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

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-04, Vol.15 (7), p.1746
• Main Authors: Wang, Jianbo, Wang, Jinyang, Chen, Shunde, Luo, Jianbo, Sun, Mingzhi, Sun, Jialong, Yuan, Jiajia, Guo, Jinyun
• Format: Article
• Language: English
• Subjects: Accuracy; Altimetry; Aquatic resources; Atmospheric correction; Climate change; Data analysis; Global temperature changes; Growth rate; Hydrology; Lakes; Landsat; Landsat satellites; multi-source altimeter satellite; optical remote sensing satellite; Outliers (statistics); Precipitation; Qinghai–Tibet Plateau; Rain; Remote sensing; Rivers; Runoff; satellite applications; Satellites; Time series; Trends; Variation; Water levels; Water storage; water volume variation in Lake Qinghai; Waveforms
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15071746

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.