Abstract
Lake surface water temperature is a fundamental metabolic indicator of lake ecosystems that affects the exchange of material and energy in lake ecosystems. Estimating and predicting changes in lake surface water temperature is crucial to lake ecosystem research. This study selected Dianchi Lake, a typical urban lake in China, as the research area and used the Air2water model combined with the Mann-Kendall mutation statistical method to analyze the temporal and spatial variation in the surface water temperature of Dianchi Lake under three climate models. The research results show that, under the RCP 5-8.5 scenario model, the surface water temperature change rate for Dianchi Lake from 2015 to 2100 would be 0.28 ℃/10a, which was the largest change rate among the three selected scenarios. The rate of change during 2015-2100 would be 9.33 times higher than that during the historical period (1900-2014) (0.03 °C/10a). Against the background of Niulan River water diversion and rapid urbanization, the surface water temperature of Dianchi Lake experienced abrupt changes in 1992, 2016, 2017, and 2022. Against the background of urbanization, the impact of human activities on the surface water temperature of urban lakes will become greater.