A process-based model for the definition of hydrological alert systems in landslide risk mitigation
Authors: Floris M. , D'Alpaos A. , De Agostini A. , Stevan G. , Tessari G. , Genevois R. 
Published: November 2012

Abstract. The definition of hydrological alert systems for rainfall-induced landslides is strongly related to a deep knowledge of the geological and geomorphological features of the territory. Climatic conditions, spatial and temporal evolution of the phenomena and characterization of landslide triggering, together with propagation mechanisms, are the key elements to be considered. Critical steps for the development of the systems consist of the identification of the hydrological variable related to landslide triggering and of the minimum rainfall threshold for landslide occurrence. In this paper we report the results from a process-based model to define a hydrological alert system for the Val di Maso Landslide, located in the northeastern Italian Alps and included in the Vicenza Province (Veneto region, NE Italy). The instability occurred in November 2010, due to an exceptional rainfall event that hit the Vicenza Province and the entire NE Italy. Up to 500 mm in 3-day cumulated rainfall generated large flood conditions and triggered hundreds of landslides. During the flood, the Soil Protection Division of the Vicenza Province received more than 500 warnings of instability phenomena. The complexity of the event and the high level of risk to infrastructure and private buildings are the main reasons for deepening the specific phenomenon occurred at Val di Maso. Empirical and physically-based models have been used to identify the minimum rainfall threshold for the occurrence of instability phenomena in the crown area of Val di Maso landslide, where a retrogressive evolution by multiple rotational slides is expected. Empirical models helped in the identification and in the evaluation of recurrence of critical rainfall events, while physically-based modelling was essential to verify the effects on the slope stability of determined rainfall depths. Empirical relationships between rainfall and landslide consist of the calculation of rainfall Depth-Duration-Frequency (DDF) curves, which allow one to determine rainfall depth (or intensity) as a function of duration for given return periods or probabilities of exceedance (frequencies). Physically-based modelling was performed through coupled seepage and slope stability analyses. Combining results from empirical and physically-based modelling, the minimum alert threshold for a reactivation of the phenomenon was found in rainfall cumulated up to 60 days with a return period of 2 yr. These results were used to set up a hydrological alert system based on the calibration of DDF curves which can be used as a sort of abacus to plot in real time rainfall depths and to set increasing levels of alert on the basis of the degree of exceptionality of rainfall. The alert system for Val di Maso was successfully tested by the rainfall events that produced displacements which have been recorded by extensometers placed in the crown area after the November 2010 landslide. However, further tests are recommendable to improve the process-based model that led to the implementation of the alert system. To this end, a monitoring system is currently being realized. In the near future, monitoring data will help in testing and improving landslide evolution and alert models. The proposed hydrological alert system proves to be effective mainly because it can be applied to different scales of investigation and geological and geomorphological contexts. In fact, it might also be applicable to territorial scale analyses, as showed by the brief example provided in this paper on how the alert system could be used for landslide early warning in the area surrounding Val di Maso. Furthermore, it is easy to set up. The needed components are a rain gauge station, a software that compares rainfall data to rainfall events with different return periods and degree of alert, and a transmission system of the warning levels to authorities.