From empirically to physically based early warning predictions of rainfall-induced landslides in silty volcanic soils: the Lattari Mountains case study

The work proposes a procedure to build an early warning predictive tool to assess the occurrence of rainfall-induced landslides in silty volcanic covers. The procedure combines both an empirically and a physically based tool used sequentially: the former is designed to be calibrated using older, highly sized and coarser rainfall data, and the latter to interpret recent and finer weather data. Both approaches need to be informed by a common experimental reference summarising the rainfall history, the rainfall point, defined as the couple made of antecedent 4-month rainfall cumulative value (C4m) and last-persistent event (CPLE). The empirical approach aims to identify if, in the (C4m–CPLE) plane, the rainfall point falls in a ‘safe’ or ‘potentially unsafe’ zone where the two distinct regions are built by interpreting rainfall data associated or not with landslide events. In the physically based approach, evaporation and runoff are estimated to refine the assessment of ‘effective’ rainfall points. The resulting transformed rainfall point (C′4 m, C′PLE) is turned into a prediction of the suction level at the mid-depth assumed as a ‘reference’ for the entire cover. Such value is compared with a suction threshold empirically defined. Suction levels prediction is developed by computing in the C′4 m–C′PLE plane the iso-suction lines generated by several rainfall scenarios. The accuracy of the developed procedure is comparable with state-of-the-art literature or operational approaches, properly identifying landslide case events and minimising the number of false alarms. Furthermore, it can inform the preparedness stages more effectively, explicitly accounting for the antecedent slope wetness stage and how it could be far from the incipient slope failure conditions. The developed procedure takes into account the effects of evaporation and antecedent rainfalls that, in dry periods, lead to very dry conditions in the subsoil, making even significant rainfall events inconsequential. Conversely, other procedures already operating in LEWS or highly considered literature background overestimate the effects of rainfalls during dry periods. The developed procedure delivers a simple but robust way to derive landslide thresholds based on the interpretation of past rainfall histories. At the same time, literature methods often require sophisticated approaches to retrieve thresholds.