优化区域水资源管理,考虑生态水需求优先考虑马哈韦利河流域,斯里兰卡
1MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, North China Electric Power University, Beijing 102206, China.
概括
本研究介绍了可持续水资源管理的间隔最小值相对遗憾分析 (IMRA). 在气候变化的不确定性下,IMRA方法优化了水分配,平衡了人类需求与生态需求.
科学领域:
- 环境科学 环境科学
- 水资源管理 水资源管理
- 适应气候变化 适应气候变化
背景情况:
- 气候变化给全球水资源管理带来了重大挑战.
- 在保护生态系统的同时,平衡来自不同部门的竞争性水需求变得越来越复杂.
- 现有的模型往往难以有效地整合不确定性,风险和生态需求.
研究的目的:
- 开发和应用一个新的间隔最小值相对遗憾分析 (IMRA) 框架,用于水资源管理.
- 将气候预测,风险管理和生态系统保护纳入水分配决策.
- 优先考虑斯里兰卡马哈韦利河流域的生态水需求.
主要方法:
- 结合间隔线性编程 (ILP) 与最小相对遗憾分析 (MRA).
- 采用多目标优化来协调竞争的水需求和用户差异.
- 系统评估了23个不同作物模式的地区的灌效益和经济损失.
主要成果:
- 通过使用绝对和相对遗憾标准,确定了[174.09,216.62] x 10^6 m^3的最佳灌用水供应范围.
- 在不同供应条件下,在Matale (36%) 和Pussellawa (40%) 发现了相当大的生态水需求.
- 证明了水资源,社会经济因素和生态决定因素之间的关键相互作用.
结论:
- 在环境不确定性中,IMRA框架为可持续的水资源管理提供了强有力的方法.
- 这项研究使得科学基础的监管和水资源的有效利用成为可能.
- 优先考虑生态水需求对于保持分配效率和生态系统完整性至关重要.
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