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 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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Publication Details

Journal
Science of Remote Sensing
Published
2024-09-10
DOI
https://doi.org/10.1016/j.srs.2024.100162
Citations
3
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.85

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article

Enhancing the temporal resolution of water levels from altimetry using D-InSAR: A case study of 10 Swedish Lakes

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3 citations
Science of Remote Sensing
Flood Risk Assessment and Management
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article

Enhancing the temporal resolution of water levels from altimetry using D-InSAR: A case study of 10 Swedish Lakes

Ian Brown, Fernando Jaramillo, Fabrice Papa, Saeid Aminjafari, Frédéric Frappart
article en
3 citations

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.

Science of Remote SensingVol. 10
Centre National de la Recherche Scientifique (FR), Université Toulouse III - Paul Sabatier (FR), Stockholm Resilience Centre (SE), Universidade de Brasília (BR), Stockholm University (SE), Université Fédérale de Toulouse Midi-Pyrénées (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Laboratoire d’Études en Géophysique et Océanographie Spatiales (FR), Interaction Sol Plante Atmosphère (FR), Unité mixte de recherche Œnologie (FR), Bolin Centre for Climate Research (SE), Institut de Recherche pour le Développement (FR)
Swedish National Space Agency, Vetenskapsrådet
Clean water and sanitation
Openalex Percentile: Top 28%
Flood Risk Assessment and Management
0.85
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