@article{fdi:010082731,
  title = {{I}dentifying drivers of streamflow extremes in {W}est {A}frica to inform a nonstationary prediction model},
  author = {{C}hun, {K}. {P}. and {D}ieppois, {B}. and {H}e, {Q}. and {S}idibe, {M}. and {E}den, {J}. and {P}aturel, {J}ean-{E}mmanuel and {M}ah{\'e}, {G}il and {R}ouch{\'e}, {N}athalie and {K}laus, {J}. and {C}onway, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{W}est {A}frica exhibits decadal patterns in the behaviour of droughts and floods, creating challenges for effective water resources management. {P}roposed drivers of prolonged shifts in hydrological extremes include the impacts of land-cover change and climate variability in the region. {H}owever, while future land-degradation or land-use are highly unpredictable, recent studies suggest that prolonged periods of high-flows or increasing flood occurrences could be predicted by monitoring sea-surface temperature ({SST}) anomalies in the different ocean basins. {I}n this study, we thus examine: i) what ocean basins would be the most suitable for future seamless flood-prediction systems; ii) how these ocean basins affect high-flow extremes (hereafter referred as extreme streamflow); and iii) how to integrate such nonstationary information in flood risk modelling. {W}e first use relative importance analysis to identify the main {SST} drivers modulating hydrological conditions at both interannual and decadal timescales. {A}t interannual timescales, {P}acific {N}ino ({ENSO}), tropical {I}ndian {O}cean ({TIO}) and eastern {M}editerranean ({EMED}) constitute the main climatic controls of extreme streamflow over {W}est {A}frica, while the {SST} variability in the {N}orth and tropical {A}tlantic, as well as decadal variations of {TIO} and {EMED} are the main climatic controls at decadal timescales. {U}sing regression analysis, we then suggest that these {SST} drivers impact hydrological extremes through shifts in the latitudinal location and the strength of the {I}ntertropical {C}onvergence {Z}one ({ITCZ}) and the {W}alker circulation, impacting the {W}est {A}frican {M}onsoon, especially the zonal and meridional atmospheric water budget. {F}inally, a nonstationary extreme model, with climate information capturing regional circulation patterns, reveals that {EMED} {SST} is the best predictor for nonstationary streamflow extremes, particularly across the {S}ahel. {P}redictability skill is, however, much higher at the decadal timescale, and over the {S}enegal than the {N}iger catchment. {T}his might be due to stronger impacts of land-use (-cover) and/or catchment properties (e.g. the {I}nner {D}elta) on the {N}iger {R}iver flow. {O}verall, a nonstationary framework for floods can also be applied to drought risk assessment, contributing to water regulation plans and hazard prevention, over {W}est {A}frica and potentially other parts of the world.},
  keywords = {{T}ropical indian ocean ({TIO}) ; {E}astern mediterranean ({EMED}) ; {F}loods ; {S}treamflow extremes ; {N}onstationary extreme model ; {W}est africa ; {AFRIQUE} {DE} {L}'{OUEST} ; {OCEAN} {INDIEN} ; {MEDITERRANEE} ; {NIGER} {BASSIN} ; {SENEGAL} {BASSIN} ; {ZONE} {GUINEENNE} ; {ZONE} {SAHELIENNE}},
  booktitle = {},
  journal = {{W}eather and {C}limate {E}xtremes},
  volume = {33},
  numero = {},
  pages = {100346 [13 p.]},
  ISSN = {2212-0947},
  year = {2021},
  DOI = {10.1016/j.wace.2021.100346},
  URL = {https://www.documentation.ird.fr/hor/fdi:010082731},
}