A reliability evaluation of four landslide failure forecasting methods in real-time monitoring applications
Citation
Sharifi, S., Macciotta, R., Hendry, M.T. (2024). A reliability evaluation of four landslide failure forecasting methods in real-time monitoring applications. Landslides, 21: 2545-2556. Link to paper
Abstract
The study examined analytical methods that use time-series kinematics: inverse velocity (INV), minimum inverse velocity (MINV), slope gradient (SLO), and velocity over acceleration (VOA). Early warning systems (EWSs) for landslides are becoming a pivotal tool to safeguard assets and stakeholders, with the mission that an EWS should be capable of reliably forecasting the failure time when the ground accelerates. Although an abundant number of studies applied these methods, they have been majorly examined in a back-analysis context where all measurements are incorporated into the forecasting process. A successful operation of EWSs in raising meaningful alarms calls for an examination in which the forecasting method is evaluated synchronously. This study evaluates the ability of the four mentioned methods to provide reliable forecasts in real time using a comprehensive database including 75 historical failures.