@article{fdi:010086836,
  title = {{A} sensitivity analysis of a {FAO}-56 dual crop coefficient-based model under various field conditions},
  author = {{L}aluet, {P}. and {O}livera-{G}uerra, {L}. and {R}ivalland, {V}. and {S}imonneaux, {V}incent and {I}nglada, {J}. and {B}ellvert, {J}. and {E}r-raki, {S}. and {M}erlin, {O}.},
  editor = {},
  language = {{ENG}},
  abstract = {{FAO}-56 dual crop coefficient ({FAO}-2{K}c) based model are increasingly applied at large scale for agricultural water monitoring, requiring field-scale data over the spatial extent of interest. {G}iven the lack of in-situ measurements, satellite products can be used to estimate indirectly the parameters through calibration. {H}owever, a lack of knowledge about model sensitivity can lead to suboptimal use of satellite data. {T}his study aims to analyze the sensitivity of {SAMIR}, a {FAO}-2{K}c-based model using satellite data. {T}he {S}obol method was applied for evapo-transpiration ({ET}) and deep percolation ({DP}) simulations on 37 contrasted agricultural seasons. {R}esults indicate that {SAMIR}'s sensitivity mainly depends on the modeled water stress. {W}e proposed a proxy for the model sensitivity which can determine 84% (73%) of the {ET} ({DP}) among the agricultural seasons. {A}n interaction analysis allowed reducing the calibration problem to the adjustment of only two parameters (a_{K}cb and {Z}r_max), accounting for most of the sensitivity.},
  keywords = {{FAO}-56 model ; {S}obol sensitivity analysis ; {E}vapotranspiration ; {D}eep percolation ; {R}emote sensing ; {C}alibration},
  booktitle = {},
  journal = {{E}nvironmental {M}odelling and {S}oftware},
  volume = {160},
  numero = {},
  pages = {105608 [13 p.]},
  ISSN = {1364-8152},
  year = {2023},
  DOI = {10.1016/j.envsoft.2022.105608},
  URL = {https://www.documentation.ird.fr/hor/fdi:010086836},
}