With the rapid advancement of agricultural intensification, nitrogen fertilizers have become indispensable inputs for sustaining crop productivity worldwide. However, the excessive and often inefficient application of these fertilizers has resulted in significant nitrogen surpluses, contributing to severe non-point source (NPS) pollution, which poses substantial threats to water quality and ecosystem health. This issue is particularly acute in ecologically sensitive regions such as the Three Gorges Reservoir Region in China, where agricultural activities are intensive and environmental vulnerabilities are high. Against this backdrop, this study aims to assess the spatial risk of nitrogen fertilizer-induced non-point source pollution across the TGRR by applying the “source-sink” theory within a geospatial modeling framework. Methodologically, the study introduces an innovative approach to improve the identification of source landscapes. This was achieved by integrating two critical factors: established buffer zones along the Yangtze River mainstream and the spatial intensity of nitrogen fertilizer application. Source landscapes were subsequently classified into five distinct grades (Grade I to V) based on their pollution potential. To evaluate the mobilization and transport risk of nitrogen pollutants, a comprehensive resistance surface was constructed using key natural factors including elevation, slope, rainfall erosivity, land use type, and soil erodibility. The Minimum Cumulative Resistance (MCR) model was then employed to quantify the diffusion resistance faced by nutrients from each source grade, leading to the categorization of the entire region into five corresponding risk levels: extremely high, high, medium, low, and extremely low.

The results revealed several key findings: 1) The composition of source landscapes exhibited clear dominance by the mid-to-high grades. Specifically, Grade IV source landscapes were the most extensive, covering 31.78% of the total study area. This indicates that areas with relatively high pollution potential are widespread. In contrast, the extremes were less common; Grade V landscapes covered the smallest area at 10.90%, while Grade I areas were also limited in extent. 2) A distinct spatial clustering of source grades was observed, closely tied to geography and economic activity. Grade I, II, and III source landscapes were predominantly located in areas distal from the main channel of the Yangtze River, often coinciding with mountainous terrain and economically less developed regions where agricultural intensity is lower. Conversely, Grade IV and V source landscapes were highly concentrated in zones immediately adjacent to the Yangtze River mainstream (particularly within 0-40 km buffers) and in other flat valley areas. These zones are characterized by frequent, intensive agricultural activities, higher population density, and greater fertilizer input, creating a high pollution potential near critical water bodies. 3) Analysis at the administrative county level revealed pronounced spatial heterogeneity in overall pollution risk. Badong County exhibited the highest mean MCR value (23,999), signifying that the cumulative resistance to pollutant movement from source areas is greatest here, thus indicating the lowest overall pollution risk among all counties. On the other end of the spectrum, Yubei District registered the lowest mean MCR value (3,058), reflecting minimal landscape resistance and consequently the highest overall pollution risk. 4) Geographically, extremely high and high-risk zones were mainly clustered in the middle and upper reaches of the Yangtze River within the TGRR, aligning with agriculturally intensive areas. Conversely, low and extremely low-risk zones were primarily situated near the administrative boundary between Hubei Province and Chongqing Municipality. 5) Based on this risk stratification, tailored ecological management strategies are proposed. For high and extremely high-risk regions (e.g., Chongqing core urban area, Wanzhou, Beibei), immediate and prioritized interventions are crucial. These should focus on implementing nitrogen fertilizer reduction and efficiency enhancement technologies and strengthening the protection, restoration, and strategic planning of riparian buffer zones to intercept runoff. For low and extremely low-risk areas (e.g., Wushan, Zigui, Badong), the management priority should shift towards preventive conservation. This involves establishing long-term environmental monitoring networks and robust early-warning systems to detect any negative trends in pollution levels, thereby preserving their current favorable environmental status. Overall, this study provides a spatially explicit decision-support framework for the precise prevention and control of nitrogen non-point source pollution in the TGRR, offering valuable insights for sustainable agricultural practices and watershed management in similar regions globally.