Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data
Performing research on the variation in lake water on the Qinghai–Tibet Plateau (QTP) can give the area’s ecological environmental preservation a scientific foundation. In this paper, we first created a high-precision dataset of lake water level variation every 10 days, from July 2002 to December 20...
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| Format: | Article |
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MDPI AG
2023-03-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/7/1746 |
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| author | Jianbo Wang Jinyang Wang Shunde Chen Jianbo Luo Mingzhi Sun Jialong Sun Jiajia Yuan Jinyun Guo |
| author_facet | Jianbo Wang Jinyang Wang Shunde Chen Jianbo Luo Mingzhi Sun Jialong Sun Jiajia Yuan Jinyun Guo |
| author_sort | Jianbo Wang |
| collection | DOAJ |
| description | Performing research on the variation in lake water on the Qinghai–Tibet Plateau (QTP) can give the area’s ecological environmental preservation a scientific foundation. In this paper, we first created a high-precision dataset of lake water level variation every 10 days, from July 2002 to December 2022, using multi-source altimetry satellite SGDR data (Envisat RA-2, SARAL, Jason-1/2, and Sentinel-3A/3B SRAL), which integrated the methods of atmospheric path delay correction, waveform re-tracking, outlier detection, position reduction using a height difference model, and inter-satellite deviation adjustment. Then, using Landsat-5 Thematic Mapper, Landsat-7 Enhanced Thematic Mapper, and Landsat 8 Operational Land Imager data, an averaged area series of Lake Qinghai (LQ) from September to November, each year from 2002 to 2019, was produced. The functional connection between the water level and the area was determined by fitting the water level–area series data, and the lake area time series, of LQ. Using the high-precision lake water level series, the fitted lake surface area time series, and the water storage variation equation, the water storage variation time series of LQ was thus calculated every 10 days, from July 2002 to December 2022. When the hydrological gauge data from the Xiashe station and data from the worldwide inland lake water level database are used as references, the standard deviations of the LQ water level time series are 0.0676 m and 0.1201 m, respectively. The results show that the water storage of LQ increases by 11.022 × 10<sup>9</sup> m<sup>3</sup> from July 2002 to December 2022, with a growth rate of 5.3766 × 10<sup>8</sup> m<sup>3</sup>/a. The growth rate from January 2005 to January 2015 is 4.4850 × 10<sup>8</sup> m<sup>3</sup>/a, and from January 2015 to December 2022, the growth rate is 8.9206 × 10<sup>8</sup> m<sup>3</sup>/a. Therefore, the increased rate of water storage in LQ over the last 8 years has been substantially higher than in the previous 10 years. |
| first_indexed | 2024-03-11T05:27:00Z |
| format | Article |
| id | doaj.art-a49941620db749eda0202b86864b5abe |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T05:27:00Z |
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| spelling | doaj.art-a49941620db749eda0202b86864b5abe2023-11-17T17:28:19ZengMDPI AGRemote Sensing2072-42922023-03-01157174610.3390/rs15071746Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite DataJianbo Wang0Jinyang Wang1Shunde Chen2Jianbo Luo3Mingzhi Sun4Jialong Sun5Jiajia Yuan6Jinyun Guo7Jiangsu Key Laboratory of Marine Bioresources and Environment/Jiangsu Key Laboratory of Marine Biotechnology, Jiangsu Ocean University, Lianyungang 222001, ChinaSchool of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, ChinaSchool of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, ChinaSchool of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, ChinaSchool of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, ChinaJiangsu Key Laboratory of Marine Bioresources and Environment/Jiangsu Key Laboratory of Marine Biotechnology, Jiangsu Ocean University, Lianyungang 222001, ChinaSchool of Geomatics, Anhui University of Science and Technology, Huainan 232001, ChinaCollege of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, ChinaPerforming research on the variation in lake water on the Qinghai–Tibet Plateau (QTP) can give the area’s ecological environmental preservation a scientific foundation. In this paper, we first created a high-precision dataset of lake water level variation every 10 days, from July 2002 to December 2022, using multi-source altimetry satellite SGDR data (Envisat RA-2, SARAL, Jason-1/2, and Sentinel-3A/3B SRAL), which integrated the methods of atmospheric path delay correction, waveform re-tracking, outlier detection, position reduction using a height difference model, and inter-satellite deviation adjustment. Then, using Landsat-5 Thematic Mapper, Landsat-7 Enhanced Thematic Mapper, and Landsat 8 Operational Land Imager data, an averaged area series of Lake Qinghai (LQ) from September to November, each year from 2002 to 2019, was produced. The functional connection between the water level and the area was determined by fitting the water level–area series data, and the lake area time series, of LQ. Using the high-precision lake water level series, the fitted lake surface area time series, and the water storage variation equation, the water storage variation time series of LQ was thus calculated every 10 days, from July 2002 to December 2022. When the hydrological gauge data from the Xiashe station and data from the worldwide inland lake water level database are used as references, the standard deviations of the LQ water level time series are 0.0676 m and 0.1201 m, respectively. The results show that the water storage of LQ increases by 11.022 × 10<sup>9</sup> m<sup>3</sup> from July 2002 to December 2022, with a growth rate of 5.3766 × 10<sup>8</sup> m<sup>3</sup>/a. The growth rate from January 2005 to January 2015 is 4.4850 × 10<sup>8</sup> m<sup>3</sup>/a, and from January 2015 to December 2022, the growth rate is 8.9206 × 10<sup>8</sup> m<sup>3</sup>/a. Therefore, the increased rate of water storage in LQ over the last 8 years has been substantially higher than in the previous 10 years.https://www.mdpi.com/2072-4292/15/7/1746water volume variation in Lake Qinghaimulti-source altimeter satelliteoptical remote sensing satellitesatellite applicationsQinghai–Tibet Plateau |
| spellingShingle | Jianbo Wang Jinyang Wang Shunde Chen Jianbo Luo Mingzhi Sun Jialong Sun Jiajia Yuan Jinyun Guo Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data Remote Sensing water volume variation in Lake Qinghai multi-source altimeter satellite optical remote sensing satellite satellite applications Qinghai–Tibet Plateau |
| title | Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data |
| title_full | Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data |
| title_fullStr | Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data |
| title_full_unstemmed | Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data |
| title_short | Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data |
| title_sort | study on the variations in water storage in lake qinghai based on multi source satellite data |
| topic | water volume variation in Lake Qinghai multi-source altimeter satellite optical remote sensing satellite satellite applications Qinghai–Tibet Plateau |
| url | https://www.mdpi.com/2072-4292/15/7/1746 |
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