@article{fdi:010073598,
  title = {{I}ntensity-duration-frequency ({IDF}) rainfall curves in {S}enegal},
  author = {{S}ane, {Y}. and {P}anthou, {G}. and {B}odian, {A}. and {V}ischel, {T}. and {L}ebel, {T}hierry and {D}acosta, {H}. and {Q}uantin, {G}uillaume and {W}ilcox, {C}. and {N}diaye, {O}. and {D}iongue-{N}iang, {A}. and {K}ane, {M}. {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{U}rbanization resulting from sharply increasing demographic pressure and infrastructure development has made the populations of many tropical areas more vulnerable to extreme rainfall hazards. {C}haracterizing 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. {U}sing a 14 series of 5 min rainfall records collected in {S}enegal, 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. {T}his study confirms previous works showing that simple scaling holds for characterizing the temporal scaling of extreme rainfall in tropical regions such as sub-{S}aharan {A}frica. {I}t 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. {F}rom this model, maps of {IDF} parameters over {S}enegal 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}. {A}n influence of the distance from the ocean was found for the scaling parameter. {I}t 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.},
  keywords = {{SENEGAL}},
  booktitle = {},
  journal = {{N}atural {H}azards and {E}arth {S}ystem {S}ciences},
  volume = {18},
  numero = {7},
  pages = {1849--1866},
  ISSN = {1561-8633},
  year = {2018},
  DOI = {10.5194/nhess-18-1849-2018},
  URL = {https://www.documentation.ird.fr/hor/fdi:010073598},
}