Landslide deformations involve approximately all geological materials (natural rocks, soil, artificial fill, or combinations of these materials) and can occur and develop in a large variety of ...volumes and shapes. The characterization of the material inhomogeneities and their properties, the study of the deformation processes, and the delimitation of boundaries and potential slip surfaces are not simple goals. Since the ‘70s, the international community (mainly geophysicists and lower geologists and geological engineers) has begun to employ, together with other techniques, geophysical methods to characterize and monitor landslides. Both the associated advantages and limitations have been highlighted over the years, and some drawbacks are still open. This review is focused on works of the last twelve years (2007-2018), and the main goal is to analyse the geophysical community efforts toward overcoming the geophysical technique limitations highlighted in the 2007 geophysics and landslide review. To achieve this aim, contrary to previous reviews that analysed the advantages and limitations of each technique using a “technique approach,” the analysis was carried out using a “material landslide approach” on the basis of the more recent landslides classification.
Natural gas is an indispensable resource not evenly distributed in the world. The gas supply chain is characterized by large imbalances between supply and demand, where the underground gas storage ...(UGS) application plays a key role for creating strategic reserves, taking advantage of geological structures. On the contrary, human activities will require clean energy with near-zero greenhouse gas emissions to be environmentally viable. A key element of this strategy is the carbon capture and storage (CCS) application useful for confining CO2 into the geosphere to reduce anthropogenic emissions. The development of appropriate injection methods and long-term monitoring systems for leak detection of the underground storage of natural gas and CO2 is important to prevent negative effects, such as ground deformations and micro seismic events. In this work, a variety of monitoring applications were gathered and critically analyzed for a total of 60 scientific contributions spanning the world. This bibliographic work shows an analytical and statistical overview of the most common use of UGS and CCS, representing the different goals of these two applications and analyzing the main monitoring techniques used in the gathered contributions. Currently, UGS monitoring requires further development, especially through multidisciplinary approaches useful for identifying possible effects on the surface and gas leaks at depth; meanwhile, CCS solutions are still at the experimental stage, also because of the high costs for large-scale applications that still need specific research. The state of the art of these two very different practices can improve the further development of new monitoring approaches or additional methods.
Regional-scale forecasting of landslides is not a straightforward task. In this work, the spatiotemporal forecasting capability of a regional-scale landslide warning system was enhanced by ...integrating two different approaches. The temporal forecasting (i.e. when a landslide will occur) was accomplished by means of a system of statistical rainfall thresholds, while the spatial forecasting (i.e. where a landslide should be expected) was assessed using a susceptibility map. The test site was the Emilia Romagna region (Italy): the rainfall thresholds used were based on the rainfall amount accumulated over variable time windows, while the methodology used for the susceptibility mapping was the Bayesian tree random forest in the tree-bagger implementation. The coupling of these two methodologies allowed setting up a procedure that can assist the civil protection agencies during the alert phases to better define the areas that could be affected by landslides. A similar approach could be easily adjusted to other cases of study. A validation test was performed through a back analysis of the 2004–2010 records: the proposed approach would have led to define a more accurate location for 83 % of the landslides correctly forecasted by the regional warning system based on rainfall thresholds. This outcome provides a contribution to overcome the largely known drawback of regional warning systems based on rainfall thresholds, which presently can be used only to raise generic warnings relative to the whole area of application.
Landslide susceptibility assessment using machine learning models is a popular and consolidated approach worldwide. The main constraint of susceptibility maps is that they are not adequate for ...temporal assessments: they are generated from static predisposing factors, allowing only a spatial prediction of landslides. Recently, some methodologies have been proposed to provide spatiotemporal landslides prediction starting from machine learning algorithms (e.g., combining susceptibility maps with rainfall thresholds), but the attempt to obtain a dynamic landslide probability map directly by applying machine learning models is still in the preliminary phase. This work provides a contribution to fix this gap, combining in a Random Forest (RF) algorithm a static indicator of the spatial probability of landslide occurrence (i.e., a classical susceptibility index) and a number of dynamic variables (i.e., seasonality and the rainfall amount cumulated over different reference periods). The RF implementation used in this work allows the calculation of the Out-of-Bag Error and depicts Partial Dependence Plots, two indices that were used to quantify the variables’ importance and to comprehend if the model outcomes are consistent with the triggering mechanism observed in the case of study (Metropolitan City of Florence, Italy). The goal of this research is not to set up a landslide probability map, but to 1) understand how to populate training and test datasets with observations sampled over space and time, 2) assess which rainfall variables are statistically more relevant for the identification of the time and location of landslides, and 3) test the dynamic application of RF in a forecasting model for the spatiotemporal prediction of landslides. The proposed dynamic methodology shows encouraging results, consistent with the actual knowledge of the physical mechanism of the triggering of shallow landslides (mainly influenced by short and intense rainfalls) and identifies some benchmark configurations that represents a promising starting point for future regional-scale applications of machine learning models to dynamic landslide probability assessment and early warning.
Gas consumption is subject to large seasonal fluctuations between the summer season (period with lower request) and the winter season (time with increased consumer demand). Underground gas storage ...applications (UGS) help to ensure a steady and reliable supply of natural gas, even during periods of peak demand, smoothing price fluctuations and providing a means of balancing the supply and demand of natural gas on a daily, weekly, or seasonal basis. However, UGS activities can induce vertical ground displacement, which is usually strictly associated with the injection and withdrawal of gas into/from the reservoir. It is necessary to carefully monitor and manage the potential impact of UGS activities on the subsurface and surface to ensure the stability and safety of the local environment. The Interferometric Synthetic Aperture Radar (InSAR) technique can provide a wide range of high-precision information on seasonal surface deformation associated with UGS activities useful for increasing the amount of information on ground deformation monitoring. This study introduces a unique and replicable approach to investigating freely available ground movement data for a fractured aquifer reservoir located in the Madrid Basin (Guadalajara, Spain), which is currently employed for seasonal underground gas storage applications. Notably, this study gives a comprehensive comparison of InSAR results of UGS activity in a deep aquifer, leveraging data that are entirely open-source and easily accessible. The Yela UGS project exploits a carbonate reservoir (dolomite) managed, since 2012, by Enagás, the Spanish main Transmission System Operator (TSO). InSAR data from 2015 to 2021 provided a full and coherent ground deformation pattern of the area. Based on this data, a fully integrated volumetric variation model was developed, elucidating the effects of gas storage activity. A significant correlation between the periodic injection/withdrawal rates of natural gas and InSAR ground deformation over time was identified.
The potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for ...mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty–clayey sedimentary cover.
In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques.
PS-InSAR™ (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to be very effective in landslide mapping in the San Fratello test site, representing a valid scientific support for local authorities and decision makers during the post-emergency management.
•We analyze slope instability phenomena in San Fratello (Sicily, Italy).•We analyze PSI data using different sensors, acquired from 1992 to 2012.•GB-SAR data were used to monitor the landslide occurred in the 2010.•Satellite and GB data were integrated to update the 2010 landslide boundary.
SIGMA is a regional landslide warning system based on statistical rainfall thresholds that operates in Emilia Romagna (Italy). In this work, we depict its birth and the continuous development ...process, still ongoing, after two decades of operational employ. Indeed, a constant work was carried out to gather and incorporate in the modeling new data (extended rainfall recordings, updated landslides inventories, temperature and soil moisture data). The use of these data allowed for regular updates of the model and some conceptual improvements, which consistently increased the forecasting effectiveness of the warning system through time. Landslide forecasting at regional scale is a very complex task, but this paper shows that, as time passes by, the systematic gathering and analysis of new data and the continuous progresses of research activity, uncertainties can be progressively reduced. Thus, by the setting up of forward-looking research programs, the performances and the reliability of regional scale warning systems can be increased with time.
The Tuscany region of Italy is widely affected by subsidence, landslides and floods, which severely impact buildings and infrastructure. In particular, Firenze-Prato-Pistoia basin has a long ...experience of ground deformation related to groundwater withdrawal. European remote-sensing satellite (ERS) data collected since 1992 have revealed the presence of several subsiding areas in the basin such as the south-eastern portion of the city of Pistoia. Sentinel-1 persistent scatterer interferometry (PSI) measurements for 2015–2018 confirmed the long-term subsidence of this area, associated with intense horticulture (plant nurseries). At the same time, Sentinel-1 data revealed the unexpected movement of Pistoia historic center, which has always been considered stable in the past. To identify the complex relationship between aquifer conditions and ground displacement, a hydrogeologic model of the Pistoia aquifers was developed, applying an integrated modelling procedure. Hydrodynamic-parameter distributions, calibrated and validated by means of Sentinel-1 PSI measurements, suggest that subsidence in Pistoia area is probably related with the combined impacts of groundwater extraction and highly compressible aquitards. To evaluate the potential evolution of ground displacement, numerical simulations were extended until 2050, using regional and global climate model data, analyzing three different pumping-rate scenarios. This led to the development of several subsidence hazard maps of the city of Pistoia that display the influence of groundwater extraction in controlling land subsidence in the area. This study emphasizes the importance of developing proper groundwater management policies, especially in alluvial aquifers made of fine compressible sediments, in order to sustainably utilize underground freshwater resources and to avoid related side effects.
This study focuses on the July-August 2019 eruption-induced wildfires at the Stromboli island (Italy). The analysis of land cover (LC) and land use (LU) changes has been crucial to describe the ...environmental impacts concerning endemic vegetation loss, damages to agricultural heritage, and transformations to landscape patterns. Moreover, a survey was useful to collect eyewitness accounts aimed to define the LU and to obtain detailed information about eruption-induced damages. Detection of burnt areas was based on PLÉIADES-1 and Sentinel-2 satellite imagery, and field surveys. Normalized Burn Ratio (NBR) and Relativized Burn Ratio (RBR) allowed mapping areas impacted by fires. LC and LU classification involved the detection of new classes, following the environmental units of landscape, being the result of the intersection between CORINE Land Cover project (CLC) and local landscape patterns. The results of multi-temporal comparison show that fire-damaged areas amount to 39% of the total area of the island, mainly affecting agricultural and semi-natural vegetated areas, being composed by endemic Aeolian species and abandoned olive trees that were cultivated by exploiting terraces up to high altitudes. LC and LU analysis has shown the strong correlation between land use management, wildfire severity, and eruption-induced damages on the island.
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