Long-Term Impacts of Land Use Changes on Lake Eutrophication: A Remote Sensing-Based Analysis of Baiyangdian Lake (1988–2022)

As a critical freshwater resource for the Xiong'an New Area, Baiyangdian Lake plays a vital role in regional water security and ecosystem stability. This study presents a comprehensive 34-year (1988–2022) assessment of eutrophication dynamics using an integrated approach combining Landsat imagery and in situ water quality monitoring. We developed robust random forest regression models (R² = 0.72–0.85) to retrieve chlorophyll-a (Chl-a), total nitrogen (TN), and total phosphorus (TP) concentrations, enabling high-resolution spatiotemporal analysis. Our results reveal divergent nutrient trends: while TP showed a significant decline (2.05×10⁻⁴ mg·L⁻¹·yr⁻¹, p < 0.01) concurrent with Chl-a reductions (0.12 µg·L⁻¹·yr⁻¹), TN exhibited a concerning increase (1.55×10⁻⁴ mg·L⁻¹·yr⁻¹). Partial least squares regression analysis identified watershed land-use changes as primary drivers, with three key findings: (1) Agricultural runoff contributed 42–58% of TP loading, with landscape fragmentation exacerbating phosphorus transport; (2) Ecological water transfers unexpectedly accounted for 31% of TN inputs through sediment resuspension; (3) Despite increasing anthropogenic pressure, environmental management measures effectively reduced the trophic level index (TLI) by 0.67 per decade. Spatial analysis highlighted hotspots near urban and agricultural areas, demonstrating the compound impacts of cropland expansion (18.7% increase) and construction land growth (24.3%). This study provides critical insights for managing nutrient imbalances in shallow lake ecosystems undergoing rapid watershed development.