Assessment of Potential Landslide Scenarios Using Morphometry, Geomorphological Constraints, and Run-Out Analysis: A Case Study from Central Apennines (Italy)

Abstract

Landslides are among the most damaging natural hazards, posing significant threats to human lives and infrastructures, especially in mountainous regions such as the Central Apennines (Italy). This study focuses on the Mt. Marsicano catchment (2245 m a.s.l.), characterized by peculiar morphometric features and geomorphological constraints that highlight the possibility of potential landslide scenarios. The methodological approach led to the identification of potential landslide propagation patterns. The RAMMS::DEBRIS FLOW module was used to model two potential landslide scenarios: a debris flow-like movement with a volume of 2.03 × 10⁴ m³ and a rock avalanche-like movement with a volume of 1.2 × 10⁶ m³. Findings from the latter scenario suggested river obstruction and potential lake formation upstream. Triggering mechanisms were partially explored, linking the debris flow scenario to heavy rainfall events (>50 mm/day) and the rock avalanche scenario to earthquakes with Mw > 5.0. Despite the absence of occurred landslides for back-calculation analysis and modeling based on geomorphic evidence rather than calibrating to a specific local past event, the study provides preliminary clues about the combination between morphometric analysis and geomorphological constraints in hypothesizing potential landslide scenarios. It provides a foundation for anticipating future landslide impacts in mountainous areas with limited historical data, offering valuable geomorphological insights for preventive hazard assessment and mitigation strategies in similar environments.

1. Introduction

Landslides are among the most widespread geomorphological hazards, posing significant threats to human life, property, and infrastructure [1,2]. Their occurrence is mainly related to specific predisposing factors (e.g., morphological and geological settings) and triggering events (e.g., extreme rainfall, earthquakes, wildfires, etc.) [3,4,5]. Moreover, these phenomena play a direct role in landscape dynamics, inducing widespread mass movements that remove soils and sediments from slopes and exert adverse effects on downstream areas, particularly in mountainous regions. Such regions are acknowledged to be susceptible to rapid mass-wasting phenomena, which appear to increase due to climate change-induced global warming and erratic rainfall patterns. However, the relationship between climate and landslides remains an open issue. Findings about landslides in high-mountainous regions suggest a potential influence of climate change (e.g., [6,7]). Still, the evidence is often ambiguous and varies depending on different geomorphological frameworks, as well as different scales of investigation and possible complications arising from rainfall- and earthquake-triggered events [8,9].

Beyond these conceptual and indicative issues, landslide hazard assessment is a priority activity for understanding specific multi-hazard events in which an initial landslide scenario could trigger cascading processes, such as river damming and downstream flooding [10,11,12]. The knowledge about triggering mechanisms, magnitude, velocity, and propagation is paramount for foreseeing landscape evolution and preventing massive socio-environmental impacts. Recent methodological approaches effectively achieve these purposes through GIS-based morphometric characterization of drainage basins [13,14], geological-geomorphological analysis [15,16,17], and empirical-statistical methods/algorithms [18,19,20,21]. Moreover, different numerical models (i.e., RAMMS, DAN3D, r.avaflow, and TITAN2D [22,23,24,25,26,27]) are effectively applied to quantitatively compute landslide run-out and potential impacts on the surrounding areas, mainly based on topographic and hydrological parameters.

Starting from this general framework, the Central Apennines (Italy) have been widely affected by rock instabilities and landslides in both historical and recent times [28,29]. Examples of different phenomena are well-documented in various catalogs and thematic literature, distinguished by type, such as earthquake-induced landslides [30], rainfall-induced landslides [31], debris flow events [32,33], rock avalanche events [34], and landslide dams [35]. The study area is situated within the axial sector of the Apennine chain in the central-southern part of the Abruzzo Region, characterized by a wide and irregular mountainous landscape dominated by Mt. Marsicano (2245 m a.s.l.). From a local-scale viewpoint, the study area stands out as a potential demonstrative case among areas prone to debris flows and/or rock avalanches, exhibiting field evidence of rapid mass movements and deep-seated instabilities. These field observations are comparable to features observed in nearby landslide events, such as the Scanno landslide [36] and the Montagna Del Morrone debris flow [37].

This study aims to apply a methodological approach to forecast the propagation of two potential landslide scenarios (debris flow-like and rock avalanche-like movements) that could impact downstream areas. Additionally, an attempt was made to formulate hypotheses about possible triggering mechanisms by examining the spatio-temporal patterns of rainfall and earthquakes. Specifically, a small catchment was investigated through a combination of direct (geomorphological field surveys) and indirect methods (morphometric analysis and orthophoto interpretation), integrated with GIS-based techniques and numerical modeling. The Rapid Mass Movement Simulation (RAMMS; version 1.8.0) software and its debris flow module [38] were applied for run-out modeling, as it is particularly well-suited for assessing comprehensive situations that refer to both debris flows and rock avalanches. Moreover, regarding RAMMS analysis, since no local historical-to-recent landslide events have affected the analyzed catchment allowing for simulations via back-analysis, morphometric and geomorphological constraints were used to calibrate the simulations in order to obtain the most probable runout distances for potential landslide events.

Finally, the data suggest that this catchment is a good example for understanding dynamic changes in high mountain areas and anticipating the environmental impacts of future landslides. This approach could be particularly relevant for forward-looking applications aimed at providing preventive geomorphologically based advice to activate proper territorial planning and preventive mitigation strategies in similar environments.

2. Study Area

The study area is located in Central Italy, within the central-southern sector of the Abruzzo Region (Figure 1a). Geographically, it extends from 41°48′54″ to 41°46′34″ N and from 13°49′21″ to 13°53′59″ E. Situated in the inner Central Apennines, the area is part of one of the highest average elevation sectors in the entire chain, characterized by a high-relief mountainous landscape (up to 2200 m a.s.l.). The region features a series of NW–SE to N–S oriented ridges, separated by longitudinal river valleys and intermontane basins (elevation 250–1000 m a.s.l.—i.e., Fucino Plain and Sulmona Basin).

The area is composed of lithological sequences originating from various Meso–Cenozoic paleogeographic domains, including pre-orogenic limestone and marly limestone sequences, as well as syn-orogenic pelitic-arenaceous turbiditic sequences [39,40]. The backbone of the ridges consists of carbonate shelf limestones and dolomites, slope limestones, basin limestones and marls, and carbonate ramp limestones. Allochthonous pelagic deposits are widespread in the southeastern sectors, forming a chaotic assemblage of clayey, marly, and limestone units. Neogene sandy-pelitic turbiditic deposits fill the main transversal valleys, while Plio-Pleistocene marine clayey-sandy-conglomeratic and volcanic deposits largely outcrop in the hilly piedmont areas [41,42,43]. Quaternary continental deposits are present within the alluvial valleys and plains, and they also fill the main intramontane basins. These deposits include fluvio-lacustrine, morainic, travertine, sandy shore, and eluvial–colluvial deposits (Figure 1b).

The main tectonic elements are represented by NW–SE- to N–S-oriented thrusts (W-dipping) and NW–SE- to NNW–SSE-oriented faults. Compressional tectonics, active from the Late Miocene to the Early Pliocene, was followed by strike-slip tectonics, which is poorly constrained in age and largely masked by extensional tectonic dynamics [44]. Since the Early Pleistocene (and more intensively during the Middle Pleistocene), the orogen has been affected by extensional tectonics and regional uplifting, contributing to the definition of a more complex tectonic setting with the formation of the intramontane basins and the emersion of the Adriatic piedmont areas [45,46,47,48].

The geomorphological framework is the result of a combination of a wide range of morphogenetic processes and factors. In addition to structurally controlled landforms and fluvial landforms, gravity-induced processes (e.g., mostly rotational–translational slides, earth flows, rockfalls, and complex slides) and fluvial-related processes characterize the chain sector [49]. The highest elevations (>1500 m a.s.l.) are predominantly characterized by karst landforms and glacial features, which are remnants of the Pleistocene glacial stages and persist today as relict landforms [50,51].

The present-day seismic setting is dominated by extensional tectonics, still active in the axial part of the chain [52]. According to historical and instrumental data [53,54,55], the area has been repeatedly affected by several earthquakes, including seismic events of moderate to high intensity (up to Mw 7.0), as well as the recent well-documented low-magnitude seismicity [56].

Climatically, the study area is influenced by the physiography of the Central Apennine chain, which determines a peculiar climatic setting, changing from a Mediterranean type with maritime influence along the coasts and piedmont areas to a more continental-like one in the inner sectors [57]. This climatic arrangement also regulates rainfall and temperature distribution. Specifically, the highest annual rainfall values (ranging from 1400 to 2000 mm/year) occur in mountainous areas, decreasing to ~600 mm/year along the hilly piedmont and coastal areas. It is also characterized by heavy rainfall events (exceeding 150 mm/day and 30–40 mm/h) and erratic rainy days (exceeding 50 mm/day). Average temperature values range from 15 to 16 °C along the valleys to 2–4 °C at the mountain peaks, with more severe (lower) temperatures, particularly during the winter season [58,59,60].

Figure 1. (a) Location map of the study area in Central Italy; (b) geolithological map of Central Apennines (modified from [41]). Legend: (1) eluvial-colluvial deposits; (2) sandy shore deposits; (3) recent fluvio-lacustrine deposits; (4) travertine deposits; (5) morainic deposits; (6) old fluvio-lacustrine deposits; (7) volcanic deposits; (8) conglomeratic deposits; (9) clayey-sandy deposits; (10) sandy turbidites; (11) pelitic turbidites; (12) carbonate deposits in conglomeratic and calcarenitic facies; (13) allochthonous pelagic deposits; (14) carbonate ramp limestones; (15) basin limestones and marls; (16) slope limestone; (17) open carbonate shelf-edge limestones; (18) carbonate shelf limestones and dolomites; (19) faults of uncertain type; (20) normal faults or faults with strike-slip kinematics; (21) thrust faults or reverse faults. Seismicity data (time period: 1005–2025) were extracted from the CPTI15 v4.0 Catalog [55] and the ISIDe Database [56]. Note: the black box locates the study area; the Coordinate System used is WGS84/UTM zone 33 N.

Figure 1. (a) Location map of the study area in Central Italy; (b) geolithological map of Central Apennines (modified from [41]). Legend: (1) eluvial-colluvial deposits; (2) sandy shore deposits; (3) recent fluvio-lacustrine deposits; (4) travertine deposits; (5) morainic deposits; (6) old fluvio-lacustrine deposits; (7) volcanic deposits; (8) conglomeratic deposits; (9) clayey-sandy deposits; (10) sandy turbidites; (11) pelitic turbidites; (12) carbonate deposits in conglomeratic and calcarenitic facies; (13) allochthonous pelagic deposits; (14) carbonate ramp limestones; (15) basin limestones and marls; (16) slope limestone; (17) open carbonate shelf-edge limestones; (18) carbonate shelf limestones and dolomites; (19) faults of uncertain type; (20) normal faults or faults with strike-slip kinematics; (21) thrust faults or reverse faults. Seismicity data (time period: 1005–2025) were extracted from the CPTI15 v4.0 Catalog [55] and the ISIDe Database [56]. Note: the black box locates the study area; the Coordinate System used is WGS84/UTM zone 33 N.

3. Materials and Methods

The study area was investigated using a methodological approach (Figure 2) that included (i) morphometric analysis, (ii) geomorphological analysis, and (iii) run-out analysis. The combination of field data collection, literature review, and GIS-based techniques provided support for these analyses. Further details are provided below.

3.1. Morphometric Analysis

The analysis was conducted using Geographic Information System (GIS) software (QGIS version 3.34.15 ‘Prizren’). It was performed using topographic maps (1:10,000–1:5000 scale) and supported by the processing of a Digital Elevation Model (5 m DEM) derived from 1:5000 scale regional technical maps, retrieved from the Open Geodata Portal of the Abruzzo Region (https://opendata.regione.abruzzo.it/; accessed on 10 January 2025). It was based on the definition of the main physiographic features. The study area is located within a small mountainous catchment, whose boundaries and drainage lines were automatically extracted from the DEM using the Hydrological Tools in QGIS. The closing point of the catchment was located at the base of the slope. Several methods have been proposed for the selection of appropriate mapping units in landslide analysis, such as techniques based on grids with uniformly sized square windows or slope units [61,62]. Even if these kinds of techniques allow for avoiding possible effects related to the shape and size of the study area, they could be influenced by the scale of analysis or the applied hydrological criteria. Hence, to establish a basic reference unit for performing multidisciplinary analyses (e.g., morphometric and run-out analyses) that are similar to slope unit-based techniques but improved with expert-based identification of drainage lines and divides, the catchment scale may be the most suitable choice [63].

Elevation, slope, aspect, and topographic curvature were extracted from the DEM using the Terrain Analysis Tools in QGIS to quantitatively describe the analyzed high mountainous environment. Specifically, the slope was calculated as the first derivate of elevation [64]. Topographic curvature was defined as the rate of change in slope gradient (profile curvature) and/or aspect (planform curvature) in a specific direction [65,66]. The obtained values were divided into three ranges, indicating concave, planar, and convex surfaces, respectively.

Additionally, basic morphometric parameters were computed to obtain the Melton ratio (R) [67], expressed by the following equation:

R = (H_max − H_min)/A^0.5

(1)

where H_max and H_min are the maximum and the minimum relief, respectively, and A is the catchment area. The catchment length (WL) was also calculated based on the model proposed by Wilford et al. [68]. According to [69], the Melton ratio and the catchment length can be used to differentiate morphometric thresholds for rapid mass-wasting phenomena. The combination of these appropriate parameters identifies different categories of catchments prone to debris flows, debris floods, and fluvial phenomena.

3.2. Geomorphological Analysis

The analysis was based on geomorphological field mapping, supported by stereoscopic aerial photo interpretation. Field mapping was conducted at a 1:5000 scale to identify the types and distribution of geomorphological landforms, with a focus on the main mass movements affecting the study area. Specifically, field activities combined traditional methods with modern techniques. The use of devices equipped with specialized software (Qfield version 3.7.0, https://qfield.org/) enabled direct digital mapping of geomorphological features in the field, as well as the collection of georeferenced photos. This work was conducted in accordance with the official Italian geomorphological guidelines [70] and in compliance with the thematic literature on geomorphological mapping [71,72,73]. The geomorphological investigation was further enhanced and refined through the use of stereoscopic aerial photo interpretation. Aerial photo interpretation was performed using 1:10,000 scale stereoscopic air photos (Flight Abruzzo Region 1981–1987), 1:5000 scale orthophoto color images (Flight AGEA 2016 and 2019), and Google Earth^® imagery.

3.3. Run-Out Analysis

The RAMMS (Rapid Mass Movements Simulation) software system was used to define the potential run-out patterns [22,74]. RAMMS is a numerical model designed for run-out simulations, applicable to both practical and research-oriented scenarios in a three-dimensional terrain. It focuses on calculating the motion of the mass movement from the initiation point to the end of the propagation [75,76,77]. In detail, its debris flow module (RAMMS::DEBRIS FLOW—version 1.8.0 [38]) was applied along the selected mountainous catchment to simulate two different potential landslide scenarios. The standard input parameters required for the simulation include:

• Digital Elevation Model (DEM);
• Release information (e.g., input hydrograph and/or block release);
• Friction parameters (μ and ξ);
• Calculation domain (spatial extension of the run-out patterns).

An accurate Digital Elevation Model (DEM) is a crucial prerequisite for accurate numerical calculations [78]. Therefore, in this study, a 5 m resolution was selected and loaded in the RAMMS software. The topographic data (5 m DEM) were previously processed using GIS-based techniques and were deemed suitable and appropriate for modeling the processes under investigation, since other available DEMs (i.e., 10 m DEM) exhibited a lower resolution, and a potential high-resolution one (such as the 1m DTM deriving from LiDAR data by Ministero dell’Ambiente e della Sicurezza Energetica—https://sim.mase.gov.it/portalediaccesso/mappe/#/viewer/new; accessed on 5 February 2025) was not fully available for the study area because its grid covered only the downslope sectors of the investigated catchment. Regarding release information, there are two options to define the starting conditions, depending on the type of movement being modeled: input hydrograph and release area. Generally, it is useful to distinguish between channeled and unchanneled run-out [38].

In this study, two simulations were performed, incorporating scenarios involving both input hydrograph and block release. In the first landslide scenario, a channelized run-out was simulated using the input hydrograph as the release condition. This scenario assumes that the flow develops strictly within a channel, moving downstream with steep scarps delimiting its path. Constructing the input hydrograph typically requires information on the amount of material (discharge) flowing at a given location [79,80,81]. This can be estimated using measured flow heights in corresponding channel cross-sections or through empirical methods that relate estimated volume and flow rates [82]. In this study, since no local real measurements or sensitivity analysis can be carried out due to the absence of documented past events to which to refer, the estimation of the total volume and maximum discharge was derived from semi-empirical formulas, already applied in thematic studies in the Eastern Italian Alps and Southern Apennines [45,83,84,85,86], which link morphometric features (i.e., basin area, main channel length, main slope channel, etc.) and the expected volume. The appropriate estimation was achieved using the semi-empirical equation developed by D’Agostino [87], as follows:

M = 45 × A^0.9 × i^1.5 × GI

(2)

where M is the total volume (debris flow magnitude, m³), A is the catchment area (km²), i is the mean gradient of the stream (m/m), and GI is a dimensionless geological index. The latter parameter expresses the erodibility of the lithology (bedrock and/or surficial deposits) outcropping within the channel network. Its value ranges between 0 and 5, depending on lithological classes, and typically assumes a value of 5 for geological frameworks similar to those of the study area involving both Quaternary deposits and calcareous bedrock [85]. Taking into account that the original predictive formula was tested over several Alpine torrential catchments (<5 km²) by means of a multiple regression to minimize the mean square error [42] and it was feasibly applied as a comparison method for the assessment of real debris flow magnitudes in small catchments (<1 km²) in the southern Apennines [81], Equation (2) was acknowledged as suitable to provide reasonable estimations of the order of magnitude of the sediment volume potentially involved in the simulated landslide scenarios along the Mt. Marsicano catchment.

Additionally, an angle of inflow direction was included as an input parameter, calculated with respect to the x-coordinate of the topographic data. The run-out stopping criterion was based on a momentum threshold (5 % of the moving mass). A summary of all input parameters essential for the first potential landslide run-out scenario is provided in

Table 1. Details of input parameters for the first potential landslide scenario.

Input Parameters	Value
Digital Elevation Model (DEM) resolution	5 m
Hydrograph volume	2.03 × 104 m3
Estimated initial velocity	10 m/s
Time associated with maximum flow discharge	10 s
Angle of inflow direction	100°
Friction coefficient μ	0.17
Turbulence coefficient ξ	150 m/s2
Density	2500 kg/m3
Simulation end time	1305 s
Momentum percentage	5%
Dump step time	5 s

.

In the second landslide scenario, an unchanneled run-out was simulated using a polygon layer of critical areas (block release) to delineate detachment zones. It was assumed that a free-slope mass movement would evolve downstream within the mountainous catchment, with uncertainty regarding its potential discharge on the slope. Additional information about release areas and depths was derived from field data and measurements. Different release depths (i.e., 1.5 and 3.0 m) were considered due to uncertainties in determining the exact depth of loose material that could be entrained during the run-out dynamics. By loading these data into the RAMMS software, specific algorithms automatically estimate the release volume and associated parameters (e.g., slope values, average altitudes, and run-out stopping criterion) [38]. A summary of all input parameters essential for the second potential landslide run-out scenario is provided in

Table 2. Details of input parameters for the second potential landslide scenario.

Input Parameters	Value
Digital Elevation Model (DEM) resolution	5 m
Release depth	1.5 m and 3.0 m
Release volume	1.2 × 106 m3
Friction coefficient μ	0.17
Turbulence coefficient ξ	150 m/s2
Density	2500 kg/m3
Simulation end time	275 s
Momentum percentage	5%
Dump step time	5 s

.

The main challenge in RAMMS lies in the selection of the friction parameters, as the model employs a Voellmy-fluid friction law, which divides the frictional resistance into two components: dry Coulomb-type friction (μ) and viscous turbulent friction (ξ) [88,89,90,91]. These user-defined parameters play a crucial role in determining the run-out characteristics, as RAMMS employs a single-phase model that cannot distinguish between fluid and solid phases, treating the material as a bulk flow [92]. The selection and calibration of these materials are typically conducted through careful back-analysis procedures integrated with field data [75,93]. The friction parameters are responsible for the behavior of the flow: μ prevails when the flow is close to stopping, and ξ prevails when the flow is flowing rapidly. Generally, μ ranges between 0.05 and 0.4, while ξ values vary depending on the flow type: smaller values (100–200 m/s²) are suitable for granular flows (solid-like), and larger values (200–1000 m/s²) are often associated with muddy flows (fluid-like) [38,75]. More in detail, since this work provides a preventive run-out analysis of potential landslide scenarios and no local back-analysis or parameter sensitivity testing can be performed due to the absence of documented past events, the values of μ (0.17) and ξ (150 m/s²) were directly derived from the best-fitting data in terms of flow heights and invasion area resulting from a recent study by Calista et al. [37], carried out in a nearby mountainous area that exhibits physiographic, lithological, and geomorphological features comparable to those observed in the study area.

4. Results

4.1. Morphometric Features

The study area reaches its maximum altitude at the summit of Mt. Marsicano (2245 m a.s.l.). The morphology fairly slopes down towards the southern portion of the catchment, reaching a minimum altitude of approximately 1060 m a.s.l. in correspondence with the Sangro River (Figure 3a). Based on the orography of the landscape, the study area can be subdivided into three sectors: a northern sector, which includes the summit of Mt. Marsicano and Mt. Forcone, where the highest altitudes are found; a central sector, characterized by intermediate elevations; and a southern sector, representing the base of the catchment, where the lowest altitudes are located.

In this study, slope values were divided into 10 classes (Figure 3b). The slopes in the northern sector range from 0° to 40°, with small areas reaching values of up to 60°. Notably, the highest part of this sector contains the flattest area in the entire catchment, with slope values not exceeding 20°. The central sector features slopes ranging from 20° to 40°, with some areas reaching up to 60°. The southern sector can be further subdivided into two sub-sectors. The northern sub-sector, with altitudes ranging from 1600 m a.s.l. to 1250 m a.s.l., is characterized by the steepest slopes in the entire study area. Here, average slope values range from approximately 40° to 50°, with the highest values exceeding 80°, particularly along the main N-S-oriented drainage line. The southern sub-sector, with altitudes ranging from 1250 m a.s.l. to 1050 m a.s.l., features much gentler slopes, not exceeding 25–30°. The lowest slope values (5–10°) are found at the base of the basin under study.

Aspect is considered a factor influencing the occurrence of landslide phenomena, as it is associated with parameters such as sunlight, dry winds, and precipitation. The related map has been divided into nine classes (Figure 3c). The overall shape of the catchment delineates a specific aspect distribution: the eastern part of the catchment predominantly faces south/southwest, while the western part predominantly faces east/southeast. Additionally, the northernmost sector of the study area, at the base of the ridge between Mt. Marsicano and Mt. Forcone, features slopes facing north/northeast.

Curvature describes the rate of change in the slope gradient (Figure 3d), and it is divided into three classes. Positive curvature values (in red) indicate convexity, which characterizes the main ridges and slopes within the study area. Negative curvature values (in green) indicate concavity, which is typically found in valleys and along the main river incisions. Values around zero (in white) represent flat surfaces, regardless of the slope.

4.2. Geomorphological Features

From a geomorphological perspective, the dominant features are associated with structural, slope, fluvial, glacial, and karst morphologies (Figure 4). Regarding the structural landforms, the principal crest lines are located at the highest altitudes (up to 2000 m a.s.l.), exhibiting a predominantly N-S orientation, and closely align with the external boundaries of the catchment. The main crest line follows a predominantly N-S trend. A secondary crest line, which is lower and more rounded, has an NNW–SSE orientation. Two main saddles interrupt the continuity of the ridges and are mainly aligned in an E–W direction. Other structural landforms include an isolated relief at approximately 1950 m a.s.l. and a small structural surface outside the catchment.

Slope landforms are undoubtedly the most significant features in the study area. In the upper slope, there are three main trenches of varying lengths and dimensions, which are interrupted and separated by gullies. The first trench (Figure 4c) is located below the summit of Mt. Marsicano at approximately 2200 m a.s.l. It has a length of ~60 m, with depth varying from 2 to 5 m, moving from west to east. The second trench (Figure 4d) is situated further east than the first one and is approximately 210 m long, with a depth ranging from 10 to 20 m, increasing from west to east. A third trench is located slightly south, at approximately 1950 m a.s.l. This trench is about 70 m long, with a depth varying between 3 and 5 m. Small, localized shallow landslides are also present in the area.

Landslide scarps are found further west of Mt. Ninna and consist of arched or semi-circular rock scarps. These scarps are generally weathered by slope gravity and cryoclastic processes, contributing to areas with large fallen rock blocks. Talus slopes and debris cones are widely present in the northernmost sector of the study area, at the base of the ridge between Mt. Marsicano and Mt. Forcone. These features are composed of bodies of heterogeneous rock blocks, ranging in size from centimeters to meters, that are homogeneously arranged and more graded toward the northern base of the slope. The couloirs with debris discharge are well-developed and oriented perpendicularly to the slope, with a N-S orientation. These couloirs are influenced by polygenic processes, including debris discharge, surface water runoff, and snow avalanches.

Scree slopes are uniformly developed within the upper sector of the study area, both along the right-catchment (Figure 5a) and the left-catchment (Figure 5b). They consist of heterogeneous calcareous material with blocks of varying sizes. Specifically, the scree slopes on the right side are characterized by medium-sized blocks (average size: 80 cm × 30 cm × 30 cm) and large-sized blocks (average size: 100 cm × 60 cm × 30 cm, Figure 5c), while those on the left side are made of significantly smaller blocks, ranging from centimeters to meters in size (Figure 5d).

Scree slopes are also extensively present below the northern slope of Mt. Marsicano. Landforms due to running water are mainly represented by several well-developed gullies. These gullies generally exhibit an NNW-SSE orientation in the upper sector of the catchment, transitioning to a N–S orientation along the main channel in the central and southern sectors. Some fluvial erosion scarps can be observed along the course of the Sangro River, displaying a general W-E direction. Glacial landforms include half-bowl or amphitheater-shaped glacial cirques (Figure 4a) in the uppermost sector of the catchment, preserved as relict features. Finally, a small doline (Figure 4b) can be observed within the rugged and irregular morphology further west of the summit of Mt. Ninna.

4.3. Run-Out Modeling

Using GIS technology (QGIS version 3.34.15 ‘Prizren’), the findings for the proposed potential landslide scenarios were analyzed separately to identify the possible run-out patterns and invasion areas. The results obtained from RAMMS are presented and described in the following subsections.

4.3.1. First Potential Landslide Scenario

The first simulation was conducted by analyzing a channelized scenario. Figure 6 shows the flow height maps at different times, illustrating the movement of debris flow along the channel. Four specific times were selected to discuss the landslide’s movement process: T = 0 s, T = 435 s, T = 870 s, and T = 1305 s.

From T = 0 s to T = 435 s (Figure 6a), the flow begins to channel along the main channel. During this stage, the debris flow reaches a maximum velocity of approximately 12 m/s. This velocity is attributed to the slopes of about 30° encountered in this section, which are the steepest slopes experienced throughout the flow’s course.

At T = 435 s (Figure 6b), the flow reaches an elevation of approximately 1150 m a.s.l., with a maximum accumulation height of 3.62 m. This represents the highest accumulation recorded during the entire simulation due to the narrowing and deepening of the channel in this area, which later widens again in the final section.

At T = 870 s (Figure 6c), the debris flow, now fully channeled along the main channel, reaches the final part of the catchment, where the slopes are gentler, ranging from 5° to 10°. As shown in Figure 4c, part of the debris flow intersects the Marsicana State Road 83 (SS83), with a maximum accumulation height of 2.20 m at this time. Compared to the initial phase, the maximum accumulation height has decreased. This reduction is due to the partial deposition of the debris flow at the Sangro River, located below the road, where the maximum deposition height is approximately 2 m.

The debris flow has completed its movement at T = 1305 s (Figure 6d). Compared to the previous phase, the flow continued to descend along the channel and spread out in the downstream area, where the slopes are lower. The maximum accumulation height at the end of the simulation is 2.37 m, recorded at the Sangro River.

4.3.2. Second Potential Landslide Scenario

The second simulation was conducted using an unchanneled scenario (i.e., a simulation based on the block release hypothesis as input). As shown in Figure 7a, two release areas were defined, each associated with different depth information: the release depth of the right-catchment side (red area) is 3.0 m, and the release depth of the left-catchment side (blue area) is 1.5 m. Once these data were entered, the software automatically calculated the estimated release volume. The landslide’s movement process was analyzed at four different time intervals: T = 0 s, T = 90 s, T = 185 s, and T = 275 s.

As illustrated in Figure 7b, most of the mass movement occurs within the first 90 s. This is because, during this initial phase, the moving mass reaches its maximum speed of approximately 29 m/s, driven by the steep slopes in this area (Figure 3b), which range between 30° and 40°. The maximum accumulation height reached at T = 90 s is approximately 30 m, representing the highest point reached during the simulation. This peak is located at an altitude of 1250 m a.s.l., corresponding to the most incised section of the slope.

At T = 185 s (Figure 7c), nearly all the flow has reached the base of the slope, where the terrain flattens and the deposition phase begins. The maximum accumulation height during this phase is approximately 17.7 m, occurring near the Sangro River. Compared to the previous phase, the maximum accumulation height has decreased because the mass movement spread out, affecting a larger area.

At T = 275 s (Figure 7d), the flow has ceased its movement. There are no significant differences from the previous phase, as the final part of the movement is characterized by low velocities due to the nearly flat terrain in this area. Almost all of the deposits have reached the downstream area.

Consequently, compared to the previous timeframe, there is an increase in the maximum accumulation height, reaching 18.4 m, still located near the Sangro River. Additionally, the simulation shows that some of the involved materials impact the Marsicana State Road 83 (SS83).

5. Discussion

Here, an attempt is made to evaluate the impact areas and run-out distances of two potential landslide scenarios within a small mountainous catchment in the Central Apennines (Italy). The integration of direct (geomorphological field surveys) and indirect investigations (morphometric analysis), combined with run-out modeling, supported the assessment of future landslide events and potential geomorphological dynamics. Additionally, to formulate preliminary hypotheses regarding the possible triggering mechanisms of landslide scenarios in the study area, the spatio-temporal patterns of rainfall and earthquakes were introduced as key discussion points.

5.1. Morphometric and Geomorphological Constraints for Run-Out Modeling

The analyzed catchment is characterized by an irregular mountainous morphology, reaching an elevation up to 2200 m a.s.l. Slope values (average values ranging between 30° and 50°) play a crucial role in determining the size of contributing areas, with steeper slopes generally requiring smaller upstream areas to generate surface runoff and trigger debris discharge and/or slope instability compared to less steep areas. The dominant east-to-southwest facing slopes primarily display concave morphologies that define the well-developed channel network. Moreover, the computation of the Melton ratio (R) and the catchment length (WL) provided a valuable identification of morphometric thresholds for debris flow [68,69]. In detail, R corresponds to 0.87, fairly above the threshold (R > 0.60) of catchment prone to debris flows, and WL is equal to 2.82 km, within the thresholds of catchment with dominant fluvial processes and/or debris floods. Hence, according to the combination of the obtained values of R and WL, the catchment can be plotted in Category E proposed by Welsh and Davies [69], suggesting that the morphometric constraints are sufficient to acknowledge the analyzed catchment among areas prone to rapid mass movements (i.e., debris flows).

The overall geomorphological analysis confirmed that the present-day landscape dynamic in the study area is closely linked to gravitational slope processes. In particular, it presents a main 60 m-long trench up to 10 m wide, as well as smaller fractures of various sizes closer to the summits. Signs of active movement (e.g., rockfalls, toppling blocks, etc.) are evident in the northernmost sector of the study area, where large amounts of heterogeneous calcareous centimetric-to-metric rock blocks are found at the base of the summits of Mt. Marsicano, Mt. Forcone, and Mt. Ninna. Debris deposits are widespread along gullies and slopes throughout the catchment, forming unstable scree slopes that are evenly distributed on both the right- and left-catchment sides.

Regarding the RAMMS analysis, no documented past events have affected the study area, allowing for simulations based on acknowledged data via back-analysis. Unlike conventional back-calculations following well-documented events [94,95,96], the modeling of landslide scenarios in this study focused on hypothetical or potential events, considering the peculiar morphometric and geomorphological features of the study area (i.e., morphometry, signs of rapid movement, and deep-seated instabilities) rather than calibrating to a specific past event. Two potential failure scenarios were assessed, with estimated volumes of 2.03 × 10⁴ m³ and 1.2 × 10⁶ m³, respectively. According to the geological-geomorphological framework defined by means of field surveys, these potential involved volumes consist of heterogeneous calcareous deposits with blocks of varying sizes. Both simulated run-out scenarios resulted in material depositions at the base of the slope, at an altitude of approximately 1060 m a.s.l., in correspondence with the Sangro River, with varying maximum accumulation heights depending on the proposed input data and release areas. In detail, the first landslide scenario exhibited a channelized evolution, clearly indicative of a debris flow-like movement. The simulation suggested that the flow could initiate through erosion along gullies in the upper sectors of the catchment, transform into a mature debris flow in the subsequent transit area, and culminate in the downstream area with a maximum accumulation height of 2.37 m. The second landslide scenario revealed an unchanneled evolution resembling a potential rock avalanche-like movement. The identified release areas correspond to signs of deep-seated movements (e.g., trenches) and extensive scree slopes along the upper slope. The mass movement was hypothesized to evolve by remobilizing the material deposited along slopes and gullies during its downhill propagation. It reached the downstream area with a maximum accumulation height of 18.4 m, suggesting potential cascading processes, such as river damming and downstream flooding. Moreover, the geomorphological adherence of the outcomes confirmed the choice of input data (e.g., DEM resolution, topographic data, friction coefficients, etc.) resulting from a trade-off between computational cost, data availability, adequacy for the scale of analysis, and level of detail for the simulated scenarios. In detail, the RAMMS provided insights about the post-failure impact of these large amounts of material on the downstream areas, including the possibility of river obstructions.

5.2. Potential Triggering Mechanisms of Landslide Scenarios

Heavy rainfall events and high-magnitude seismicity have been considered as the possible triggering mechanisms of landslide scenarios in the study area. Regarding rainfall, data were provided by the Functional Center and Hydrographic Office of the Abruzzo Region. They were integrated with the online consultation of Hydrological Annals (available at https://protezionecivile.regione.abruzzo.it/agenzia/agenzia-regionale-di-protezione-civile-abruzzo/servizio-emergenze-di-protezione-civile/ufficio-idrologia-idrografico-mareografico/annali-idrologici/; accessed on 5 February 2025). This data gathering referred to 3 rainfall stations located in the surroundings of the Mt. Marsicano catchment: Barrea station (980 m a.s.l.), Pescasseroli station (1150 m a.s.l.), and Passo Godi station (1542 m a.s.l.). However, data from these stations reveal annual historical pluviometric series (time periods ranging from 30 to 70 years) that exhibit several gaps and shortcomings in daily-to-monthly rainfall recording [58,59]. Hence, for the study, rainfall data only referring to the Pescasseroli station were selected, as its dataset shows a nearly uninterrupted pluviometric series compliant with the World Meteorological Organization (WMO) directives [97], covering a 50-year period (1951–2001). This dataset was deemed suitable for a general characterization of the local microclimatic setting due to its relative proximity to the study area, despite the rainfall station being located approximately 1000 m downstream from the main landslide release areas. Annual dataset analysis indicates an average annual rainfall of about 1160 mm, distributed across 115 rainy days. The maximum recorded hourly and daily rainfall values correspond to 64 mm and 310 mm, respectively. The monthly dataset reveals a bimodal rainfall distribution, with an absolute maximum in November/December and a minimum in July/August. Notably, monthly rainfall levels never drop below 60 mm, except in the summer minimum, with 46 mm recorded in July (

Table 3. Annual and monthly rainfall datasets at the Pescasseroli station (timespan 1951–2001).

Annual Average
Rainfall (mm)	1578	Monthly Average
Maximum in 1 h (mm)	64		Jan	Feb	Mar	Apr	May	Jun	Jul	Aug	Sep	Oct	Nov	Dec
Maximum in 24 h (mm)	310	Rainfall (mm)	141	142	123	117	95	98	46	58	115	176	262	235
Rainy days (n°)	115	Rainy days (n°)	10	10	11	11	11	8	6	5	8	10	12	12

).

To potentially predict the rainfall conditions that could be likely to trigger the first landslide run-out scenario (debris flow-like movement), two climate extreme indexes were used to identify potential rainfall episodes based on the counts of rainy days exceeding defined thresholds (R > 20 mm: very intense rainfall; R > 50 mm: extremely intense rainfall) within the annual timeframe (time period: 1975–2001) recorded at the Pescasseroli station. In detail, these indexes (R20 mm and R50 mm; Figure 8) were calculated by means of a specific spreadsheet (e.g., XLSTAT—Microsoft Excel add-on), in accordance with thematic literature [98,99,100,101,102] and suiting the technical guidelines proposed by the Joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI, https://www.clivar.org/organization/etccdi/etccdi.php, accessed on 5 February 2025).

Figure 8a presents a scatter plot showing the number of days per year with rainfall exceeding 20 mm. The number of such days fluctuates significantly, with some years experiencing around 30 rainy days and others fewer than 10 days. The positive slope of the linear regression trend line (black dashed line in Figure 8a) indicates a slight trend in the frequency of days with rainfall exceeding 20 mm over this 27-year period from 1975 to 2001. This suggests a potential increase in the occurrence of heavy rainy days. However, the low coefficient of determination (R² = 0.1789) indicates that the linear model explains only about 17.9% of the observed interannual variability. Even if the data exhibit considerable scatter around the trend line, this upward increase may indicate changing climate patterns, leading to more frequent occurrences of heavy rainy days, which could potentially contribute to debris flow initiation.

Figure 8b displays a scatter plot representing the number of days per year with daily rainfall exceeding 50 mm. The data points fluctuate, with some years experiencing very heavy rainy days, while others record very few (close to zero). No single, consistent temporal pattern is immediately apparent from the raw data, as years with high frequency (e.g., up to 10 events) are interspersed with years of very low frequency (e.g., 0–2 events). The linear regression trend line (black dashed line in Figure 8b) indicates a slight positive trend, suggesting a marginal long-term increase in the frequency of days with rainfall exceeding 50 mm over this 27-year period from 1975 to 2001. However, the extremely low coefficient of determination (R² = 0.0063) signifies that the linear model explains only 0.63% of the observed variance in the data, demonstrating that the positive trend is statistically weak with a very high interannual variability. While the trend is not steep, it may reflect shifting climate patterns and a gradual rise in the occurrence of extreme rainfall events, which could be linked to debris flow triggering.

Nevertheless, even if no direct evidence for local rainfall thresholds can be discriminated, findings from the computation of these extreme rainfall indexes (R20 mm and R50 mm) indicate a significant long-term increase potentially consistent with the outcomes of thematic and detailed studies [37,103,104,105] focused on estimating rainfall thresholds for landslide (i.e., debris flow) triggering.

Regarding seismicity, data were extracted from the CPTI15 Catalog [55] and the DISS Database [106] to accurately define the study area’s background. Figure 9 illustrates that the study area is situated within a complex seismotectonic context, strongly influenced by the main seismogenic sources of the Central Apennines. In detail, the study area suffers from the proximity of several NW-SE trending seismogenic sources with predominantly normal-type focal mechanisms (e.g., ITCS024 Miranda-Apice; ITCS025 Salto Lake-Ovindoli-Barrea; ITCS013 Borbona-L’Aquila-Aremogna; ITCS040 Barisciano-Sulmona). These sources were responsible for moderate (4.0 < Mw < 5.0) to damaging (Mw > 6.0) seismicity. Several earthquakes enucleated in the study area in historical times (e.g., 1349, Mw 6.80 Lazio-Molise; 1654, Mw 6.33 Sorano; 1706, Mw 6.84 Maiella; 1874, Mw 5.48 Val Comino; 1901, Mw 5.16 Sorano; 1915, Mw 7.08 Marsica; 1984, Mw 5.47 and 5.86 Monti della Meta; 2013, Mw 4.94 Valle del Liri), along with well-documented recent low-magnitude seismic events [56]. This peculiar framework is also supported by Peak Ground Acceleration (PGA) values available for the study area through the MPS04-S1 seismic hazard map of Italy [107] and by thematic literature dealing with the potential for triggering landslides based on seismic hazard [108]. Hence, according to the geological and tectonic context of the area, seismic loading can influence geomorphological dynamics and slope instabilities, either by reducing the strength of rock masses by propagation and widening of present gravitational trenches or by triggering rockfall and topple phenomena [109,110].

Therefore, earthquakes cannot be ruled out as a potential triggering mechanism for the landslide scenarios, reinforcing the consistency of this study with previous research on earthquake-induced landslides [108,111,112,113].

In conclusion, additional attention was given to the possibility of river obstruction following the simulated landslide scenarios. Considering the two probable release areas and the different initial volumes, the second potential landslide scenario (rock avalanche-like movement) is more damaging. The resulting landscape evolution could be fairly complex, as the total amount of displaced material may reach the downstream areas, potentially causing road blockages and environmental impacts (Figure 9). After its downhill propagation, this landslide scenario ultimately results in the deposition in the downstream area with accumulation ranging from 11 to 18 m at an elevation of ~1060 m a.s.l. (Figure 10a). Simulation results (Figure 10b,c) indicate that the maximum accumulation heights of 18.4 m occur at the river channel’s confluence. Therefore, the results suggest that this scenario could obstruct the Sangro River, potentially leading to river blockage. This, in turn, may trigger a significant landscape-impacting process, resulting in the formation of a new lake in the upstream sectors of the river course. This could be a plausible evolutionary scenario, also in accordance with previous well-documented landslide damming events in the surroundings of the study area (e.g., the Scanno rock avalanche, which completely dammed the Tasso River, causing the impoundment of the Scanno lake [36]).

5.3. Assumptions and Limitations

The study presented valuable insights, and the adopted methodological approach led to simulating the propagation of two potential landslide scenarios (debris flow-like and rock avalanche-like movements), but it is important to acknowledge its assumptions and limitations. Although these issues were partially described, it is essential to contemplate potential shortcomings that could impact the interpretation of their outcomes.

The basic assumption is that the analysis was carried out as a purely preventive and forward-looking application within the Mt. Marsicano catchment, where no historical and/or recent landslide events have been recorded. In detail, the RAMMS::DEBRIS FLOW—version 1.8.0 was applied to model “what-if” landslide scenarios by hypothesizing initial conditions (e.g., location of detachment zones, release volume, friction parameters, etc.) based on geomorphic evidence and literature data rather than calibrating them to a specific past event. These working hypotheses were supported by the peculiar morphometric and geomorphological features of the study area (i.e., debris flow-prone catchment according to the Melton ratio; signs of rapid movement—scree slope, rockfalls, and toppling blocks, and deep-seated instabilities—well-elongated trenches and smaller fractures). These features suggest the potential development of future landslide scenarios, as they are comparable to field evidence observed in nearby locations with literature-documented landslide phenomena (i.e., debris flows and rock avalanches) [36,37]. Moreover, the working hypothesis can be supported by the results of run-out modeling, which provide estimations of the total volume of involved material (2.03 × 10⁴ m³ and 1.2 × 10⁶ m³) showing orders of magnitude comparable to nearby landslide events in the Central Apennines [34,37].

6. Conclusions

Landslides are recognized as one of the most damaging natural hazards threatening human lives, infrastructures, and landscapes in mountainous regions. The Central Apennines have been extensively affected by different types of mass movements (e.g., earthquake-induced and rainfall-induced landslides, debris flows, rock avalanches, landslide dams, etc.), whose frequency and magnitude have been accentuated due to the peculiar morphostructural and seismotectonic context, as well as by the changes in the climate regime.

The study area (Mt. Marsicano catchment, 2245 m a.s.l.) could represent a potential demonstrative case among areas prone to debris flows and/or rock avalanches, exhibiting both evidence of rapid movements and deep-seated instabilities comparable to features observed in nearby locations, such as the Scanno landslide [36] and the Montagna Del Morrone debris flow [37]. It was investigated by adopting a proactive methodological approach involving direct (geomorphological field surveys) and indirect (morphometric analysis and orthophoto interpretation) methods, integrated with numerical modeling (RAMMS::DEBRIS FLOW—version 1.8.0) and GIS-based techniques.

The geomorphological field survey was crucial for understanding the present-day dynamics in this mountainous area, which are strictly related to slope gravity processes. It enabled the identification of the main hypothetical release areas within the catchment, where physiographic and geomorphological variations influence the potential propagation of landslide scenarios towards downstream areas. Regarding RAMMS analysis, since no past landslide events have been recorded in the study area, allowing for back-analysis simulations, the run-out modeling focused on potential future landslide events. The simulations were based on significant field evidence of active phenomena (e.g., rockfalls and scree slopes) and indications of deep-seated movements (e.g., well-elongated trenches). Specifically, two potential landslide scenarios were evaluated, characterized by volumes of 2.03 × 10⁴ m³ and 1.2 × 10⁶ m³, respectively. According to the results, both run-out simulations culminated in the deposition of materials at an altitude of ~1060 m a.s.l. in correspondence with the Sangro River. However, the flow patterns and maximum accumulation heights varied depending on the input data and release areas. In the first scenario, the debris flow-like movement was laterally confined and channelized into the main gullies, reaching the downstream area with a maximum accumulation height of 2.37 m. In contrast, the second scenario, indicative of a potential rock avalanche, was not laterally confined. Its propagation path was curved, rapidly remobilizing material deposited across slopes during its downhill movement, with a maximum accumulation height of 18.4 m. This simulation also provided insights into the potential post-failure impacts on the downstream areas, suggesting the possibility of river obstruction and the subsequent formation of a new lake upstream of the Sangro River. Moreover, an attempt was made to hypothesize potential triggering mechanisms by analyzing the spatio-temporal patterns of rainfall and earthquakes. This analysis linked the first landslide scenario (debris flow-like movement) to potential heavy rainfall events exceeding 50 mm/day (i.e., ~95 mm of rainfall in 48 h, as reported by Calista et al. [37]). For the second scenario (rock avalanche-like movement), strong earthquakes (Mw > 5.0) can be considered as possible trigger mechanisms in accordance with literature-documented earthquake-induced landslides [111] and studies about the triggering of potential landslides based on seismic hazard [108].

This study provides clues about the combination of morphometric analysis and geomorphological constraints in assessing potential landslide scenarios. The resulting data provide a foundation for forward-looking geomorphological studies aimed at anticipating potential impact areas and run-out distances of landslides (e.g., debris flows and/or rock avalanches) in high mountainous regions in order to foresee hypothetical scenarios and potentially prevent catastrophic environmental consequences, as recently happened in Switzerland (https://www.unesco-floods.eu/landslide-catastrophe-in-blatten-central-switzerland/; accessed on 25 September 2025) and in Northern Italy (https://tg24.sky.it/cronaca/2025/06/16/frana-cadore-oggi; accessed on 25 September 2025). Moreover, this could be particularly relevant in catchments without past event data, where back-analysis cannot support run-out modeling, but a preventive geomorphologically based study may highlight priority advice to support evidence-based decision-making regarding investments in Early Warning Systems, preventive strategies, impact mitigation, and engineering interventions.

Finally, this work provides a critical and innovative foundation for advancing future developments in geomorphological hazard studies, since foreseeing the failure of important unstable volumes is a major concern in mountainous areas. Hence, key directions for future research could be represented by: (i) employ of remote sensing techniques to support geomorphological field surveys (e.g., LiDAR or Laser scanner for characterizing rockfall events, Ground-Based InSAR for monitoring slow and/or deep-seated rockslide movements, UAV-based surveys to gain enhanced spatial and temporal data coverage, etc.), (ii) expand the data on the regional climatic setting to better investigate future rainfall variability (e.g., improved network of rainfall stations, regional rainfall thresholds and nowcasting models, etc.), (iii) implement a regional-scale methodological approach to systematically define landslide critical areas starting from the configuration of hazard protocols (i.e., debris flow susceptibility mapping) not yet developed for the Central Apennines, and (iv) provide a scientific basis to effectively inform citizens and interested stakeholders about multi-hazard scenarios and/or cascading events, in order to promote land management decisions at both regional and catchment scales in a changing environment.