基于半阶导数的湖泊蓄热变化模型

IF 4.6 1区地球科学 Q2 ENVIRONMENTAL SCIENCES

Water Resources Research Pub Date : 2025-01-08 DOI:10.1029/2024wr038269

Yuanbo Liu, Liangjun Tang, Wanqiu Xing, Jingfeng Wang, Ruonan Wang, Yifan Cui, Qi Li

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引用次数: 0

摘要

蓄热变化（HSC）是湖泊热能收支的重要组成部分。传统的基于温度剖面的HSC模型需要特定位置的参数，如湖床地形。基于热通量的半阶时间导数公式，建立了不使用地理相关参数，利用水面温度和太阳辐射估算热通量的解析模型。该模型在鄱阳湖进行了野外实测，鄱阳湖是一个浅内陆湖，其水位和湖泊面积具有明显的季节性变化。我们的分析表明，该模型准确地模拟了研究期间的日HSC，决定系数为0.94，均方根误差（RMSE）为77.5±21.6 Wm−2。夜间的RMSE值（75.0±26.8 Wm−2）大于白天的RMSE值（55.1±19.7 Wm−2），这是由于夜间湍流通量的测量误差较大。该模型估算的HSC不依赖于温度剖面和湖泊特征参数，有利于全球水体HSC的遥感监测。

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A Half-Order Derivative Based Model of Lake Heat Storage Change

Heat storage change (HSC) is a crucial component of lake's thermal energy budget. Conventional temperature profile based models of HSC require location specific parameters such as lakebed topography. Based on the half-order time-derivative formula of heat fluxes, an analytical model was formulated for estimating HSC from water surface temperature and solar radiation without using geography dependent parameters. The proposed model was tested against field measurements at Poyang Lake, a shallow inland lake, which has pronounced seasonal variations in water level and lake area. Our analysis indicates that the model accurately simulates diurnal HSC with a coefficient of determination of 0.94 and a root mean squared error (RMSE) of 77.5 ± 21.6 Wm⁻² for the study period. Larger nighttime RMSE (75.0 ± 26.8 Wm⁻²) than the daytime value (55.1 ± 19.7 W m⁻²) is attributable to larger measurement errors of nighttime turbulent fluxes. The estimation of HSC independent of temperature profile and lake-specific parameters by the proposed model facilitates remote sensing monitoring the HSC of global water bodies.

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来源期刊

Water Resources Research 环境科学-湖沼学

CiteScore

8.80

自引率

13.00%

发文量

599

审稿时长

3.5 months

期刊介绍： Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.