Methods for predicting water temperature in data-scarce areas under different climate regions of China
Water temperature is an important index that affects physical, chemical and biological reactions in water environments, and accurate water temperature prediction is important. Water temperature prediction in a data-deficient area along the Yangtze River trunk stream was selected as the research obje...
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KeAi Communications Co., Ltd.
2025-01-01
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| Series: | Water Cycle |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666445325000078 |
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| author | Jiaqi Zhang Jun Ma Yaqian Xu Defu Liu Zhangpeng Wang Zeyi Tao Hao Wei Ran Xiao |
| author_facet | Jiaqi Zhang Jun Ma Yaqian Xu Defu Liu Zhangpeng Wang Zeyi Tao Hao Wei Ran Xiao |
| author_sort | Jiaqi Zhang |
| collection | DOAJ |
| description | Water temperature is an important index that affects physical, chemical and biological reactions in water environments, and accurate water temperature prediction is important. Water temperature prediction in a data-deficient area along the Yangtze River trunk stream was selected as the research object, the factors influencing water temperature changes, such as air temperature, latitude and elevation, were analyzed, and the main factors were determined. A linear regression equation of water temperature and air temperature under different climate types was constructed. The Air2stream model was used for water temperature prediction, and the model prediction accuracies were compared. (1) Water temperature changes are mainly controlled by air temperature, and (2) the averaged root mean square error (RMSE) of water temperatures predicted by the linear regression equation and Air2stream model were 1.79 °C and 1.40 °C, respectively. The averaged determination coefficients (R2) for the Air2stream model under the plateau alpine and subtropical monsoon climate types were 0.97 and 0.95, respectively. (3) The prediction accuracy of the Air2stream model exceeded that of the linear regression equation. Although the phenomenon of water temperature lagging behind air temperature is becoming increasingly obvious in high-flow areas, the water temperature prediction method of the water temperature-air temperature linear regression equation coupled with the Air2stream model can provide more reliable prediction results, thereby providinge a reference for water temperature prediction in data-deficient areas. |
| format | Article |
| id | doaj-art-018db18cc2c64a0c81f0318c2d140c86 |
| institution | OA Journals |
| issn | 2666-4453 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | KeAi Communications Co., Ltd. |
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| series | Water Cycle |
| spelling | doaj-art-018db18cc2c64a0c81f0318c2d140c862025-08-20T02:16:21ZengKeAi Communications Co., Ltd.Water Cycle2666-44532025-01-01625927110.1016/j.watcyc.2025.03.001Methods for predicting water temperature in data-scarce areas under different climate regions of ChinaJiaqi Zhang0Jun Ma1Yaqian Xu2Defu Liu3Zhangpeng Wang4Zeyi Tao5Hao Wei6Ran Xiao7Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, ChinaKey Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, China; Corresponding author. Hubei University of Technology, No.28, Nali Road, Hongshan District, Wuhan, 430068, Hubei Province, PR China.Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, China; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, PR China; Corresponding author. Hubei University of Technology, No.28, Nali Road, Hongshan District, Wuhan, 430068, Hubei Province, PR China.Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, China; State Key Laboratory of Water Resources Engineering and Management, Wuhan University, Wuhan, 430072, PR ChinaKey Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, ChinaKey Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, ChinaKey Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, ChinaKey Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes, Ministry of Education, Hubei University of Technology, Wuhan, 430068, China; Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes, Hubei University of Technology, Wuhan, 430068, China; Hubei Key Laboratory of Environmental Geotechnology and Ecological Remediation for Lake & River, Hubei University of Technology, Wuhan, 430068, ChinaWater temperature is an important index that affects physical, chemical and biological reactions in water environments, and accurate water temperature prediction is important. Water temperature prediction in a data-deficient area along the Yangtze River trunk stream was selected as the research object, the factors influencing water temperature changes, such as air temperature, latitude and elevation, were analyzed, and the main factors were determined. A linear regression equation of water temperature and air temperature under different climate types was constructed. The Air2stream model was used for water temperature prediction, and the model prediction accuracies were compared. (1) Water temperature changes are mainly controlled by air temperature, and (2) the averaged root mean square error (RMSE) of water temperatures predicted by the linear regression equation and Air2stream model were 1.79 °C and 1.40 °C, respectively. The averaged determination coefficients (R2) for the Air2stream model under the plateau alpine and subtropical monsoon climate types were 0.97 and 0.95, respectively. (3) The prediction accuracy of the Air2stream model exceeded that of the linear regression equation. Although the phenomenon of water temperature lagging behind air temperature is becoming increasingly obvious in high-flow areas, the water temperature prediction method of the water temperature-air temperature linear regression equation coupled with the Air2stream model can provide more reliable prediction results, thereby providinge a reference for water temperature prediction in data-deficient areas.http://www.sciencedirect.com/science/article/pii/S2666445325000078Data-deficient areaWater temperature forecastingLinear fittingAir2stream modelClimate type |
| spellingShingle | Jiaqi Zhang Jun Ma Yaqian Xu Defu Liu Zhangpeng Wang Zeyi Tao Hao Wei Ran Xiao Methods for predicting water temperature in data-scarce areas under different climate regions of China Water Cycle Data-deficient area Water temperature forecasting Linear fitting Air2stream model Climate type |
| title | Methods for predicting water temperature in data-scarce areas under different climate regions of China |
| title_full | Methods for predicting water temperature in data-scarce areas under different climate regions of China |
| title_fullStr | Methods for predicting water temperature in data-scarce areas under different climate regions of China |
| title_full_unstemmed | Methods for predicting water temperature in data-scarce areas under different climate regions of China |
| title_short | Methods for predicting water temperature in data-scarce areas under different climate regions of China |
| title_sort | methods for predicting water temperature in data scarce areas under different climate regions of china |
| topic | Data-deficient area Water temperature forecasting Linear fitting Air2stream model Climate type |
| url | http://www.sciencedirect.com/science/article/pii/S2666445325000078 |
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