from the ocean was found for the scaling parameter. It is acknowledged in conclusion that climate change renders the inference of IDF curves sensitive to increasing non stationarity effects, requiring to warn end-users that they should be used with care and discernment.

Citation: Sane, Y., Panthou, G., Bodian, A., Vischel, T., Lebel, T., Dacosta, H., Quantin, G., Wilcox, C., Ndiaye, O., Diongue-Niang, A., and Diop Kane, M.: Intensity-Duration-Frequency (IDF) rainfall curves in Senegal, Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2017-352, in review, 2017.
Youssouph Sane et al.
Youssouph Sane et al.
Youssouph Sane et al.

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Short summary
Urbanization resulting from a sharply increasing demographic pressure and the development of infrastructures have made the populations of many tropical areas more vulnerable to extreme rainfall hazards. Characterizing extreme rainfall distribution is thus becoming an overarching need for hydrological applications. Using 14 tipping-bucket rain-gauges series, this study provides IDF curves and uncertainties over Senegal. Climate change requires to warn end-users that they should be used with care.
Urbanization resulting from a sharply increasing demographic pressure and the development of...
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