@article{fdi:010078915,
  title = {{V}alidation of the {AROME}, {ALADIN} and {WRF} meteorological models for flood forecasting in {M}orocco},
  author = {{E}l {K}halki, {E}. and {T}ramblay, {Y}ves and {A}mengual, {A}. and {H}omar, {V}. and {R}omero, {R}. and {S}aidi, {M}. {E}. and {A}laouri, {M}.},
  editor = {},
  language = {{ENG}},
  abstract = {{F}lash floods are common in small {M}editerranean watersheds and the alerts provided by real-time monitoring systems provide too short anticipation times to warn the population. {I}n this context, there is a strong need to develop flood forecasting systems in particular for developing countries such as {M}orocco where floods have severe socio-economic impacts. {I}n this study, the {AROME} ({A}pplication of {R}esearch to {O}perations at {M}esoscale), {ALADIN} ({A}ire {L}imited {D}ynamic {A}daptation {I}nternational {D}evelopment) and {WRF} ({W}eather {R}esearch and {F}orecasting) meteorological models are evaluated to forecast flood events in the {R}heraya and {O}urika basin located in the {H}igh-{A}tlas {M}ountains of {M}orocco. {T}he model evaluation is performed by comparing for a set of flood events the observed and simulated probabilities of exceedances for different precipitation thresholds. {I}n addition, two different flood forecasting approaches are compared: the first one relies on the coupling of meteorological forecasts with a hydrological model and the second one is a based on a linear relationship between event rainfall, antecedent soil moisture and runoff. {T}hree different soil moisture products (in-situ measurements, {E}uropean {S}pace {A}gency's {C}limate {C}hange {I}nitiative {ESA}-{CCI} remote sensing data and {ERA}5 reanalysis) are compared to estimate the initial soil moisture conditions before flood events for both methods. {R}esults showed that the {WRF} and {AROME} models better simulate precipitation amounts compared to {ALADIN}, indicating the added value of convection-permitting models. {T}he regression -based flood forecasting method outperforms the hydrological model-based approach, and the maximum discharge is better reproduced when using the {WRF} forecasts in combination with {ERA}5. {T}hese results provide insights to implement robust flood forecasting approaches in the context of data scarcity that could be valuable for developing countries such as {M}orocco and other {N}orth {A}frican countries.},
  keywords = {flood forecasting ; {AROME} ; {ALADIN} ; {WRF} ; {ESA}-{CCI} ; {ERA}5 ; {R}heraya ; {O}urika ; {M}orocco ; {MAROC} ; {HAUT} {ATLAS} ; {RHERAYA} {BASSIN} ; {OURIKA} {BASSIN}},
  booktitle = {},
  journal = {{W}ater},
  volume = {12},
  numero = {2},
  pages = {437 [18 ]},
  year = {2020},
  DOI = {10.3390/w12020437},
  URL = {https://www.documentation.ird.fr/hor/fdi:010078915},
}