Contribution of Snow-Melt Water to the Streamflow over the Three-River Headwater Region, China
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| Publicado en: | Remote Sensing vol. 13, no. 8 (2021), p. 1585 |
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| Otros Autores: | , , , , , , |
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| Acceso en línea: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2072-4292 | ||
| 024 | 7 | |a 10.3390/rs13081585 |2 doi | |
| 035 | |a 2550451125 | ||
| 045 | 2 | |b d20210101 |b d20211231 | |
| 084 | |a 231556 |2 nlm | ||
| 100 | 1 | |a Li, Sisi |u Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, China; <email>liss.16b@igsnrr.ac.cn</email> (S.L.); <email>huawei.pi@wsu.edu</email> (H.P.) | |
| 245 | 1 | |a Contribution of Snow-Melt Water to the Streamflow over the Three-River Headwater Region, China | |
| 260 | |b MDPI AG |c 2021 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Snowmelt water is essential to the water resources management over the Three-River Headwater Region (TRHR), where hydrological processes are influenced by snowmelt runoff and sensitive to climate change. The objectives of this study were to analyse the contribution of snowmelt water to the total streamflow (fQ,snow) in the TRHR by applying a snowmelt tracking algorithm and Variable Infiltration Capacity (VIC) model. The ratio of snowfall to precipitation, and the variation of the April 1 snow water equivalent (SWE) associated with fQ,snow, were identified to analyse the role of snowpack in the hydrological cycle. Prior to the simulation, the VIC model was validated based on the observed streamflow data to recognize its adequacy in the region. In order to improve the VIC model in snow hydrology simulation, Advanced Scanning Microwave Radiometer E (ASMR-E) SWE product data was used to compare with VIC output SWE to adjust the snow parameters. From 1971 to 2007, the averaged fQ,snow was 19.9% with a significant decreasing trend over entire TRHR (p < 0.05).The influence factor resulted in the rate of change in fQ,snow which were different for each sub-basin TRHR. The decreasing rate of fQ,snow was highest of 0.24%/year for S_Lantsang, which should be due to the increasing streamflow and the decreasing snowmelt water. For the S_Yangtze, the increasing streamflow contributed more than the stable change of snowmelt water to the decreasing fQ,snow with a rate of 0.1%/year. The April 1 SWE with the minimum value appearing after 2000 and the decreased ratio of snowfall to precipitation during the study period, suggested the snow solid water resource over the TRHR was shrinking. Our results imply that the role of snow in the snow-hydrological regime is weakening in the TRHR in terms of water supplement and runoff regulation due to the decreased fQ,snow and snowfall. | |
| 651 | 4 | |a Fraser River | |
| 651 | 4 | |a China | |
| 653 | |a Climate change | ||
| 653 | |a Water resources management | ||
| 653 | |a Snowmelt | ||
| 653 | |a Snow-water equivalent | ||
| 653 | |a Glaciers | ||
| 653 | |a Runoff | ||
| 653 | |a Basins | ||
| 653 | |a Snowpack | ||
| 653 | |a Stream flow | ||
| 653 | |a Hydrology | ||
| 653 | |a Rivers | ||
| 653 | |a Hydrologic data | ||
| 653 | |a Meltwater | ||
| 653 | |a Infiltration capacity | ||
| 653 | |a Precipitation | ||
| 653 | |a Water resources | ||
| 653 | |a Hydrologic regime | ||
| 653 | |a Adequacy | ||
| 653 | |a Hydrologic cycle | ||
| 653 | |a Snow | ||
| 653 | |a Snowfall | ||
| 653 | |a Regions | ||
| 653 | |a Global warming | ||
| 653 | |a Algorithms | ||
| 653 | |a Stream discharge | ||
| 653 | |a Remote sensing | ||
| 700 | 1 | |a Liu, Mingliang |u Department of Civil and Environmental Engineering, Washington State University, Pullman, WA 99164, USA; <email>mingliang.liu@wsu.edu</email> | |
| 700 | 1 | |a Adam, Jennifer C |u Department of Civil and Environmental Engineering, Washington State University, Pullman, WA 99164, USA; <email>mingliang.liu@wsu.edu</email> | |
| 700 | 1 | |a Pi, Huawei |u Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, China; <email>liss.16b@igsnrr.ac.cn</email> (S.L.); <email>huawei.pi@wsu.edu</email> (H.P.) | |
| 700 | 1 | |a Su, Fengge |u Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China; <email>fgsu@itpcas.ac.cn</email> | |
| 700 | 1 | |a Li, Dongyue |u Department of Geography, University of California, Los Angeles, CA 90095, USA; <email>dongyueli@ucla.edu</email> | |
| 700 | 1 | |a Liu, Zhaofei |u Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; <email>zfliu@igsnrr.ac.cn</email> (Z.L.); <email>yaozj@igsnrr.ac.cn</email> (Z.Y.) | |
| 700 | 1 | |a Yao, Zhijun |u Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; <email>zfliu@igsnrr.ac.cn</email> (Z.L.); <email>yaozj@igsnrr.ac.cn</email> (Z.Y.) | |
| 773 | 0 | |t Remote Sensing |g vol. 13, no. 8 (2021), p. 1585 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/2550451125/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/2550451125/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/2550451125/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |