United States Department of Transportation
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Predicting Seismic-Induced Rockfall Hazard for Targeted Site Mitigation
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2020-12-01
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[PDF-53.75 MB]
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Edition:Final Report
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Abstract:This research develops methods to predict seismic rockfall hazard areas by integrating two recent complementary research products (1) a lidar database of terrestrial surveys of rock slopes that span multiple earthquake events in Canterbury, NZ, and (2) a streamlined lidar-based rockfall hazard assessment method called RAI. Models were developed from those products to estimate increases in rockfall activity and magnitude with time as a result of seismic events. First, a simplified framework called the Rockfall Activity Rate System enables a statewide analysis for identifying sites for mitigation priority or detailed assessments. Next, a seismic version of the RAI framework was developed with scale factors for activity rates and failure depths to identify vulnerable sections of highway adjacent to the slope at a site. Third, a logistic regression model enables detailed analysis highlighting portions of a slope likely to fail in a seismic event. In addition to the models, a software package called Rambo enables efficient change analysis between point cloud datasets, surface modeling, morphological analysis, RAI analysis, as well as implementation of the seismic RAI and logistic regression analysis techniques developed in this research. Finally, several key findings from this research provide important context for seismic resilience of ODOT infrastructure. The authors estimate that rockfall activity may increase by 1-2 orders of magnitude in the days and weeks following an earthquake. Depending on the magnitude of shaking and geological conditions at a site, it might take several years to return to approximately to baseline levels of rockfall risk. Use of the knowledge and tools developed herein may help transportation planners prioritize sites and estimate maintenance needs for debris removal.
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