Irrigation optimization and assessment of deep percolation losses for winter wheat in a semi-arid using the SIMDualKc model

¹ Agrobiotech center, Faculty of Sciences and Techniques, Cadi Ayyad University, Marrakesh, Morocco.
² Center for Remote Sensing Applications, UM6P, Morocco.
³ LMFE, Faculty of Sciences Semlalia, Cadi Ayyad University, Marrakesh, Morocco.
⁴ LMFE, National School of Applied sciences, Cadi Ayyad University - Safi, Morocco.

^* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Abstract

In arid and semi-arid regions, where water resources face increasing pressure, efficient water use in agriculture has become a strategic priority. Although irrigation is essential for agricultural productivity, it can lead to significant water losses if not properly managed. Among these losses, deep percolation (DP) is a key process in the soil water balance. It influences both groundwater recharge and overall irrigation efficiency, thereby directly impacting the sustainability of agricultural systems. This study focuses on wheat cultivation in two experimental plots subjected to contrasting irrigation regimes (with and without water stress) over two growing seasons (2016-2017 and 2017-2018) in the Haouz plain, Morocco. Using the SIMDualKc model, the main objective was to quantify water losses due to deep percolation under different irrigation conditions and to optimize the irrigation strategy. Results revealed that traditional irrigation practices used by farmers caused substantial deep percolation losses, ranging from 203 to 435 mm in the non-stressed plot and from 203 to 307 mm in the stressed plot. By simulating optimized irrigation schedules, the SIMDualKc model enabled an average reduction in deep percolation losses of 88% under both regimes. Irrigation volumes were also reduced by an average of 45% compared to farmer-applied amounts, while maintaining effective water supply to crops. These findings highlight the importance of rational irrigation planning to improve water use efficiency and ensure sustainable agriculture in arid and semi-arid regions.