Estimation of Nutrient Fluxes in Small and Medium-Sized Rivers Based on Remote Sensing and Hydrological Modeling
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更新:2026-08-31 22:57:29 浏览:0次
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摘要
Small and medium-sized rivers (SMRs) in Zhejiang Province, adjacent to the Changjiang River Estuary, are critical conduits of terrestrial nutrients to coastal waters. However, their nutrient discharge fluxes and long-term evolutionary trends remain poorly quantified due to a severe scarcity of continuous monitoring data. Integrating high-spatial-resolution nutrient concentrations retrieved from Sentinel-2 satellite data with monthly discharge simulated by the SWAT hydrological model, this study estimated the monthly fluxes of total nitrogen (TN) and total phosphorus (TP) from seven major SMRs (Aojiang, Feiyunjiang, Oujiang, Jiaojiang, Yongjiang, Cao'ejiang, and Qiantangjiang) from 2016 to 2025, and elucidated their spatiotemporal patterns and driving mechanisms.The results reveal that the seven rivers had mean annual TN and TP fluxes of 22.61×104 and 0.72×104 t/yr, respectively. The resulting N/P molar ratio of 33.2 indicates a widespread phosphorus-limited coastal environment. Over the 2016–2025 period, both nutrient fluxes and N/P ratios exhibited an overall declining trend. Spatially, N/P ratios consistently displayed an "upstream-high and downstream-low" gradient across watersheds. This pattern is primarily governed by regional land-use configurations: extensive upstream forests exert a strong retention effect on TP relative to TN, whereas downstream agricultural and urban lands exhibit accelerated TP release. Notably, although these seven SMRs account for only 2.13% of the total watershed area of China's primary outflowing rivers, they deliver 5.22% of TN and 3.52% of TP to national marine inputs. Their areal nutrient export rates far exceed those of large river systems like the Changjiang and Yellow Rivers, underscoring the exceptional transport efficiency of terrestrial matter by SMRs in eastern China. This coupled remote-sensing and hydrological modeling framework provides an innovative paradigm for flux estimation and precision environmental governance in data-scarce small-to-medium river basins.
稿件作者
Zhihong Wang
Second Institute of Oceanography, Ministry of Natural Resources
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