Yujiao Wu, Yu Li, Yiding Men, Zhe Zhu, Yan Sun, Changchun Song
{"title":"Spatial optimization of Best Management Practices (BMPs) for nonpoint source pollution mitigation in agricultural watersheds","authors":"Yujiao Wu, Yu Li, Yiding Men, Zhe Zhu, Yan Sun, Changchun Song","doi":"10.1016/j.jhydrol.2025.133739","DOIUrl":null,"url":null,"abstract":"<div><div>Spatial optimization of Best Management Practices (BMPs) is an effective approach to minimizing nonpoint source pollution under limited cost constraints. However, the integration of physical models with optimization models still faces challenges due to the significant computational demands of physical models. We propose a Surrogate-Based Multi-Objective Optimization Method for watershed BMPs, enabling the efficient coupling of physical models with multi-objective optimization models. The method is applied to the Fuzhou River watershed, where the spatial optimization of BMPs under different objectives is obtained. The results indicate that the optimal of BMPs measures vary depending on different water quality objectives. Total nitrogen (TN) and total phosphorus (TP) control primarily rely on protective tillage and grass waterways, while nitrate (NO<sub>3</sub>) control is more effectively achieved through reducing fertilization and vegetated filter strips. We also highlight the importance of fine scale zonal management. High cost and high effect measures are applied to key pollution areas, while low cost measures are selected for other areas, achieving the best balance between treatment effectiveness and financial feasibility. These findings provide technical support for nonpoint source pollution control and contribute to the foundation of sustainable development.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"661 ","pages":"Article 133739"},"PeriodicalIF":6.3000,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydrology","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022169425010777","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0
Abstract
Spatial optimization of Best Management Practices (BMPs) is an effective approach to minimizing nonpoint source pollution under limited cost constraints. However, the integration of physical models with optimization models still faces challenges due to the significant computational demands of physical models. We propose a Surrogate-Based Multi-Objective Optimization Method for watershed BMPs, enabling the efficient coupling of physical models with multi-objective optimization models. The method is applied to the Fuzhou River watershed, where the spatial optimization of BMPs under different objectives is obtained. The results indicate that the optimal of BMPs measures vary depending on different water quality objectives. Total nitrogen (TN) and total phosphorus (TP) control primarily rely on protective tillage and grass waterways, while nitrate (NO3) control is more effectively achieved through reducing fertilization and vegetated filter strips. We also highlight the importance of fine scale zonal management. High cost and high effect measures are applied to key pollution areas, while low cost measures are selected for other areas, achieving the best balance between treatment effectiveness and financial feasibility. These findings provide technical support for nonpoint source pollution control and contribute to the foundation of sustainable development.
期刊介绍:
The Journal of Hydrology publishes original research papers and comprehensive reviews in all the subfields of the hydrological sciences including water based management and policy issues that impact on economics and society. These comprise, but are not limited to the physical, chemical, biogeochemical, stochastic and systems aspects of surface and groundwater hydrology, hydrometeorology and hydrogeology. Relevant topics incorporating the insights and methodologies of disciplines such as climatology, water resource systems, hydraulics, agrohydrology, geomorphology, soil science, instrumentation and remote sensing, civil and environmental engineering are included. Social science perspectives on hydrological problems such as resource and ecological economics, environmental sociology, psychology and behavioural science, management and policy analysis are also invited. Multi-and interdisciplinary analyses of hydrological problems are within scope. The science published in the Journal of Hydrology is relevant to catchment scales rather than exclusively to a local scale or site.