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Characteristics and modeling of agricultural nonpoint source pollution in arid and semi-arid irrigation areas: a review.

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Title: Characteristics and modeling of agricultural nonpoint source pollution in arid and semi-arid irrigation areas: a review.
Authors: Zhang, Tianpeng1 (AUTHOR), Lei, Qiuliang1 (AUTHOR) leiqiuliang@caas.cn, Luo, Jiafa2 (AUTHOR), Du, Xinzhong1 (AUTHOR) duxinzhong@caas.cn, Wu, Shuxia1 (AUTHOR), Qiu, Weiwen2 (AUTHOR), Liu, Hongbin1 (AUTHOR)
Source: Environmental Reviews. 3/16/2026, Vol. 34, p1-24. 24p.
Subject Terms: *Nonpoint source pollution, *Irrigation, *Water shortages, *Irrigation farming, Empirical research, Dynamic simulation, Hydrological research
Abstract: Arid and semi-arid irrigated areas (ASAIAs) face a complex interplay of water scarcity and agricultural pollution, making accurate nonpoint source pollution (NPS) modeling and model selection particularly challenging. This review comprehensively evaluates 22 widely used mechanistic and empirical models for their applicability in simulating NPS pollution processes under the unique environmental and anthropogenic conditions of ASAIAs. The review reveals that intensive human intervention fundamentally transforms the hydrological processes in ASAIAs, shifting the modeling paradigm from a "natural precipitation-runoff" pattern to an "artificial water network" pattern that encompasses the entire sequence from water sources–canal systems–croplands–drainage systems–receiving water bodies. This transformed process is further influenced by the extreme boundary conditions characteristic of ASAIAs, particularly the wet–dry cycles driven by intermittent rainfall and high evaporation. While mechanistic models offer strengths in detailed process description, they exhibit significant limitations in capturing irrigation-dominated hydrological processes, salinity dynamics, and engineered drainage systems; mechanistic models such as APEX, PRMS, and SWAT have shown relatively better performance in ASAIAs. In contrast, empirical models are computationally efficient but often oversimplify nonlinear pollution transport processes and fail to adequately represent complex water–soil–plant interactions under extreme climatic variability; empirical models such as AN-Footprint, ECM, and WEC have shown relatively better performance in ASAIAs. In future, model development and refinement should prioritize addressing the extreme boundary conditions in ASAIAs, including natural features such as intermittent rainfall, high evaporation, and flat topography, as well as management-induced dry–wet cycles resulting from irrigation and salt leaching practices. The review proposes mechanistic and empirical model selection tables to guide researchers in choosing context-appropriate tools, thereby reducing model misuse and improving simulation accuracy. These insights contribute to the advancement of NPS pollution modeling and support sustainable water quality management in water-limited agricultural regions. [ABSTRACT FROM AUTHOR]
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Abstract:Arid and semi-arid irrigated areas (ASAIAs) face a complex interplay of water scarcity and agricultural pollution, making accurate nonpoint source pollution (NPS) modeling and model selection particularly challenging. This review comprehensively evaluates 22 widely used mechanistic and empirical models for their applicability in simulating NPS pollution processes under the unique environmental and anthropogenic conditions of ASAIAs. The review reveals that intensive human intervention fundamentally transforms the hydrological processes in ASAIAs, shifting the modeling paradigm from a "natural precipitation-runoff" pattern to an "artificial water network" pattern that encompasses the entire sequence from water sources–canal systems–croplands–drainage systems–receiving water bodies. This transformed process is further influenced by the extreme boundary conditions characteristic of ASAIAs, particularly the wet–dry cycles driven by intermittent rainfall and high evaporation. While mechanistic models offer strengths in detailed process description, they exhibit significant limitations in capturing irrigation-dominated hydrological processes, salinity dynamics, and engineered drainage systems; mechanistic models such as APEX, PRMS, and SWAT have shown relatively better performance in ASAIAs. In contrast, empirical models are computationally efficient but often oversimplify nonlinear pollution transport processes and fail to adequately represent complex water–soil–plant interactions under extreme climatic variability; empirical models such as AN-Footprint, ECM, and WEC have shown relatively better performance in ASAIAs. In future, model development and refinement should prioritize addressing the extreme boundary conditions in ASAIAs, including natural features such as intermittent rainfall, high evaporation, and flat topography, as well as management-induced dry–wet cycles resulting from irrigation and salt leaching practices. The review proposes mechanistic and empirical model selection tables to guide researchers in choosing context-appropriate tools, thereby reducing model misuse and improving simulation accuracy. These insights contribute to the advancement of NPS pollution modeling and support sustainable water quality management in water-limited agricultural regions. [ABSTRACT FROM AUTHOR]
ISSN:11818700
DOI:10.1139/er-2025-0202