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The Alpi Apuane (Italy) are located a few kilometres from the coast of the Ligurian Sea, and they are characterized by peak elevations up to two thousand meters above sea level, as well as narrow, deeply incised valleys and steep slopes. Due to these morphoclimatic conditions, heavy rains are frequent, causing floods, landslides, and debris flows, particularly within the Vezza catchment. In this work we applied two different hydrological-hydraulic models to this catchment, focusing on the catastrophic debris flow event of June 19, 1996. Firstly, recent, well-documented rainfall events were used to validate the engineering geological model of the study area, then we began to analyse the rainfall-runoff and debris flow event of 1996 in the Cardoso sub-catchment. As models, we used the FLO-2D and a novel experimental model, developed by some of the authors and based on TRENT2D, in which the dynamic of a debris flow is fully coupled with the rainfall-runoff response of a basin. Preliminary results show how the used approach allowed us to gain some insight into the hydrological behaviour and debris flows formation, erosion, transport, and deposition in the Cardoso sub-catchment.

In this work, we evaluated the influence of root structure on shallow landslide distribution. Root density measurements were acquired in the field and the corresponding root cohesion was estimated. Data were acquired from 150 hillslope deposit trenches dug in areas either devoid or affected by shallow landslides within the Garfagnana Valley (northern Tuscany, Italy). Results highlighted a correlation between the root reinforcement and the location of measurement sites. Namely, lower root density was detected within shallow landslides, with respect to neighboring areas. Root area ratio (RAR) data allowed us to estimate root cohesion by the application of the revised version of the Wu and Waldron Model. Then, we propose a new method for the assimilation of the lateral root reinforcement into the infinite slope model and the limit equilibrium approach by introducing the equivalent root cohesion parameter. The results fall within the range of root cohesion values adopted in most of the physically based shallow landslide susceptibility models known in the literature (mean values ranging between ca. 2 and 3 kPa). Moreover, the results are in line with the scientific literature that has demonstrated the link between root mechanical properties, spatial variability of root reinforcement, and shallow landslide locations. [ABSTRACT FROM AUTHOR]

Variability in lithology and weathering degree affects physical and mechanical properties of rocks. In this study, we investigated the relationships between weathering degree and engineering geological properties of trachydacitic volcanic rocks from Monte Amiata (central Italy) by coupling field and laboratory analyses. We collected in situ Schmidt hammer tests in the field. We evaluated weathering quantifying the percentage of secondary minerals through thermal analysis in the laboratory. We also determined dry density ( ρ d ), specific gravity of solids (Gs), porosity (n) and two-dimensional (2D) porosity as resulted from scanning electron microscopy investigations. The results of our study indicate a negative linear correlation between Schmidt hammer rebound values and secondary mineral percentage. This correlation provides a tool to quantitatively estimate the deterioration of rock uniaxial compressive strength (UCS) as weathering increases. Moreover, thermal analysis turned out to be a quantitative and reproducible method to evaluate weathering degree of magmatic rocks. [ABSTRACT FROM AUTHOR]

This paper presents the MINDED-FBA, a remote-sensing-based tool for the determination of both flooded and burned areas. The tool, freely distributed as a QGIS plugin, consists of an adaptation and development of the previously published Multi Index Image Differencing methods (MINDED and MINDED-BA). The MINDED-FBA allows the integration and combination of a wider diversity of satellite sensor datasets, now including the synthetic aperture radar (SAR), in addition to optical multispectral data. The performance of the tool is evaluated for six case studies located in Portugal, Australia, Pakistan, Italy, and the USA. The case studies were chosen for representing a wide range of conditions, such as type of hazardous event (i.e., flooding or fire), scale of application (i.e., local or regional), site specificities (e.g., climatic conditions, morphology), and available satellite data (optical multispectral and SAR). The results are compared in respect to reference delineation datasets (mostly from the Copernicus EMS). The application of the MINDED-FBA tool with SAR data is particularly effective to delineate flooding, while optical multispectral data resulted in the best performances for burned areas. Nonetheless, the combination of both types of remote sensing data (data fusion approach) also provides high correlations with the available reference datasets. The MINDED-FBA tool could represent a new near-real-time solution, capable of supporting emergency response measures. [ABSTRACT FROM AUTHOR]

On 27–28 July 2019, in a catchment of the Mt. Amiata area (Italy), an extreme rainfall induced a debris flow, which caused a channeled erosive process just upstream of the Abbadia San Salvatore village, the obstruction of a culvert at the entrance to the urban area, and the subsequent flooding of the village. In this paper, we present the back analysis of this event. The complexity of this case study is due to several peculiar characteristics, but above all, to the clogging of the culvert, a phenomenon difficult to simulate numerically. The methodology used for the reconstruction of the event is based on a multidisciplinary approach. A geological field investigation was carried out to characterize the catchment and assess the availability of debris. Then, a cascade of numerical models was employed to reconstruct the debris flow: the FLO-2D software was used to model the runoff along the hydrographic network while the mobile-bed debris flow TRENT2D model, available through the WEEZARD system, was used to quantify both the erosion and deposition processes that occurred during the event. To simulate the culvert clogging, a novel modelling procedure was developed and applied. Despite the challenging framework, the results, in terms of debris volume, erosion rates, deposition area, and timing of the culvert obstruction, agree reasonably well with the observed data. It is worth noticing that these results were obtained mainly using parameters set a priori, namely calibrated on a physical basis. This proves that the proposed methodology is robust and effective, with good predictive capability. Therefore, it may be considered, according to the European Union (EU) Flood Directive, an "appropriate practice and the best available technology that does not imply excessive costs" to support predictive hazard mapping of situations as the one here considered. [ABSTRACT FROM AUTHOR]

This work presents a change detection method (MINDED-BA) for determining burned extents from multispectral remote sensing imagery. It consists of a development of a previous model (MINDED), originally created to estimate flood extents, combining a multi-index image-differencing approach and the analysis of magnitudes of the image-differencing statistics. The method was implemented, using Landsat and Sentinel-2 data, to estimate yearly burn extents within a study area located in northwest central Portugal, from 2000–2019. The modelling workflow includes several innovations, such as preprocessing steps to address some of the most important sources of error mentioned in the literature, and an optimal bin number selection procedure, the latter being the basis for the threshold selection for the classification of burn-related changes. The results of the model have been compared to an official yearly-burn-extent database and allow verifying the significant improvements introduced by both the pre-processing procedures and the multi-index approach. The high overall accuracies of the model (ca. 97%) and its levels of automatization (through open-source software) indicate potential for being a reliable method for systematic unsupervised classification of burned areas. [ABSTRACT FROM AUTHOR]

Satellite remote sensing data are often used to extract water surfaces related to extreme events like floods. This study presents the Multi INDEx Differencing (MINDED) method, an innovative procedure to estimate flood extents, aiming at improving the robustness of single water-related indices and threshold-based approaches. MINDED consists of a change detection approach integrating specific sensitivities of several indices. Moreover, the method also allows to quantify the uncertainty of the Overall flood map, based on both the agreement level of the stack of classifications and the weight of every index obtained from the literature. Assuming the lack of ground truths to be the most common condition in flood mapping, MINDED also integrates a procedure to reduce the subjectivity of thresholds extraction focused on the analysis of water-related indices frequency distribution. The results of the MINDED application to a case study using Landsat images are compared with an alternative change detection method using Sentinel-1A data, and demonstrate consistency with local fluvial flood records. [ABSTRACT FROM AUTHOR]

Shallow landslide susceptibility is often assessed by means of physically-based models evaluating stability of slope deposits by the so-called infinite slope approach. In our experience, this approach has good predictive performance if the input datasets are well constrained by engineering geology field survey and laboratory data for the involved slope deposits. For these reasons we developed a procedure based on integration of bedrock geology, cluster analysis of morphometric variables and soil laboratory data which allowed us to obtain maps of depth and engineering geological properties of slope deposits for about. 200 km2 study area in the Garfagnana basin (Northern Apennines, Italy). Then, shallow landslide susceptibility was assessed by a probabilistic infinite slope model which provided AUROC values ranging from 0.75 to 0.78. Nevertheless, on-site checks highlighted that almost 70% of landslides involved both slope deposits and a weathered and fractured upper portion of the underlying bedrock. In order to investigate the engineering geology characteristics of the bedrock, we conducted a field survey aimed to classify rock masses inside, in the surroundings and far from shallow landslides. In the study area the Late Oligocene-Early Miocene arenaceous flysch of the Macigno is the most widespread formation, also showing the highest landslide density, hence we focused the survey within this formation for an area of about 100 km2. For each survey site, in order to obtain estimations of the Rock-mass Quality Index (RQI), we collected 200-400 Schmidt hammer rebound measures, bedding and joint data, samples for laboratory analyses (unit weight and slake durability test) and we also estimated degree of weathering as well as the Geological Strengh Index. The results allowed us to identify three different spatial domains discriminated by both landslide density and RQI, where we can observe that lower landslide density values are characterised by higher RQI. Moreover, low RQI values characterize those areas where high density of landslide involving bedrock occur. Comparing the susceptibility maps to shallow landslide distribution, we also observed that some landslides unexpectedly fall within very low susceptibility areas. Field observations allowed us to realize that these landslides are often characterized by thin slope deposits and involve low RQI bedrock. This suggests that better AUROC values could be obtained by implementing a multi-layer infinite slope model where also the shear strength parameters of the weathered and fractured bedrock are taken into account. [ABSTRACT FROM AUTHOR]

Hydraulic conductivity (K) is a relevant engineering geology property of slope deposits (SD)overlying the geological bedrock. This parameter is relevant at the field scale to simulateinfiltration and runoff processes, hillslope stability numerical analysis, hydrological studiesand environmental issues. Direct measurements (field and laboratory tests), as well as indirect estimations (e.g.correlations from grain size distribution, pedotransfer functions) are available in the literaturefor estimating K. Many measurements are required to obtain significant results since Kdepends on many factors such as grain size distribution, bulk density, organic matter,etc. A big set (about 750) of K field measurements in the vadose zone of SD in NorthernTuscany (Italy) has been performed by means of constant and/or falling head permeameter.For each test site (a total of 150 locations), other engineering geology properties of SD suchas depth, texture, bulk density, Atterberg limits and grain size distribution have beendetermined. In this work the local variability of K has been estimated thanks to a statistical analysis ofK for each test site. Moreover geostatistical techniques have been applied to infer the spatialcorrelation of K at the catchment scale. The results show that K varies across the SD profile and in the geographicneighborhood of the test site exhibiting high spatial variability within the study area.The new pedotransfer function, that has been developed with satisfactory results(the determination coefficient R2 = 0.84), suggests that the depth of SD and d20(is the diameter corresponding to 20% finer in the particle-size distribution) playa relevant role in the prediction of K.These parameters can be considered withprofit in spatial analysis of K for SD allowing to produce K maps in the study area. [ABSTRACT FROM AUTHOR]