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<p>The study presents the use of Ground-Based Synthetic Aperture Radar (GB-SAR) for large-scale and continuous deformation monitoring of dams, using the Enguri Dam in Georgia as a case study. The developed method includes precise georeferencing and a dedicated geocoding approach to correct geometric distortions associated with GB-SAR imaging of dams. The time-series-based interferometric analysis of image pairs (InSAR) incorporates phase unwrapping, atmospheric correction, and a smoothing of the observations using Functional Data Analysis (FDA), enabling the estimation of robust daily solutions of dam displacements with sub-millimeter accuracy. The analysis reveals a primary correlation between dam deformation and the reservoir water level, with deviations successfully explained by the Hydrostatic-Season-Time model (HST model). Model fitting yields standard deviations below 1 mm and highlights both hydrostatic and seasonal deformation components. The comparison with GNSS displacement measurements on the dam crest shows good correlation, although the results are strongly dependent on the chosen reference point. Overall, the findings show the potential of GB-SAR for highly precise, continuous, and long-term stable monitoring of dams.</p>

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Deformationsmonitoring mittels bodengestützter SAR-Interferometrie

  • 期刊论文

  • 发表日期：

    2026年4月27日

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  • Matthieu Rebmeister,
  • Andreas Schenk​,
  • Stefan Hinz,
  • Frédéric Andrian

摘要

The study presents the use of Ground-Based Synthetic Aperture Radar (GB-SAR) for large-scale and continuous deformation monitoring of dams, using the Enguri Dam in Georgia as a case study. The developed method includes precise georeferencing and a dedicated geocoding approach to correct geometric distortions associated with GB-SAR imaging of dams. The time-series-based interferometric analysis of image pairs (InSAR) incorporates phase unwrapping, atmospheric correction, and a smoothing of the observations using Functional Data Analysis (FDA), enabling the estimation of robust daily solutions of dam displacements with sub-millimeter accuracy. The analysis reveals a primary correlation between dam deformation and the reservoir water level, with deviations successfully explained by the Hydrostatic-Season-Time model (HST model). Model fitting yields standard deviations below 1 mm and highlights both hydrostatic and seasonal deformation components. The comparison with GNSS displacement measurements on the dam crest shows good correlation, although the results are strongly dependent on the chosen reference point. Overall, the findings show the potential of GB-SAR for highly precise, continuous, and long-term stable monitoring of dams.