基于替代模型的多目标优化,用于非点源污染的最佳管理实践
Aoyun Long1, Ruochen Sun2, Xiyezi Mao3
1The National Key Laboratory of Water Disaster Prevention, Hohai University, Nanjing, China; College of Hydrology and Water Resources, Hohai University, Nanjing, China.
Water research
|November 23, 2024
概括
一种新的优化方法,MO-ASMOCH,有效地确定了流域非点源污染控制的最佳管理实践 (BMP). 这种方法显著降低了计算成本,同时改善了水质,这在中国的四湖流域中得到了证明.
科学领域:
- 环境科学 环境科学
- 水资源管理 水资源管理
- 计算水文学计算水文学
背景情况:
- 流域非点源 (NPS) 污染管理依赖于水文模型和最佳管理实践 (BMP).
- 优化BMP选择是由于混合离散连续变量的计算密集型.
- 有效的决策工具对于有效的流域污染控制至关重要.
研究的目的:
- 开发和评估一种新的优化方法,MO-ASMOCH,以有效地在流域中部署BMP.
- 为了比较MO-ASMOCH与NSGA-II等BMP优化传统算法的性能.
- 评估优化BMP对四湖流域水质和污染物负载的影响.
主要方法:
- 为受约束的混合问题 (MO-ASMOCH) 集成基于多目标适应替代模型的优化与土壤和水评估工具 (SWAT) 模型.
- 为了计算效率,对MO-ASMOCH和非主导排序基因算法II (NSGA-II) 的比较分析.
- 场景分析以量化污染物负载减少 (TN,TP) 和相关成本.
主要成果:
- MO-ASMOCH实现了与NSGA-II相比较的帕雷托最佳解决方案,模型评估显著减少 (1,150对10,000).
- 最大的减少场景使总 (TN) 和总 (TP) 的负载分别减少了18.3%和20.7%.
- 优化的BMP改善了TN的水质,从V级改为IV-V级,TP改为III级.
结论:
- MO-ASMOCH为优化混合决策变量BMP提供了卓越的计算效率.
- 综合建模方法为NPS污染管理和有针对性的环境决策提供了有效的战略.
- 优化的BMP实施可以导致流域水质的大幅改善和污染物负载的减少.
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