Adapting to climate change in arid agricultural systems: An optimization model for water-energy-food nexus sustainability

• Published in: Agricultural water management 2024-10, Vol.303, p.109052, Article 109052
• Main Authors: Radmehr, Riza, Brorsen, B. Wade, Shayanmehr, Samira
• Format: Article
• Language: English
• Subjects: Crop pattern; Multi-objective programming; Optimal resource allocation; Sustainable development
• ISSN: 0378-3774; 1873-2283
• DOI: 10.1016/j.agwat.2024.109052

Sustainable management of water, energy, and food (WEF) under climate change will be a significant challenge for arid agricultural systems. This study developed a fractional non-linear multi-objective programming (FNLMOP) model to optimize resource allocation and improve agricultural sustainability in these systems under climate change. The model was designed in the framework of the WEF nexus to simultaneously improved energy productivity (profit/energy), and water productivity (profit/water), while mitigating environmental damage (damage to groundwater resources/output) and ensuring food security in an arid watershed in Iran. The long Ashton research station weather generator (LARS-WG) and the coupled model intercomparison project 6 (CMIP6) were employed to project climate parameters for both future dry and wet conditions. The sustainability of the optimal solutions was then assessed using a hybrid criteria importance through intercriteria correlation (CRITIC)-VIKOR approach. The optimal solutions revealed a reduction in the land under cultivation and produced less water-intensive crops. The optimization model can ensure WEF security, enhancing agricultural system sustainability by optimizing crop cultivation patterns and resource allocation. Current crop choices were highly inefficient with the bigger changes being from the current crops to optimal crops. Climate change showed a substantial but lesser influence on optimal crop choice. [Display omitted] •An optimization model is developed to manage the Water, Energy, Food (WEF) nexus under climate change.•The Long Ashton Research Station Weather Generator is used to project climate parameters for future dry and wet conditions.•The developed approach is applied to a watershed in northeast Iran.•Optimal solutions reduce land use by 24–26 %, increase economic profit by 37 %, and decrease environmental damage by 30 %.•Optimal resource allocations improve WEF security and sustainability under climate change.