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The use of real-time landslide early warning systems is attracting the attention of the scientific community, since it allows to assess “where” and “when” a shallow rainfall-induced landslide might occur by coupling rainfall amounts, hydrological models and slope-stability analysis. The paper deals with the main results of a back analysis, which refers to the application of a physically based stability model [Shallow Landslides Instability Prediction (SLIP)] on regional scale. The analysis concerns the occurrence of some recent rainfall-induced shallow landslides in the municipal territory of Broni, in the area of Oltrepo Pavese (Northern Italy). The study area is a hilly region 2.4 km2 wide, where more than 40 % of the territory has slopes steeper than 15° and altitudes are between 90 and 250 m a.s.l. As regards the geologic setting, clayey-silty shallow colluvial deposits, with a maximum thickness of about 3 m, overlap a bedrock made of clayey shales, calcareous flysch and marls. The SLIP model is based on the limit equilibrium method applied to an infinite slope and on the Mohr–Coulomb strength criterion for the soil. By assuming that the main hydro-geotechnical process that leads to failure is the saturation of parts of the soil, the model allows to take into account the condition of partial saturation of the soil. The safety factor (F S ) of a slope is also function of previous rainfalls. After the implementation of the model at territory scale, the input data have been introduced through a geographic information systems platform. In the current paper we mainly intend to evaluate the performance of SLIP at catchment scale, by comparison to (1) observed landslide events and (2) another well-established physically based model (TRIGRS). Further, we want to assess the suitability of the model as early warning tool. The results produced by the model are analyzed both in terms of safety factor maps, corresponding to some particular rainfall events, and in terms of the time-varying percentage of unstable areas over a 2-year span period. The paper shows the comparison between observed landslide localizations and model predictions. A quantitative comparison between the SLIP model and TRIGRS is presented, only for the most important event that occurred during the analyzed period. Overall, the results of the stability analyses based on observed rainfalls show the capability of the SLIP model to predict, in real-time and on a wide area, the occurrence of the analyzed phenomena.

On the 27 and 28 April 2009, the area of Oltrepo Pavese in northern Italy was affected by a very intense rainfall event that caused a great number of shallow landslides. These instabilities occurred on slopes covered by vineyards or recently formed woodlands and caused damage to many roads and one human loss. Based on aerial photographs taken immediately after the event and field surveys, more than 1600 landslides were detected. After acquiring topographical data, geotechnical properties of the soils and land use, susceptibility analysis on a territorial scale was carried out. In particular, different physically based models were applied to two contiguous sites with the same geological context but different typologies and sizes of shallow landslides. This paper presents the comparison between the ex-post results obtained from the different approaches. On the basis of the observed landslide localizations, the accuracy of the different models was evaluated, and the significant results are highlighted.

Rainfall-induced shallow landslides are hazardous phenomena that could cause several damages to infrastructures and people. To understand the hydrological and mechanical triggering conditions of shallow landslides in an area of Oltrepo Pavese (Northern Apennines, Italy) a field monitoring was conducted. In this work the results of 16 months monitoring are shown, focusing on the hydrological behaviour of the studied materials as function of rainfall and its effect on slope stability. Keywords Slope monitoring Shallow landslides Stability analysis Introduction Rainfall-induced

Le frane superficiali indotte da piogge intense e concentrate sono annoverabili tra i fenomeni franosi che causano il maggior numero di danni. Al fine di identificare, a scala di versante, i processi idrologici e geotecnici che controllano il loro innesco è stata installata una stazione sperimentale in un’area campione dell’Oltrepo Pavese per il monitoraggio del contenuto in acqua del terreno, della pressione interstiziale negativa, delle precipitazioni, della direzione ed intensità del vento e della radiazione netta. Il lavoro presenta i risultati preliminari ottenuti nel corso dei primi mesi di monitoraggio.

In this work a data-driven methodology for shallow landslide susceptibility assessment is presented. The procedure is based on the Generalized Additive Model (Hastie and Tibshirani, 1990) and it is developed to be applied in different contexts, using terrain attributes, land use and lithological data. The application of the method in three different contexts in Italy shows the good forecasting capability of the model. The implementation of this method allows for building landslide susceptibility maps, which are a fundamental basis in hazard and risk assessment.

Shallow landslides are generally triggered by intense rainfall of short duration. Even though they only involve small portions of hilly and mountainous terrain, they are the cause of widespread damages to people and infrastructure. The identification of shallow landslide-prone areas is, therefore, a necessity, to plan mitigation measures. Stereoscopic analysis of photogrammetric products is generally the most used technique for mapping landslides, especially if combined with intensive field surveys. The new generation of high-resolution satellites presents resolutions ranging from 0.5 to 2 m, offering a baseline for a quick and accurate update of regional inventory maps. In this paper we discuss the application of Pleiades images for rainfall-triggered shallow landslide mapping.

A long-term field monitoring proves very helpful to understand the effect of climatic variables on the hydrological response of a shallow soil and the role of atmospheric features in the triggering mechanism of rainfall-induced landslides. In this work, field measurements of the soil saturation in a sample slope, coming from 18 months continuous monitoring of soil water content, are presented. The experimental data are compared with the seasonal trends of the soil saturation resulting from the application of a simplified empirical model, based on rainfall and air temperature input data. The performance of the model is evaluated for two different soil depths, in order to establish a future application of this method to predict time trends of the saturation for large scale slope stability analyses. .

Rainfall-induced shallow landslides are hazardous phenomena that could cause several damages to infrastructures and people. To understand the hydrological and mechanical triggering conditions of shallow landslides in an area of Oltrepo Pavese (Northern Apennines, Italy) a field monitoring was conducted. In this work the results of 16 months monitoring are shown, focusing on the hydrological behaviour of the studied materials as function of rainfall and its effect on slope stability.

This paper presents the analysis of Pleiades images for the detection and the mapping of rainfall-induced shallow landslides in an area located in the Northern Apennines of Italy. The high resolution of the used images allowed to efficiently recognize also the landslides with small size and to quickly create an inventory map of these phenomena. Field investigations carried up for checking the real presence of the mapped landslides showed a good agreement with the detected through Pleiades images landslides, also in terms of appearance and size of these phenomena. For these reasons Pleiades images can be an useful device for identifying landslides events and to create a complete database of susceptible areas.

The principal aim of this study is to compare different landslide susceptibility zonation models for predicting areas prone to shallow landsliding using both physically distributed landslide models and artificial neural networks. Necessary geotechnical and hydrological parameters were obtained coupling sample laboratory analysis and in situ measures; soil thickness was estimated using an empirical model while distribution of rainfall intensity was analyzed by performing a spatial interpolation. The predictive capabilities of these models were finally evaluated using a threshold-independent quantitative method (the ROC plot).

Sand boils, which are also known as sand blows or sand volcanoes, are among the most common superficial effects induced by high-magnitude earthquakes. These generally occur in or close to alluvial plains when a strong earthquake (M >5) strikes on a lens of saturated and unconsolidated sand deposits that are constrained between silt-clay layers [Ambraseys 1988, Carter and Seed 1988, Galli 2000, Tuttle 2001, Obermeier et al. 2005], where the sediments are converted into a fluid suspension. The liquefaction phenomena requires the presence of saturated and uncompacted sand, and a groundwater table near the ground surface. This geological–geomorphological setting is common and widespread for the Po Plain (Italy) [Castiglioni et al. 1997]. The Po Plain (ca. 46,000 km2) represents 15% of the Italian territory. It hosts a population of about 20 million people (mean density of 450 people/km2) and many infrastructures. Thus, the Po Plain is an area of high vulnerability when considering the liquefaction potential in the case of a strong earthquake. Despite the potential, such phenomena are rarely observed in northern Italy [Cavallin et al. 1977, Galli 2000], because strong earthquakes are not frequent in this region; e.g., historical data report soil liquefaction near Ferrara in 1570 (M 5.3) and in Argenta 1624 (M 5.5) [Prestininzi and Romeo 2000, Galli 2000]. In the Emilia quakes of May 20 and 29, 2012, the most widespread coseismic effects were soil liquefaction and ground cracks, which occurred over wide areas in the Provinces of Modena, Ferrara, Bologna, Reggio Emilia and Mantova (Figure 1). […]

il contributo prende in analisi il rapporto tra il popolamento antio della valle del cesano e l'evoluzione della geografia fisica, allo scopo di ricostruire le variazioni del paesaggio legate in particolare alle vicende della città romana di suasa