@article{fdi:010083150,
  title = {{O}ptimizing the sowing date to improve water management and wheat yield in a large irrigation scheme, through a remote sensing and an evolution strategy-based approach},
  author = {{B}elaqziz, {S}. and {K}habba, {S}. and {K}harrou, {M}. {H}. and {B}ouras, {E}. and {E}r-{R}aki, {S}. and {C}hehbouni, {A}bdelghani},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his study aims to investigate the effects of an optimized sowing calendar for wheat over a surface irrigation scheme in the semi-arid region of {H}aouz ({M}orocco) on irrigation water requirements, crop growth and development and on yield. {F}or that, a scenario-based simulation approach based on the covariance matrix adaptation-evolution strategy ({CMA}-{ES}) was proposed to optimize both the spatiotemporal distribution of sowing dates and the irrigation schedules, and then evaluate wheat crop using the 2011-2012 growing season dataset. {S}ix sowing scenarios were simulated and compared to identify the most optimal spatiotemporal sowing calendar. {T}he obtained results showed that with reference to the existing sowing patterns, early sowing of wheat leads to higher yields compared to late sowing (from 7.40 to 5.32 t/ha). {C}ompared with actual conditions in the study area, the spatial heterogeneity is highly reduced, which increased equity between farmers. {T}he results also showed that the proportion of plots irrigated in time can be increased (from 40% to 82%) compared to both the actual irrigation schedules and to previous results of irrigation optimization, which did not take into consideration sowing dates optimization. {F}urthermore, considerable reduction of more than 40% of applied irrigation water can be achieved by optimizing sowing dates. {T}hus, the proposed approach in this study is relevant for irrigation managers and farmers since it provides an insight on the consequences of their agricultural practices regarding the wheat sowing calendar and irrigation scheduling and can be implemented to recommend the best practices to adopt.},
  keywords = {seeding date ; irrigation scheduling ; evolutionary algorithm ; optimization ; water resources ; wheat ; grain yield ; {MAROC} ; {TENSIFT} {BASSIN}},
  booktitle = {},
  journal = {{R}emote {S}ensing},
  volume = {13},
  numero = {18},
  pages = {3789 [27 p.]},
  year = {2021},
  DOI = {10.3390/rs13183789},
  URL = {https://www.documentation.ird.fr/hor/fdi:010083150},
}