{"title":"农业可持续水足迹管理:基于线性规划模型的综述及未来发展方向。","authors":"Amjad Mizyed","doi":"10.1093/inteam/vjaf130","DOIUrl":null,"url":null,"abstract":"<p><p>The sustainable management of water resources in agriculture is a global imperative as climate change, population growth, and competing demands increasingly strain freshwater systems. This review systematically analyzes 58 peer-reviewed studies that utilize linear programming (LP) and its advanced variants to optimize agricultural water use, with a specific emphasis on improving water footprint (WF) efficiency. Applications are categorized into three core domains: crop allocation and land use, irrigation scheduling, and economic optimization. The findings reveal that while LP continues to dominate, alternative models-such as mixed-integer programming (MILP), weighted and fuzzy goal programming (WGP, FGP), and fractional programming-are gaining traction for their ability to address real-world complexities and multi-objective decision environments. However, critical gaps remain, particularly in the integration of WF indicators, climate variability, and socio-economic dynamics. This review not only maps the existing optimization landscape but also proposes a forward-looking research agenda. Key directions include the development of hybrid models, the explicit incorporation of WF metrics into objective functions, and the integration of decision-support systems for policy and farm-level planning. WF-aware optimization is thus positioned not merely as a technical instrument, but as a transformative tool for advancing agricultural sustainability-enhancing resilience, equity, and ecological stewardship in water-scarce regions and beyond.</p>","PeriodicalId":13557,"journal":{"name":"Integrated Environmental Assessment and Management","volume":" ","pages":""},"PeriodicalIF":8.4000,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sustainable Water Footprint Management in Agriculture: A Review of Linear Programming-Based Models and Future Directions.\",\"authors\":\"Amjad Mizyed\",\"doi\":\"10.1093/inteam/vjaf130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The sustainable management of water resources in agriculture is a global imperative as climate change, population growth, and competing demands increasingly strain freshwater systems. This review systematically analyzes 58 peer-reviewed studies that utilize linear programming (LP) and its advanced variants to optimize agricultural water use, with a specific emphasis on improving water footprint (WF) efficiency. Applications are categorized into three core domains: crop allocation and land use, irrigation scheduling, and economic optimization. The findings reveal that while LP continues to dominate, alternative models-such as mixed-integer programming (MILP), weighted and fuzzy goal programming (WGP, FGP), and fractional programming-are gaining traction for their ability to address real-world complexities and multi-objective decision environments. However, critical gaps remain, particularly in the integration of WF indicators, climate variability, and socio-economic dynamics. This review not only maps the existing optimization landscape but also proposes a forward-looking research agenda. Key directions include the development of hybrid models, the explicit incorporation of WF metrics into objective functions, and the integration of decision-support systems for policy and farm-level planning. WF-aware optimization is thus positioned not merely as a technical instrument, but as a transformative tool for advancing agricultural sustainability-enhancing resilience, equity, and ecological stewardship in water-scarce regions and beyond.</p>\",\"PeriodicalId\":13557,\"journal\":{\"name\":\"Integrated Environmental Assessment and Management\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":8.4000,\"publicationDate\":\"2025-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Integrated Environmental Assessment and Management\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://doi.org/10.1093/inteam/vjaf130\",\"RegionNum\":4,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integrated Environmental Assessment and Management","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1093/inteam/vjaf130","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Sustainable Water Footprint Management in Agriculture: A Review of Linear Programming-Based Models and Future Directions.
The sustainable management of water resources in agriculture is a global imperative as climate change, population growth, and competing demands increasingly strain freshwater systems. This review systematically analyzes 58 peer-reviewed studies that utilize linear programming (LP) and its advanced variants to optimize agricultural water use, with a specific emphasis on improving water footprint (WF) efficiency. Applications are categorized into three core domains: crop allocation and land use, irrigation scheduling, and economic optimization. The findings reveal that while LP continues to dominate, alternative models-such as mixed-integer programming (MILP), weighted and fuzzy goal programming (WGP, FGP), and fractional programming-are gaining traction for their ability to address real-world complexities and multi-objective decision environments. However, critical gaps remain, particularly in the integration of WF indicators, climate variability, and socio-economic dynamics. This review not only maps the existing optimization landscape but also proposes a forward-looking research agenda. Key directions include the development of hybrid models, the explicit incorporation of WF metrics into objective functions, and the integration of decision-support systems for policy and farm-level planning. WF-aware optimization is thus positioned not merely as a technical instrument, but as a transformative tool for advancing agricultural sustainability-enhancing resilience, equity, and ecological stewardship in water-scarce regions and beyond.
期刊介绍:
Integrated Environmental Assessment and Management (IEAM) publishes the science underpinning environmental decision making and problem solving. Papers submitted to IEAM must link science and technical innovations to vexing regional or global environmental issues in one or more of the following core areas:
Science-informed regulation, policy, and decision making
Health and ecological risk and impact assessment
Restoration and management of damaged ecosystems
Sustaining ecosystems
Managing large-scale environmental change
Papers published in these broad fields of study are connected by an array of interdisciplinary engineering, management, and scientific themes, which collectively reflect the interconnectedness of the scientific, social, and environmental challenges facing our modern global society:
Methods for environmental quality assessment; forecasting across a number of ecosystem uses and challenges (systems-based, cost-benefit, ecosystem services, etc.); measuring or predicting ecosystem change and adaptation
Approaches that connect policy and management tools; harmonize national and international environmental regulation; merge human well-being with ecological management; develop and sustain the function of ecosystems; conceptualize, model and apply concepts of spatial and regional sustainability
Assessment and management frameworks that incorporate conservation, life cycle, restoration, and sustainability; considerations for climate-induced adaptation, change and consequences, and vulnerability
Environmental management applications using risk-based approaches; considerations for protecting and fostering biodiversity, as well as enhancement or protection of ecosystem services and resiliency.