Warming lake surface water temperatures in Lake Qiandaohu, China: Spatiotemporal variations, influencing factors and implications for the thermal structure

被引:4
|
作者
Li, Yuan [1 ]
Shi, Kun [2 ,3 ]
Zhang, Yunlin [2 ,3 ]
Zhu, Guangwei [2 ,3 ]
Guo, Yulong [4 ]
Li, Huiyun [2 ,3 ]
Du, Chenggong [5 ]
机构
[1] Zhejiang Gongshang Univ, Sch Tourism & Urban & Rural Planning, Hangzhou, Peoples R China
[2] Chinese Acad Sci, Nanjing Inst Geog & Limnol, Taihu Lab Lake Ecosyst Res, State Key Lab Lake Sci & Environm, Nanjing, Peoples R China
[3] Univ Chinese Acad Sci, Beijing, Peoples R China
[4] Henan Agr Univ, Coll Resources & Environm Sci, Zhengzhou, Peoples R China
[5] Huaiyin Normal Univ, Jiangsu Collaborat Innovat Ctr Reg Modern Agr & En, Huaian, Peoples R China
基金
中国国家自然科学基金;
关键词
lake surface water temperature; Landsat; Lake Qiandaohu; thermal structure; Google Earth engine; SINGLE-CHANNEL ALGORITHM; CLIMATE-CHANGE; RETRIEVAL; STRATIFICATION; RESERVOIR; TRENDS; VARIABILITY; DECREASES; RESPONSES; TESTS;
D O I
10.3389/fenvs.2022.995862
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
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 degrees 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 degrees C, with a mean value of 20.2 degrees C. The northeast and southwest subsegments had the minimum (19.7 degrees C) and maximum (20.6 degrees 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 degrees C/year. The warming rate of Lake Qiandaohu was faster than that of the local air temperature (warming rate = 0.04 degrees 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.
引用
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页数:16
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