Stochastic multi-objective modeling for optimization of water-food-energy nexus of irrigated agriculture

Abstract

Irrigated agriculture is the primary user of world's fresh water resources on one hand and the producer of food to feed the world's growing population on the other hand. Water, food, and energy are intertwined in irrigated agricultural systems and an effective and coordinated management of the water-food-energy nexus is needed for the sustainable development of agriculture which is challenging because of large uncertainties involved therein. This paper developed an optimization model for the allocation of resources toward the sustainable management of agricultural water, food, and energy nexus under uncertainty. The model is capable of providing policy makers with the ability to determine optimal policy options among water, energy, and land resources to obtain the maximum system economic benefit and simultaneously minimize environmental impacts. The model is also capable of handling complex uncertainties of random boundary intervals. The model is demonstrated to solve a real-world nexus management problem in an irrigation district in northeast China. Results highlight the sensitivity of food production and environmental pollution to the utilization of water, energy, and land resources. The model is applicable for similar agriculture-centered regions with limited resources.