Landslide failure forecast in near-real-time

Abstract

We present a new method to achieve failure forecast of landslide phenomena by considering near-real-time monitoring data. Starting from the inverse velocity theory, we jointly analyse landslide surface displacements on different time windows, and apply straightforward statistical methods to obtain confidence intervals on the forecasted time of failure. Our results can be relevant to support the management of early warning systems during landslide emergency conditions, also when the predefined displacement and/or velocity thresholds are exceeded. In addition, our statistical approach for the definition of confidence interval and forecast reliability can be applied also to different failure forecast methods. We applied for the first time the herein presented approach in near-real-time during the emergency scenario relevant to the reactivation of the La Saxe rockslide, a large mass wasting menacing the population of Courmayeur, northern Italy, and the important European route E25. Our results show how the application of simplified but robust forecast models can be a convenient method to manage and support early warning systems during critical situations.