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<p>The complex basin conditions give rise to pronounced spatial heterogeneity in non-point source (NPS) pollution loads, which renders conventional basin-wide management strategies ineffective due to their neglect of spatial specificity at the sub-basin scale. To address this critical limitation, this study integrates the Soil and Water Assessment Tool (SWAT) model with random forest regression to establish a dual-dimensional "zoning-driving" management framework operating at the sub-basin scale. Taking the Tianshui section of the Wei River Basin as a case, precise management was achieved at the sub-basins scale. Key findings include: (1) Significant spatial heterogeneity in NPS pollution loads was observed, characterized by a "lowest in the west, moderate in the east, and highest in the center" pattern, with an average load of 603.97&#xa0;kg/km<sup>2</sup>; (2) Three-tiered management zones were delineated based on pollution intensity, with the high-priority zone (2,231.43&#xa0;kg/km<sup>2</sup>) concentrated in Sub-basins 5 and 16. Despite covering merely 11% of the basin area, this zone contributes 40% of the total pollution load, establishing it as a critical intervention target.(3) Driving factors exhibit marked sub-basin heterogeneity in their impacts on NPS pollution, necessitating spatially differentiated control measures. This study provides methodological innovations and actionable guidance for precision NPS pollution management in complex basins.</p>

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Strategic management of non-point source pollution in river Basins: a case study of the Tianshui section, Wei River Basin, China

  • 期刊论文

  • 发表日期：

    2025年8月7日

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  • Yangan Ren,
  • Tingting Shang,
  • Yaqun Zhang

摘要

The complex basin conditions give rise to pronounced spatial heterogeneity in non-point source (NPS) pollution loads, which renders conventional basin-wide management strategies ineffective due to their neglect of spatial specificity at the sub-basin scale. To address this critical limitation, this study integrates the Soil and Water Assessment Tool (SWAT) model with random forest regression to establish a dual-dimensional "zoning-driving" management framework operating at the sub-basin scale. Taking the Tianshui section of the Wei River Basin as a case, precise management was achieved at the sub-basins scale. Key findings include: (1) Significant spatial heterogeneity in NPS pollution loads was observed, characterized by a "lowest in the west, moderate in the east, and highest in the center" pattern, with an average load of 603.97 kg/km2; (2) Three-tiered management zones were delineated based on pollution intensity, with the high-priority zone (2,231.43 kg/km2) concentrated in Sub-basins 5 and 16. Despite covering merely 11% of the basin area, this zone contributes 40% of the total pollution load, establishing it as a critical intervention target.(3) Driving factors exhibit marked sub-basin heterogeneity in their impacts on NPS pollution, necessitating spatially differentiated control measures. This study provides methodological innovations and actionable guidance for precision NPS pollution management in complex basins.