@article{fdi:010077459,
  title = {{A}bility of a soil-vegetation-atmosphere transfer model and a two-source energy balance model to predict evapotranspiration for several crops and climate conditions},
  author = {{B}igeard, {G}. and {C}oudert, {B}. and {C}hirouze, {J}. and {E}r-{R}aki, {S}. and {B}oulet, {G}illes and {C}eschia, {E}. and {J}arlan, {L}ionel},
  editor = {},
  language = {{ENG}},
  abstract = {{T}he heterogeneity of {A}groecosystems, in terms of hydric conditions, crop types and states, and meteorological forcing, is difficult to characterize precisely at the field scale over an agricultural landscape. {T}his study aims to perform a sensitivity study with respect to the uncertain model inputs of two classical approaches used to map the evapotranspiration of agroecosystems: (1) a surface energy balance ({SEB}) model, the {T}wo-{S}ource {E}nergy {B}alance ({TSEB}) model, forced with thermal infrared ({TIR}) data as a proxy for the crop hydric conditions, and (2) a soil- vegetation-atmosphere transfer ({SVAT}) model, the {SE}t{H}y{S} model, where hydric conditions are computed from a soil water budget. {T}o this end, the models' skill was compared using a large and unique in situ database covering different crops and climate conditions, which was acquired over three experimental sites in southern {F}rance and {M}orocco. {O}n average, the models provide 30 min estimations of latent heat flux ({LE}) with a {RMSE} of around 55 {W} m(-2) for {TSEB} and 47 {W} m(-2) for {SE}t{H}y{S}, and estimations of sensible heat flux ({H}) with a {RMSE} of around 29 {W} m(-2) for {TSEB} and 38 {W} m(-2) for {SE}t{H}y{S}. {A} sensitivity analysis based on realistic errors aimed to estimate the potential decrease in performance induced by the spatialization process. {F}or the {SVAT} model, the multi-objective calibration iterative procedure ({MCIP}) is used to determine and test different sets of parameters. {TSEB} is run with only one set of parameters and provides acceptable performance for all crop stages apart from the early growing season ({LAI} < 0.2 m(2)m(-2)) and when hydric stress occurs. {A}n in-depth study on the {P}riestley- {T}aylor key parameter highlights its marked diurnal cycle and the need to adjust its value to improve flux partitioning between the sensible and latent heat fluxes (1.5 and 1.25 for {F}rance and {M}orocco, respectively). {O}ptimal values of 1.8-2 were highlighted under cloudy conditions, which is of particular interest due to the emergence of low-altitude drone acquisition. {U}nder developed vegetation ({LAI} > 0.8 m(2)m(-2)) and unstressed conditions, using sets of parameters that only differentiate crop types is a valuable trade-off for {SE}t{H}y{S}. {T}his study provides some scientific elements regarding the joint use of both approaches and {TIR} imagery, via the development of new data assimilation and calibration strategies.},
  keywords = {},
  booktitle = {},
  journal = {{H}ydrology and {E}arth {S}ystem {S}ciences},
  volume = {23},
  numero = {12},
  pages = {5033--5058},
  ISSN = {1027-5606},
  year = {2019},
  DOI = {10.5194/hess-23-5033-2019},
  URL = {https://www.documentation.ird.fr/hor/fdi:010077459},
}