农业用地优化决策的食品-能源-水关联评价方法

农业用地系统优化决策旨在通过统筹食品-能源-水(FEW)和用地资源、经济投入以及环境可持续发展问题,在满足生产需求的基础上,实现节能增效等多个优化目标。目前,以FEW全生产要素为主开展实际食品-能源-水关联(FEW-N)的农业用地系统研究,尚缺乏能够全面量化评估不同决策影响的系统性评估指标。针对此现状,从资源合理利用角度出发,在中国山东省选择相关区域为典型研究对象,开展农业用地系统多目标优化和评估研究,以实现资源利用效率最大化和投入产出比最高为系统目标,提出一套系统多目标优化方法和综合评估指标,以实现用地和FEW资源配置的系统折衷最优。研究结果显示,以双线性整合方式为基础构建的FEW-N综合度量指标不仅能够高效求解多目标优化问题,获得系统折衷最优的用地和资源配置方案,还可以通过可视化方式对不同方案进行量化评估,提供决策依据。

Towards a food-energy-water nexus metric for agricultural land use optimization and decision

Food, energy and water (FEW) are the three essential pillars for human-being and society. Agricultural land is the largest ecosystem to provide food for human by consuming a large amount of energy and water. As population increases, there is an increasing pressure to address issues of the resource allocation and other conflicting objectives. Systematic thinking based on food-energy-water nexus (FEW-N) is necessary for the modeling and the optimization of the systems. However, challenges arise in making decisions among conflicting objectives, such as the profit, the food demand, the friendly environment, and the efficient use of water and energy. Despite the global studies of data, models and multi-objective optimization techniques, the holistic studies navigating the land use problems, exploring the trade-offs of land and the FEW resources are still few and far between, as well as the general and quantitative metrics for different solutions of the land use systems. Taking an experimental station in Shandong province as a FEW-N land use system, series of composite FEW-N metrics are developed to help solve the multiobjective optimization problem with systematic assessments. Computational results indicate that the trade-offs among diverse stakeholders can be achieved most effectively and consistently based on the composite FEW-N metrics. All objective-related solutions can be quantitatively evaluated by the proposed metrics, and the geometric metric GA can provide a visualization tool for comparisons of different solutions, to help the policy-makers to adjust policies across different stakeholders, production sectors, and technologies.