农业可持续的水足迹管理:对基于线性编程的模型和未来方向的审查
1PhD in Civil and Environmental Engineering, Joint Water Technology Program, Islamic University of Gaza, Palestine.
Integrated environmental assessment and management
|September 19, 2025
概括
线性编程 (LP) 优化了农业用水的可持续性. 正在出现先进的模型来应对复杂的挑战,提高水足迹效率并指导未来的研究.
科学领域:
- 农业用水管理农业用水管理
- 优化技术 优化技术
- 环境可持续性 环境可持续性
背景情况:
- 全球水资源因气候变化,人口增长和竞争需求而面临越来越大的压力.
- 可持续的农业水资源管理对于粮食安全和生态平衡至关重要.
- 优化模型是有效分配农业资源的重要工具.
研究的目的:
- 系统地审查使用线性编程 (LP) 和其变体的研究,以优化农业用水.
- 分析这些模型在提高水足迹 (WF) 效率方面的应用.
- 确定研究缺口,并为世界粮食基金意识的农业优化提出未来方向.
主要方法:
- 对58项同行评审的研究进行了系统审查.
- 将应用程序分类为作物分配,灌时间表和经济优化.
- 分析各种优化模型的采用趋势,包括LP,MILP,WGP,FGP和分数编程.
主要成果:
- 线性编程 (LP) 仍然是主要的优化方法.
- 像MILP,WGP,FGP和分数编程这样的高级变体越来越多地用于复杂的多目标问题.
- 在将水足迹指标,气候变化和社会经济因素纳入优化模型方面存在重大差距.
结论:
- 世界粮食基金意识的优化是可持续农业的转型工具,增强性和生态管理.
- 未来的研究应该集中在混合模型,明确的WF指标集成和决策支持系统上.
- 整合先进的优化技术是有效解决农业水资源短缺问题的关键.
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