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<p>Slope stability in tailings ponds is crucial for both environmental safety and operational efficiency, as instability can lead to significant hazards. This study introduces a novel integrated approach combining SBAS-InSAR and fluid–structure interaction numerical modeling to enhance the monitoring and stability analysis of tailing pond slopes. A fluid–structure interaction model is presented, incorporating the effects of pore pressure generated by reservoir water level on slope stability, thereby improving the accuracy of internal stress and deformation analysis. Sentinel-1 SAR data were used to monitor surface displacements over a 2-year period (2021–2023), while a three-dimensional numerical model was employed to simulate the mechanical behavior of the tailings dam, considering different material properties and reservoir water level conditions. The results reveal notable spatial patterns of slope deformation, with the presence of reservoir water level and stratigraphic boundaries leading to significant changes in stress and displacement profiles. Comparison between the InSAR results and numerical simulations shows a high level of agreement, with error and statistical analyses, respectively, validating the robustness of the integrated approach. This study provides a comprehensive multi-source method for tailing pond slope monitoring, offering a more accurate and reliable technique for predicting slope instability and improving risk assessment.</p>

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Integration of InSAR and numerical modelling to assess tailings pond slope deformation affected by reservoir water

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月8日

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  • Liwei Lu,
  • Menghua Li,
  • Liang Chao

摘要

Slope stability in tailings ponds is crucial for both environmental safety and operational efficiency, as instability can lead to significant hazards. This study introduces a novel integrated approach combining SBAS-InSAR and fluid–structure interaction numerical modeling to enhance the monitoring and stability analysis of tailing pond slopes. A fluid–structure interaction model is presented, incorporating the effects of pore pressure generated by reservoir water level on slope stability, thereby improving the accuracy of internal stress and deformation analysis. Sentinel-1 SAR data were used to monitor surface displacements over a 2-year period (2021–2023), while a three-dimensional numerical model was employed to simulate the mechanical behavior of the tailings dam, considering different material properties and reservoir water level conditions. The results reveal notable spatial patterns of slope deformation, with the presence of reservoir water level and stratigraphic boundaries leading to significant changes in stress and displacement profiles. Comparison between the InSAR results and numerical simulations shows a high level of agreement, with error and statistical analyses, respectively, validating the robustness of the integrated approach. This study provides a comprehensive multi-source method for tailing pond slope monitoring, offering a more accurate and reliable technique for predicting slope instability and improving risk assessment.