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An optimal modelling approach for managing agricultural water-energy-food nexus under uncertainty

Author:
Li, Mo, Fu, Qiang, Singh, Vijay P., Ji, Yi, Liu, Dong, Zhang, Chenglong, Li, Tianxiao
Source:
The Science of the total environment 2019 v.651 pp. 1416-1434
ISSN:
0048-9697
Subject:
carbon footprint, case studies, crops, decision making, energy, food production, freshwater, issues and policy, land resources, models, quantitative analysis, uncertainty, China
Abstract:
Agriculture is the largest user of freshwater which is essential for food production. Water, energy and food are closely intertwined, as both water and energy are critical inputs for food production. Increasing pressure from shortages of resources and increasing demand for food reinforce the need for optimal management of the water, energy, and food nexus. Uncertainties caused by natural conditions and human activities complicate the optimal allocation. An integrated model, called AWEFSM, was developed for the sustainable management of limited water-energy-food resource in an agricultural system by incorporating multi-objective programming, nonlinear programming, and intuitionistic fuzzy numbers into a general framework. The AWEFSM model is capable of identifying the tradeoffs of water, energy and land resources among various subareas and crops, generating high-profile and environment-friendly strategies and policies, and addressing parameter uncertainties associated with the fluctuations of natural resources and variation of socioeconomic activities. The AWEFSM model was solved, considering nonlinear membership and non-membership functions with both optimistic and pessimistic views of decision makers, and was demonstrated for a real-world case study in northwest China. The interrelationships and trade-offs among system components, including water supply-demand, energy supply-demand, land demand, food production, as well as water and energy footprints, were quantitatively analyzed under different scenarios. The AWEFSM model is applicable for similar regions dominated by agriculture with limited resource supplies to determine water-energy-food strategies under uncertainty.
Agid:
6154370