Study on the Variations in Water Storage in Lake Qinghai Based on Multi-Source Satellite Data

Author:

Wang Jianbo1234,Wang Jinyang4,Chen Shunde45,Luo Jianbo4,Sun Mingzhi6ORCID,Sun Jialong1234,Yuan Jiajia7,Guo Jinyun8ORCID

Affiliation:

1. Jiangsu Key Laboratory of Marine Bioresources and Environment/Jiangsu Key Laboratory of Marine Biotechnology, Jiangsu Ocean University, Lianyungang 222001, China

2. Jiangsu Marine Resources Development Institute, Lianyungang 222005, China

3. Co-Innovation Center of Jiangsu Marine Bio-Industry Technology, Jiangsu Ocean University, Lianyungang 222001, China

4. School of Marine Technology and Geomatics, Jiangsu Ocean University, Lianyungang 222005, China

5. Wuhan Geotechnical Engineering and Surveying Institute, Wuhan 430022, China

6. School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China

7. School of Geomatics, Anhui University of Science and Technology, Huainan 232001, China

8. College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao 266590, China

Abstract

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 × 109 m3 from July 2002 to December 2022, with a growth rate of 5.3766 × 108 m3/a. The growth rate from January 2005 to January 2015 is 4.4850 × 108 m3/a, and from January 2015 to December 2022, the growth rate is 8.9206 × 108 m3/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.

Funder

Priority Academic Program Development Project of Jiangsu Higher Education Institutions

Science and Technology Plan Project of the Lianyungang City

Open Fund Project of the Marine Information Technology Innovation Center of the Ministry of Natural Resources

Scientific Research Foundation for High-level Talents of Anhui University of Science and Technology

NSFC

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3