Journal of Geophysical Research Atmospheres · 2007 · 202 citations · 40 references
EngineeringEarth SciencesGeologyGeomorphologyGeotechnical EngineeringSlope StabilityRock FailureRock Mass CharacterizationSlope AnalysisSlope Failure MechanismsSlope MonitoringBrittle FailureFailure MechanismsFailure-time ModelsRockfall DynamicsRockfallsSlope Failure ProcessesSlopesTime-dependent Failure
Large slope failures are increasingly governed by strain accumulation in the rock mass, with environmental conditions having a diminishing influence, suggesting that wide‑area monitoring of precursory behavior could enable failure time forecasting. The study aims to identify spatial and temporal patterns in rockfall activity preceding slope failure using high‑resolution laser scanning data. The authors analyze high‑resolution 3‑D laser‑scanned data from coastal rock cliffs to detect spatial and temporal patterns in rockfall activity before slope failure. The analysis shows that precise monitoring of rockfall rates reveals a time‑dependent sequence of smaller events leading up to major failures, enabling detection, measurement, and monitoring of precursory behavior, which has implications for slope management, mechanism understanding, and new warning systems.
In this paper we examine data generated using high‐resolution three‐dimensional laser scanning monitoring of coastal rock cliffs. These data are used to identify spatial and temporal patterns in rockfall activity behavior prior to slope failure. Analysis of the data suggests that given sufficient measurement precision precursory behavior, here manifest as the rate of rockfall activity prior to failure, can be detected, measured, and monitored. Environmental conditions appear to have a diminishing influence on the occurrence of increasingly large slope failures. The monitoring data implies a time‐dependent sequence in the occurrence of smaller rockfalls in the period leading to the largest failures recorded. This behavior is attributed to the mechanisms of strain accumulation in the rock mass resulting from brittle failure of the slope. The implication is that combining these data with models of failure mechanisms may allow failure time to be forecast from wide‐area monitoring of precursory behavior. These findings have implications for the management of potentially unstable slopes, the understanding of slope failure mechanisms, and the generation of a new type of slope failure warning systems.
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