Italian journal of engineering geology and environment

Numerical modelling or conventional analyses? When an integrated approach becomes fundamental in understanding slope failure mechanisms

Thu, 18 Jun 2026 00:00:00 +0000

Conventional kinematic and limit equilibrium analyses represent fundamental tools for slope stability assessment, especially under relatively simple geological and geometrical conditions. In structurally complex rock slopes, however, these approaches may be insufficient to fully describe failure kinematics, making integration with numerical modelling necessary. This study presents an integrated methodological framework combining conventional analyses and numerical modelling, applied to the Monte Conero coastal sector (Ancona, central Italy), an area characterized by a highly complex structural setting and significant exposure to rockfall and toppling hazards. Engineering geological and geomorphological surveys were combined with UAV-based photogrammetry and LiDAR to reconstruct slope geometry and discontinuity networks, providing the basis for kinematic and limit equilibrium analyses. While these methods allowed the identification of potential instability mechanisms, they were unable to fully reproduce deformation patterns observed in the field. Numerical modelling was therefore applied to simulate different geological and mechanical scenarios, enabling a more realistic representation of slope behaviour and failure mechanisms. The results highlight both the capabilities and the limitations of numerical approaches, underlining the importance of careful model calibration, validation and critical interpretation. Overall, the study demonstrates that an integrated analytical and numerical approach is essential for reliable slope stability assessment in structurally complex coastal environments and, at the same time, that geological interpretation remains the key component of any engineering geological assessment.

Prediction of rainfall-induced shallow landslides at a geographical scale using deep learning: an application to the Liguria region (NW Italy)

Thu, 18 Jun 2026 00:00:00 +0000

The present work addresses the implementation of a probabilistic framework for the spatio-temporal prediction of rainfall-induced shallow landslides at geographic scales. The methodological approach consists of two main phases. In the first phase, based on statistical analysis and machine learning, landslide occurrence is modelled as a Bernoulli experiment. Using a historical catalogue of rainfall-induced shallow landslides in Italy and a 20-year pluviometric dataset collected from the rain gauges of the national civil protection network, the probability of rainfall-induced landslide initiation is estimated at locations where rainfall data are available. In the second phase, the rainfall-based probability is spatialized and coupled with landslide susceptibility, a spatial variable that accounts for the influence of geological and geomorphological characteristics of the territory. Two techniques were used: a deterministic approach based on the Voronoi tessellation and a stochastic model implemented using the MUSE (Modeling Uncertainty as a Support for Environments) software. The coupled spatio-temporal forecasting model was tested over the entire Liguria region during a significant rainfall event that occurred in early March 2018. The outcomes showed that integrating both temporal and spatial variables is effective in forecasting rainfall-induced shallow landslides.

Quantitative shallow landslide risk assessment at regional – scale: Tuscany region (central Italy) as case study

Thu, 18 Jun 2026 00:00:00 +0000

Landslides are one of the most common geohazards globally, causing considerable losses in human life and property damage. Italy is one of the European countries most severely affected by landslides due to its geological and urban setting. Moreover, as the climate continues to change, extreme rainfall events are becoming more frequent, leading to a sharp rise in landslide occurrences, often numbering in the hundreds or even thousands during a single episode. An example of this trend is represented by the Tuscany region (central Italy), which has experienced an extreme rainfall event on 2 November 2023 that triggered severe flooding and widespread landslides, highlighting the need for an updated and comprehensive assessment of landslide risk. As a result, in this contribution, we present a quantitative landslide risk assessment for the Tuscany region, focusing on rapid shallow landslides. Risk is expressed as potential economic losses (€) to building and land use. The findings show that the highest risk values are concentrated along the Apennine chain, where geomorphologically susceptible terrains overlap with urbanized and agricultural areas. The aggregation of potential losses yields a total economic risk of approximately 1.7 billion €.

Seismically induced acceleration of deep-seated creep in the complex Monte Saresano landslide

Thu, 18 Jun 2026 00:00:00 +0000

The Monte Saresano landslide (Tavernola Bergamasca, Italy), is a large rockslide (up to 4.5 million m3) along the slope of an old quarry, with at least three reactivation stages since 1900. In February 2021, after a seismic event of ML=2.2 that occurred 2 km east of the municipality of Viadanica (BG approximately 7 km west of the landslide site, the entire monitoring network has recorded a significant acceleration of the movement with displacement rate of 6.34-11.23 mm/day compared to 0.1-0.2 mm/day before the event. This study uses a variety of approaches, through the analysis of monitoring data from a comprehensive monitoring network (active mostly since 2017), laboratory geomechanical characterization of the materials (UCS, TCS, BTS, LTS), compositional investigations (XRF, XRD, thin sections), geophysical and borehole data, has allowed the identification of 2.6 million m3 unstable mass, potentially extending to 4.45 million m3 Using these results, a 3D Finite Element Analysis (FEA) was implemented to study the slope stability. The numerical results, suggest the presence of widespread fracturing and severely weakened cataclastic levels developed from prehistorical activity. Such weakened planes have been reactivated by recent quarrying activites and the 2021 seismic event.

MERCURY: multi-platform monitoring system for railway infrastructure safety

Thu, 18 Jun 2026 00:00:00 +0000

The MERCURY project aims to develop an innovative multi- platform monitoring system designed to support the inspection and maintenance of regional railway infrastructures, with the ultimate goal of implementing a Decision Support System (DSS). This objective is achieved through a modular and scalable framework capable of integrating data from different sources. MERCURY addresses the critical need for regional railway operators to have a flexible tool that responds to the specific geological and structural vulnerabilities of the territories they traverse. Optimising maintenance procedures is essential for averting critical conditions that could compromise passenger safety, while simultaneously minimising costs related to line downtime and manual on-site inspections. This study discusses the preliminary results obtained following the in-situ installation of a sensor network (comprising flat jacks, capacitive probes, crack gauges, and strain gauges) in the Scrajo locality, situated within the municipality of Vico Equense (Naples, Italy), along the Circumvesuviana railway network. This site was selected as a strategic testbed for the MERCURY project due to its susceptibility to landslides (triggered by rockfall or topple) and rapid debris flows, as exemplified by the historical landslide event of 1966. The implemented infrastructure is designed to monitor both exogenous phenomena, such as landslides (tracked via capacitive probes and weather stations) that could impact the railway track, and endogenous factors, including structural damage to underground assets (monitored via flat jacks, strain gauges, crack meters, and velocimeters). Consequently, the system enables the comprehensive observation of both potential environmental triggers and their direct effects on railway assets.

Assessment of groundwater recharge in a Mediterranean karst system using chelsa and modis data

Thu, 18 Jun 2026 00:00:00 +0000

This study aims to quantify and map groundwater recharge in a Mediterranean karst aquifer in southern Italy over the period 2000–2018 by integrating analyses based on high-resolution climatological and remote sensing datasets. The approach uses annual precipitation (P) from the CHELSA v2.1 dataset, which provides ~1 km resolution climatological variables derived from downscaled ERA-interim reanalysis and ground observations. Actual evapotranspiration (AET) was obtained from the MODIS MOD16A3GF product (500 m resolution), based on the Penman– Monteith algorithm. GR was estimated through two methods employing groundwater recharge coefficients (GRCs). The first applied the APLIS model, a GIS-based empirical method specifically designed for karst aquifers, which determines a spatially distributed GRC as a function of five environmental variables. The second method used effective precipitation (P–AET) combined with lithology-dependent GRCs from the literature. Both recharge methods yielded slightly different GR estimates in terms of discharge rate at the basin scale, with values of 1.3 m3∙s-1 and 1.0 m3∙s-1 for the first and the second method, respectively. Locally, some spatial differences emerged due to methodological contrasts. Overall, the integrated GIS-based framework proved effective for estimating groundwater recharge in data-limited karst environments and demonstrates strong potential for application in other Mediterranean karst systems.

Thermal effects on soil water repellency: experimental evidence and relevance for post-fire slope stability

Thu, 18 Jun 2026 00:00:00 +0000

Wildfires are among the most impactful natural phenomena affecting ecosystems, with a concerning increased frequency driven by climate change and human activity. Beyond the immediate destruction of vegetation, wildfires trigger a series of cascading effects within the slopes, significantly modifying shallow processes and compromising their stability. Wildfires significantly alter the hydrological and geo-mechanical properties of soils, often increasing the susceptibility to shallow landslides and debris flows. Several authors have reported that the development of soil water repellency plays a crucial role in controlling post-fire infiltration dynamics and runoff generation. However, depending on vegetation coverage and organic matter content, soil water repellency may already characterize slopes prior to wildfires. Laboratory studies have shown that the onset of soil water repellency is strongly influenced by granulometry, organic matter content and temperature rise, whereas its breakdown occurs at higher temperatures. Yet, the direct contribution of temperature-induced changes in soil water repellency to slope failure processes remains unclear. The present study investigates how temperature influences the development and breakdown of soil water repellency, and how this property influences soil infiltration capacity. Controlled thermal treatments were conducted on soil samples in laboratory, coupled with the assessment of the hydrophobic behaviour through Water Drop Penetration Time (WDPT) tests and the evaluation of the hydraulic conductivity with a permeameter after heating. Results reveal a temperature dependent response only in samples containing organic matter. Differences in thermal conductivity among the tested materials produced heterogeneous responses to heating, suggesting a non-uniform alteration even after prolonged exposure to elevated temperatures. These findings indicate that temperature exerts a complex control on soil wettability and, consequently, on post-fire infiltration behaviour.

Assessment of slope processes in a deep-seated rockslide-earthslide by integrated investigation and monitoring: Brugneto case study (Northern Apennines, Italy)

Thu, 18 Jun 2026 00:00:00 +0000

This study defines the reference geological model of the Brugneto deep-seated landslide (Northern Apennines, Piacenza province, Italy). An integrated mapping and monitoring approach reconstructs its internal structure and kinematics and defines its controlling factors for hazard assessment purposes. The landslide affects an area of approximately 1.18 km2 and develops mainly within the Monte Caio Flysch, in a structurally complex dip- slope setting. Specifically, the study integrates UAV-LiDAR derived DTM analysis, electrical resistivity tomography, boreholes logging, inclinometers, continuous GNSS monitoring, and multi-temporal InSAR analyses (RAINS and MT-SBAS) based on Sentinel-1 data. This multi-source approach allowed the identification of three main landslide sub-units, characterized by different materials, movement mechanisms, and displacement rates. Results show a kinematic transition from rotational rock sliding in the upper sector to translational earth sliding in the lower sector. Sliding surfaces reach depths of 70 m. GNSS data reveal increasing displacement rates toward the lower landslide sector and a clear relationship between acceleration phases and prolonged rainfall periods. InSAR data are consistent with ground-based measurements but tend to underestimate velocities in the most active areas. The resulting landslide map and cross sections represent the reference geological model for this complex landslide while the adopted study approach can be replicated in similar geological settings.

Satelite tecniques for natural hazard in the internal area of Basilicata Region southern Italy – the case history of Stigliano town

Antonio Fiorentino, Lorenzo Di Taranto, Angelo Doglioni, Vincenzo Simeone — Thu, 18 Jun 2026 00:00:00 +0000

The inner areas of the Basilicata Region are particularly exposed to hydrogeological instability phenomena due to the intrinsic dynamics that led to the genesis of these territories. Satellite observation systems and remote sensing applications make it possible to objectively assess ongoing processes, also with the aim of supporting appropriate decision-making for land and environmental protection. The research activity focused on a case study of a town in Basilicata: Stigliano, in the province of Matera, which can be considered a pilot site. In particular, the study aimed to analyze slow-moving ground deformations, which are not always immediately detectable but may represent precursory signs of more rapid and paroxysmal events, as occurred between January and February 2014 on the southern outskirts of the settlement. The gravitational deformation phenomena affecting the town of Stigliano (MT) are partly known, but they have never been adequately investigated, mainly because they involve slow deformations whose monitoring was partly problematic before the development of techniques based on interferometric data. The study was carried out using interferometric datasets available through the EGMS portal (https://egms.land.copernicus.eu). The work conducted so far has made it possible to identify and quantify the significant deformations affecting the north-eastern sector of the town, characterized by continuously evolving dynamics. The analysis of satellite data shows, for area a), a trend with a settlement rate of about 4 mm/year, and a westward displacement of about 2.4 mm/year. In fact, the entire sector is characterized by comparable movements, showing a settlement of about 3–3.5 mm/year and a displacement towards the north-east. These movements are consistent with the mechanics of lateral spreading phenomena.

Data-driven modeling of soil water content using different rainfall predictors

Thu, 18 Jun 2026 00:00:00 +0000

Soil moisture is a crucial component of hydrological and geotechnical processes, especially for shallow slope failures. When adopting a physically-based modeling approachfor the prediction of hydrological variables, it can however be challenging to gather the necessary data and findwhat parameters to use on a large scale. The goal of this study is therefore to adopt a data-riven approach to predict the amount of water in the soil using only rainfall based predictors. The study used a Random Forest algorithm that was trained using only cumulative rainfall indices and time markers. The analysis was performed independently for the two distinct soil management practices (Control and Rolling) at depths of 10, 50, and 90cm. A randomized validation test was done and the results show that the prediction of water content has very high internal consistency (R2 > 0.98). However, the predictions for the year 2024, which had not been used for the trainingof the model, showed clear physical limits.The reason of this poor perfomance is related to meterological conditions on January-April 2024 period, which differed from the ones present in training time series. Consequently, the results highlight the importance of reconstructing data-driven models with a training time- series long enough to consider all the possible meterological conditions. Nevertheless, the results show that the model can find important near-saturation conditions with a small margin of error.This means that this Random Forest model can be reliable in predicting conditions that could lead to shallow landslide triggering, even while neglecting air temperature data.

2D shallow water modeling for MAR implementation: surface–groundwater interaction in Val di Cornia (Tuscany)

Federica Giaccio, Francesco Maria De Filippi, Giuseppe Sappa, Giovanni Cannata — Thu, 18 Jun 2026 00:00:00 +0000

Surface water and groundwater interactions play a crucial role in water resource management, particularly in overexploited alluvial systems, as in Val di Cornia (Tuscany, Italy). The study area, within the system formed by the lower course of the Cornia River and the alluvial plain aquifer, has hosted a Managed Aquifer Recharge (MAR) scheme with a monitoring network that has enabled continuous acquisition of different parameters for surface water and groundwater.To further investigate river-aquifer transfer mechanisms, two transects were identified as potential candidates for instrumentation, including some of the existing monitoring piezometers. The analysis of the data thus acquired could, in theory, allow observation of how the aquifer response varies with distance from the river. To isolate the river input, periods of MAR inactivity were identified, and the most significant flood events were analyzed using river stage time series registered from two upstream and downstream stations of the Regional Hydrological Service. This study provides a knowledge base for the development of conceptual and numerical models of river-aquifer interactions, with practical implications for integrated water resource management.

Enhanced mapping and modeling of multiple debris flow by lidar-based fixed wing UAV surveying

Thu, 18 Jun 2026 00:00:00 +0000

Debris flows are a major geo-hydrological hazard in areas with steep slopes and unconsolidated deposits. Accurate characterization of source areas and flow paths is essential for hazard assessment and for planning mitigation measures. In contexts where initiation zones are distributed across multiple slopes or small catchments, traditional terrestrial surveys or multirotor UAV techniques are limited in spatial coverage and continuity. To overcome these limitations, this study proposes a methodological approach based on fixed-wing UAVs equipped with LiDAR and high-resolution cameras, aimed at the synoptic mapping of multiple debris flow channels and the quantitative assessment of morphological changes. Survey campaigns enabled the generation of high-resolution Digital Terrain Models (DTMs) and the derivation of elevation difference models using GIS-based techniques, allowing the estimation of eroded and deposited volumes, the delineation of source areas, and the identification of main flow paths through flow accumulation and watershed analysis algorithms. Analysis of multitemporal surveys, conducted a few months apart, revealed that the most significant erosional processes are concentrated in the upper portions of slopes, with average erosion depths of several tens of centimeters and localized incisions exceeding 5–10 meters. Delineating of flow lines and drainage basins also allowed mobilized volumes to be correlated with specific channels, identifying basins with the highest reactivation potential. The use of fixed-wing UAVs proved particularly effective for covering large areas within short operational times, ensuring centimeter-scale spatial resolution even at poorly accessible sites. Integration with LiDAR technology allowed for the accurate reconstruction of ground morphology in densely vegetated areas, providing a solid basis for subsequent numerical simulations of debris flow propagation. These simulations enabled the estimation of potential inundation scenarios and supported the design of structural mitigation measures. The results show that the integrated UAV–LiDAR and numerical modeling approach constitutes an effective tool for the geomorphological characterization of multiple basins affected by debris flows, providing quantitat.

Underground cavities and their aggravation effects on the local seismic response: a parametric analysis

Thu, 18 Jun 2026 00:00:00 +0000

Underground cavities are widely distributed in urban areas and pose a significant risk to buildings and infrastructures. Beyond structural instability issues, cavities can significantly affect seismic wave propagation, modifying the amplitude, frequency content, and duration of ground motion. This study presents an integrated approach to investigate the dynamic response of underground cavities, combining two-dimensional numerical modelling of seismic wave propagation and in situ ambient vibration measurements. The numerical analyses, performed under linear-elastic conditions, aim to explore the interaction between seismic input and underground cavities. In a similar way, ambient vibration measurements carried out at the Ghar il-Latnija cave (Malta) were analysed using Operational and Numerical Modal Analysis techniques. The results highlight local amplification effects and marked spatial variability in the dynamic response, providing a preliminary framework for assessing the seismic response of underground cavities.

Geothermal plants and critical minerals distribution: a preliminary spatial dataset for co-production screening

Fatemeh Hosseinpour, Glenda Taddia, Stefano Lo Russo, Martina Gizzi — Thu, 18 Jun 2026 00:00:00 +0000

Geothermal systems have the potential to co-produce renewable energy and critical raw materials (CRMs) from mineral-rich brines; however, existing information about their potential is scattered across uncoordinated datasets. This work develops a QGIS-based global database to support the assessment of CRM co-production from geothermal systems. Five open- access datasets were analyzed within a spatial framework: the Joint Research Centre (JRC) Geothermal Power Plant dataset, the Global Geothermal Power Tracker (GGPT), the U.S. Geological Survey (USGS) global distribution of critical minerals, the European Geological Data Infrastructure (EGDI) CRMs’ occurrences, and REFLECT European Geothermal Fluid Atlas. JRC and GGPT together provide complementary information on geothermal power plants worldwide, while USGS-CRM and EGDI-CRM supply data on hard-rock mineralization settings for key critical raw materials. Moreover, the REFLECT database adds the fluid dimension by providing well-level data on fluid properties for selected European geothermal systems, allowing plant and mineralization information to be complemented with geothermal brine properties. Rather than presenting a single, fully developed case study, the paper outlines how the integrated database can be used in future analyses, including tracking temporal changes in geothermal deployment and critical mineral reports; integrating REFLECT-compatible fluid chemistry for selected fields; and assessing plant and critical mineral proximity for scaling-related problems.

Monitoring of large landslides using the automated inclinometer system (AIS)

Massimo Mangifesta, Paolo Allasia, Danilo Godone, Nicola Sciarra — Thu, 18 Jun 2026 00:00:00 +0000

The inclinometer monitoring is a standard method of identifying sliding surfaces on landslide slopes. However traditional manual techniques are subject to systematic errors relating to operator and probe repositioning and only provide periodic data. To overcome these limitations and gain a better understanding of the complex kinematics of landslide movements, the Automated Inclinometer System (IRPI-CNR) was developed. This robotic solution integrates a single, high- precision probe with an automatic control unit, which allows the entire vertical surface to be sampled at a high temporal frequency. In high-risk systems, eliminating human error and ensuring data continuity can activate real-time early warning systems. The system’s performance was demonstrated in various case studies, ranging from the analysis of deep lateral spreading in fractured sandstones in Borrello, Italy, to the study of roto-translational landslides in clayey-sandy soils in Chieti, Italy. In both cases, automation has proved essential for accurately reconstructing the deep deformation profile and providing an important tool for assessing instability and managing hydrogeological risk.

A near real-time forecasting system for shallow landslides at regional scale based on distributed modelling and weather predictions

Elena Benedetta Masi, Guglielmo Rossi, Nicolò Brilli, Veronica Tofani — Thu, 18 Jun 2026 00:00:00 +0000

This work presents the development of a forecasting system for shallow rainfall-induced landslides, designed to provide daily near–real-time outputs at a regional scale. The system integrates hydrological and slope stability distributed modelling with daily rainfall forecasts from a weather prediction model to generate daily shallow landslide initiation forecasts for an area of hundreds of square kilometers. Research activities focused on: i) the optimization of the HIRESSS model to enhance computational efficiency and physical consistency for real-time forecasting; (ii) the calibration of the system based on the hydrological, geotechnical, morphological and climatic characteristics of the study area and (iii) developing algorithms enabling the continuous use of meteorological forecasts and the production of both distributed (grid-based) and aggregated (sub-basin) outputs. The operational system based on the HIRESSS model has been active since June 2024 for the Alert Zone B of the Aosta Valley Region. It uses precipitation forecasts from the ICON-CH1 weather prediction model as dynamic input. The system generates landslide initiation susceptibility maps in terms of failure probability, with a 10 m spatial and 3-hour temporal resolution, producing forecastsfor the current and following day. Additionally, it provides aggregated probabilities at sub-basin level through a calibrated threshold system, supporting early warning activities. Recent developments have focused on optimizing the real-time dissemination of model outputs through an open-data platform ensuring transparency, accessibility, and operational usability for regional authorities and decision-makers. The developed system represents a significant step toward a fully operational landslide early warning system at the regional scale based on physically based distributed modelling and meteorological forecasting.

Advanced numerical modelling of earthflow dynamics: application of the material point method (MPM) to the montaguto case study

Dario Milella, Piernicola Lollino — Thu, 18 Jun 2026 00:00:00 +0000

This study addresses the modelling of Apennine earthflows, which threaten infrastructures due to their complex kinematics characterized by alternating rapid and slow phases. Since traditional numerical methods (e.g. FEM) are not suitable to simulate the landslide behavior at large strains, this research applies the Material Point Method (MPM) to the Montaguto earthflow in Southern Italy. Focusing on the 2006-2010 reactivation, a 2D MPM model successfully simulated the two- phase soil behavior and the crucial role of excess pore pressures. The numerical results are consistent with the displacement and pore pressure trends recorded by the monitoring system installed in the landslide area. The findings demonstrate that MPM is a robust tool, superior to classical numerical methods for simulating the full life cycle of earthflows, thereby significantly enhancing the assessment of large mobility landslide hazard and the design of mitigation strategies.

Digital twin based framework for rockfall hazard assessment: remote analysis of an urban cliff in Palermo (Italy)

Thu, 18 Jun 2026 00:00:00 +0000

Rockfall phenomena influence human activities in areas where anthropic expansion reaches the slopes of the reliefs. The rockfall hazard assessment is particularly required when exposed elements exist in the area, causing the conditions for a risk scenario. Since direct data acquisition (i.e., in contact with the rock face) for rockfall hazard characterization is not always feasible due to logistical constraints and exposure to the factors generating the hazard, indirect (i.e., remote) approaches have emerged over the past decades as a reliable solution. The main goal of these approaches is to generate a three-dimensional model of the analyzed rock mass, making it possible to extract parameters for the characterization of discontinuity systems and to perform stability analyses remotely. The proposed case study focuses on a portion of the eastern sector of Mount Pellegrino (Sicily), overlooking an urban area of Palermo that includes, among other elements, the monumental cemetery of Santa Maria dei Rotoli. The mount, a carbonate massif that rises 606 a.s.l. within the city of Palermo, has historically been affected by rockfall phenomena. The cemetery represents a vulnerable element to be preserved, both as an artistic and historical heritage site and as a place where human lives are exposed due to tourism and religious activities. In this context, a Terrestrial Laser Scanning (TLS) survey was conducted, allowing the acquisition of a high-resolution 3D point cloud model of the rock face. Once processed and filtered, the point cloud can be considered the geometric basis of a digital twin of the investigated rock front, serving as the raw dataset from which to extract useful information for the geomechanical characterization. Whitin this context, the application of rock mass classification systems can be considered a first digital twin–enabled step, allowing the identification of more critical sectors where specific analyses were subsequently performed to determine quantitative parameters for hazard analysis.

Urban sinkholes and implications in coastal cliff retreat

Alfredo Motta, Agnese Messina, Simone Mineo, Giovanna Pappalardo — Thu, 18 Jun 2026 00:00:00 +0000

The development of collapse sinkholes in urbanized coastal areas represents a serious threat to the safety of infrastructures and human settlements. Although this phenomenon is linked to natural coastal evolution processes, it poses a significant risk in densely urbanized settings. This study investigates two sinkholes that developed along the eastern coast of Sicily (Italy), in different geological settings. One occurs within a carbonate rock mass affected by karst processes and tectonics, whereas the other formed in a volcanic environment prone to intense fracturing and marked heterogeneity of the lava rocks. Aerial photogrammetric surveys were conducted to perform a digital rock mass analysis aimed at identifying the main discontinuities controlling the formation of these structures. The results highlight how lithological and structural differences govern sinkhole development, providing valuable insights for risk assessment and management of critical coastal areas.

Groundwater flow and microbial contaminant dynamics in low-permeability heterogeneous aquifers: a multidisciplinary study from the Northern Apennines, Italy

Thu, 18 Jun 2026 00:00:00 +0000

Low-permeability aquifers hosted in marls, sandstones, and pelites represent strategic but often complex water storage bodies in regions where extensive and highly productive groundwater reservoirs are absent. Understanding the hydrogeological functioning of these systems and their vulnerability to microbial contamination is a key scientific challenge, relevant to many areas worldwide where similar lithological and structural settings occur. In this framework, the area of Varano de’ Melegari (Northern Apennines, Italy) was selected as a representative test site to investigate groundwater flow and fecal contamination dynamics within low-permeability aquifers. The study area, covering approximately 15 km2, includes two formations of the sedimentary Epiligure Succession, the Monte Piano and Ranzano Formations, and hosts numerous wells and springs used for irrigation, domestic supply, and livestock farming. The main objective of this preliminary work was toidentify the processes governing the occurrence and spatial distribution of fecal indicators in such aquifer systems, and to develop a conceptual framework applicable to comparable hydrogeological contexts. A multidisciplinary approach was employed, combining (i) detailed geological surveys, (ii) long-term monitoring of discharge, hydraulic head, and (iii) sampling for bacteriological (fecal indicators), and isotopic (Tritium) analyses. The integrated results provided a preliminary interpretation of the hydraulic behavior of this heterogeneous system. Despite the low permeability of the aquifer, both piezometric levels and spring discharge responded rapidly to rainfall events, with discharge ranging from 0,0 to 0,3 L/s. The hydraulic gradient was consistently high and locally reached values of approximately 50% (i ≈ 0,5), in agreement with the topographic gradient, as expected for low-permeability media. In addition, the low tritium content (0,46–4,51 TU) suggests the coexistence of both faster and slower flow components, as well as mixing between waters associated with groundwater flow paths of different lengths and/or depths within the aquifer. From a microbiological perspective, the rapid response of the aquifer to effective infiltration was further confirmed. However, the spatial and temporal distribution of fecal indicators (Fecal Enterococci) was found to be primarily controlled by local meteorological and microclimatic conditions, particularly by the influence of temperature on bacterial colony growth in the surrounding soils. The results also provide new insights for further investigation in both qualitative and quantitative fields for these kinds of aquifers.

Visibility of sinkhole and subsidence processes in the Lazio Region through combined spatiotemporal PS interferometric analysis and ancillary data integration

Thu, 18 Jun 2026 00:00:00 +0000

The availability of periodic scans of the entire Lazio region through the European Ground Motion Service, EGMS release enables administrations to monitor vast areas, characterize ground deformation processes, classify Active Deformation Areas and prioritize Areas of Interest (AOIs). Within the framework of the agreement between the Lazio region and CERI–Sapienza, the analysis was extended to slow subsidence processes and potential sinkholes, integrating Sentinel-1 interferometric data provided by the European Ground Motion Service (EGMS, Copernicus) with geological and hydrogeological information. The 2019–2023 EGMS releases allowed the identification of 1,804 AOIs exhibiting coherent lowering along the Line of Sight, located mainly in alluvial and intermontane plains, associated in several sites with the presence of subsurface compressible deposits or hydrogeological discharge sectors, with approximately 5% situated within 500 m of known sinkholes. A subset of 1,369 AOIs is considered newly formed compared to the 2015–2021 interval: of these, 78 show velocities >6 mm/year and an area < 5 km2, with one-third situated in zones with high sinkhole susceptibility. The analysis of deformation time series allowed for the identification of Turning Points and Jumps, effective indicators of subsidence anomalies, signatures of impulsive ground deformation processes, and potential precursor signals of instability. Ongoing activities include data integration with geophysical surveys and remote sensing surveys, as well as the analysis of dual-geometry COSMO-SkyMed datasets over wider-timescales. The objective is to consolidate an integrated system capable of monitoring both slow deformations and precursors of sinkhole occurrence.

Systematic application of photomonitoring for landslide surveillance in Italy: first results from the geosciences IR project

Thu, 18 Jun 2026 00:00:00 +0000

This study presents results from the first systematic evaluation of Photomonitoring techniques for landslide surveillance at national scale, conducted within the PNRR “Geosciences IR” project. Between January 2024 and June 2025, thirteen landslide sites across Italy were monitored using 15 cameras, including a UAV system. Change detection analysis identified 1235 gravitational events spanning five orders of magnitude (0.007–2080 m2). Quantitative validation at Baldiola earthflow against robotic total station measurements yielded correlation coefficients of r = 0.831–0.999 (mean 0.966), demonstrating accuracy comparable to conventional geodetic techniques. Meteorological correlation analysis at Baldiola confirmed rainfall-triggered mechanisms (r > 0.973) consistent with previous studies, while seasonal acceleration patterns at La Saxe aligned with documented snowmelt-driven processes. Fixed camera installations demonstrated superiority over periodic monitoring approaches that suffer of changes in lighting conditions and large variations in the scene (e.g. snow or vegetation coverages). This study establishes Photomonitoring as a cost-effective technique for operational landslide surveillance.

Foreword

Simone Mineo, Giovanna Pappalardo, Monica Papini, Gabriele Scarascia Mugnozza — Thu, 18 Jun 2026 00:00:00 +0000