Study region A typical oxbow lake, central Yangtze River, China Study focus The deterioration of the lake water quality has become a major environmental concern worldwide. However, how nutrient inputs from different hydrologic pathways drive the seasonal variability of lake water quality is still poorly understood. Thus, this study applied an integrated framework combining four nutrient flux estimation models, VIKOR method, and Monte Carlo simulation to explore the seasonal dynamics of lake water quality and link their relationships with different hydrologic pathways. New hydrologic insights Lacustrine groundwater discharge (LGD) was the primary hydrologic pathway driving seasonal variability of lake water quality throughout the year (except in June). Its contribution to nutrient inputs reached up to 98.67% for total phosphorus (TP) and 96.89% for total nitrogen (TN). In June 2024, water quality was jointly influenced by Yangtze River backflow, atmospheric deposition, and sediment diffusion. The lake exhibited mild to moderate eutrophication, with probabilities of severe eutrophication of 15.00%, 6.10%, and 27.60% in the dry, normal, and wet seasons, respectively. Sensitivity results further indicated that TN control is critical during the dry season, whereas TP reduction should be prioritized during other periods. This study highlights the important role of LGD in lake nutrient inputs and provides insights for water quality management in lakes with weak surface-water connectivity.
Shi et al. (Sat,) studied this question.
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