Leveraging ICESat, ICESat‐2, and Landsat for Global‐Scale, Multi‐Decadal Reconstruction of Lake Water Levels

Author:

Yao Fangfang12ORCID,Livneh Ben13ORCID,Rajagopalan Balaji13ORCID,Wang Jida45ORCID,Yang Kehan67ORCID,Crétaux Jean‐François8,Wang Chao9ORCID,Minear J. Toby1ORCID

Affiliation:

1. Cooperative Institute for Research in Environmental Sciences (CIRES) University of Colorado Boulder Boulder CO USA

2. Environmental Institute (EI) University of Virginia Charlottesville VA USA

3. Department of Civil, Environmental and Architectural Engineering University of Colorado Boulder Boulder CO USA

4. Department of Geography and Geographic Information Science University of Illinois Urbana‐Champaign Urbana IL USA

5. Department of Geography and Geospatial Sciences Kansas State University Manhattan KS USA

6. Department of Civil & Environmental Engineering University of Washington Seattle WA USA

7. eScience Institute University of Washington Seattle WA USA

8. Laboratoire d'Études en Géophysique et Océanographie Spatiales (LEGOS) CNES‐IRD‐CNRS‐UT3 Centre National d'Études Spatiales (CNES) Université de Toulouse Toulouse France

9. Department of Earth, Marine and Environmental Sciences University of North Carolina Chapel Hill NC USA

Abstract

AbstractLakes provide important water resources and many essential ecosystem services. Some of Earth's largest lakes recently reached record‐low levels, suggesting increasing threats from climate change and anthropogenic activities. Yet, continuous monitoring of lake levels is challenging at a global scale due to the sparse in situ gauging network and the limited spatial or temporal coverage of satellite altimeters. A few pioneering studies used water areas and hypsometric curves to reconstruct water levels but suffered from large uncertainties due to the lack of high‐quality hypsometry data. Here, we propose a novel proxy‐based method to reconstruct multi‐decadal water levels from 1992 to 2018 for both large and small lakes using Landsat images and ICESat (2003–2009) and recently launched ICESat‐2 (2018+) laser altimeters. Using the new method, we evaluate reconstructed levels of 342 lakes worldwide, with sizes ranging from 1 to 81,844 km2. Reconstructed water levels have a median root‐mean‐square error (RMSE) of 0.66 m, equivalent to 57% of the standard deviation of monthly level variability. Compared with two recently reconstructed water level data sets, the proposed method reduces the median RMSE by 27%–32%. The improvement is attributable to the new method's robust construction of high‐quality hypsometry, with a median R2 value of 0.92. Most reconstructed water level time series have a bi‐monthly or higher frequency. Given that ICESat‐2 and Landsat can observe hundreds of thousands of water bodies, this method can be applied to conduct an improved global inventory of time‐varying lake levels and thus inform water resource management more broadly than existing methods.

Publisher

American Geophysical Union (AGU)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Monitoring of Surface Water Area and Water Level Changes in Nine Plateau Lakes in Yunnan and Analysis of Influencing Factors;2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC);2024-05-24

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