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Volume 18, issue 7 | Copyright
Nat. Hazards Earth Syst. Sci., 18, 1849-1866, 2018
https://doi.org/10.5194/nhess-18-1849-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 05 Jul 2018

Research article | 05 Jul 2018

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 Mariane Diop Kane1 Youssouph Sane et al.
  • 1Agence Nationale de l'Aviation Civile et de la Météorologie (ANACIM), Dakar, Senegal
  • 2Univ. Grenoble Alpes, IRD, CNRS, Grenoble INP, IGE, 38000 Grenoble, France
  • 3Laboratoire Leidi, Université Gaston Berger, Saint-Louis, Senegal
  • 4Département de Géographie, Université Cheikh Anta Diop, Dakar, Senegal

Abstract. Urbanization resulting from sharply increasing demographic pressure and infrastructure development has 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 intensity–duration–frequency (IDF) curves. Using a 14 series of 5min rainfall records collected in Senegal, a comparison of two generalized extreme value (GEV) and scaling models is carried out, resulting in the selection of the more parsimonious one (four parameters), as the recommended model for use. A bootstrap approach is proposed to compute the uncertainty associated with the estimation of these four parameters and of the related rainfall return levels for durations ranging from 1 to 24h. This study confirms previous works showing that simple scaling holds for characterizing the temporal scaling 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, which requires warning end-users that such tools should be used with care and discernment.

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Urbanization, resulting from a sharply increasing demographic pressure and the development of infrastructure, has made the population of many tropical areas more vulnerable to extreme rainfall hazards. Characterizing extreme rainfall distribution is thus becoming an overarching need in hydrological applications. Using 14 tipping-bucket rain-gauge series, this study provides IDF curves and uncertainties over Senegal. Climate change requires warning 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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