Identifying critical landslide events: a novel approach based on equivalent displacements

The growing frequency and intensity of natural hazards has resulted in increased efforts towards their study and control. As a consequence, monitoring systems have emerged as pivotal components of landslide Early Warning Systems (EWS), facilitating comprehension of process evolution and assessment of mitigation needs. This progress stems from technological advancements, yielding more precise sensors and automated data acquisition procedures. Nevertheless, challenges persist in interpreting data, particularly in identifying critical events and forecasting failures. This paper presents the application of a methodology developed by the authors to identify significant deviations in potentially critical events from previously sampled data, with the objective of separating them from false alarms. The core of this approach relies on establishing a threshold value based on antecedent landslide behavior. Specifically, the reference value is derived from assessing equivalent displacements, defined as displacements observed within a time interval equal to that of the critical event. The paper presents various case studies highlighting the efficacy of the proposed model as a valuable tool for near-real-time assessment of landslide behavior