Robust optimization for sustainable agricultural management of the water-land-food nexus under uncertainty

Abstract

Global climate change has led to a severe loss of water and land resources and has exacerbated food crisis concerns. The water-land-food nexus in agricultural irrigation systems is receiving increasing attention. However, for sustainable food production, land and water resources must be managed effectively. The allocation of agricultural water and land resource components involves a large amount of uncertainty regarding readily available water. A robust optimization model of water-land-food nexus for agricultural irrigation systems is presented in this study, which comprehensively considers the uncertainty of the system and optimizes the allocation of scarce water and land resources for diverse crops to maximize irrigation system productivity. Using the Yellow River Basin as a case study, the results revealed that the developed optimization model can successfully resolve the system uncertainty perturbation and provide the finest potential allocation of water and land resources. Its irrigation system productivity can attain 1.6843–1.7143 kg/m3, which is improved by 6.6%–8.5%, and it can also reveal the interaction between WLF-nexus systems. This study also discovered that crop type and proportion can be modified to improve resource-use efficiency based on regional water and land resource endowment. Finally, policy implications are proposed to enhance resource utilization efficiency.