Abstract

Long-term lake surface water temperature (LSWT) products are valuable for understanding the responses of lake ecosystems to climate warming and for proposing suitable policies to protect lake ecosystems. Here, using Landsat satellite data and various in situ data, we documented 36 years (1986–2021) of spatiotemporal variations in LSWT in Lake Qiandaohu, a subtropical deep-water lake in China, and explored the potential driving factors of these variations. We validated the performances of the practical single-channel (PSC) algorithm, the generalized single-channel algorithm and the Landsat Level 2 land surface temperature product on Lake Qiandaohu with long-term in situ buoy data. Overall, the PSC algorithm had the best performance, with a mean absolute percent error (MAPE) of 7.5% and root mean square difference (RMSE) of 1.7°C. With 36 years of Landsat data and the PSC algorithm, the spatiotemporal variations in LSWT were constructed. The Landsat-derived 36-year mean LSWT in Lake Qiandaohu ranged from 18.2 to 23.1°C, with a mean value of 20.2°C. The northeast and southwest subsegments had the minimum (19.7°C) and maximum (20.6°C) mean LSWT values, respectively. The spatial variations in LSWT could be explained in part by the water depth. From 1986 to 2021, a significant warming trend was observed in Lake Qiandaohu, with a warming rate of 0.07°C/year. The warming rate of Lake Qiandaohu was faster than that of the local air temperature (warming rate = 0.04°C/year). The LSWT warming in Lake Qiandaohu can mainly be attributed to the warming air temperatures. Lake warming has increased the thermal stability in Lake Qiandaohu and has had negative impact on the lake ecosystem. Our work highlights the importance of using satellite data to understand the responses of lake ecosystems to climate change.

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