Artificial Intelligence Application in Nonpoint Source Pollution Management: A Status Update

作者：Almando Morain, Ryan Nedd, Kevin Poole, Lauren Hawkins, Micala Jones, Brian Washington, Aavudai Anandhi · 发表于：Sustainability · 年份：2025 · DOI：10.3390/su17135810 · 被引用次数：4 · 研究领域：Air Quality Monitoring and Forecasting、Hydrological Forecasting Using AI、Water Quality and Pollution Assessment

Artificial intelligence (AI) has the potential to significantly advance the management of nonpoint source pollution (NPSP), a critical environmental issue characterized by diffuse sources and complex transport mechanisms. This study systematically examines current AI applications addressing NPSP through bibliometric and systematic analyses. A total of 124 studies were included after rigorous identification, screening, and eligibility assessments based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework. Key findings from the bibliometric analysis include publication trends, regional research contributions, author and journal contributions, and core concepts in NPSP. The systematic analysis further provided: (a) a comprehensive synthesis of NPSP characterization, covering pollution sources, key drivers, pollutants, transport pathways, and environmental impacts; (b) identification of emerging AI technologies such as the Internet of Things, unmanned aerial vehicles, and geographic information systems, and their potential applications in NPSP contexts; (c) a detailed classification of AI models used in NPSP assessment, highlighting predictors, predictands, and performance metrics specifically in water quality prediction and monitoring, groundwater vulnerability mapping, and pollutant-specific modeling; and (d) a critical assessment of knowledge gaps categorized into AI model development and validation, data constraints, governance and poli...