ArticleEnvironmental science and pollution research international2021
Framework of multi-level regionalization schemes based on non-point source pollution to advance the environmental management of small watersheds.
Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Demand-oriented regionalization with local data.Scientific reports · 2026Article
- Spatial Pattern Evolution and Influencing Factors on Agricultural Non-Point Source Pollution in Small Town Areas under the Background of Rapid Industrialization.International journal of environmental research and public health · 2023Article
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Authors and funding
5 authors.
Funding
Abstract
Regionalization exerts an important guiding role for sound environmental management, regional development, and schemes toward regionalizing ecological function, involving multiple levels. This paper formulated a framework for a detailed regionalization approach using the Ashi River watershed, China, as case study. Human activities, especially agriculture non-point source pollution (ANPS) and social factors, were identified as main factors. The results indicated that (1) the export coefficient model (ECM) can be used to determine ANPS loads in the watershed as well as total nitrogen and total phosphorus loads. (2) The minimum cumulative resistance model (MCR) showed that the middle and lower reaches had high risk for ANPS occurrence. (3) Based on the identified key factors, the watershed was divided into level IV and combined with existing level III using cluster analysis. Corresponding management countermeasures were proposed. This provides a scientific basis for pollution control planning and for management measures.
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Registered trials
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