Abstract
Climate change-induced higher water temperature is increasing the risk of algal blooms (ABs) in eutrophic water bodies. However, it is not well known how and to what extent warming affects ABs risk. In this work, with simple data input (satellite product, lake surface observation, and climate) and method structure (ensemble learning, statistical downscaling, and hierarchical clustering), a systematic lake surface water temperature (LSWT) and ABs risk evaluation system are constructed and applied in a typical eutrophic freshwater lake. The main results are as follows: 1. The warming rate of LSWT and air temperature from 2000 to 2023 reached 0.21 °C/10a and 0.30 °C/10a respectively, resulting in an extended ABs risk in the historical period. 2. The Nash–Sutcliffe efficiency between climate and LSWT reached 0.89, and LSWT showed a significant (p < 0.05) positive correlation with algal density. 3. The escalation of ABs risks mainly spread to spring and autumn in the forthcoming future, the adverse effect of high emission scenarios will evidently emerge in the mid-21st century. Policymakers and catchment managers should be cautious of lake warming and develop countermeasures in advance.
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