Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations
Satellite laser altimetry has been widely used for monitoring surface height changes in inland waters. However, constructing time series of water levels is partially limited in temporal resolution only based on the individual orbit of altimeter observations. To densify and optimize the time series o...
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| Format: | Article |
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MDPI AG
2023-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/3/780 |
| _version_ | 1797623335613366272 |
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| author | Tan Chen Chunqiao Song Pengfei Zhan Chenyu Fan |
| author_facet | Tan Chen Chunqiao Song Pengfei Zhan Chenyu Fan |
| author_sort | Tan Chen |
| collection | DOAJ |
| description | Satellite laser altimetry has been widely used for monitoring surface height changes in inland waters. However, constructing time series of water levels is partially limited in temporal resolution only based on the individual orbit of altimeter observations. To densify and optimize the time series of altimetry-based water levels is crucial to the scientific understanding of lake hydrologic dynamics. This paper focuses on synthesizing the multi-orbit on-lake observations from the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) to densify and refine the water level time series for large lakes. The approach of synthesizing water level time series has been validated through experiments applied to 18 large lakes worldwide, resulting in an average R of 0.93, RMSE of 0.14 m, MAE of 0.12 m, NSE of 0.67, and CV of 2.86, according to the hydrologic gauge stations. The evaluation results demonstrate that our approach can provide an effective solution for densifying the water level series of large lakes covered by multi-orbit ICESat-2 observations. Further, the approach can be extended to monitor the high-frequency variation of other lakes covered by the multiple ICESat-2 orbits. This approach provides the potential of generating higher-frequency estimates of water levels based on satellite altimetry, which could not only help to reveal the characteristics of the seasonal dynamics of lakes but also be used to investigate the abrupt water level changes due to hydrological extreme events (e.g., floods, droughts, etc.). |
| first_indexed | 2024-03-11T09:27:19Z |
| format | Article |
| id | doaj.art-80ab2a8c0f52449a8d8d9d9000f7d578 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T09:27:19Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-80ab2a8c0f52449a8d8d9d9000f7d5782023-11-16T17:54:08ZengMDPI AGRemote Sensing2072-42922023-01-0115378010.3390/rs15030780Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 ObservationsTan Chen0Chunqiao Song1Pengfei Zhan2Chenyu Fan3Key Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaKey Laboratory of Watershed Geographic Sciences, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, ChinaSatellite laser altimetry has been widely used for monitoring surface height changes in inland waters. However, constructing time series of water levels is partially limited in temporal resolution only based on the individual orbit of altimeter observations. To densify and optimize the time series of altimetry-based water levels is crucial to the scientific understanding of lake hydrologic dynamics. This paper focuses on synthesizing the multi-orbit on-lake observations from the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) to densify and refine the water level time series for large lakes. The approach of synthesizing water level time series has been validated through experiments applied to 18 large lakes worldwide, resulting in an average R of 0.93, RMSE of 0.14 m, MAE of 0.12 m, NSE of 0.67, and CV of 2.86, according to the hydrologic gauge stations. The evaluation results demonstrate that our approach can provide an effective solution for densifying the water level series of large lakes covered by multi-orbit ICESat-2 observations. Further, the approach can be extended to monitor the high-frequency variation of other lakes covered by the multiple ICESat-2 orbits. This approach provides the potential of generating higher-frequency estimates of water levels based on satellite altimetry, which could not only help to reveal the characteristics of the seasonal dynamics of lakes but also be used to investigate the abrupt water level changes due to hydrological extreme events (e.g., floods, droughts, etc.).https://www.mdpi.com/2072-4292/15/3/780assimilationICESat-2lakemulti-orbitwater level |
| spellingShingle | Tan Chen Chunqiao Song Pengfei Zhan Chenyu Fan Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations Remote Sensing assimilation ICESat-2 lake multi-orbit water level |
| title | Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations |
| title_full | Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations |
| title_fullStr | Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations |
| title_full_unstemmed | Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations |
| title_short | Densifying and Optimizing the Water Level Series for Large Lakes from Multi-Orbit ICESat-2 Observations |
| title_sort | densifying and optimizing the water level series for large lakes from multi orbit icesat 2 observations |
| topic | assimilation ICESat-2 lake multi-orbit water level |
| url | https://www.mdpi.com/2072-4292/15/3/780 |
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