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| Nitrogen loss loads assessment and mitigation scenarios in Shaoguan City: a regional case study |
| Received:May 21, 2025 |
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| KeyWord:InVEST model;nitrogen loss load;Mantel analysis;scenario simulation;reduction |
| Author Name | Affiliation | E-mail | | XIAN Weixuan | The College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Key Laboratory of Arable Land Conservation(South China), MOA, College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China | | | LI Dawei | The College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
College of Resources and Environmental Sciences, China Agricultural University, Beijing 100193, China | | | ZENG Qijing | The College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Key Laboratory of Arable Land Conservation(South China), MOA, College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China | | | YANG Xingjian | The College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
Key Laboratory of Arable Land Conservation(South China), MOA, College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China | xjyang@scau.edu.cn |
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| Abstract: |
| To accurately quantify the agricultural non-point source pollution loads and support high-quality agrarian development, this study investigated the total nitrogen emissions and spatiotemporal distribution characteristics in Shaoguan, 2022, based on the InVEST model, Mantel correlation analysis, and spatial autocorrelation analysis, and identified the key factors influencing total nitrogen emissions. The results showed that the total nitrogen loads in Shaoguan reached 3 419 t, with a temporal distribution trend of lower loads from January to April, higher loads from June to August, and a subsequent decline from September to December. This trend was related to regional precipitation. Spatially, higher nitrogen loads were observed in the northwest and southeast corners of the region, while lower loads were concentrated in the central urban area, possibly influenced by topography and river networks. Mantel analysis indicated that the spatial distribution of nitrogen loads was significantly associated with soybeans and rice planting areas, as well as nitrogen fertilizer application. According to the InVEST model simulations, the predicted reduction rates of total nitrogen loads under city-wide implementation of reduction, retention, and restoration measures were 50.0.%, 24.9%, and 20.0%, respectively, indicating that the reduction measure was the most effective strategy. |
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