@article{fdi:010070259,
  title = {{M}odeling water needs and total irrigation depths of maize crop in the south west of {F}rance using high spatial and temporal resolution satellite imagery},
  author = {{B}attude, {M}. and {A}l {B}itar, {A}. and {B}rut, {A}. and {T}allec, {T}. and {H}uc, {M}. and {C}ros, {J}. and {W}eber, {J}. {J}. and {L}huissier, {L}. and {S}imonneaux, {V}incent and {D}emarez, {V}.},
  editor = {},
  language = {{ENG}},
  abstract = {{C}limate change is projected to increase water resources limitation and to impact significantly agricultural production. {A} big challenge for agriculture will be to reduce the amount of water used to fit the environmental constraints, while maintaining a level of production that ensure food security. {I}n this context, we develop a methodology based on high spatial and temporal resolution remote sensing data combined with a semi-empirical crop model coupling the {S}imple {A}lgorithm {F}or {Y}ield estimates ({SAFY}, {D}uchemin et al., 2008, 2015) with the new formulation ({B}attude et al., 2016) to a water balance model adapted from the {FAO}-56 method ({A}llen et al., 1998). {A} module was added to automatically simulate irrigation. {T}he model was used to assess the dynamics of actual {E}vapotranspiration ({ET}ca) and water supplies of maize crop over large areas and during contrasted climatic years in the south west of {F}rance. {I}t was first calibrated and evaluated over an experimental field using four years of {ET}ca measurements. {T}he validation was done over 18 maize fields and larger irrigated zones (135 ha to 450 ha) using total irrigation depths. {T}his work permitted to quantify the ability of different methods to estimate the storage capacity (soil map vs in situ data) and the basal crop coefficient {K}cb (standard vs remotely sensed values) and their impact on total irrigation depths. {G}ood estimations were obtained for {ET}ca ({R}=0.88; {RRMSE}=20%). {T}he model also reproduced correctly the total irrigation depth over the 18 maize fields ({R}=0.79; {RRMSE}=18.8%) and three larger irrigated zones ({R}=0.8; {RRMSE}=42%). {T}he underestimation ({B}ias = -93 mm) is due to several reasons such as errors in soil water storage capacity estimates, but also to an overestimation of water needs by water managers or a potential over-irrigation carried out by farmers. {F}inally, the work demonstrates the high potential of combining a simple agro-meteorological model using only few parameters with satellite imagery for a large-scale monitoring of total irrigation depth.},
  keywords = {{E}vapotranspiration ; {I}rrigation management ; {C}rop model ; {M}aize ; {R}emote sensing ; {FRANCE}},
  booktitle = {},
  journal = {{A}gricultural {W}ater {M}anagement},
  volume = {189},
  numero = {},
  pages = {123--136},
  ISSN = {0378-3774},
  year = {2017},
  DOI = {10.1016/j.agwat.2017.04.018},
  URL = {https://www.documentation.ird.fr/hor/fdi:010070259},
}