@article{fdi:010063111,
  title = {{P}otential of soil moisture observations in flood modelling : estimating initial conditions and correcting rainfall},
  author = {{M}assari, {C}. and {B}rocca, {L}. and {M}oramarco, {T}. and {T}ramblay, {Y}ves and {L}escot, {J}. {F}. {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{R}ainfall runoff ({RR}) models are fundamental tools for reducing flood hazards. {A}lthough several studies have highlighted the potential of soil moisture ({SM}) observations to improve flood modelling, much research has still to be done for fully exploiting the evident connection between {SM} and runoff. {A}s a way of example, improving the quality of forcing data, i.e. rainfall observations, may have a great benefit in flood simulation. {S}uch data are the main hydrological forcing of classical {RR} models but may suffer from poor quality and record interruption issues. {T}his study explores the potential of using {SM} observations to improve rainfall observations and set a reliable initial wetness condition of the catchment for improving the capability in flood modelling. {I}n particular, a {RR} model, which incorporates {SM} for its initialization, and an algorithm for rainfall estimation from {SM} observations are coupled using a simple integration method. {T}he study carried out at the {V}alescure experimental catchment ({F}rance) demonstrates the high information content retained by {SM} for {RR} transformation, thus giving new possibilities for improving hydrological applications. {R}esults show that an appropriate configuration of the two models allows obtaining improvement in flood simulation up to 15% in mean and 34% in median {N}ash {S}utcliffe performances as well as a reduction of the median error in volume and on peak discharge of about 30% and 15%, respectively.},
  keywords = {{S}oil moisture ; {F}loods ; {R}ainfall ; {FRANCE} ; {ZONE} {MEDITERRANEENNE}},
  booktitle = {},
  journal = {{A}dvances in {W}ater {R}esources},
  volume = {74},
  numero = {},
  pages = {44--53},
  ISSN = {0309-1708},
  year = {2014},
  DOI = {10.1016/j.advwatres.2014.08.004},
  URL = {https://www.documentation.ird.fr/hor/fdi:010063111},
}