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Sane Y., Panthou G., Bodian A., Vischel T., Lebel Thierry, Dacosta H., Quantin Guillaume, Wilcox C., Ndiaye O., Diongue-Niang A., Kane M. D. (2018). Intensity-duration-frequency (IDF) rainfall curves in Senegal. Natural Hazards and Earth System Sciences, 18 (7), 1849-1866. ISSN 1561-8633

Fichier PDF disponible http://horizon.documentation.ird.fr/exl-doc/pleins_textes/divers18-08/010073598.pdf

Lien direct chez l'éditeur doi:10.5194/nhess-18-1849-2018

Titre
Intensity-duration-frequency (IDF) rainfall curves in Senegal
Année de publication2018
Type de documentArticle référencé dans le Web of Science WOS:000437504900001
AuteursSane Y., Panthou G., Bodian A., Vischel T., Lebel Thierry, Dacosta H., Quantin Guillaume, Wilcox C., Ndiaye O., Diongue-Niang A., Kane M. D.
SourceNatural Hazards and Earth System Sciences, 2018, 18 (7), p. 1849-1866. ISSN 1561-8633
RésuméUrbanization 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 5 min 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 24 h. 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.
Plan de classementHydrologie [062] ; Sciences fondamentales / Techniques d'analyse et de recherche [020]
Descr. géo.SENEGAL
LocalisationFonds IRD [F B010073598]
Identifiant IRDfdi:010073598
Lien permanenthttp://www.documentation.ird.fr/hor/fdi:010073598

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