In the context of growing evidence of climate change and the fact that agriculture uses about 70% of all the water available for irrigation in semi-arid areas, there is an increasing probability of water scarcity scenarios. Water irrigation optimization is, therefore, one of the main goals of researchers and stakeholders involved in irrigated agriculture. Irrigation scheduling is often conducted based on simple water requirement calculations without accounting for the strong link between water movement in the root zone, soil–water–crop productivity and irrigation expenses. In this work, we present a combined simulation and optimization framework aimed at estimating irrigation parameters that maximize the crop net margin. The simulation component couples the movement of water in a variably saturated porous media driven by irrigation with crop water uptake and crop yields. The optimization component assures maximum gain with minimum cost of crop production during a growing season. An application of the method demonstrates that an optimal solution exists and substantially differs from traditional methods. In contrast to traditional methods, results show that the optimal irrigation scheduling solution prevents water logging and provides a more constant value of water content during the entire growing season within the root zone. As a result, in this case, the crop net margin cost exhibits a substantial increase with respect to the traditional method. The optimal irrigation scheduling solution is also shown to strongly depend on the particular soil hydraulic properties of the given field site.

在气候变化的证据越来越多以及半干旱地区农业使用约 70% 的可用灌溉用水这一事实的背景下，出现缺水情景的可能性越来越大。因此，水灌溉优化是参与灌溉农业的研究人员和利益相关者的主要目标之一。灌溉调度通常基于简单的需水量计算进行，而没有考虑根区水分运动、土壤-水-作物生产力和灌溉费用之间的密切联系。在这项工作中，我们提出了一个综合模拟和优化框架，旨在估计使作物净利润最大化的灌溉参数。模拟组件将灌溉驱动的可变饱和多孔介质中的水运动与作物吸水量和作物产量相结合。优化组件确保在生长季节以最低的作物生产成本获得最大收益。该方法的应用表明存在最优解并且与传统方法有很大不同。与传统方法相比，结果表明，最佳灌溉调度解决方案可防止水涝，并在整个生长季节根区内提供更恒定的含水量值。因此，在这种情况下，作物净边际成本相对于传统方法显着增加。