作者
G. Xie,Yibo Zhang,Qing Wang,Kun� Shi,Yunlin Zhang,Yongqiang Zhou,Boqiang Qin,Junliang He,Na Li,Junliang He,Na Li
摘要
The trophic state index (TSI) serves as a fundamental indicator for evaluating the water quality of lake ecosystems. Under climate change and human activities, global lake TSI has changed significantly, yet its response mechanisms remain unclear. To address this challenge, we developed a generalized TSI estimation model by integrating semi-analytical algorithms with machine learning techniques, based on a comprehensive dataset comprising 3756 pairs of in situ measurements and remote sensing observations. The developed model demonstrated superior predictive performance with R2 of 0.77 and RMSE of 8.25 for the testing dataset. Applying the model, we reconstructed a 21-year time series (2003-2023) TSI for 14,189 global lakes with surface area ≥ 10 km2. The global mean TSI was estimated to be 54.07 ± 0.31. Among the lakes, 4.1% were classified as oligotrophic (TSI ≤ 38), 18.9% as mesotrophic (38 < TSI ≤ 48), 56.8% as eutrophic (48 < TSI ≤ 61), and 20.2% as hypereutrophic (TSI > 61). Globally, TSI showed a significantly increasing trend at a rate of 0.19 per decade (p < 0.01). Specifically, lakes with increasing TSI were primarily located in North America, Europe, Russia, and parts of Africa. In contrast, lakes with decreasing TSI were primarily located in South America, Australia, and West Asia. Subsequently, we aggregated the TSI data by country and quantified the contributions of climate, land use, and fertilizer application to the TSI variations using a Generalized Linear Model. The results showed that climate warming, increased solar radiation, stronger wind, intensified precipitation, urbanization, agricultural expansion, and fertilizer use, particularly phosphate application, have all contributed to increasing TSI. In contrast, surrounding vegetation growth showed a negative correlation with TSI, helping to improve water quality. This study underscores the value of remote sensing for large-scale eutrophication assessment, offering insights into sustainable lake management under global change.