Enhancing the temporal resolution of water levels from altimetry using D-InSAR: A case study of 10 Swedish Lakes
Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirement...
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| Published in | Science of Remote Sensing Vol. 10; p. 100162 |
|---|---|
| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.12.2024
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2666-0172 2666-0172 |
| DOI | 10.1016/j.srs.2024.100162 |
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| Abstract | Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirements. With its advanced hardware and computational capabilities, altimetry has become a popular alternative to conventional in-situ gauging, although subject to the temporal availability of altimetric observations. To further improve the temporal resolution of altimetric measurements, we here combine radar altimetry data with Differential Interferometric Synthetic Aperture Radar (D-InSAR), using ten lakes in Sweden as a testing platform. First, we use Sentinel-1A and Sentinel-1B SAR images to generate consecutive six-day baseline interferograms across 2019. Then, we accumulate the phase change of coherent pixels to construct the time series of InSAR-derived water level anomalies. Finally, we retrieve altimetric observations from Sentinel-3, estimate their mean and standard deviation, and apply them to the D-InSAR standardized anomalies. In this way, we build a water-level time series with more temporal observations. In general, we find a strong agreement between water level estimates from the combination of D-InSAR and Satellite Altimetry (DInSAlt) and in-situ observations in eight lakes (Concordance Correlation Coefficient - CCC >0.8) and moderate agreement in two lakes (CCC >0.57). The applicability of DInSAlt is limited to lakes with suitable conditions for double-bounce scattering, such as the presence of trees or marshes. The accuracy of the water level estimates depends on the quality of the altimetry observations and the lake's width. These findings are important considering the recently launched Surface Water and Ocean Topography (SWOT) satellite, whose capabilities could expand our methodology's geographical applicability and reduce its reliance on ground measurements. |
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| AbstractList | Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirements. With its advanced hardware and computational capabilities, altimetry has become a popular alternative to conventional in-situ gauging, although subject to the temporal availability of altimetric observations. To further improve the temporal resolution of altimetric measurements, we here combine radar altimetry data with Differential Interferometric Synthetic Aperture Radar (D-InSAR), using ten lakes in Sweden as a testing platform. First, we use Sentinel-1A and Sentinel-1B SAR images to generate consecutive six-day baseline interferograms across 2019. Then, we accumulate the phase change of coherent pixels to construct the time series of InSAR-derived water level anomalies. Finally, we retrieve altimetric observations from Sentinel-3, estimate their mean and standard deviation, and apply them to the D-InSAR standardized anomalies. In this way, we build a water-level time series with more temporal observations. In general, we find a strong agreement between water level estimates from the combination of D-InSAR and Satellite Altimetry (DInSAlt) and in-situ observations in eight lakes (Concordance Correlation Coefficient - CCC >0.8) and moderate agreement in two lakes (CCC >0.57). The applicability of DInSAlt is limited to lakes with suitable conditions for double-bounce scattering, such as the presence of trees or marshes. The accuracy of the water level estimates depends on the quality of the altimetry observations and the lake's width. These findings are important considering the recently launched Surface Water and Ocean Topography (SWOT) satellite, whose capabilities could expand our methodology's geographical applicability and reduce its reliance on ground measurements. Lakes provide societies and natural ecosystems with valuable services such as freshwater supply and flood control. Water level changes in lakes reflect their natural responses to climatic and anthropogenic stressors; however, their monitoring is costly due to installation and maintenance requirements. With its advanced hardware and computational capabilities, altimetry has become a popular alternative to conventional in-situ gauging, although subject to the temporal availability of altimetric observations. To further improve the temporal resolution of altimetric measurements, we here combine radar altimetry data with Differential Interferometric Synthetic Aperture Radar (D-InSAR), using ten lakes in Sweden as a testing platform. First, we use Sentinel-1A and Sentinel-1B SAR images to generate consecutive six-day baseline interferograms across 2019. Then, we accumulate the phase change of coherent pixels to construct the time series of InSAR-derived water level anomalies. Finally, we retrieve altimetric observations from Sentinel-3, estimate their mean and standard deviation, and apply them to the D-InSAR standardized anomalies. In this way, we build a water-level time series with more temporal observations. In general, we find a strong agreement between water level estimates from the combination of D-InSAR and Satellite Altimetry (DInSAlt) and in-situ observations in eight lakes (Concordance Correlation Coefficient - CCC >0.8) and moderate agreement in two lakes (CCC >0.57). The applicability of DInSAlt is limited to lakes with suitable conditions for double-bounce scattering, such as the presence of trees or marshes. The accuracy of the water level estimates depends on the quality of the altimetry observations and the lake's width. These findings are important considering the recently launched Surface Water and Ocean Topography (SWOT) satellite, whose capabilities could expand our methodology's geographical applicability and reduce its reliance on ground measurements. |
| ArticleNumber | 100162 |
| Author | Aminjafari, Saeid Papa, Fabrice Jaramillo, Fernando Brown, Ian Frappart, Frédéric |
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| Cites_doi | 10.1016/j.asr.2016.10.008 10.1016/j.rse.2005.10.027 10.3390/rs10060966 10.3390/w10030297 10.1109/TGRS.2009.2026895 10.1029/EO081i048p00583 10.1038/s43017-020-0067-5 10.1029/2006RG000197 10.3390/rs12183055 10.1038/s41598-021-84282-x 10.1175/1520-0434(2001)016<0736:SAATSC>2.0.CO;2 10.1029/2002EO000007 10.1002/hyp.13899 10.1016/j.rse.2007.06.008 10.1088/1748-9326/aa9d23 10.1029/2021GL095950 10.5194/hess-18-2007-2014 10.1080/01490410903094833 10.1038/s41467-020-14624-2 10.1016/j.rse.2017.09.003 10.1016/j.jhydrol.2017.02.038 10.1016/j.rse.2016.12.029 10.1029/2017JB015305 10.1038/s41586-021-03262-3 10.1016/j.rse.2018.02.037 10.1016/j.rse.2017.10.038 10.1016/j.image.2020.116061 10.1007/s10333-022-00890-x 10.1016/j.earscirev.2020.103269 10.1029/2022WR034290 10.1016/j.rse.2021.112580 10.1080/01431169408954125 10.1016/j.rse.2019.111444 10.3390/rs12071156 10.3390/rs13112196 10.1016/j.rse.2011.03.005 10.1029/2023WR036160 10.1029/1998GL900033 10.1016/j.jhydrol.2021.126196 10.1038/35004560 10.1016/j.rse.2020.111750 |
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| Keywords | DInSAlt Lake water levels Satellite altimetry D-InSAR |
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