Coupled InVEST-GTWR modeling reveals scale-dependent drivers of N and P export in a Chinese mountainous region
Nitrogen (N) and phosphorus (P) export from non-point sources significantly threaten water quality in mountainous regions undergoing rapid agricultural intensification and urbanization. However, existing research often neglects multi-scale analyses across administrative levels and provides limited i...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843225003528 |
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| Summary: | Nitrogen (N) and phosphorus (P) export from non-point sources significantly threaten water quality in mountainous regions undergoing rapid agricultural intensification and urbanization. However, existing research often neglects multi-scale analyses across administrative levels and provides limited insight into the complex drivers of nutrient export in data-scarce mountainous regions. This study presents a novel integrated modeling framework by coupling the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model with Geographically and Temporally Weighted Regression (GTWR) to analyze N and P export dynamics in Yunnan Province from 2000 to 2019. We reveal a temporal turning point around 2011, with declining nutrient exports before 2011 followed by a rising trend linked to policy changes and intensified land use. Spatially, high N and P export clusters occur in densely populated, agriculturally intensive central and southeastern Yunnan, while forested northwestern areas exhibit low export. Prefecture-scale drivers are dominated by population density, fertilizer application, and industrial activity, whereas county-scale drivers highlight cropland area, precipitation, and terrain factors. Importantly, natural and anthropogenic factors interact to shape nutrient export patterns, underscoring the need for spatially differentiated management. The integration of InVEST-GTWR reflects methodological innovations that capture spatio-temporal non-stationarity and provide actionable insights for targeted nutrient pollution control in mountainous regions, with high model accuracy (R2 = 0.98 at the prefecture scale and R2 = 0.95 at the county scale). |
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| ISSN: | 1569-8432 |