Early identification and dynamic processes of ridge-top rockslides: implications from the Su Village landslide in Suichang County, Zhejiang Province, China
Ridge-top rockslides frequently cause huge property losses and casualties due to the difficulties involved in detecting their precursors by means of manual surveys. Their early identification and the surrounding area’s evaluation in terms of potential danger are essential for preventing disasters. The recent large rockslide which occurred at Su Village, which is in possession of data related to pre-failure images, real-time video, and post-failure boreholes, is helpful for providing new insights into the processes associated with these events. Due to a strong sustained rainfall, a large volume of granite blocks rapidly descended from the upper part of the hillside, causing 27 deaths and destroying more than 20 houses. It is found that the early identification of the hazard associated with such rockfalls can be made by the analysis of remote sensing images and Persistent Scatterer Interferometry (PSI) analysis of Synthetic Aperture Radar (SAR) data. The depth-integrated continuum method, including taking the entrainment effect into account, was adopted to analyze the dynamic processes and to identify the areas at risk. The computational results show that the evaluated runout distance and extent match well with the field investigation results. The parameter sensitivity surrounding cohesion, coefficients of lateral earth pressure, and volume amplification were analyzed. It is demonstrated that the cohesion plays a significant role in the dynamic processes and the deposited area. However, the effects from the earth pressure coefficient and volume bulking are comparatively weaker.
KeywordsRockslide Remote sensing image InSAR Dynamic process MacCormack-TVD scheme Numerical modeling
The authors wish to thank the armed police traffic team who assisted us greatly during the field work. The Sentinel-1A SAR images were provided by the European Space Agency (EAS).
Financial support was provided by the National Key Research and Development Program of China (Project No. 2017YFC1501000), the NSFC (Grant No. 41572303, 41520104002), and the CAS Youth Innovation Promotion Association and Joint Project of GAS and CAS (2017HZ-03).
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