Warming of surface water in the large and shallow lakes across the Yangtze River Basin, China, and its driver analysis

被引:4
|
作者
Li, Jing [1 ,2 ]
Sun, Jingjing [3 ]
Wang, Ruonan [4 ]
Cui, Tiejun [1 ,2 ]
Tong, Yindong [3 ]
机构
[1] Tianjin Normal Univ, Sch Geog & Environm Sci, Tianjin 300387, Peoples R China
[2] Tianjin Normal Univ, Tianjin Geospatial Informat Technol Engn Ctr, Tianjin 300387, Peoples R China
[3] Tianjin Univ, Sch Environm Sci & Engn, Tianjin 300072, Peoples R China
[4] Sichuan Ecol Environm Monitoring Stn, Chengdu 610074, Peoples R China
关键词
Surface water temperature; Climatic driver; Declining wind speed; Climate change; Yangtze River Basin; MIXING REGIMES; WIND-SPEED; CLIMATE; TEMPERATURE; TRENDS; CYANOBACTERIA; DECLINE; BLOOMS; OXYGEN;
D O I
10.1007/s11356-022-23608-2
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A variety of physical, chemical, and biological processes within the lakes relies on the surface water temperature while the spatial pattern of large lakes of different warming trends and their connections with climate change remain unclear. Using correlation analysis, regression tree analysis (RTA), and general linear models (GLMs), we have estimated the warming trends of 192 lakes since 2000 in the populated Yangtze River Basin, China, to identify dominant climate drivers and quantify their contributions. The results show that surface water temperature has increased substantially in the majority of the investigated lakes (179 from a total of 192 lakes) at a rate of 0.29 (- 0.12 to 0.62) degrees C/decade (median and 95% confidence interval). The shallower lakes (< 13.1 m in depth) usually have the faster median warming rates than the deeper lakes (i.e., 0.37 degrees C/decade versus 0.16 degrees C/decade). We find that in the shallow lakes, rising air temperatures and declining wind speeds can explain the majority of variation in surface water temperature (i.e., 31.4-80.3% and 13.0-21.0%, respectively). In contrast, in deeper lakes, change of air temperatures plays a dominant role in water warming (75.4-91.2%). This study has emphasized the importance of declining wind speed in water warming in large and shallow lakes and illustrated a difference of dominant climatic drivers in water warming between the shallow and deep lakes.
引用
收藏
页码:20121 / 20132
页数:12
相关论文
共 50 条
  • [31] Attribution Analysis on Regional Differentiation of Water Resources Variation in the Yangtze River Basin under the Context of Global Warming
    Ye, Xuchun
    Zhang, Zengxin
    Xu, Chong-Yu
    Liu, Jia
    [J]. WATER, 2020, 12 (06)
  • [32] Food-Energy-Water Analysis at Spatial Scales for Districts in the Yangtze River Basin (China)
    Wang, Zhuomin
    Thuy Nguyen
    Westerhoff, Paul
    [J]. ENVIRONMENTAL ENGINEERING SCIENCE, 2019, 36 (07) : 789 - 797
  • [33] Distribution and spatial variation of volatile methylsiloxanes in surface water and wastewater from the Yangtze River Basin, China
    Zhang, Yimeng
    Yin, Ge
    Sheng, G. Daniel
    Yu, Zhenyang
    Yin, Daqiang
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 929
  • [34] Projection of Future Climate Change and Its Influence on Surface Runoff of the Upper Yangtze River Basin, China
    Wan, Hanli
    [J]. ATMOSPHERE, 2023, 14 (10)
  • [35] Water quantity as a driver of change in the Great Lakes-St. Lawrence River Basin
    Maghrebi, Mahdi
    Nalley, Deasy
    Laurent, Katrina L.
    Atkinson, Joseph F.
    [J]. JOURNAL OF GREAT LAKES RESEARCH, 2015, 41 : 84 - 95
  • [36] Geographic Patterns of Bacterioplankton among Lakes of the Middle and Lower Reaches of the Yangtze River Basin, China
    Bai, Chengrong
    Cai, Jian
    Zhou, Lei
    Jiang, Xingyu
    Hu, Yang
    Dai, Jiangyu
    Shao, Keqiang
    Tang, Xiangming
    Yang, Xiangdong
    Gao, Guang
    [J]. APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2020, 86 (06)
  • [37] Subfossil cladocerans as quantitative indicators of past ecological conditions in Yangtze River Basin lakes, China
    Dong, Xuhui
    Kattel, Giri
    Jeppesen, Erik
    [J]. SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 728
  • [38] Eutrophication Prediction Using a Markov Chain Model: Application to Lakes in the Yangtze River Basin, China
    Jiacong Huang
    Junfeng Gao
    Yinjun Zhang
    [J]. Environmental Modeling & Assessment, 2016, 21 : 233 - 246
  • [39] Eutrophication Prediction Using a Markov Chain Model: Application to Lakes in the Yangtze River Basin, China
    Huang, Jiacong
    Gao, Junfeng
    Zhang, Yinjun
    [J]. ENVIRONMENTAL MODELING & ASSESSMENT, 2016, 21 (02) : 233 - 246
  • [40] Comparison of microbial community between two shallow freshwater lakes in middle Yangtze basin, East China
    Tong, Y
    Lin, GF
    Ke, X
    Liu, FP
    Zhu, GW
    Gao, G
    Shen, JH
    [J]. CHEMOSPHERE, 2005, 60 (01) : 85 - 92