Exploring the potential of SWOT for water level monitoring in the Qinghai Lake
- Vol. 27, Issue 8, Pages: 1888-1898(2023)
Published： 07 August 2023
DOI： 10.11834/jrs.20231628
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摘要
青藏高原湖泊群水位变化是反映全球气候变化的重要指标。在实测数据稀缺和现有卫星时空覆盖范围低的限制下，基于雷达干涉模式的新一代SWOT（Surface Water and Ocean Topography）卫星可为全球内陆水体提供高时空分辨率和高精度的水位信息，是对传统观测形式的有力补充。在卫星发射之前探讨其监测潜力具有重要意义。本研究以青藏高原最大的青海湖为例，使用CNES SWOT水文模拟器，模拟2010年—2018年类SWOT水位序列。通过分别采用实测水位、光学水位和雷达水位作为SWOT模拟器驱动，探讨了SWOT模拟器模拟精度对输入驱动的敏感性，并在多个尺度下评价了其模拟表现。结果表明：多种驱动数据情景下，类SWOT水位均可在季节和全年尺度上捕捉青海湖水位变化过程，相关系数和纳什效率系数分别在0.9—1.0和0.8—0.99变化；且可较好监测到青海湖水位长期变化趋势。SWOT具有监测青藏高原湖泊群水位动态的巨大潜力，能够有效观测湖泊水位变化。
Abstract
The water level changes in the lake groups on the Qinghai‒Tibetan Plateau is crucial for understanding global climate change and melting glaciers regionally. However
in-situ measurements are still lacking due to remote locations and material requirements. The current in-orbit optical satellites as well as radar and laser altimetry satellites have a relatively coarse spatiotemporal resolution and poor retrieval accuracies
both of which can be addressed in the future Surface Water and Ocean Topography (SWOT) mission. Therefore
the main objective of our study is to assess the water level monitoring potential of SWOT for the largest lake in China
that is
the Qinghai Lake in the Qinghai‒Tibetan Plateau.
This study obtained SWOT-like water level time series covering the years 2010 to 2018 for the Qinghai Lake from in-situ measurements
the optical altimetry dataset
and radar altimetry products by using the CNES SWOT Hydrology Toolbox. A systematical performance evaluation of SWOT-like lake level was then conducted by comparing this level with the reference height. SWOT-like water volume time series under different input scenarios for the Qinghai Lake were estimated based on its hypsometric curve and were subsequently validated using the results derived from the Gravity Recovery and Climate Experiment (GRACE) mission and the WaterGAP global hydrological model (WGHM).
In general
the SWOT-like water level time series can capture the seasonal and annual water level variations with an r/NSE ranging from 0.9 to 1.0 and from 0.8 to 0.99
respectively. Meanwhile
the SWOT-like lake level time series accurately demonstrate the long-term trends of water level in Qinghai Lake for the years 2010 to 2018 at various scales. The SWOT-inferred water volume changes under multiple forcing scenarios show change patterns that are comparable with the GRACE and WGHM results.
The SWOT-like water level for the Qinghai Lake for the years 2010 to 2018 shows satisfactory accuracy at both seasonal and annual scales as revealed in comparisons with in-situ measurements
the optical altimetry dataset
and the radar altimetry product. The patterns of the SWOT-inferred water volume changes are also similar to the GRACE and WGHM results
thereby indicating the great water level and volume monitoring potential of the future SWOT mission. In our future work
we will derive time-varying water extent maps of Qinghai Lake by using multi-source optical imageries
including Landsat
Sentinel
and Gaofen series satellites. We also plan to carry further experiments for all lakes (
>
1 km
2
) in the Qinghai‒Tibetan Plateau to assess the large-scale lake level monitoring potential of SWOT.
关键词
SWOT卫星青藏高原青海湖水位监测遥感测高
Keywords
SWOTQinghai-Tibetan PlateauQinghai Lakewater level monitoringremote sensingaltimetry
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Aerospace Information Research Institute, Chinese Academy of Sciences
State Key Laboratory of Remote Sensing Science, Beijing Normal University
Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University
Institute of Remote Sensing Science and Engineering, Faculty of Geographical Science, Beijing Normal University
Academy of Plateau Science and Sustainability, Qinghai Normal University
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