Spatial‐Temporal Variation of Lake Surface Water Temperature and Its Driving Factors in Yunnan‐Guizhou Plateau

• Published in: Water resources research 2019-06, Vol.55 (6), p.4688-4703
• Main Authors: Yang, Kun, Yu, Zhenyu, Luo, Yi, Zhou, Xiaolu, Shang, Chunxue
• Format: Article
• Language: English
• Subjects: Air temperature; Biodiversity; Classification; Climate and human activity; Climate change; climate warming; Clustering; Environmental impact; Geographical distribution; Geographical locations; Global warming; Human factors; Human influences; K‐Means clustering method; lake surface water temperature; lake type; Lake water; Lakes; Marine environment; Multiculturalism & pluralism; Periodic variations; Periodicity; plateau lake; Plateaus; Surface temperature; Surface water; Surface-air temperature relationships; Temperature effects; Temporal variations; Urbanization; Water temperature; Watersheds
• ISSN: 0043-1397; 1944-7973
• DOI: 10.1029/2019WR025316

Lake surface water temperature (LSWT) is an important factor of water ecological environment. In the context of global warming, the LSWT of global lakes generally reveals an upward trend. With a continuous intensification of human activities and a rapid expansion of the impervious surface, urbanization has exerted an increasing impact on the environment, so the impact of human activities on LSWT cannot be ignored. Because of the special geographical location, the change of LSWT in plateau lakes has important impacts on climate diversity, biodiversity, and cultural diversity. As a result, it is critical to monitor and model the variation characteristics of LSWT in the plateau area. Based on the data set of natural factors representing climate change and human factors representing human activities, this study proposes a classification of lake types by K‐Means clustering method. At watershed scale, 11 lakes in the study area are divided into three types: Natural Lake, Semi‐urban Lake, and Urban Lake (UL). Based on this classification, the variation characteristics of LSWT for the eleven lakes from 2001 to 2017 are analyzed. The causal relationship and contribution of climate change and human activities to the rise of LSWT are discussed. Results show that (1) from 2001 to 2017, the annual mean of LSWT‐day/night and near‐surface air temperature in the 11 lakes show a warming trend, a significant correlation (R = 0.82, α = 0.0164 < 0.5) and a same periodicity, which indicates that near‐surface air temperature is one of the main influencing factors of LSWT warming in Yunnan‐Guizhou Plateau. (2) LSWT warming trend of UL is more obvious than those of Semi‐urban Lake and Natural Lake, indicating that human activities have more significant impact on LSWT of UL. The main driving factors are the impervious surface expansion and population increase. (3) The influence of human activities on the LSWT in Yunnan‐Guizhou Plateau is becoming more and more significant, and it is also the main factor in causing the deterioration of lake water environment in Yunnan‐Guizhou Plateau. Key Points Lakes are divided into Natural Lake, Semi‐urban Lake, and Urban Lake by K‐Means clustering algorithm LSWT warming rate is dependent on combinations of NSAT and human activities; the average rate of LSWT increased is faster than the rate at which air temperatures increased Human activity will become the main driving factor of LSWT increasing in the research area