A Food-Energy-Water Nexus approach for land use optimization

Area of Science:

• Agricultural Science
• Environmental Science
• Systems Engineering
• Operations Research

Background:

• Global challenges of land scarcity, diminishing resources (energy, water), and rising food demand necessitate integrated agricultural land management.
• The interconnectedness of food, energy, and water (FEW) systems, known as the Food-Energy-Water Nexus (FEW-N), requires holistic approaches.
• Limited studies address the complex interactions and trade-offs within agricultural FEW-N systems.

Purpose of the Study:

• To develop a systematic engineering framework and quantitative decision-making tools for analyzing and optimizing stressed FEW-N networks in agricultural land use.
• To identify synergistic benefits and explore interactions and trade-offs among food, energy, and water elements.
• To facilitate informed decision-making for social, economic, and environmental goals in agricultural land management.

Main Methods:

• Utilized an experimental station in China as a model system.
• Combined data analytics with mixed-integer nonlinear modeling and optimization techniques.
• Employed a multi-objective optimization strategy with composite FEW-N metrics for trade-off analysis and decision support.

Main Results:

• The developed framework effectively balances multiple objectives and benchmarks competing interests in systematic decision-making.
• Optimal solutions prioritize food production while minimizing water and energy consumption.
• The framework demonstrated robust performance across alternative pathways and diverse climate scenarios.

Conclusions:

• The proposed engineering framework provides a quantitative approach to managing the complexities of the Food-Energy-Water Nexus in agricultural land use.
• The findings support sustainable agricultural practices that enhance food security while conserving critical resources.
• The decision-making tools facilitate robust and adaptable strategies for land management under varying conditions.