Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature Model
River water temperature (RWT), a primary parameter for hydrological and ecological processes, is influenced by both climate change and anthropogenic intervention. Studies on such influences have been severely restricted due to the scarcity of river temperature data. This paper proposed a three-stage...
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| Format: | Article |
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MDPI AG
2021-01-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/13/2/133 |
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| author | Xi Shi Jian Sun Zijun Xiao |
| author_facet | Xi Shi Jian Sun Zijun Xiao |
| author_sort | Xi Shi |
| collection | DOAJ |
| description | River water temperature (RWT), a primary parameter for hydrological and ecological processes, is influenced by both climate change and anthropogenic intervention. Studies on such influences have been severely restricted due to the scarcity of river temperature data. This paper proposed a three-stage method to obtain long-term daily water temperature for rivers and river-type reservoirs by integrating remote sensing technique and river water temperature modelling. The proposed three-stage method was applied to the Three Gorges Reservoir (TGR) and validated against in situ measured RWTs in the two study sites, Cuntan and Huanglingmiao. The result showed improvements in the method: the quadrate window selection and RWT correction jointly reduce RMSE from 1.8 to 0.9 °C in Cuntan and from 2.1 to 1.2 °C in Huanglingmiao. As a whole, the estimated daily RWT has a consistent RMSE of 1.1–1.9 °C. Meanwhile, by analysing the Landsat-derived daily RWT, we demonstrated that the TGR had a significant impact on the outflow’s thermal regime. At the downstream reach of TGR, an apparent increase in RWT in the cold season and interannual thermal regime delay compared to inflow were found with the increasing water level after the dam construction. All the results and analyses indicate that the proposed three-stage method could be applied to obtain long time series of daily RWT and provide a promising approach to qualitatively analyse RWT variation in the poorly gauged catchment for river water quality monitoring and management. |
| first_indexed | 2024-03-09T05:35:41Z |
| format | Article |
| id | doaj.art-80e1995cefc3401b874427f415f05418 |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T05:35:41Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
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| series | Water |
| spelling | doaj.art-80e1995cefc3401b874427f415f054182023-12-03T12:29:19ZengMDPI AGWater2073-44412021-01-0113213310.3390/w13020133Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature ModelXi Shi0Jian Sun1Zijun Xiao2State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, ChinaState Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, ChinaRiver water temperature (RWT), a primary parameter for hydrological and ecological processes, is influenced by both climate change and anthropogenic intervention. Studies on such influences have been severely restricted due to the scarcity of river temperature data. This paper proposed a three-stage method to obtain long-term daily water temperature for rivers and river-type reservoirs by integrating remote sensing technique and river water temperature modelling. The proposed three-stage method was applied to the Three Gorges Reservoir (TGR) and validated against in situ measured RWTs in the two study sites, Cuntan and Huanglingmiao. The result showed improvements in the method: the quadrate window selection and RWT correction jointly reduce RMSE from 1.8 to 0.9 °C in Cuntan and from 2.1 to 1.2 °C in Huanglingmiao. As a whole, the estimated daily RWT has a consistent RMSE of 1.1–1.9 °C. Meanwhile, by analysing the Landsat-derived daily RWT, we demonstrated that the TGR had a significant impact on the outflow’s thermal regime. At the downstream reach of TGR, an apparent increase in RWT in the cold season and interannual thermal regime delay compared to inflow were found with the increasing water level after the dam construction. All the results and analyses indicate that the proposed three-stage method could be applied to obtain long time series of daily RWT and provide a promising approach to qualitatively analyse RWT variation in the poorly gauged catchment for river water quality monitoring and management.https://www.mdpi.com/2073-4441/13/2/133river water temperatureLandsatthe Three Gorges Dam |
| spellingShingle | Xi Shi Jian Sun Zijun Xiao Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature Model Water river water temperature Landsat the Three Gorges Dam |
| title | Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature Model |
| title_full | Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature Model |
| title_fullStr | Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature Model |
| title_full_unstemmed | Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature Model |
| title_short | Investigation on River Thermal Regime under Dam Influence by Integrating Remote Sensing and Water Temperature Model |
| title_sort | investigation on river thermal regime under dam influence by integrating remote sensing and water temperature model |
| topic | river water temperature Landsat the Three Gorges Dam |
| url | https://www.mdpi.com/2073-4441/13/2/133 |
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