This paper presents the preliminary results of the IPL project 196 BDevelopment and applications of a multi-sensor drone for geohazards monitoring and mapping.^The objective of the project is to test the applicability of a multi-sensor drone for the mapping and monitoring of different types of geohazards. The Department of Earth Sciences of the University of Florence has developed a new type of drone airframe. Several survey campaigns were performed in the village of Ricasoli, in the Upper Arno river Valley (Tuscany, Italy) with the drone equipped with an optical camera to understand the possibility of this rising technology to map and characterize landslides. The aerial images were combined and analyzed using Structure-from-Motion (SfM) software. The collected data allowed an accurate reconstruction and mapping of the detected landslides. Comparative analysis of the obtained DTMs also permitted the detection of some slope portions being prone to failure and to evaluate the area and volume of the involved mass.
Abstract. In this work, we apply a physically based model, namely the HIRESSS (HIgh REsolution Slope Stability Simulator) model, to forecast the occurrence of shallow landslides at the regional scale. HIRESSS is a physically based distributed slope stability simulator for analyzing shallow landslide triggering conditions during a rainfall event. The modeling software is made up of two parts: hydrological and geotechnical. The hydrological model is based on an analytical solution from an approximated form of the Richards equation, while the geotechnical stability model is based on an infinite slope model that takes the unsaturated soil condition into account. The test area is a portion of the Aosta Valley region, located in the northwest of the Alpine mountain chain. The geomorphology of the region is characterized by steep slopes with elevations ranging from 400 m a.s.l. on the Dora Baltea River's floodplain to 4810 m a.s.l. at Mont Blanc. In the study area, the mean annual precipitation is about 800–900 mm. These features make the territory very prone to landslides, mainly shallow rapid landslides and rockfalls. In order to apply the model and to increase its reliability, an in-depth study of the geotechnical and hydrological properties of hillslopes controlling shallow landslide formation was conducted. In particular, two campaigns of on site measurements and laboratory experiments were performed using 12 survey points. The data collected contributed to the generation of an input map of parameters for the HIRESSS model. In order to consider the effect of vegetation on slope stability, the soil reinforcement due to the presence of roots was also taken into account; this was done based on vegetation maps and literature values of root cohesion. The model was applied using back analysis for two past events that affected the Aosta Valley region between 2008 and 2009, triggering several fast shallow landslides. The validation of the results, carried out using a database of past landslides, provided good results and a good prediction accuracy for the HIRESSS model from both a temporal and spatial point of view.
Riverbanks along the Arno River have been investigated with the aims of defining the main mechanisms of failure and retreat, their spatial distribution, and their causes. Geomorphological aspects were investigated by a reconnaissance of riverbank processes, for a number (26) of representative sites. Laboratory and in situ tests were then performed on a selected number of riverbanks (15). Based on the material characteristics, six main typologies of riverbanks have been defined, with homogeneous fine-grained and composite banks representing the most frequent types. Slab-type failures are the most frequent mechanism observed on fine-grained banks, while cantilever failures prevail on composite banks.The role of river stage and related pore water pressure distributions in triggering the main observed mechanisms of failure has been investigated using two different types of stability analysis. The first was conducted for 15 riverbanks, using the limit equilibrium method and considering simplified hypotheses for pore water pressure distribution (annulment of negative pore pressures in the portion of the bank between low water stage and peak stage). Stability conditions and predicted mechanisms of failure are shown to be in reasonably good agreement with field observations. Three riverbanks, representative of the main alluvial reaches of the river, were then selected for a more detailed bank stability analysis, consisting of: (a) definition of characteristic hydrographs of the reach with different return periods; (b) modelling of saturated and unsaturated flow using finite element seepage analysis; and (c) stability analysis with the limit equilibrium method, by adopting pore water pressure values derived from the seepage analysis. The results are compared to those obtained from the previous simplified analysis, and are used to investigate the different responses, in terms of stability, to different hydrological and riverbank conditions.
A severe rainstorm of high intensity occurred on 20th-21st November 2000, in the region of Pistoia, Tuscany, Italy, which triggered, within the entire province, over 50 landslides. These landslides can be broadly defined as complex earth slides-earth flows,originating as rotational slides that develop downslope into a flow. In this paper, two such landslides have been investigated by modelling the process of rainwater infiltration, the variations in both the positive and negative pore water pressures and their effect on slope stability during the storm. For both sites, results from morphometric and geotechnical analyses were used as a direct input to the numerical modelling. A modified Chu, 1978 approach was used to estimate the surface infiltration rate by adapting the original Green and Ampt, 1911 equations for unsteady rainfall intensity in conjunction with the surficial water balance. For transient conditions, a finite element analysis was used to model the fluctuations in pore water pressure during the storm, with the computed surface infiltration rate as the surface boundary condition. This was then followed by the application of the limit equilibrium Morgenstern and Price, 1965 slope-stability method, using the temporal pore water pressure distributions derived from the seepage analysis. From this methodology, a trend for the factor of safety was produced for both landslide sites. These results indicate that the most critical time step for failure was a few hours following the rainfall peak.
We attempt a characterization of the geotechnical and hydrological properties of hillslope deposits, with the final aim of providing reliable data to distributed catchment-scale numerical models for shallow landslide initiation. The analysis is based on a dataset built up by means of both field tests and laboratory experiments over 100 sites across Tuscany (Italy). The first specific goal is to determine the ranges of variation of the geotechnical and hydrological parameters that control shallow landslide-triggering mechanisms for the main soil classes. The parameters determined in the deposits are: grain size distribution, Atterberg limits, porosity, unit weight, in situ saturated hydraulic conductivity and shear strength parameters. In addition, mineral phases recognition via X-ray powder diffraction has been performed on the different soil types. The deposits mainly consist of well-sorted silty sands with low plastic behavior and extremely variable gravel and clay contents. Statistical analyses carried on these geotechnical and hydrological parameters highlighted that it is not possible to define a typical range of values only with relation to the main mapped lithologies, because soil characteristics are not simply dependent on the bedrock type from which the deposits originated. A second goal is to explore the relationship between soil type (in terms of grain size distribution) and selected morphometric parameters (slope angle, profile curvature, planar curvature and peak distance). The results show that the highest correlation between soil grain size classes and morphometric attributes is with slope curvature, both profile and planar.
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