This work focused on a post-wildfire landslide hazard assessment, applied to the 2017 Montagna del Morrone fire. This wildfire increased the possibility of landslides triggering, as confirmed by the occurrence of a debris flow, triggered by an intense, short duration rainfall event in August 2018. The study area was investigated through a detailed analysis incorporating morphometric analysis of the topography and hydrography and geomorphological field mapping, followed by the landslide hazard assessment. In detail, the analysis was performed following a heuristic or expert-based approach, integrated using GIS technology. This approach led to the identification of five instability factors. These factors were analyzed for the construction of thematic maps. Hence, each factor was evaluated by assigning appropriate expert-based ranks and weights and combined in a geomorphology-based matrix, that defines four landslide hazard classes (low, moderate, high, and very high). Moreover, the morphometric analysis allowed us to recognize basins prone to debris flows, which, in relevant literature, are those that show a Melton ratio of >0.6 and a watershed length of <2.7 km. Finally, all the collected data were mapped through a cartographic and weighted overlay process in order to realize a new zonation of landslide hazard for the study area, which can be used in civil protection warning systems for the occurrence of landslides in mountainous forested environments.

In this research, we present a new approach to define the distribution of block volumes during rockfall simulations. Unmanned aerial vehicles (UAVs) are utilized to generate high-accuracy 3D models of the inaccessible SW flank of the Mount Rava (Italy), to provide improved definition of data gathered from conventional geomechanical surveys and to also denote important changes in the fracture intensity. These changes are likely related to the variation of the bedding thickness and to the presence of fracture corridors in fault damage zones in some areas of the slope. The dataset obtained integrating UAV and conventional surveys is then utilized to create and validate two accurate 3D discrete fracture network models, representative of high and low fracture intensity areas, respectively. From these, the ranges of block volumes characterizing the in situ rock mass are extracted, providing important input for rockfall simulations. Initially, rockfall simulations were performed assuming a uniform block volume variation for each release cell. However, subsequent simulations used a more realistic nonuniform distribution of block volumes, based on the relative block volume frequency extracted from discrete fracture network (DFN) models. The results of the simulations were validated against recent rockfall events and show that it is possible to integrate into rockfall simulations a more realistic relative frequency distribution of block volumes using the results of DFN analyses.

The current climate change could lead to an intensification of extreme weather events, such as sudden floods and fast flowing debris flows. Accordingly, the availability of an early-warning device system, based on hydrological data and on both accurate and very fast running mathematical-numerical models, would be not only desirable, but also necessary in areas of particular hazard. To this purpose, the 2D Riemann–Godunov shallow-water approach, solved in parallel on a Graphical-Processing-Unit (GPU) (able to drastically reduce calculation time) and implemented with the RiverFlow2D code (version 2017), was selected as a possible tool to be applied within the Alpine contexts. Moreover, it was also necessary to identify a prototype of an actual rainfall monitoring network and an actual debris-flow event, beside the acquisition of an accurate numerical description of the topography. The Marderello’s basin (Alps, Turin, Italy), described by a 5 × 5 m Digital Terrain Model (DTM), equipped with five rain-gauges and one hydrometer and the muddy debris flow event that was monitored on 22 July 2016, were identified as a typical test case, well representative of mountain contexts and the phenomena under study. Several parametric analyses, also including selected infiltration modelling, were carried out in order to individuate the best numerical values fitting the measured data. Different rheological options, such as Coulomb-Turbulent-Yield and others, were tested. Moreover, some useful general suggestions, regarding the improvement of the adopted mathematical modelling, were acquired. The rapidity of the computational time due to the application of the GPU and the comparison between experimental data and numerical results, regarding both the arrival time and the height of the debris wave, clearly show that the selected approaches and methodology can be considered suitable and accurate tools to be included in an early-warning system, based at least on simple acoustic and/or light alarms that can allow rapid evacuation, for fast flowing debris flows.

Digital photogrammetry (DP) represents one of the most used survey techniques in engineering geology. The availability of new high-resolution digital cameras and photogrammetry software has led to a step-change increase in the quality of engineering and structural geological data that can be collected. In particular, the introduction of the structure from motion methodology has led to a significant increase in the routine uses of photogrammetry in geological and engineering geological practice, making this method of survey easier and more attractive. Using structure from motion methods, the creation of photogrammetric 3D models is now easier and faster, however the use of ground control points to scale/geo-reference the models are still required. This often leads to the necessity of using total stations or Global Positioning System (GPS) for the acquisition of ground control points. Although the integrated use of digital photogrammetry and total station/GPS is now common practice, it is clear that this may not always be practical or economically convenient due to the increase in cost of the survey. To address these issues, this research proposes a new method of utilizing photogrammetry for the creation of georeferenced and scaled 3D models not requiring the use of total stations and GPS. The method is based on the use of an object of known geometry located on the outcrop during the survey. Targets located on such objects are used as ground control points and their coordinates are calculated using a simple geological compass and trigonometric formula or CAD 3D software. We present three different levels of survey using (i) a calibrated digital camera, (ii) a non-calibrated digital camera and (iii) two commercial smartphones. The data obtained using the proposed approach and the three levels of survey methods have been validated against a laser scanning (LS) point cloud. Through this validation we highlight the advantages and limitations of the proposed method, suggesting potential applications in engineering geology.

We investigated the role of the morphostructural setting and seismic and meteorological factors in the development of landslides in the piedmont of the Abruzzo Apennines. In February 2017, following a heavy snow precipitation event and a moderate seismic sequence (at the end of the Central Italy 2016–2017 seismic crisis), several landslides affected the NE-Abruzzo chain and piedmont area. This work is focused on the Ponzano landslide (Civitella del Tronto, Teramo) and the Castelnuovo landslide (Campli, Teramo) in the NE Abruzzo hilly piedmont. These landslides consist of: (1) a large translational slide-complex landslide, affecting the Miocene–Pliocene sandstone clay bedrock sequence of the piedmont hilly sector; and (2) a complex (topple/fall-slide) landslide, which occurred along a high and steep scarp on conglomerate rocks pertaining to terraced alluvial fan deposits of the Pleistocene superficial deposits. Both of the landslides are typical of the Abruzzo hilly piedmont and both of them largely affected houses and villages located on top of the scarp or within the slope. The landslides were studied by means of field geological and geomorphological mapping, borehole investigations, geostructural analysis and photogeological analysis. For the Ponzano landslide, a detail pre-post-landslide air photo interpretation allowed for defining the deformation pattern occurred on the slope. For the Castelnuovo landslide, the triggering factors and the stability of the slope were evaluated with FLAC3D numerical modelling, in pre- and post-landslide conditions. Through this integrated analysis, the triggering factors, the landslide mechanism and the stability conditions of the landslides and the characterization of two main types of landslides affecting the piedmont hilly area of the Abruzzo region were investigated.

This research aims to highlight the importance of adopting a multi-disciplinary approach to understanding the factors controlling large rock avalanches using the Scanno landslide, Italy, as a case study. The study area is the Mount Genzana, Abruzzi Central Apennines, characterized by the regional Difesa-Mount Genzana-Vallone delle Masserie fault zone. The Scanno landslide is famous for its role in the formation of the Scanno Lake. The landslide is characterized by a wide exposed scar, which was interpreted in previous studies as the intersection of high-angle joints and an outcropping bedding plane on which the landslide failed sometime between the Upper Pleistocene and the Holocene. In this study, the Scanno landslide was investigated through the integration of geological, geomechanical and geomorphological surveys. Remote sensing techniques were used to enrich the conventionally gathered datasets, while Geographic Information Systems (GIS) were used to integrate, manage and investigate the data. The results of the authors investigation show that the outcropping landslide scar can be interpreted as a low-angle fault, associated with the Difesa-Mount Genzana-Vallone delle Masserie fault zone, which differs from previous investigations and interpretations of the area. The low-angle fault provides the basal failure surface of the landslide, with two systematic high-angle joint sets acting as lateral release and back scarp surfaces, respectively. In light of these new findings, pre- and post-failure models of the area have been created. The models were generated in GIS by combining LiDAR (Light Detection and Ranging) and geophysics data acquired on the landslide body and through bathymetric survey data of the Scanno Lake. Using the pre- and post-failure models it was possible to estimate the approximate volume of the landslide. Finally, back-analyses using static and dynamic limit equilibrium methods is also used to show the possible influence of medium-to-high magnitude seismic events in triggering the Scanno landslide.