The Rock Mass Quality Index (RQI): a quantitative tool for the quality evaluation of near-surface rock masses

The knowledge of rock masses behaviour is an important information in various fields such as civil engineering, land use planning and hazard/risk zoning. Different rock mass classification methods, initially aimed at assisting underground excavations (Hoek, 2007), are widely used nowadays for preliminary design procedures (Bieniawski, 1989; Hoek, 2007), like the RMR (Bieniawski, 1976) and the Q (Barton et al., 1974) and their modifications. These methods incorporate geological, geomechanical and geometric parameters in order to obtain a quantitative estimation of the rock mass quality, but, on the other hand, their implementation is time-consuming. Despite the dominance of these two methods, further rock mass classifications systems have been proposed in the last decades and, among these, the Geological Strength Index (GSI) classification system is currently widely used as it allows to estimate the strength of rock mass through empirical semiquantitative evaluation (Hoek, 1994; Cai et al., 2004), based on both rock mass structure and condition of the joints (Hoek et al., 1995). Estimating the GSI is straightforward and fast, but it comes at the cost of a certain degree of subjectivity. Moreover, the index does not adequately account for the lithology of the rock mass matrix. Hence, for the above reasons, these classification methods are not fully suitable to collect rock mass data over wide scale areas for engineering geological mapping. The Rock mass Quality Index (RQI, Disperati et al., 2016; Mammoliti et al., 2018) is a rock mass classification system developed for cartographic purposes and it is based on the systematic fieldwork measurement and processing of sets of the Schmidt hammer rebound values (R). Each representative rock mass outcrop is analysed by collecting ca. 20 R values at the 15-25 nodes of a regular grid conceived to investigate the typical features of the rock mass. This allows to perform statistical analyses and to calculate the RQI, a quantitative indicator of the global strength and quality of the rock mass. In the last decade, a dataset of ca 1100 outcrops sites spreading over a large area (ca. 12000 km2) were acquired in Tuscany (Italy), according to different lithology, weathering, jointing conditions. The dataset consists of both RQI measurements and GSI estimations for the main different lithological groups (flysch, limestones, marls, magmatic rocks and schists) of the Northern Apennines (Italy), as well as the laboratory determinations of the Slake Durability Index (Id2; Franklin & Chandra, 1974) obtained by testing representative outcrop rock samples. The large dataset has allowed to analyse the correlation among RQI, GSI and Id2 and to perform an in-depth critical analysis of the relationships among RQI, lithology, rock mass structure, as well as the suitability of the RQI as reference index for engineering geological mapping of near-surface rock mass quality

MINDED-FBA: An Automatic Remote Sensing Tool for the Estimation of Flooded and Burned Areas

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

Engineering geological mapping of near-surface rock mass quality of folded and thrusted arenaceous flysch units in the Northern Apennines (Italy)

The regionalized knowledge of the quality of near-surface rock masses is an important tool for land management/planning, as well as for guiding further in-depth studies aimed at landslide and earthquake risk assessment and civil engineering planning. The characterization of heterogeneous rock masses like flysch units represents a relevant challenge to engineering geologists due to the complex structure of these materials, which results from both their depositional context and tectonic history. Flysches are widespread all over the Apennines chain and their mechanical characterization is a difficult task given the occurrence of intercalation of layers with different lithology and strength. Moreover, the complexity of the thrust and fold tectonic framework makes the regional distribution of these characters difficult to predict. The aim of this work is to provide a method to map the near-surface rock masses quality for an arenaceous flysch widely cropping out in the outer Northern Apennines (Torrente Carigiola Formation, Aquitanian; Bettelli et al., 2002). This formation is mapped in both the geological map of the Regione Toscana (Italy) at the scale of 1:10,000 and the geological sheet “252 – Barberino di Mugello” (Bettelli et al., 2002) of the Italian Geological Map at the scale of 1:50,000 (CARG). It is made up by intercalated arenaceous (A) and pelitic (P) layers characterized by variable A/P ratio. The rock mass quality is evaluated by estimating, for a set of representative rock outcrops, the Rock Mass Quality Index (RQI; Disperati et al. 2016; Mammoliti et al. 2018). This index results from the analysis of both systematic Schmidt hammer rebound measurements (R) acquired at the nodes of a regular grid (ca. 20 R measurements for ca. 15-25 nodes) and the determination of the unit weight for representative outcrop rock samples. For the same outcrops, also the A/P ratio and bedding attitude are determined. The results show a positive linear correlation between RQI and the A/P ratio, confirming that the latter parameter is an important feature controlling the rock mass strength. This correlation is used to assess the distribution of both parameters within a set of geological cross sections traced normal to the regional structures trend (main thrusts and km-scale folds). Then, the structural features available from the literature geological maps allow us to extrapolate both the RQI and A/P ratio from the profiles to the map scale. Finally, a further set of the same rock outcrop data acquired after the above-described modelling procedure is used to check the accuracy of the method

Back-analysis of the Abbadia San Salvatore (Mt. Amiata, Italy) debris flow of July 27-28, 2019 using the WEEZARD system

Mountain environments are naturally exposed to debris flows, a mass movement which represents one of the major geomorphological hazard sources for urbanized alluvial fan. In the last decades, climate change has contributed to extreme precipitations increase, making debris flows both larger and more frequent than in the past. The assessment and management of the risk associated with these events, according to UE Flood Directive, is feasible and desirable by using appropriate practices and the best available technology that do not imply excessive costs. In line with the above-mentioned European Directive, we present a multidisciplinary approach for the numerical modelling of the debris flow event that occurred on July 27-28, 2019 in Abbadia San Salvatore, a village located in a catchment of the Mt. Amiata area (Southern Tuscany, Italy). Debris flow was triggered by an extreme rainfall of 110 mm/1 h causing a channelled erosive process, and the subsequent obstruction of a culvert at the entrance to the village, flooding and damaging it. Mt. Amiata is an extinct Pleistocene volcano mainly consisting of trachidacitic lavas characterized by a pervasive saprolite weathering, resulting in a large amount of residual loose debris resting on the hillslopes and along the hydrographic network. Specific geological and engineering-geological field investigations were carried out to assess the availability of debris material and its hydrological behaviour, providing more constraints for numerical modelling. The Green-Ampt model, implemented in the FLO-2D software, was used for the evaluation of discharge values in the hydrographic network. Subsequently, the debris flow modelling was conducted applying the WEEZARD system, composed of a previously developed advanced two-phase debris-flow model (TRENT2D), re-coded as a web service. The mass movement was simulated to quantify erosive and depositional processes that occurred during the event. In addition, a specific approach was implemented to model the effect of the culvert that was clogged during the event. Despite the challenging modelling aspects, the results in terms of debris volume, erosion rates, flooded area and timing of the culvert obstruction, are in agreement with observed data. The WEEZARD system has therefore proved to be an effective tool, in line with the indications of the European Directive. Moreover, the reconstruction was obtained using most of the a priori parameters setting. This shows that the used modelling approach has a good predictive capacity and can therefore be reasonably used to support further predictive hazard mapping analyses. Finally, another important element to be highlighted is that an accurate input model based on the integration of detailed geological-geomorphological investigations is necessary to obtain reliable modelling results

Back-Analysis of the Abbadia San Salvatore (Mt. Amiata, Italy) Debris Flow of 27–28 July 2019: An Integrated Multidisciplinary Approach to a Challenging Case Study

On 27–28 July 2019, in a catchment of the Mt. Amiata area (Italy), an extreme rainfall induced a debris flow, which caused a channelled 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

Multiple Gender Expressions: Identity and Representation in Digital and Physical Realm

The essay aims to explore the fluid and non-binary forms of body representation, self-image making and gender identities that are expressed through dress in digital culture.  In fact, the use of fashion products makes the cultural system explicit and socially active through the construction of universes of values and everyday practices that help define individual identity as "belonging" to a complex system of cultural micro-worlds whose variety has a systemic impact on the conception and acceptance of the infinite possibilities of gender. Digital culture poses additional layers of complexity, proposing new norms and counter-norms that act in the sphere of influence between fashion and culture, altering, expanding and influencing the way fashion can be produced, remembered, communicated and known. In this framework, it is interesting to address the case of Ambrosia (Vincenzo D'Ambrosio, born in 1993), a performer and artist of the contemporary Italian scene, linked to fashion. Ambrosia seeks to intercept the now increasingly fluid and nonbinary forms of body representation, also tracing the historical roots of the Italian queer scene

Geomatics for Integrated Coastal Zone Management: multitemporal shoreline analysis and future regional perspective for the Portuguese Central Region

Shoreline mapping and change detection are critical for Integrated Coastal Zone Management (ICZM) and all that it represents. This research utilized previous studies that combined both Remote Sensing and Geographical Information System (GIS) techniques to assess, map and forecast shoreline evolution from short-term perspectives. The study area is located in the central region of Portugal, between the counties of Ovar and Marinha Grande (circa 140 km) and the time period assessed was from 1984 to 2011. Historical data were used to calculate advance and retreat rates in order to support environmental scenarios for the Portuguese Central Region’s Coastal Management Plan. To ensure accuracy, a repeatable procedure was validated using Landsat TM and ETM+ satellite images, which were subsequently enhanced and elaborated by Remote Sensing analyses to detect and extract shorelines. They were subsequently integrated within an Esri ArcGIS software application (DSAS - Digital Shoreline Analysis System) to determine and predict rates of coastline change. Graphical DSAS plots identified coastline phases and shifts and were used to simulate the 2022 coastline scenario. These results will be integrated into the Coastal Zone Management Plan (Horizon – 2022). Importantly this methodological planning approach provides visual coastline change information for regional decision-makers and stakeholders

Mapping slope deposits depth by means of cluster analysis: a comparative assessment

In this work a comparison among slope deposits (SD) maps obtained by integrating field measurements of SD depth and cluster analysis of morphometric data has been performed. Three SD depth maps have been obtained for the same area (SA1) by using different approaches. Two maps have been achieved by implementing both the supervised and unsupervised approaches and exploiting the dataset of SD depths previously collected in a region (SA2) characterized by the same bedrock lithology, although located 35 km far from the SA1. The results have been validated against a reference map based on SD depth measurements acquired during this work within the SA1 and mapped by unsupervised clustering. The outcome of the study shows the feasibility of the methodology proposed to obtain depth maps of SD. Nevertheless the very low map accuracy suggests that relationships among main morphometric variables and slope deposits depth are not constant at regional scale, although considering areas characterized by the same bedrock lithology. Hence, maps of SD depth should be based on depth data specifically acquired within the area under study. In order to improve the exploitation of SD depth datasets outside their provenance area, further research are necessary on clustering algorithms performance as well as additional morphometric and environmental variables to be employed in spatial analysis

Land use/cover change in the Tam Giang - Cau Hai Lagoon (Central Vietnam) by means of SPOT 5, Aster and Landsat images

Abstract Number: EGG01617

Investigating the relationships among vegetation characters, saturated hydraulic conductivity and surface morphology at catchment scale by integrating new field data and morphometric analysis

Shallow landslides susceptibility assessment by physically based methods relies on the parametrization of both hydraulic and geotechnical properties of soils, which in turn depend on the conditions of root structures and vegetation cover. Vegetation roots contribute to the shear strength of soils, but their quantitative contribution is currently uncertain. Saturated hydraulic conductivity (Ks) is also relevant for slope stability as it influences infiltration rates and runoff. While the literature clearly shows the dependence of Ks on soil texture, there is a general understatement of the role of root structures on this parameter. Moreover, the distribution patterns of vegetation follow relations with surface morphologies which are not fully understood and therefore, are worthy of further investigations. For these reasons, this work focuses on the quantitative assessment of the influence of vegetation on shear strength for shallow landsliding and the investigation of the relationships between vegetation characters, saturated hydraulic conductivity and topographic parameters. Study areas affected by shallow landslides are chosen in the Garfagnana and Alpi Apuane regions (Northern Apennines, Italy), as well as in the Mt. Amiata volcano area (Southern Tuscany, Italy), where field measurements of below-ground vegetation (Root Area Ratio - RAR), above-ground vegetation (Leaf Area Index - LAI and vegetation load) and Ks are acquired inside, in the neighbour and far from shallow landslide sites. To this aim, a multitemporal landslide inventory is already available for the study area. Below-ground data are collected in trench profiles, while above-ground data are acquired by using a digital relascope as well as implementing vegetation cover photography methods. Measurements of Ks are carried out by means of both constant and falling head approaches. The morphometric analysis is performed by using some morphometric variables (eg. slope and hillslope curvatures) derived from a digital elevation model with cell size of 10 m. Morphometric clustering of these variables allows us to extract a set of land units where the distribution of vegetation characters and Ks are assessed. First results show that: a) root reinforcement to soil in terms of root-related cohesion plays a relevant role within the soil depths involved in shallow landslides; b) the weight of above-ground vegetation plays a “mild” negative role on slope stability; c) Ks is correlated with both RAR and soil depth, suggesting possible criteria for the straightforward parametrization of input parameters