Assessing Maize Water Productivity and Management Strategies with AquaCrop under Semi-Arid Conditions in Morocco

Mohamed Amine BENALY^1*Mohamed Hakim Kharrou²El Houssaine BOURAS³Youssef Brouziyne⁴Alyene Brih⁵Adnane Beniaich⁶Abdelghani Chehbouni³Lhoussaine Bouchaou^2,7

• ¹International Water Research Institute (IWRI), Mohammed VI Polytechnic University, Ben Guerir, Morocco
• ²International Water Research Institute (IWRI), Mohammed VI Polytechnic University, Benguerir, Morocco
• ³Center for Remote Sensing Applications (CRSA), Mohammed VI Polytechnic University, Benguerir, Morocco
• ⁴MENA Office, International Water Management Institute, Giza, Egypt
• ⁵Al-Moutmir Program, OCP Group, Casablanca, Morocco
• ⁶Agricultural Innovation and Technology Transfer Center, College of Agriculture and Environmental Sciences, Mohammed VI Polytechnic University, Benguerir, Morocco
• ⁷Laboratory of Applied Geology and Geo-Environment, Faculty of Sciences,, Universite Ibn Zohr Faculte des Sciences Agadir, Agadir, Morocco

Climate change is increasingly constraining agricultural productivity, particularly for smallholder farmers in semi-arid regions. Rising demand for water and other agricultural inputs necessitates the use of process-based modeling tools to optimize agricultural practices and support water management. The limited application of the AquaCrop model to silage maize in the Souss-Massa region underscores the need for site-specific calibration to improve model reliability and optimize crop management practices. This study aims (i) to evaluate, for the first time, the ability of the AquaCrop model in simulating canopy cover (CC), total soil water content (SWC), and silage maize biomass in the Souss-Massa region, using data collected from 17 fields during the 2022-2024 growing seasons, and (ii) to study the effects of management practices such as mulching, shifting sowing dates, and irrigation management scenarios on silage maize yield and water productivity as climate change adaptation strategies. AquaCrop demonstrated high performance in estimating CC, SWC, and final above‑ground biomass, with coefficients of determination (R2) ranging from 0.93 to 0.98 and Nash-Sutcliffe Efficiency (NSE) above 0.94. Root Mean Square Error (RMSE) varied slightly, from 7.0-7.25% for CC, 5.71-7.56 mm for SWC, and 0.74-1.12 t ha-1 for biomass. Scenario analysis indicated that synthetic mulch reduced actual evapotranspiration (ETc act) by 17% and improved water productivity by 35%. Advancing the sowing date by 40 days improved above‑ground biomass by 8% and a 14% in transpiration‑based productivity (WPTr). Irrigation triggered at 120% depletion of readily available water (RAW) reduced soil evaporation by 41%, improve ET‑based water productivity by 14% and maintains 95 % of the reference yield compared to farmers’ irrigation practices. Application of a 75% ETc (crop evapotranspiration under standard conditions) deficit-irrigation strategy represents an optimal trade-off, reducing water use by 26%, maintaining 94% of biomass. These results confirm that the AquaCrop model is a valuable tool for designing management practices that enhance water conservation and productivity in semi-arid regions.