Lorella Montrasio

Shallow landslides triggered by rainfalls: modeling of some case histories in the Reggiano Apennine (Emilia Romagna Region, Northern Italy)

On April 10–11, 2005, the Emilia Romagna Apennine was affected by an intense rainfall event that triggered dozens of soil slips in the Province of Reggio Emilia. These shallow landslides occurred mainly on slopes of cultivated lands, often blocking roads, causing damages to crops and economic loss. Based on the analysis of an inventory of aerial photographs, it was possible to locate 45 sites where soil slips have occurred. In this paper, the area of study is described from a geological and climatic point of view. The authors analyze both the predisposing factors, related to the morphology of the territory, and the phenomena triggering factors, related to the rain trend. Once the geometrical features and characteristics of the soil slopes were available, a physically based triggering model, recently developed by the authors, was locally applied at each site. The model, which is based on the limit equilibrium method and on the hypothesis of infinite slope, is briefly described. It assumes a partial saturation condition of the soil and provides the safety factor of each slope as a function of time-variable rainfall intensity. The choice of the input parameters of the model is explained in detail. It is underlined, in particular, how the only parameter that has been determined through a procedure of back analysis, i.e., the discharge capability, is comparable to the typical permeability values obtained through field measurements by other authors, for similar kinds of soils and conditions. In this article, the results of the application of our model to the study areas, within a three-year time frame, are presented. Furthermore, on the basis of the analysis carried out, some observations on the operating mode of the model are carried out and its ability to predict a phenomenon triggering is evaluated.

Prediction of shallow landslide occurrence: validation of a physically-based approach through a real case study

In recent years, physically-based numerical models have frequently been used in the framework of early-warning systems devoted to rainfall-induced landslide hazard monitoring and mitigation. For this reason, in this work we describe the potential of SLIP (Shallow Landslides Instability Prediction), a simplified physically-based model for the analysis of shallow landslide occurrence. In order to test the reliability of this model, a back analysis of recent landslide events occurred in the study area (located SW of Messina, northeastern Sicily, Italy) on October 1st, 2009 was performed. The simulation results have been compared with those obtained for the same event by using TRIGRS, another well-established model for shallow landslide prediction. Afterwards, a simulation over a 2-year span period has been performed for the same area, with the aim of evaluating the performance of SLIP as early warning tool. The results confirm the good predictive capability of the model, both in terms of spatial and temporal prediction of the instability phenomena. For this reason, we recommend an operating procedure for the real-time definition of shallow landslide triggering scenarios at the catchment scale, which is based on the use of SLIP calibrated through a specific multi-methodological approach.

A prototype system for space–time assessment of rainfall-induced shallow landslides in Italy

In the last decades, physically based distributed models turned out rather promising to achieve the space–time assessment of shallow landslides at large spatial scale. This technical note deals with the application of a physically based stability model named Shallow Landslides Instability Prediction (SLIP), which has been adopted by the Department of National Civil Protection of Italy as a prototype early warning system for rainfall-induced shallow landslides on national scale. The model is used as a main methodology to create space–time shallow landslide susceptibility maps based on a simple deterministic slope-stability approach, combined with high-resolution rainfall information and geographic information system-based geospatial datasets. The safety factor as an index to measure slope instability is modeled as function of topographic, geologic, geotechnical and hydrologic variables. Although the main aim of this work was to prove the operational viability of such model on a nationwide domain and some simplification are adopted at this stage, hind cast tests on some relevant case histories of shallow landslides occurred between October 2009 and October 2011 showed that the model has skill in representing both timing and location of those shallow landslides.

Physical and numerical modelling of shallow landslides

Physical modelling is an extremely useful tool for the study of the triggering process of shallow landslides. For this reason, in this work, numerous laboratory tests have been performed using a specific flume test apparatus. A wide range of initial soil conditions (i.e. porosity and water content) has been investigated to analyze the induced effect on failure time and mode, even simulating the presence of preferential flow directions within the soil. Different tests have been performed also reproducing, on a laboratory scale, the landslide event occurred on October 1, 2009, in the area where the testing material was sampled (i.e. Giampilieri, north-eastern Sicily, Italy). Furthermore, the experimental results have been employed to verify the capability of shallow landslide instability prediction (SLIP), a simplified stability model for the prediction of shallow landslide occurrence, to reproduce the triggering process.

Space-Time Hazard Assessment of Rainfall-Induced Shallow Landslides

The paper deals with the application of a physically-based stability model that has been adopted by the Department of National Civil Protection as a prototype early warning system for rainfall-induced landslides in Italy, using rainfall data and geospatial datasets. The main features of the model are briefly recalled and particular attention is devoted to the discussion of the input data. The slope-stability analysis has been carried out on national scale, concerning some case-histories occurred between October 2009 and March 2011, on the basis of observed rainfalls. The comparison between observed landslide localizations and model back analysed results is finally presented.

Soil Saturation and Stability Analysis of a Test Site Slope Using the Shallow Landslide Instability Prediction (SLIP) Model

It is well-known that the degree of saturation is a soil state condition able to represent the hydrological response of a shallow soil to weather conditions. One of the oldest models that referred on the degree of saturation to carry out the slope stability analysis at different scales, was the Shallow Landslide Instability (SLIP) Model. This paper shows how the SLIP model can be used to derive a simplified method to estimate multiple seasonal cycles of the mean degree of saturation of soil and to carry out the time-varying stability analysis of a test site slope. The simplified method to assess the degree of saturation uses easily available climatic data, such as air temperature and rainfall depth, and is validated through the comparison with long-term field measurements on a slope in Canneto Pavese, northern Italy. The SLIP model is also applied to obtain the safety factor of the slope, that was subjected to a rainfall-induced shallow landslide during the field monitoring period. Comparisons between field measurements and model outputs are used to validate the capability of the model of predicting both the mean degree of saturation of the topsoil and the observed unstable condition.

Modeling the Shallow Landslides Occurred in Tizzano Val Parma in April 2013

In April 2013 a severe precipitation event hit the northern part of the Italian Apennines triggering more than a thousand landslides, which caused heavy damages to structures and infrastructures with consequent economic losses. A physically based model, named Shallow Landslide Instability Prediction (SLIP), has been used to evaluate, in back-analysis, the distribution of safety factor values in a small municipality of the Parma province, taking into account the rainfall precipitation events of April 2013. Different information layers, such as a 5 m × 5 m DEM, and pre-event flight images were used to retrieve the input parameters of the model. The modeled instability was evaluated according to the ROC plot evaluation method. The AUC (area under curve) of the ROC plot resulted 0.81, suggesting a good suitability of the prediction model in the studied context.