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The prediction and prevention of landslide hazard is a challenging topic involving the assessment and quantitative evaluation of several elements: geological and geomorphological setting, rainfalls, and ground motion. This paper presents the multi-approach investigation of the Nevissano landslide (Asti Province, Piedmont, NW Italy). It shows a continuous and slow movement, alongside few paroxysmal events, the last recorded in 2016. The geological and geomorphological models were defined through a field survey. An inventory of the landslide's movements and rainfall records in the period 2000–2016 was performed, respectively, through archive investigations and the application of "Moving Sum of Daily Rainfall" method, allowing for the definition of rain thresholds for the landslide activation (105 mm and 193 mm, respectively, in 3 and 30 days prior to the event). The displacements over the last 8 years (2016–2023) were monitored through an innovative in-continuum monitoring inclinometric system and Earth Observation (EO) data (i.e., relying on Interferometric Synthetic Aperture Radar, or InSAR data): it gave the opportunity to validate the rainfall thresholds previously defined. This study aims to provide information to public authorities for the appropriate management of the site. Moreover, the proposed workflow could be adopted as a guideline for investigating similar situations. [ABSTRACT FROM AUTHOR]

Flow-like landslides are recognized to be the most destructive slope movements and to threaten human life. They may occur in several geological settings, as is the case of the pyroclastic soil covers resting on either igneous, or carbonate, bedrocks. The pyroclastic soil strata involved in these shallow landslides typically are partially saturated over the whole year. Intense rainfall, considered at hourly time scale, represents the triggering factor because it causes the decrease in matric suction and the consequent decrease in soil shear strength. However, it is recognized as the role of the hydromechanical slope behavior, the vegetation cover, and the geomorphological irregularities on shallow landslide hazard. These factors should be properly simulated in physically based predictive models of the failure onset to set up a reliable early warning system (EWS). This paper presents a new coupled thermohydraulic modeling of a pyroclastic soil cover in Campania, accounting for several slope factors that may predispose landslide activation, including the geomorphological local irregularities. The Mount Faito test site, in the Lattari Mountains (Southern Italy), has been adopted as a prototype slope for the geomorphological and hydromechanical scenarios of reference because of the extensive field and laboratory characterizations of the soil strata already available from previous studies. Once validated with these data, the numerical model has been used to estimate the slope response to critical rainfall scenarios. Such numerical estimations have been then compared to the instability predictions currently provided by empirical approaches, defined in terms of the intensity and duration of rainstorms threshold of shallow landslide activations. By comparison between the empirical and physically based approaches, the crucial role of antecedent slope hydraulic conditions and the geological setting for implementing reliable EWS, reducing false alarms, is proved. [ABSTRACT FROM AUTHOR]

Broad mountainous areas in the western Campania (southern Italy), where young pyroclastic deposits extensively outcrop, frequently experience rainfall-induced slope movements of different degrees of mobility, causing heavy damage and fatalities. Such landslides cannot be easily mitigated, and the implementation of physically based early warning systems is still not able to predict the post-failure evolution of slope movements and the exposed areas at risk. This paper is devoted to overcoming this limit. To this end, the mechanical characterization of pyroclastic soil, carried out through an extensive laboratory testing program, is presented and compared with those of two other ashy soils of different depositional mechanisms. The results show that the depositional mode influences soil properties; to begin with, it affects the unsaturated shear strength, whose intercept of cohesion is up to 5 kPa higher in ashes of flow deposition than in airfall ash deposits. The saturated undrained soil response allowed for the identification of different levels of susceptibility to the liquefaction of pyroclastic deposits, which is one of the main factors governing the post-failure evolution of landslides. Gathering all the acquired information, including saturated and unsaturated soil shear strength, permeability function, and water retention curves, into a soil database, it was possible to present all data under a unitary framework. Finally, the implementation of the proposed flowchart for a simplified assessment of post-failure evolution to be employed in regional early warning systems can enhance our knowledge of the areas at risk. [ABSTRACT FROM AUTHOR]

Cultural heritage is one of the most exceptional resources characterizing the Italian territory. Archaeological heritage, i.e., the archaeological sites with different types of archaeological artifacts, strongly contributes to enriching the national and international cultural heritage. Nevertheless, it is constantly exposed to external factors, such as natural deterioration, anthropic impact, and climate-related hazards, which may compromise its conservation. In Italy, many archaeological areas are affected by significant soil settlements that involve a large part of monuments. This paper focuses on the landslide hazard assessment of the archaeological site of Pietrabbondante (Molise region, Italy). The impact of the expected rainfall regimes, according to the EURO-CORDEX projections, on slope stability conditions were evaluated through the application of a physically based model that couples a hydraulic and a mechanical model to evaluate slope stability evolution due to pore pressure changes. Given the unavoidable lack of knowledge of the geotechnical soil properties in an archaeological heritage area, the proposed method considered the random uncertainty of soil parameters by means of a probabilistic approach in order to assess the stability conditions in terms of probability of occurrence of a landslide. The results of this study provide a reference for the safety assessment and preventive conservation of archaeological areas characterized by high cultural value. [ABSTRACT FROM AUTHOR]

Earth flows are complex gravitational events characterised by a heterogeneous displacement pattern in terms of scale, style, and orientation. As a result, their monitoring, for both knowledge and emergency purposes, represents a relevant challenge in the field of engineering geology. This paper aims to assess the capabilities, peculiarities, and limitations of different remote sensing monitoring techniques through their application to the Pietrafitta earth flow (Southern Italy). The research compared and combined data collected during the main landslide reactivations by different ground-based remote sensors such as Robotic Total Station (R-TS), Terrestrial Synthetic Aperture Radar Interferometry (T-InSAR), and Terrestrial Laser Scanner (TLS), with data being derived by satellite-based Digital Image Correlation (DIC) analysis. The comparison between R-TS and T-InSAR measurements showed that, despite their different spatial and temporal resolutions, the observed deformation trends remain approximately coherent. On the other hand, DIC analysis was able to detect a kinematic process, such as the expansion of the landslide channel, which was not detected by the other techniques used. The results suggest that, when faced with complex events, the use of a single monitoring technique may not be enough to fully observe and understand the processes taking place. Therefore, the limitations of each different technique alone can be solved by a multi-sensor monitoring approach. [ABSTRACT FROM AUTHOR]

Detailed and accurate geomorphological historical landslide inventory maps are an invaluable source of information for many research topics and applications. Their systematic preparation worldwide has been advised by many researchers as it may foster our knowledge on landslides, their spatial and temporal distribution, their potential interaction with the built environment, their contribution to landscape dynamics, and their response to climate change in the past. Due to the extreme variability of the morphological and radiometric elements that can reveal historical landslides, geomorphological historical landslide inventory maps are produced by expert interpretation, which makes it a time-consuming and expensive process, which often discourages wide-area mapping activities. In this paper we present a new geomorphological historical landslide inventory map for a 1460 km 2 area in the Daunia Apennines, the north-western sector of the Apulia (Puglia) region, in southern Italy. The inventory contains 17 437 landslides classified according to relative age, type of movement, and estimated depth. Landslides were mapped according to rigorous and reproducible criteria applied by two teams of expert photo interpreters to two sets of stereoscopic aerial photographs taken in 1954/55 and 2003. The dataset consists of a digital archive publicly available at 10.1594/PANGAEA.942427 (Cardinali et al., 2022). [ABSTRACT FROM AUTHOR]

This paper investigates the possibility to detect the short-time evolution of the slow-moving Vomice earth flow, located in the northeastern sector of the Calabria region (South Italy), by combining the information obtained from two different drone flights, carried out in February 2019 and June 2022, with field surveys. The obtained results consisted of delimiting all landslide bodies constituting the Vomice earth flow, detecting landslide types and the state of activity, as well as identifying spatial and volumetric changes. The obtained results showed that depletion and transition zones of the Vomice earth flow are active, while the accumulation zone appears prevalently dormant. Particularly, in the analyzed period, the depletion zone was characterized by local collapses of the main scarps where several slides evolving in earth flows caused more than 20 m of retrogressive fail upslope. The maximum elevation changes observed in these zones were about ±5 m. The volume of the material mobilized by mass movements was about 114.2 × 103 m3, whereas the volume of the accumulated material was approximately 92.7 × 103 m3. The transition zone was affected by several slow earthflows that re-mobilized the displaced material located in the middle portion of the landslide and reached the accumulation zone. Overall, the results of this study demonstrated the practicality and feasibility of using UAV tools for detecting the short-time evolution of a large landslide. [ABSTRACT FROM AUTHOR]

Transferability of knowledge from well-investigated areas to a new study region is gaining importance in landslide hazard research. Considering the time-consuming compilation of landslide inventories as a prerequisite for landslide susceptibility mapping, model transferability can be key to making hazard-related information available to stakeholders in a timely manner. In this paper, we compare and combine two important transfer-learning strategies for landslide susceptibility modeling: case-based reasoning (CBR) and domain adaptation (DA). Care-based reasoning gathers knowledge from previous similar situations (source areas) and applies it to solve a new problem (target area). Domain adaptation, which is widely used in computer vision, selects data from a source area that has a similar distribution to the target area. We assess the performances of single- and multiple-source CBR, DA, and CBR–DA strategies to train and combine landslide susceptibility models using generalized additive models (GAMs) for 10 study areas with various resolutions (1, 10, and 25 m) located in Austria, Ecuador, and Italy. The performance evaluation shows that CBR and combined CBR–DA based on our proposed similarity criterion were able to achieve performances comparable to benchmark models trained in the target area itself. Particularly the CBR strategies yielded favorable results in both single- and multi-source strategies. Although DA tended to have overall lower performances than CBR, it had promising results in scenarios where the source–target similarity was low. We recommend that future transfer-learning research for landslide susceptibility modeling can build on the similarity criterion we used, as it successfully helped to transfer landslide susceptibility models by identifying suitable source regions for model training. [ABSTRACT FROM AUTHOR]

Detailed and accurate geomorphological historical landslide inventory maps are an invaluable source of information for many research topics and applications. Their systematic preparation worldwide has been advised by many researchers as it may foster our knowledge on landslides, their spatial and temporal distribution, their potential interaction with the built environment, their contribution to landscape dynamics, their response to climate change in the past. Due to the extreme variability of the morphological and radiometric elements that can reveal historical landslides, geomorphological historical landslide inventory maps are produced by expert interpretation, which makes it a time consuming and expensive process, which often discourages wide area mapping activities. In this paper we present a new geomorphological historical landslide inventory map for a 1,460 km² area in the Daunia Apennines, the northern-western sector of the Apulia (Puglia) region, in Southern Italy. The inventory contains 17,437 landslides classified according to relative age, type of movement and estimated depth. Landslides were mapped according to rigorous and reproducible criteria applied by two teams of expert photo interpreters to two sets of stereoscopic aerial photographs taken in 1954/55 and 2003. The dataset consists of a digital archive publicly available at https://doi.pangaea.de/10.1594/PANGAEA.942427 (Cardinali et al., 2022). [ABSTRACT FROM AUTHOR]

Transferability of knowledge from well-investigated areas to a new study region is gaining importance in landslide hazard research. Considering the time-consuming compilation of landslide inventories as a prerequisite for landslide susceptibility mapping, model transferability can be key to making hazard-related information available to stakeholders in a timely manner. In this paper, we compare and combine two important transfer-learning strategies for landslide susceptibility modelling: case-based reasoning (CBR) and domain adaptation (DA). CBR gathers knowledge from previous similar situations (source areas) and applies it to solve a new problem (target area). DA, which is widely used in computer vision, selects data from a source area that has a similar distribution to the target area. We assess the performances of single- and multiple-source CBR, DA and CBR-DA strategies to train and combine landslide susceptibility models using generalized additive models (GAMs) for 10 study areas with various resolutions (1 m, 10 m and 25 m) located in Austria, Ecuador, and Italy. The performance evaluation shows that CBR and combined CBR-DA based on our proposed similarity criterion was able to achieve performances comparable to benchmark models trained in the target area itself. Particularly the CBR strategies yielded favourable results in both single- and multi-source strategies. DA tended to have overall lower performances than CBR; yet, it had promising results in scenarios when the source-target similarity was low. We recommend that future transfer learning research for landslide susceptibility modelling can build on the similarity criterion we used, as it successfully helped to achieve landslide susceptibility model transfers by discovering suitable training datasets from various regions. [ABSTRACT FROM AUTHOR]

Recent events, including the floods in central Europe in May 2021, have highlighted how climate change is giving rise to scenarios that were neither foreseen nor predictable. One problem this poses is the need to rethink the logic of various environmental constraints that are often based on return times of 20-50 years or 100-200. A single event does not change the statistical expectations for the recurrence of the event itself, but the recurrence of several extraordinary events in a few years is a clear indication of a changing trend. The prevention of the effects of such events is based on the definition of the areas at greater or lesser risk specifically based on the return times of the exceptional events, so it is foreseeable that a series of territorial plans, mostly carried out a few decades ago, will have to be updated or re-executed from scratch. These reworkings will be able to take advantage of the opensource software and open spatial data that have become available in the meantime, facilitating the entire process, and making it more open and shareable. In this paper we tested on a real case (the May 1999 pyroclastic flows in Campania, southern Italy) the actual possibility of implementing a model for forecasting such events using only open-source software and open data. It has been demonstrated that the entire process can be carried out using only open-source resources and it has been verified that the predictions of the hazard and risk model obtained with only input data prior to the event, give an output prediction that is significantly coincident with the events that actually occurred as documented by the authorities. [ABSTRACT FROM AUTHOR]

Starting on 24th August 2016, Central Italy was struck by a six-month earthquake sequence that caused 303 victims and extensive major damages to urban areas and infrastructures, in some cases entire villages needed complete rebuilding. In this paper we present a map that portrays the overall susceptibility to multiple landslide types and the exposure to landslides of the rural-urban areas of the Castelsantangelo sul Nera Municipality, a typical village of the central Italian Apennine. The map is based on a procedure that ingests geomorphological data and models and groups the individual landslide susceptibility maps in a joint susceptibility and exposure map based on expert-defined criteria. The procedure has been applied to built-up and to undeveloped areas to highlight their exposure and was used as a tool for planning post-seismic reconstruction. We advise that such maps are used also as basic tool for ordinary urban planning. [ABSTRACT FROM AUTHOR]

The paper describes the multitemporal landslide inventory map prepared for the urban areas of Motta Montecorvino and Volturino, two municipalities located in the Southern Apennines (Apulia Region, Italy). These territories show a high propensity to landslides of different types and magnitude, which periodically interfere with the anthropic structures and infrastructures. For the study area, the spatial and temporal distribution of landslides is detected for the period between 1954 and 2003, through the visual interpretation of multiple sets of black and white digital stereoscopic aerial photographs at different scales. The analysis reveals locally high frequency of landslide occurrence and built-up areas on existing landslides, either on the body or on the crown areas. In particular, we show that over the years new residential areas were developed despite the presence of large old mass movements. [ABSTRACT FROM AUTHOR]

In this paper, a geomorphological map of Pescara del Tronto area (Sibillini Mts, Marche Region) is presented. The work focuses on the geomorphological analysis performed in a zone strongly struck by the 2016–2017 seismic sequence of Central Apennines. The geomorphological map (1:7,500 scale) was obtained through an integrated approach that incorporates geological-geomorphological field mapping and geomorphological profile drawing, supported by air-photo interpretation and GIS analysis. The main purpose of the work is to describe a geomorphological approach for representing and mapping the evidence of several debris flows and landslides recognized in the framework of seismic microzonation (SM) activities. Finally, in order to elevate geomorphological maps into effective tools for land management and risk reduction, it could provide a scientific and methodological basis to demonstrate that accurate mapping provides important information, readily available for local administrations and decision-makers, for the implementation of sustainable territorial planning and loss-reduction measures. [ABSTRACT FROM AUTHOR]

Starting on 24th August 2016, Central Italy was struck by a six-month earthquake sequence that caused 303 victims and extensive major damages to urban areas and infrastructures, in some cases entire villages needed complete rebuilding. In this paper we present a map that portrays the overall susceptibility to multiple landslide types and the exposure to landslides of the rural-urban areas of the Castelsantangelo sul Nera Municipality, a typical village of the central Italian Apennine. The map is based on a procedure that ingests geomorphological data and models and groups the individual landslide susceptibility maps in a joint susceptibility and exposure map based on expert-defined criteria. The procedure has been applied to built-up and to undeveloped areas to highlight their exposure and was used as a tool for planning post-seismic reconstruction. We advise that such maps are used also as basic tool for ordinary urban planning. [ABSTRACT FROM AUTHOR]

The paper describes the multitemporal landslide inventory map prepared for the urban areas of Motta Montecorvino and Volturino, two municipalities located in the Southern Apennines (Apulia Region, Italy). These territories show a high propensity to landslides of different types and magnitude, which periodically interfere with the anthropic structures and infrastructures. For the study area, the spatial and temporal distribution of landslides is detected for the period between 1954 and 2003, through the visual interpretation of multiple sets of black and white digital stereoscopic aerial photographs at different scales. The analysis reveals locally high frequency of landslide occurrence and built-up areas on existing landslides, either on the body or on the crown areas. In particular, we show that over the years new residential areas were developed despite the presence of large old mass movements. [ABSTRACT FROM AUTHOR]

• Novel prognostic method for bridge SHM based on InSAR analysis. • Applied Element Method to simulate the behaviour of bridges up to total collapse. • Combination of InSAR monitoring and numerical modelling. • Estimation of residual service life of bridges affected by slow deformation phenomena. • Application to the Albiano-Magra Bridge case study collapsed in 2020. This paper proposes an innovative approach for structural prognosis of bridges, that combines displacement information obtained by Synthetic Aperture Radar Interferometry (InSAR), applied to satellite data, with structural and collapse analysis performed through numerical modelling. The purpose of this multidisciplinary approach is to recognize potentially critical conditions and predict the time to failure of bridges affected by slow deformation phenomena, such as slow landslide-induced movements. The methodology involves advanced pre- and post-processing techniques for satellite SAR acquisitions, which allow tracking two-dimensional displacement evolution of multi-span bridges with properly defined error bounds, and uses numerical modelling to simulate damage propagation and structural behaviour up to total collapse. The effectiveness of the proposed synergy between remote displacement measurements and numerical collapse analysis is exemplified through the application to the Albiano-Magra Bridge in Italy, which collapsed on April 8th, 2020. The results have allowed to identify the triggering cause of the collapse and have provided an estimate of the residual service life of the bridge, with increasing reliability as the available satellite monitoring period gets longer. The work demonstrates that a combined analysis considering both satellite measurements and numerical modelling can improve the comprehension of the phenomena concerning the structural collapse due to slow deformations and its prevention. [ABSTRACT FROM AUTHOR]

The triggering of shallow landslides in granular deposits is highly controlled by the groundwater regime, namely, the pore water pressure distribution, which directly affects soil shear strength. The slope hydraulic state is usually variable over time and space due to the high variability of atmospheric loads at the ground surface and local geologic conditions, such as stratigraphic irregularities and preferential groundwater flow paths. The unfavourable combination among critical geomorphological and topographical settings with stratigraphic and hydrogeological features are commonly recognized as predisposing factors of flowslides and debris flow occurrences. This paper proposes a multidisciplinary approach that combines geological, geophysical and geotechnical investigations to identify the role of local geological and geotechnical factors on the groundwater regime in slopes prone to flow-like landslides. The study is based on seasonally repeated electrical resistivity tomography measurements integrated with geotechnical numerical modelling of hydraulic phenomena affecting the soil cover. The latter is used to analyse the effects of the stratigraphic variability in terms of the geometry, continuity, and thickness of the soil horizons on the groundwater regime over time. The proposed approach has been applied to a test site located on the northern slope of Faito Mt. in the Lattari/Sorrento Peninsula mountain chain (southern Italy), an area historically affected by many rapid instability phenomena, such as flow-like landslides and flash floods. Both geophysical and geotechnical models obtained for the test site were cross-checked and validated, providing significant insights into the hydraulic response of the soil cover to rainfall and its hydraulic interaction with the underlying bedrock. Specifically, the integrated approach proved that i) the buried paleo-morphology of the bedrock severely affects the pore water distribution in the soil cover and ii) ashy soil fills the upper karst portion of the bedrock, providing a hydraulic connection of the water flow infiltrating from the topsoil downwards. • The local geological factors severely affect flowslide's occurrence. • Geophysical modelling provides spatial distribution of water content in the slope. • Geotechnical models study the effects of local factors on hydraulic slope behaviour. • Bedrock paleo-morphology heavily affects pore water into soil cover. • Soil-filled fractures of the bedrock represent hydraulic connection of water flow. [ABSTRACT FROM AUTHOR]

The paper explores the potential of the satellite advanced differential synthetic aperture radar interferometry (A-DInSAR) technique for the identification of impending slope failure. The advantages and limitations of satellite InSAR in monitoring pre-failure landslide behaviour are addressed in five different case histories back-analysed using data acquired by different satellite missions: Montescaglioso landslide (2013, Italy), Scillato landslide (2015, Italy), Bingham Canyon Mine landslide (2013, UT, USA), Big Sur landslide (2017, CA, USA) and Xinmo landslide (2017, China). This paper aimed at providing a contribution to improve the knowledge within the subject area of landslide forecasting using monitoring data, in particular exploring the suitability of satellite InSAR for spatial and temporal prediction of large landslides. The study confirmed that satellite InSAR can be successful in the early detection of slopes prone to collapse; its limitations due to phase aliasing and low sampling frequency are also underlined. According to the results, we propose a novel landslide predictability classification discerning five different levels of predictability by satellite InSAR. Finally, the big step forward made for landslide forecasting applications since the beginning of the first SAR systems (ERS and Envisat) is shown, highlighting that future perspectives are encouraging thanks to the expected improvement of upcoming satellite missions that could highly increase the capability to monitor landslides' pre-failure behaviour. [ABSTRACT FROM AUTHOR]

Recent research in Umbria, Italy, has shown that landslide susceptibility is controlled by a process called path-dependency, which describes how past landslides control the locations of future landslides. To date, landslide path-dependency has only been characterised in Italy. This raises the question of whether this process occurs in other geomorphic settings, and thus whether path-dependency should be more universally included in landslide susceptibility assessments. Therefore, the main aim of this paper is to investigate and quantify landslide path dependency in the Nepal Himalaya. This is achieved by applying several path dependent metrics to three monsoon-triggered landslide inventories for the central-eastern Nepal Himalaya. These inventories were developed at two different spatial and temporal resolutions. As such, we aim not just to quantify landslide path-dependency, but also to assess whether path dependency characteristics are resolution-dependent. We find strong evidence that landslide path dependency is occurring in Nepal, with all three inventories having more overlap between past and new landslides than expected from a random distribution, and a tentative observation that the expected degree of overlap between landslides decreases with time. Finally, whilst path-dependency is observable across both of the investigated inventory resolutions, we find that the rates and magnitudes of the quantified path dependent metrics are sensitive to inventory length, study region size and the size/type of landslides mapped. Overall, our results corroborate the path-dependency observations from Italy, confirming that this process does occur in other geomorphic settings, and thus suggesting that path-dependency should be explicitly and universally considered in landslide susceptibility approaches. [ABSTRACT FROM AUTHOR]

The 2016 Italian seismic sequence was characterized by three main shocks that occurred on August 24th, on October 26th and 30th. The latter, a Mw 6.5 event, is the strongest seismic event recorded in Italy since the 1980, Mw 6.9 Irpinia Earthquake. In this time span between the first and the third shock of the 2016 sequence, more than 1000 seismic events of Mw greater than 3.0 and shallow hypocentral depth between 7 and 11 km were recorded, triggering more than of 1300 observed landslides. In this paper, the identification of the triggering models for four selected rock slides was performed together with the mechanical characterization of the affected rock masses both in situ and in laboratory. Large scale morphostructural setting was analysed to verify the role of regional tectonics in the failures. Discontinuity sets were identified at detail-scale using three-dimensional (3D) point clouds developed from structure from motion (SfM) reconstruction using unmanned aerial vehicles (UAVs). In situ and laboratory tests coupled to data from UAV 3D models were used for geomechanical characterization. Data were finally adopted as input of limit equilibrium static analyses, which allowed a better comprehension of the stability conditions prior to seismic events and clarify some aspects of the mobilized strength. • 3D Rockslides models were obtained from UAV surveys. • Structure from Motion (SfM) permitted to characterize the discontinuty sets. • The tectonic pattern of the area is controlled by NW-SE Quaternary faults. • Rockslides are locally controlled by more ancient discontinuity systems. • Failures of rock bridges were involved in the sliding. [ABSTRACT FROM AUTHOR]

Rainfall-induced shallow landslides occurring along slopes of mountains around the city of Naples (southern Italy), characterized by pyroclastic covers laying upon fractured limestone bedrock, pose serious threat to settlements and towns located at their foot. Although the triggering mechanism, related to suction reduction in the initially unsaturated soil cover is quite clear, there is still debate about the hydrological processes which predispose the slopes to failure. In this paper, the predisposing factors are analyzed with reference to two intense storms, both with about 300 mm rainfall, occurred in the same period of the year in 1999 and 2019. The two storms triggered several shallow landslides in an area of few km2 of the northeast-facing slopes of Partenio Mountains. The two events are compared analyzing both the characteristics of antecedent and event precipitations, as well as simulating the response of the slopes to rainfall with the help of a mathematical model. Specifically, two slopes are analyzed: one, near the town of Cervinara, where landslides were triggered only in 1999; another, near the town of San Martino Valle Caudina, where landslides occurred during both the events. The results of the model simulations indicate that rainstorm duration (shorter in 1999) and antecedent precipitation during the weeks before the event (smaller in 1999) are the main reasons of the different responses of the slopes to the two rainfall events. In fact, both drier initial conditions at the base of the soil cover and shorter storm duration limit the possibility of drainage of infiltrating water out of the soil cover through the soil-bedrock interface, thus favoring the suction reduction required for slope failure. The obtained results provide a key for the interpretation of landslides, often occurring in late autumn-early winter in the area. • Two landslides (1999 and 2019) on near slopes compared through mathematical modeling • Water leakage through soil-bedrock interface can prevent landslide triggering • Streams supplied by perched aquifer in the uppermost bedrock ensure slope drainage • Landslide predisposing conditions are controlled by soil moisture profile • Antecedent precipitation alone is not a proxy of landslide predisposing conditions [ABSTRACT FROM AUTHOR]