| 引用本文: | 潘惠敏,蔡华阳,王博芝,张萍,姚宇.1973—2020年洞庭湖水温演变特征.湖泊科学,2023,35(1):326-337. DOI:10.18307/2023.0125 |
| Pan Huimin,Cai Huayang,Wang Bozhi,Zhang Ping,Yao Yu.Evolution characteristics of water temperature in Lake Dongting from 1973 to 2020. J. Lake Sci.2023,35(1):326-337. DOI:10.18307/2023.0125 |
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| 摘要: |
| 表层水温是影响湖泊水生生态系统的关键因素,研究其对气候变化的响应过程及机制是评估湖泊生态环境可持续发展的重要切入点。本文针对水温的长期演变趋势问题,基于实测水文气象数据,采用Air2water数据驱动模型重构洞庭湖长序列水温资料,研究湖泊表层水温在气象条件驱动下的演变特征,为湖泊生态环境监测、水安全保障和综合治理等提供理论依据。主要结论有:(1)尽管Air2water数据驱动模型以常微分方程的简化形式概化湖泊热力学过程,但可较准确地反演水温的变化趋势。根据长序列实测气温资料重构的1973—2020年洞庭湖日均水温序列具有较高的可信度。(2)1973—2020年,洞庭湖水温年内变化具有显著的上升期和下降期,且降温过程较升温快。在气候变暖背景下,年均水温呈现持续的波动性上升趋势,且1996年发生突变后上升趋势更为显著,其中城陵矶站和南咀站年均水温的上升率分别达到0.20和0.16℃/10 a。1996年洞庭湖流域的突变式增温主要是由冷季的显著增暖过程驱动。(3)采用广义单位线法建立水温-气温之间的耦合关系,水温随气温上升的速率先增大至极大值后逐渐减缓。1996年水温发生突变后,水温随气温的变化速率略有减小,表明水温对气温响应的敏感性降低,水温-气温的耦合关系有所削弱。 |
| 关键词: 湖泊表层水温 数据驱动模型 广义单位线法 气候变暖 洞庭湖 |
| DOI：10.18307/2023.0125 |
| 分类号: |
| 基金项目:洞庭湖水环境治理与生态修复湖南省重点实验室开放基金项目(2020DT001)资助。 |
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| Evolution characteristics of water temperature in Lake Dongting from 1973 to 2020 |
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Pan Huimin1, Cai Huayang1, Wang Bozhi1, Zhang Ping1, Yao Yu2
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1.Institute of Estuarine and Coastal Research, School of Ocean Engineering and Technology, Sun Yat-sen University, Guangzhou 510275, P. R. China;2.School of Hydraulic and Environmental Engineering, Changsha University of Science and Technology, Changsha 410114, P. R. China
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| Abstract: |
| Surface water temperature is a key factor influencing the lake aquatic ecosystem. Studying its responses and mechanisms to climate change is an important issue for assessing the sustainability of the lake ecological environment. This paper focuses on the issue of long-term trend of water temperature. Based on the observed hydrological and meteorological data, the evolution characteristics of the lake surface water temperature driven by meteorological conditions were examined by means of the Air2water data-driven model to reconstruct the long-term, time-series water temperature in Lake Dongting, which provides a theoretical basis for the monitoring of lake ecological environment, water security and comprehensive management. The main conclusions are: (1) Although the Air2water data-driven model describes the main heat exchange processes of a lake in a simplified form of an ordinary differential equation, it can well reproduce the actual trend of water temperature. The long-term, time-series observed air temperature can be used to reconstruct the daily averaged water temperature time series in Lake Dongting from 1973 to 2020 with high reliability. (2) From 1973 to 2020, the water temperature within a year in Lake Dongting had apparent warming and cooling periods, where the cooling rates were faster than the warming rates. Driven by the global climate warming, the annual mean water temperature showed consistent increasing trends, and the increasing rates were much more significant after the mutation in 1996, in which the increasing rates of annual mean water temperature at the Chenglingji Station and the Nanju Station were 0.20 and 0.16℃/10 a, respectively. The abrupt warming of Lake Dongting in 1996 was mainly driven by the significant warming process during the cold season. (3) The coupling relationships between water temperature and air temperature have been established using the general unit hydrograph theory, where the rising rates of water temperature with air temperature increased to a maximum value and then gradually slowed down. After the mutation of water temperature in 1996, the rates of water temperature variation with air temperature slightly decreased, indicating that the sensitivity of water temperature to air temperature decreased and the coupling relationships between water temperature and air temperature were weakened. |
| Key words: Lake surface water temperature data-driven model general unit hydrograph theory climate warming Lake Dongting |
