Optimizing 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

This study aims to investigate the effects of an optimized sowing calendar for wheat over a surface irrigation scheme in semi-arid region Haouz (Morocco) on water requirements, crop growth and development yield. For that, scenario-based simulation approach based covariance matrix adaptation–evolution strategy (CMA-ES) was proposed optimize both spatiotemporal distribution dates schedules, then evaluate using 2011–2012 growing season dataset. Six scenarios were simulated compared identify most optimal calendar. The obtained results showed that with reference existing patterns, early leads higher yields late (from 7.40 5.32 t/ha). Compared actual conditions area, spatial heterogeneity is highly reduced, which increased equity between farmers. also proportion plots irrigated time can be 40% 82%) schedules previous optimization, did not take into consideration optimization. Furthermore, considerable reduction more than applied achieved by optimizing dates. Thus, this relevant managers farmers since it provides insight consequences their agricultural practices regarding scheduling implemented recommend best adopt.