@article{fdi:010071358,
  title = {{E}ffects of high spatial and temporal resolution {E}arth observations on simulated hydrometeorological variables in a cropland (southwestern {F}rance)},
  author = {{E}tchanchu, {J}. and {R}ivalland, {V}. and {G}ascoin, {S}. and {C}ros, {J}. and {T}allec, {T}. and {B}rut, {A}. and {B}oulet, {G}illes},
  editor = {},
  language = {{ENG}},
  abstract = {{A}gricultural landscapes are often constituted by a patchwork of crop fields whose seasonal evolution is dependent on specific crop rotation patterns and phenologies. {T}his temporal and spatial heterogeneity affects surface hydrometeorological processes and must be taken into account in simulations of land surface and distributed hydrological models. {T}he {S}entinel-2 mission allows for the monitoring of land cover and vegetation dynamics at unprecedented spatial resolutions and revisit frequencies (20 m and 5 days, respectively) that are fully compatible with such heterogeneous agricultural landscapes. {H}ere, we evaluate the impact of {S}entinel-2-like remote sensing data on the simulation of surface water and energy fluxes via the {I}nteractions between the {S}urface {B}iosphere {A}tmosphere ({ISBA}) land surface model included in the {EX}ternalized {SUR}face ({SURFEX}) modeling platform. {T}he study focuses on the effect of the leaf area index ({LAI}) spatial and temporal variability on these fluxes. {W}e compare the use of the {LAI} climatology from {ECOCLIMAP}-{II}, used by default in {SURFEX}-{ISBA}, and time series of {LAI} derived from the high-resolution {F}ormosat-2 satellite data (8 m). {T}he study area is an agricultural zone in southwestern {F}rance covering 576 km(2) (24 km x 24 km). {A}n innovative plot-scale approach is used, in which each computational unit has a homogeneous vegetation type. {E}valuation of the simulations quality is done by comparing model outputs with in situ eddy covariance measurements of latent heat flux ({LE}). {O}ur results show that the use of {LAI} derived from high-resolution remote sensing significantly improves simulated evapotranspiration with respect to {ECOCLIMAP}-{II}, especially when the surface is covered with summer crops. {T}he comparison with in situ measurements shows an improvement of roughly 0.3 in the correlation coefficient and a decrease of around 30% of the root mean square error ({RMSE}) in the simulated evapotranspiration. {T}his finding is attributable to a better description of {LAI} evolution processes with {F}ormosat-2 data, which further modify soil water content and drainage of soil reservoirs. {E}ffects on annual drainage patterns remain small but significant, i.e., an increase roughly equivalent to 4% of annual precipitation levels with simulations using {F}ormosat-2 data in comparison to the reference simulation values. {T}his study illustrates the potential for the {S}entinel-2 mission to better represent effects of crop management on water budgeting for large, anthropized river basins.},
  keywords = {{FRANCE}},
  booktitle = {},
  journal = {{H}ydrology and {E}arth {S}ystem {S}ciences},
  volume = {21},
  numero = {11},
  pages = {5693--5708},
  ISSN = {1027-5606},
  year = {2017},
  DOI = {10.5194/hess-21-5693-2017},
  URL = {https://www.documentation.ird.fr/hor/fdi:010071358},
}