Articles | Volume 17, issue 1
https://doi.org/10.5194/tc-17-349-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-349-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Jan 2023
Research article |
| 24 Jan 2023
| 24 Jan 2023
Ice thickness and water level estimation for ice-covered lakes with satellite altimetry waveforms and backscattering coefficients
Xingdong Li
State Key Laboratory of Hydroscience and Engineering, Department of
Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Collaborative Innovation Center for Integrated Management of Water
Resources and Water Environment in the Inner Mongolia Reaches of the Yellow
River, Hohhot 010018, China
State Key Laboratory of Hydroscience and Engineering, Department of
Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Collaborative Innovation Center for Integrated Management of Water
Resources and Water Environment in the Inner Mongolia Reaches of the Yellow
River, Hohhot 010018, China
Yanhong Cui
State Key Laboratory of Hydroscience and Engineering, Department of
Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Collaborative Innovation Center for Integrated Management of Water
Resources and Water Environment in the Inner Mongolia Reaches of the Yellow
River, Hohhot 010018, China
Tingxi Liu
CORRESPONDING AUTHOR
Water Conservancy and Civil Engineering College, Inner Mongolia Key
Laboratory of Water Resource Protection and Utilization, Inner Mongolia
Agricultural University, Hohhot 010018, China
Collaborative Innovation Center for Integrated Management of Water
Resources and Water Environment in the Inner Mongolia Reaches of the Yellow
River, Hohhot 010018, China
Jing Lu
State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Mohamed A. Hamouda
Department of Civil and Environmental Engineering, United Arab
Emirates University, Al Ain 15551, United Arab Emirates
National Water and Energy Center, United Arab Emirates University, Al Ain 15551, United Arab Emirates
Mohamed M. Mohamed
Department of Civil and Environmental Engineering, United Arab
Emirates University, Al Ain 15551, United Arab Emirates
National Water and Energy Center, United Arab Emirates University, Al Ain 15551, United Arab Emirates
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Cited
13 citations as recorded by crossref.
- Lake Ice Thickness Estimation Using Calibrated Enhanced-Resolution Passive Microwave Data L. Shi et al. https://doi.org/10.1109/TGRS.2025.3586818
- Assessing the impacts of ice penetration on monitoring water levels of high-latitude and -altitude lakes from CryoSat-2 altimetry Y. Feng & C. Song https://doi.org/10.1016/j.jhydrol.2024.131147
- Improving the Estimation of Lake Ice Thickness with High-Resolution Radar Altimetry Data A. Mangilli et al. https://doi.org/10.3390/rs16142510
- A first characterization of lake ice thickness on the Tibetan Plateau by leveraging satellite altimetry and ERA5 reanalysis T. Xia et al. https://doi.org/10.1016/j.jag.2026.105284
- Satellite-observed surging dynamics of North Kunchhang Glacier I in the Eastern Karakoram F. Zhao et al. https://doi.org/10.5194/tc-20-2143-2026
- Unveiling lake ice phenology in Central Asia under climate change with MODIS data and a two-step classification approach Y. Xu et al. https://doi.org/10.1016/j.rse.2023.113955
- Satellite altimetry reveals intensifying global river water level variability C. Fang et al. https://doi.org/10.1038/s41467-025-67682-9
- A Dual-Threshold Algorithm for Ice-Covered Lake Water Level Retrieval Using Sentinel-3 SAR Altimetry Waveforms F. Tang et al. https://doi.org/10.3390/s23249724
- Changes and attribution in lake ice phenology on the Mongolian Plateau from 2000 to 2023 and its future scenario projection based on CMIP6 and machine learning C. Ke et al. https://doi.org/10.1007/s11430-024-1614-y
- <bold>2000</bold><bold>~</bold><bold>2023</bold>年蒙古高原湖冰物候变化<bold>、</bold>归因分析以及基于<bold>CMIP6</bold>和机器学习的未来情景预估 长. 柯 et al. https://doi.org/10.1360/N072024-0384
- Rapid thinning of lake ice for Himalayan glacial lakes since 2010 M. Zhang et al. https://doi.org/10.1016/j.rse.2025.115062
- Lake Ice Thickness Retrieval Method with ICESat-2-Assisted CyroSat-2 Echo Peak Selection H. Ye et al. https://doi.org/10.3390/rs16030546
- Laboratory study of ultrasonic pulse reflection from freshwater ice D. Kovaldov et al. https://doi.org/10.1121/10.0044143
13 citations as recorded by crossref.
- Lake Ice Thickness Estimation Using Calibrated Enhanced-Resolution Passive Microwave Data L. Shi et al. https://doi.org/10.1109/TGRS.2025.3586818
- Assessing the impacts of ice penetration on monitoring water levels of high-latitude and -altitude lakes from CryoSat-2 altimetry Y. Feng & C. Song https://doi.org/10.1016/j.jhydrol.2024.131147
- Improving the Estimation of Lake Ice Thickness with High-Resolution Radar Altimetry Data A. Mangilli et al. https://doi.org/10.3390/rs16142510
- A first characterization of lake ice thickness on the Tibetan Plateau by leveraging satellite altimetry and ERA5 reanalysis T. Xia et al. https://doi.org/10.1016/j.jag.2026.105284
- Satellite-observed surging dynamics of North Kunchhang Glacier I in the Eastern Karakoram F. Zhao et al. https://doi.org/10.5194/tc-20-2143-2026
- Unveiling lake ice phenology in Central Asia under climate change with MODIS data and a two-step classification approach Y. Xu et al. https://doi.org/10.1016/j.rse.2023.113955
- Satellite altimetry reveals intensifying global river water level variability C. Fang et al. https://doi.org/10.1038/s41467-025-67682-9
- A Dual-Threshold Algorithm for Ice-Covered Lake Water Level Retrieval Using Sentinel-3 SAR Altimetry Waveforms F. Tang et al. https://doi.org/10.3390/s23249724
- Changes and attribution in lake ice phenology on the Mongolian Plateau from 2000 to 2023 and its future scenario projection based on CMIP6 and machine learning C. Ke et al. https://doi.org/10.1007/s11430-024-1614-y
- <bold>2000</bold><bold>~</bold><bold>2023</bold>年蒙古高原湖冰物候变化<bold>、</bold>归因分析以及基于<bold>CMIP6</bold>和机器学习的未来情景预估 长. 柯 et al. https://doi.org/10.1360/N072024-0384
- Rapid thinning of lake ice for Himalayan glacial lakes since 2010 M. Zhang et al. https://doi.org/10.1016/j.rse.2025.115062
- Lake Ice Thickness Retrieval Method with ICESat-2-Assisted CyroSat-2 Echo Peak Selection H. Ye et al. https://doi.org/10.3390/rs16030546
- Laboratory study of ultrasonic pulse reflection from freshwater ice D. Kovaldov et al. https://doi.org/10.1121/10.0044143
Saved (final revised paper)
Latest update: 01 Nov 2026
Short summary
This study blends advantages of altimetry backscattering coefficients and waveforms to estimate ice thickness for lakes without in situ data and provides an improved water level estimation for ice-covered lakes by jointly using different threshold retracking methods. Our results show that a logarithmic regression model is more adaptive in converting altimetry backscattering coefficients into ice thickness, and lake surface snow has differential impacts on different threshold retracking methods.
This study blends advantages of altimetry backscattering coefficients and waveforms to estimate...
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