@article{fdi:010088222,
  title = {{E}vapotranspiration estimates in a traditional irrigated area in semi-arid {M}editerranean : comparison of four remote sensing-based models},
  author = {{E}lfarkh, {J}. and {S}imonneaux, {V}incent and {J}arlan, {L}ionel and {E}zzahar, {J}. and {B}oulet, {G}illes and {C}hakir, {A}dnane and {E}r-{R}aki, {S}.},
  editor = {},
  language = {{ENG}},
  abstract = {{Q}uantification of actual crop evapotranspiration ({ET}a) over large areas is a critical issue to manage water resources, particularly in semi-arid regions. {I}n this study, four models driven by high resolution remote sensing data were intercompared and evaluated over an heterogeneous and complex traditional irrigated area located in the piedmont of the {H}igh {A}tlas mountain, {M}orocco, during the 2017 and 2018 seasons: (1) {SA}tellite {M}onitoring of {IR}rigation ({SAMIR}) which is a software-based on the {FAO}-56 dual crop coefficient water balance model fed with {S}entinel-2 high-resolution {N}ormalized {D}ifference {V}egetation {I}ndex ({NDVI}) to derive the basal crop coefficient ({K}cb); (2) {S}oil {P}lant {A}tmosphere and {R}emote {S}ensing {E}vapotranspiration ({SPARSE}) which is a surface energy balance model fed with land surface temperature ({LST}) derived from thermal data provided from {L}andsat 7 and 8; (3) a modified version of the {S}huttleworth-{W}allace ({SW}) model which uses the {LST} to compute surface resistances and (4) {METRIC}-{GEE} which is a version of {METRIC} model ("{M}apping {E}vapotranspiration at high {R}esolution with {I}nternalized {C}alibration") that operates on the {G}oogle {E}arth {E}ngine platform, also driven by {LST}. {A}ctual evapotranspiration ({ET}a) measurements from two {E}ddy-{C}ovariance ({EC}) systems and a {L}arge {A}perture {S}cintillometer ({LAS}) were used to evaluate the four models. {O}ne {EC} was used to calibrate {SAMIR} and {SPARSE} ({EC}1) which were validated using the second one ({EC}2), providing a {R}oot {M}ean {S}quare {E}rror ({RMSE}) and a determination coefficient ({R}) of 0.53 mm/day ({R}=0.82) and 0.66 mm/day ({R}=0.74), respectively. {SW} and {METRIC}-{GEE} simulations were obtained respectively from a previous study and {G}oogle {E}arth {E}ngine ({GEE}), therefore no calibration was performed in this study. {T}he four models predict well the seasonal course of {ET}a during two successive growing seasons (2017 and 2018). {H}owever, their performances were contrasted and varied depending on the seasons, the water stress conditions and the vegetation development. {B}y comparing the statistical results between the simulation and the measurements of {ET}a it has been shown that {SAMIR} and {METRIC}-{GEE} are the less scattered and the better in agreement with the {LAS} measurements ({RMSE} equal to 0.73 and 0.68 mm/day and {R} equal to 0.74 and 0.82, respectively). {O}n the other hand, {SPARSE} is less scattered ({RMSE} = 0.90 mm/day, {R} = 0.54) than {SW} which is slightly better correlated ({RMSE} = 0.98 mm/day, {R} = 0.60) with the observations. {T}his study contributes to explore the complementarities between these approaches in order to improve the evapotranspiration mapping monitored with high-resolution remote sensing data},
  keywords = {{E}vapotranspiration modeling ; {R}emote sensing ; {E}nergy balance ; {FAO}-56 ; {I}rrigation ; {MAROC} ; {ZONE} {MEDITERRANEENNE}},
  booktitle = {},
  journal = {{A}gricultural {W}ater {M}anagement},
  volume = {270},
  numero = {},
  pages = {[18 ]},
  ISSN = {0378-3774},
  year = {2022},
  DOI = {10.1016/j.agwat.2022.107728},
  URL = {https://www.documentation.ird.fr/hor/fdi:010088222},
}