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Terraced landscapes represent one of the most widespread human-induced/man-made transformations of hilly-mountainous environments. Slope terracing produces peculiar morphologies along with unusual soil textures and stratigraphic features, which in turn strongly influence slope hydrology. The investigation of the hydrological features of terraced soils is of fundamental importance for understanding the hydrological dynamics occurring in these anthropogenic landscapes, especially during rainfall events. To this purpose, the availability of extensive field monitoring data series and of information on subsoil properties and structure is essential. In this study, multi-sensor hydrological data were acquired over a period longer than 2 years in the experimental site of Monterosso al Mare, in the Cinque Terre National Park (Liguria region, Italy), one of the most famous examples of terraced landscape worldwide. Monitoring data were coupled with accurate engineering-geological investigations to achieve the hydro-mechanical characterization of backfill soils and to investigate their hydrological response at both the seasonal and the single rainstorm scale. The results indicated that the coarse-grained, and anthropically remolded texture of the soils favors the rapid infiltration of rainwater, producing sharp changes in both soil volumetric water content and pore water pressure. Furthermore, the pattern of hydrological parameters showed seasonal trends outlined by alternating phases of slow drying and fast wetting. The study outcomes provide useful insights on the short and long-term evolution of hydrological factors operating in agricultural terraces. These findings represent a useful basis for a better understanding of the time-dependent processes that guide water circulation in terraced systems, which have a key role in controlling the occurrence of erosion and landslide processes. [ABSTRACT FROM AUTHOR]

Landslides represent a severe geohazard in many countries. The availability of inventories depicting the spatial and temporal distribution of landslides is crucial for assessing landslide susceptibility and risk for territorial planning or investigating landscape evolution. Nevertheless, these inventories are usually affected by limitations due to their nonpublic availability and inhomogeneities in characterization and mapping. Such problems are fully recognizable by the analysis of the multiple landslide inventories of the Campania region, which is one of the Italian regions with the highest exposure to landslide hazard and risk. On this basis, a revised Landslide Inventory of the Campania region (LaICa), resulting from the processing of multiple existing landslide inventories, has been reconstructed. It aims to (i) provide a new geodatabase that is able to overcome issues derived from the coexistence of multiple inventories and (ii) provide a methodological paradigm able to support the reorganization of existing official inventories. The implication of LaICa, with its 83,284 records, will possibly improve the assessment of landslide susceptibility and then reassess the related risk. Measurement(s) landslide Technology Type(s) Data Set [ABSTRACT FROM AUTHOR]

This paper reports a detailed study on some relevant portions of the main façades of Caserta Royal Palace (Reggia di Caserta), one of the most important Italian monuments, comparable for its impressive architecture to the Royal Palace of Versailles in France and considered the largest royal palace in the world by volume. The research was focused on the weathering pathologies affecting the stone surfaces that, in the last decades, suffered several detachments of fragments from the coatings and from other architectural elements such as string courses, eaves, and capitals. A preliminary characterization of the materials of the façades and an evaluation of the relative weathering pathologies provided the information required for appropriate restoration and securing of these portions of the building. In particular, an innovative evaluation procedure which draws on techniques typical of the earth sciences allowed the proposal of a 'risk attitude' applied to discrete portions of the geomaterials used in the built heritage which is based on the influence of different factors leading to weakening of the stone and to the final detachment of rock fragments. Such a large and complete set of information should be carefully considered by the project planners to adopt the required steps for a suitable risk mitigation and for securing the site during restoration. [ABSTRACT FROM AUTHOR]

Different interferometric approaches have been developed over the past few decades to process SAR data and recover surface deformation, and each approach has advantages and limitations. Finding an accurate and reliable interval for preparing mean deformation rate maps (MDRMs) remains challenging. The primary purpose of this paper is to implement an application consisting of three unsupervised clustering algorithms (UCAs) for determining the best interval from SAR-derived deformation data, which can be used to interpret long-term deformation processes, such as subsidence, and identify displacement patterns. Considering Port Harcourt (in the Niger Delta) as the study area, it was essential to remove the sources of error in extracting deformation signals from SAR data, spatially ionospheric and tropospheric delays, before using UCAs to obtain its characteristics and real deformation data. Moreover, another purpose of this paper is to implement the advanced integration method (AIM) for atmospheric phase screen (APS) correction to enhance deformation signals obtained through different SAR processing approaches, including interferometric SARs (two-pass interferometry, InSAR) and multitemporal interferometry SARs (n-pass interferometry, DInSAR; permanent scatterer interferometry (PSI); and small baseline subset (SBAS)). Two methods were chosen to evaluate and find the best technique with which to create an MDRM: The first one was to compare the signals corrected by the AIM and the vertical component of the GPS station, which showed the AIM providing 58%, 42%, and 28% of the matching with GNSS station outputs for InSAR, PSI, and SBAS, respectively. Secondly, similarity measures and Davies–Bouldin index scores were implemented to find an accurate and reliable interval in which the SBAS technique with the unsupervised K-medians method has been chosen. Based on GNSS vertical deformation in a 500 m radius around the station, the SBAS K-medians technique expressed up to 5.5% better deformation patterns than the map of SAR processing techniques. [ABSTRACT FROM AUTHOR]

The assessment of timing and potential locations of rainfallinduced shallow landslides through mathematical models represents a challenge for the assessment of landslide hazard, especially in cases with limited or not available data. In fact, modeling slope hydrological response and stability requires accurate estimates of unsaturated/saturated hydraulic and geotechnical properties of materials involved in landsliding, as well as climate and topography. Such aspect is relevant for the prediction of location and timing of landslide events, which is greatly needed to reduce their catastrophic effects in terms of economic losses and casualties. To such a scope, we present the comparison of results of two physics-based models applied to the assessment of susceptibility to shallow rainfall-induced landslides in Valtellina region (northern Italy). The analyses were carried out considering effects of availability, resolution and type of data concerning spatial distribution, thickness and properties of soils coverings. For such a scope, the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) and the Climatic Rainfall Hydrogeological Modeling Experiment (CHRyME) models were considered. The study emphasizes issues in performing distributed numerical slope stability modeling depending on the availability of spatially distributed soil properties which hamper the quality of physic-based models. Further analyses aimed at the probabilistic assessment of landslide spatial distribution, related to a specific value of rainfall threshold, can be considered as potentially applicable to multi-scale landslide hazard mapping and extendable to other similar mountainous frameworks. [ABSTRACT FROM AUTHOR]

Landslides are among the most intense geological disasters worldwide. Several remote sensing techniques have been used to study these phenomena over the last few decades, including Global Navigation Satellite Systems (GNSS) and Multi-Temporal Interferometric Synthetic Aperture Radars (MT-InSAR), in particular, Small Baseline Subset (SBAS) and Permanent Scatterer Interferometry (PSI). The University of Azuay and highway infrastructure (Cuenca - Ecuador) were affected by slow-moving landslides which in urban areas had more noticeable deformation effects due to their crowns. Furthermore, evidence indicates that the landslide toe was developed in a rural area. To study landslide boundary and deformation kinematics comprehensively, we need to observe two distinct scattering surfaces using SAR imagery (high coherence areas in the urban area and low coherence areas in the rural area). We can also observe different distributions in X- and C-bands due to the rural area covered by vegetation and trees at the toe of the landslide. Two sets of radar images were analyzed and compared for monitoring the aforementioned slow-moving landslide kinematics, including Sentinel1-A (S1-A) and COSMO-SkyMed (CSK). PSI and SBAS techniques have been used to measure the rate of surface deformation and displacement time series at CSK over the period (2017-2019) and S1-A units over the period (2015-2018), respectively. Furthermore, a GNSS station in the stable area was used as a reference station to integrate the PSI and SBAS results over space. Then, an unsupervised machine learning algorithm (K-medians) was used to determine the most appropriate intervals for preparing mean deformation rate maps. Finally, a comparison was made between the outputs obtained from this study and displacement recorded at two additional GNSS stations located in the area affected by deformation. As a result, by comparing and monitoring double-band SAR satellites and different SAR image processing techniques, it became possible to analyze the whole landslide of our case study appropriately. [ABSTRACT FROM AUTHOR]

Artificial reservoirs are crucial infrastructures, since they allow for the management of the water resource they store and for their role in the hydroelectric production. Water is modulated and stored inside artificial basins built upstream of the dams for hydroelectric, industrial, drinking, irrigation, and flood mitigation purposes. However, as time passes, the deposition of solid material, transported by rivers flowing into the reservoir, reduces its storage capacity. In this work, a novel physicallybased erosion and sediment transport model developed by Politecnico di Milano (SMART-SED) is used to estimate dam filling in different Italian geological contexts. The present model differs from others in the literature since it can automatically detect drainage zones and it works at a basin scale, requiring few input parameters that can be easily downloaded from global or government databases. Moreover, it is based on robust and unconditionally stable numerical techniques, and it guarantees the mass conservation. The proposed model was applied to four watersheds, two in the Southern Alps and two in the Southern Apennines, with catchment areas ranging from 5 to 48 km². After the model calibration on the local geological context, a validation of the obtained results was accomplished considering different time intervals and the available sediment filling data. It was observed that the SMART-SED model, initially developed for the evaluation of fluvial hazard and of sediment transport in mountainous areas, was also suitable for the estimation of dam filling. Results indeed show a precise approximation of the order of magnitude of the cumulative sediment volume produced inside the catchments and transported to the water basins. In the framework of a complex problem affecting the production of "clean" energy in a changing world, SMART-SED could become a useful tool also for dam management. [ABSTRACT FROM AUTHOR]

This paper focuses on Deep-Seated Gravitational Slope Deformations (DSGSDs) identified in the Molise region (Italy), along the central-southern sector of the Apennines chain. These phenomena were detected and mapped through a combination of aerial-photo interpretation, morphological analyses, and field surveys, integrated through satellite SAR interferometry (InSAR). The obtained general map is organized in different sections: inventory map with identification of DSGSDs and main geological and orographic features, geostructural scheme, representative cross sections, list and characteristics of DSGSDs, geomorphometric maps, landslides map, and seismotectonic setting. This study allowed us to realize a complete inventory of DSGSDs in the Molise region and define the main characteristics of each phenomenon. Through this research, it was possible to establish a general correlation between the analyzed deformations and the geological and geomorphological setting of the region as well as with its geodynamic context. [ABSTRACT FROM AUTHOR]

This work presents a sinkhole susceptibility and risk assessment mapping in Guidonia-Bagni di Tivoli plain (Italy), a travertine sinkhole-prone area where sudden occurrences of sinkholes have happened in past and recent times. We collected a point-like sinkhole inventory and we considered a series of different sinkholecontrolling and precursory factors over the study area, related to its geo-litho-hydrological setting and to its terrain deformational scenario, i.e. ground motion rates derived from InSAR COSMOSkyMed imagery. A sinkhole susceptibility map was produced through a machine learning model, namely Maximum Entropy algorithm (MaxEnt). Results highlight that the most determining factors for sinkhole formation are the lithology, the travertine thickness, groundwater and the land use. The sinkhole susceptibility map was then combined with data on vulnerability and elements-at-risk economic exposure in order to provide a sinkhole risk map of the area. The outcomes show that areas at higher risk covers about 2% of the total study area and primarily relies on the zoning of the main urban fabric. In particular, it is worth to highlight that 5% of the whole road-network pavement and 27% of all the residential buildings fall into High and Very High risk classes. Overall, results of this work demonstrate capabilities of machine learning models to assess sinkhole susceptibility for predicting potential sinkhole areas, and provide a sinkhole risk map, along with information on urban environment, as a useful tool for urban planning and geohazard risk management. [ABSTRACT FROM AUTHOR]

Groundwater bodies in the urbanized and densely populated aquifers or coastal floodplains may be subjected to groundwater rebound (GR), often causing serious risks of groundwater flooding (GF) to underground structures and infrastructures. This paper shows the results of a study carried out in the Naples' periurban area (Italy) to: investigate the dynamics and features of GR and GF phenomena, map flooded sites during 2013-2015 period, and provide an interpretative analysis of the factors that control the GF of private buildings and agricultural lands. At the municipality scale, since 1990 and until 2015, a remarkable and widespread GR was observed, with magnitude up to +16.54 m, triggering an unexpected GF of basements of buildings and agricultural soils. Field surveys proved that there is a time delay of the GF, ranging from 17 to 20 years, compared to the start of GR. Moreover, inhomogeneous distribution of flooding episodes is controlled by anthropogenic and natural factors. The obtained results are fundamental to design mitigation measures to GF hazard, and offer new perspectives to make Naples' periurban area more robust, smart and resilient against this new hydrogeological risk, undervalued by Italian legislation and local authorities. [ABSTRACT FROM AUTHOR]

Patients with acute aortic dissection (AD) remain at risk for long-term complications and thus are recommended to adhere closely to American College of Cardiology and American Heart Association aorta guideline-based follow-up imaging and clinic visits. The long-term outcomes of compliance with such a model are not well understood. This was a retrospective cohort study of patients at a regional AD center who survived hospital discharge for AD and who were analyzed by compliance with initial follow-up at 3 months and long term after AD. The primary end point was death. A total of 172 (66% type A; 33% type B) patients survived hospitalization and were followed up over 48 months (interquartile range [IQR], 21, 88 months). Of these patients, 122 (71%) attended the first follow-up appointment, and 90 (52%) attended more than two-thirds of recommended appointments. Patients who attended the first follow-up visit had improved long-term follow-up compliance (75% [IQR, 50%, 91%]) compared with patients who did not attend the first visit (18% [IQR, 0%, 57%]). Noncompliance with the scheduled long-term follow-up was associated with a 50% increase in the risk of death (hazard ratio, 1.6; 95% confidence interval, 1.2, 2.1; P <.001). Furthermore, in patients with low compliance (consistently attending less than one-third of follow-up appointments), the lifetime risk of death after AD was more than double that of patients with high compliance (consistently attending more than two-thirds of appointments) (hazard ratio, 2.2; 95% confidence interval, 1.5, 3.1; P <.001). Nearly one-third of patients with AD do not attend the first recommended follow-up visit, and such failure was associated with later noncompliance with subsequent follow-up. Low-compliant patients have double the lifetime risk of death after AD than do high-compliant patients. [ABSTRACT FROM AUTHOR]

Over the last decade, preoperative anemia has become recognized as a clinical condition in need of management. Although the etiology of preoperative anemia can be multifactorial, two thirds of anemic elective surgical patients have iron deficiency anemia. At the same time, one third of nonanemic elective surgical patients are also iron deficient. Modified RAND Delphi methodology was used to identify areas of consensus among an expert panel regarding the management of iron deficiency in patients undergoing cardiac surgery. A list of statements was sent to panel members to respond to using a five-point Likert scale. All panel members subsequently attended a face-to-face meeting. The initial survey was presented and discussed, and panel members responded to each statement on the Likert scale again. Based on the second survey, the panel came to a consensus on recommendations. The panel recommended all patients undergoing cardiac surgery be evaluated for iron deficiency, whether or not anemia is present. Evaluation should include iron studies and reticulocyte hemoglobin content. If iron deficiency is present, with or without anemia, patients should receive parenteral iron. Erythropoietin-stimulating agents may be appropriate for some patients. Consensus of an expert panel resulted in a standardized approach to diagnosing and managing iron deficiency in patients undergoing cardiac surgery. [ABSTRACT FROM AUTHOR]

The building stock around the world is exposed to different types of natural actions such as earthquakes or landslides. In particular, Italy is one of the countries worldwide most affected by landslides. Mitigation of landslide risk is a topic of great interest for the evaluation and management of its consequences. Periodical monitoring of the landslide-induced damage on structures require high costs due to the large number of exposed elements. With respect to the reinforced concrete structures, slow-moving landslides can affect primary structural elements, but more frequently damage occurs on the most vulnerable elements of the structure such as infills. The aim of this work is to demonstrate the potential utility of satellite data derived from a remote sensing technique, known as differential synthetic aperture radar interferometry, to support the structural health monitoring of reinforced concrete buildings affected by landslides. This article shows the structural health monitoring process for a reinforced concrete infilled building within a landslide-affected area, using the differential synthetic aperture radar interferometry data as input for the structural analysis in order to investigate the evolution of damage over the years. Three-dimensional structure, including the explicit infills consideration, has been modeled based on the information available from a visual survey, obtaining the missing parameters from a simulated design process and from the literature. In the field of the civil protection programs for the landslide risk reduction, this methodology can be quickly repeated for large sets of reinforced concrete buildings. Evidence of the visual survey showed a significant damage pattern in some infills. A good agreement has been found between analytical previsions and existing damage. Moreover, a global infills damage assessment of the case study building is proposed. Finally, assuming a constant increase in displacements in future years, a prediction of the future expected damage is shown. [ABSTRACT FROM AUTHOR]

Nowadays, several methodologies, implemented for satellite or terrestrial surveys, reveal that daily and weekly site-positioning time series can exhibit linear trends plus seasonal oscillations. Such periodic components affect the evaluation of subsidence rates and, thus, they must be recognized and properly modelled. In this work, the periodic component of vertical land motion in Po Delta (Northern Italy) is estimated by a multi-component and multi-source procedure recently proposed by some of the authors for studying land subsidence in delta areas. First, land vertical motion data, acquired in the central part of the Po Delta over a six-year time interval, were compared with hydro-meteorological and climate datasets collected from nineteen stations distributed over the entire Delta. Then, four physically based models of the test site were implemented to verify the water pressure- and water mass-dependent processes inferred from the analytical phase. Modelling results show that the annual ground oscillation is better explained by soil moisture change, although river water mass variation gives a relevant contribution to land deformation, especially in the wet periods. Finally, to account for intra-annual processes, the joint contributions of all the inferred sources were treated as a nonlinear problem and solved applying the generalized reduced gradient method. The obtained combination is well supported by statistical parameters and provides the best agreement with the geodetic observations. [ABSTRACT FROM AUTHOR]

In the present paper, the capillary barrier formation at the interface between soil layers, which is characterized by textural discontinuities, has been analyzed. This mechanism has been investigated by means of a finite element model of a two-layer soil stratification. The two considered formations, belonging to the pyroclastic succession of the "Pomici di Base" Plinian eruption (22 ka, Santacroce et al., 2008) of the Somma–Vesuvius volcano, are affected by shallow instability phenomena likely caused by progressive saturation during the rainfall events. This mechanism could be compatible with the formation of capillary barriers at the interface between layers of different grain size distributions during infiltration. One-dimensional infiltration into the stratified soil was parametrically simulated considering rainfall events of increasing intensity and duration. The variations in the suction and degree of saturation over time allowed for the evaluation of stability variations in the layers, which were assumed as part of stratified unsaturated infinite slopes. [ABSTRACT FROM AUTHOR]

Many of the UNESCO World Heritage Sites face geological threats which could have negative effects on the value, integrity and accessibility of their heritage assets. A relevant example is the Derwent Valley Mills UNESCO World Heritage site, one of the key sites of Britain's industrial revolution of the 18th century and located along the Derwent River Valley. Individual susceptibility scenarios of natural hazards in the area like collapsible deposits, compressible ground, debris flow, landslide, running sands, shrink-swell, soluble rock and flooding (both riverine and groundwater) are available, but a comprehensive product able to support disaster mitigation measurement and land planning still does not exist. On this basis, a multi-hazard susceptibility analysis was completed with the added benefit of reducing the complexity and providing a methodological framework for multi-hazard estimation. The analysis was completed in a GIS environment through an Analytical Hierarchy Process (AHP) multicriteria decision-making process. Since the AHP method is affected by a user selection bias, a quantitative Relative significance index was derived to rank the AHP factors during the susceptibility estimation. This index suggests that flooding is the principal natural hazard for the Derwent Valley Mills UNESCO World Heritage site. The multi-hazard susceptibility map also indicates that most of the areas where the mills are located are subject to significant susceptibility to natural hazards. [ABSTRACT FROM AUTHOR]

Natural hazards such as landslides, soil erosion and floods are increasingly affecting many regions of the world in relation to ongoing climate change and the abandonment of rural areas. In the last decades, the need to mitigate such phenomena and preserve natural resources, including landscapes, has motivated a number of local and national authorities to promote the use of soil bioengineering techniques. Consequently, these techniques have been increasingly used with variable success rates. This study analysed the efficiencies of different bioengineering structures to mitigate geo-hydrological risks by examining the interventions installed between 2007 and 2013 in the Avellino Province southern Italy. To this end, a specific project consistency analysis and functionality classification were carried out and the causes of inefficiencies were identified. The analysis showed that after a few years, only a small number of the installed bioengineering structures were fully functional and efficient. Overall, the installed structures were generally affected by maintenance issues and in many cases they suffered from design and execution issues, inducing a generally lower degree of efficiency, with most of them classified as 'not very efficient'. The conclusions of this work are that i) the long-term efficiency of a bioengineering structure is related to its correct design, installation, and maintenance; ii) the design of a bioengineering structure should account for the geological, geotechnical and hydrological characteristics of the area of interest, and iii) maintenance must not affect the short-term efficiency of a structure, but may affect the long-term efficiency. • The efficiency of bioengineering structure was analysed. • Bioengineering structure functionality was estimated three years after the installation. • A matrix-based approach accounting for causes of inefficiency was used. • Only 7% of the interventions were fully working and integrated with the landscape. • Most of the bioengineering structures were affected by design and installation issues. [ABSTRACT FROM AUTHOR]