Climate change is increasing the intensity and frequency of storms, floods, and landslides in the Nordic region, making linear infrastructure such as roads, railways, and power grids increasingly vulnerable. As safety and maintenance challenges intensify, innovative solutions are required to enhance resilience to natural hazards.
The NordicLink project (https://www.nordiclink.no/), 2020-2023, aimed to safeguard Nordic infrastructure against natural hazards through improved risk assessments and climate adaptation solutions. This study explores the potential for increased use of nature-based solutions (NbS) for linear infrastructure in rural areas. The study is based on a survey among the key owners of roads, railways, and power grids in the Nordic region, with the goal of identifying which natural hazards cause the greatest concern in a future climate, and understanding what information and documentation are needed to increase the use of NbS in rural areas.
Flooding, erosion, landslides, and rockfalls were identified as the most significant natural hazards. These results formed the basis for a NbS review with a specific focus on linear infrastructure in the Nordic Region.
Despite few examples on the use of NbS directly along roads, railways and power grids in the Nordic region, several solutions have the potential for implementation in these areas. Based on Nordic and international examples, we have developed an overview of NbS options suitable for linear infrastructure (Capobianco et al., 2022). This overview provides quick and easy access to NbS, categorized into green, blue, blue-green, and hybrid measures, and is supported by case studies from Norway and Sweden.
This review highlights both opportunities and challenges in mainstreaming NbS. Barriers such as limited expertise, spatial and climatic constraints, and path dependency on adoption of traditional infrastructure must be addressed. Moreover, the study highlights the need for standardization, European guidelines, and technical manuals to increase the use of NbS among infrastructure managers. Additionally, the many co-benefits of NbS - such as carbon sequestration, increased biodiversity, and ecosystem services – should be integral to the decision-making process.
This study contributes to a better understanding of NbS as potential measures to mitigate natural hazards related to Nordic infrastructure networks. By bridging knowledge gaps and providing feasible recommendations, it aims to support infrastructure managers and policymakers in adapting to the challenges posed by a changing climate.
References
Capobianco, V., Palau, R. M., Solheim, A., Gisnås, K., Gilbert, G., Danielsson, P., & van der Keur, P. (2024). The potential use of nature-based solutions as natural hazard mitigation measure for linear infrastructure in the Nordic Countries. Geoenvironmental Disasters, 11(1), 27. https://doi.org/10.1186/s40677-024-00287-4
How to cite: Capobianco, V., Palau Berastegui, R. M., Gisnås, K., Gilbert, G., and Solheim, A.: Enhancing Nordic infrastructure resilience via Nature-based Solutions: a review , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18813, https://doi.org/10.5194/egusphere-egu25-18813, 2025.
Optical fiber technology has emerged as a remarkable tool for groundwater monitoring. It provides high-resolution spatial and temporal data alongside exceptional sensitivity. Increasingly applied to monitor groundwater parameters such as pressure, temperature, flow, and contamination levels, this technology provides a comprehensive framework for real-time hazard assessment and risk management by integrating geotechnical and environmental variables. This study focuses on the San Lorenzo tunnel, a site characterized by significant water inflows that pose substantial hydrogeological challenges. The primary objective is to monitor these inflows closely and develop effective risk mitigation strategies. Preliminary investigations have shown that the rock mass enclosing the tunnel is highly fractured, resulting in substantial water ingress, particularly during heavy rainfall. While water in the tunnel is well-documented, the precise localization and timing of these inflows remain inadequately understood. Distributed Temperature Sensing (DTS) was employed to address these gaps to monitor water inflows and temperature variations along approximately 700 meters of the tunnel. Temperature data were combined with conductivity measurements to infer the origin of the aquifers. Initial findings suggest the presence of at least two independent aquifers, potentially fed by a common upstream source. Three types of optical fibers were installed along the tunnel. The function of these fibers is to detect both the presence and temperature of inflows of water that are intercepted and channeled into conduits. This study aims to detect and assess the location of inflows along the tunnel, temporal and spatial evolution of the water accumulation and discharge associated with external meteorological events. By correlating these observations with environmental variables such as rainfall, snowmelt, groundwater levels, and the discharge of nearby springs, we seek to refine the hydrogeological conceptual model and evaluate the feasibility of extending the draining tunnel as a mitigation measure. This research demonstrates an innovative application of fiber optic technology to monitor subsurface water flow. It contributes to hydrogeological risk mitigation in the San Lorenzo tunnel and advances our understanding of groundwater dynamics in complex fractured rock environments.
How to cite: Ballaera, A., Fullin, N., Marcato, G., Schenato, L., Vorlicek, L., and Borgatti, L.: Distributed Temperature Sensing for hydrogeological risk mitigation in the San Lorenzo tunnel, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5973, https://doi.org/10.5194/egusphere-egu25-5973, 2025.
Nature-based slope stabilization offers a sustainable solution to enhance the climate resilience of long linear infrastructures in Thailand's changing climate. This approach integrates local species such as vetiver grass with biochar-amended soil, erosion control blankets, capillary barrier systems, and flexible bioengineering structures—including vegetated flapped soil bags and micro screw piles. This combination effectively improves erosion control, slope stability, and movement tolerance while fostering vegetation growth and promoting biodiversity.
However, the adaptive and continuously growing nature of these living systems necessitates in-depth investigation of their mechanical and hydraulic behaviours. This study emphasizes the critical role of IoT-based monitoring systems in delivering early landslide warnings and assessing the performance of nature-based slope stabilization. Key parameters include pore-water pressure, suction, slope deformation which are then used to estimate the performance metrics for geotechnical stability and water demand.
Field data from various bio-stabilized slopes across Thailand—collected through tensiometers, tiltmeters, inclinometers—demonstrate the system's efficacy. The integration of advanced technologies, such as remote sensing and NASA's Soil Moisture Active Passive (SMAP) mission, is also discussed, highlighting future research directions in enhancing slope stability and resilience. Potential carbon credit gains are also discussed by means of root mass measurement and evapotranspiration flux.
How to cite: Jotisankasa, A., Praphatsorn, W., Tanyacharoen, K., Siriyakorn, V., Nishimura, S., Sanukool, W., Sukjaroen, B., and Thiampak, S.: Smart IoT Monitoring System for Nature-Based Slope Stabilization, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5326, https://doi.org/10.5194/egusphere-egu25-5326, 2025.
Since the early 2000s, advancements in remote sensing technologies have enabled the acquisition of increasingly extensive and sophisticated datasets. These technological advances emphasize the critical need for effective and efficient methods of data communication and visualization. This study examines the uncertainties inherent in model’s reconstruction and demonstrates how mixed reality (MR) systems can be an important tool in address complex geological challenges by enabling the visualization of intricate datasets with important detail and user engagement.
This research focuses on the challenges associated with creating true digital twins and the application of MR in visualizing multi-sensor remote sensing and monitoring data. The study uses the CNR ID 3 landslide in the Friuli Region (UD) as a test site, using decades of investigation and monitoring data. A conceptual workflow is presented, detailing the processes of data retrieval, interpretation, and landslide morphology reconstruction, culminating in final visualization through MR headsets.
These innovative tools have the potential to significantly improve the capacity of local authorities and stakeholders to comprehend complex spatial interactions. By fostering collaboration with scientists, they facilitate more informed and effective decision-making processes, considering the unknowns properly.
*financed by the European Union, Next Generation EU, Mission 4 Component 1 CUP B53D23006960006
How to cite: Fullin, N., Ballaera, A., Donati, D., Lambertini, A., Festi, P., Marcato, G., and Francioni, M.: Can we still talk about digital twins in engineering geology? An overview to the Passo della Morte (UD) landslide and mixed reality application. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6332, https://doi.org/10.5194/egusphere-egu25-6332, 2025.
Abstract
Current research interest in geotechnical design for climate change adaptation focuses on
utilizing waste materials for slope stability against rainfall-induced failures. Therefore, steel
slag and recycled concrete were integrated into the retaining wall, known as the GeoBarrier
system (GBS), to prevent such failures. The present study investigated the feasibility of steel
slag as a coarse-grained material and recycled concrete as a fine-grained material within
GBS. Index properties, soil-water characteristic curves, permeability functions, and
unsaturated shear strength parameters of steel slag and recycled concrete were determined via
comprehensive experimental works. Numerical assessments of the rainfall infiltration into the
slope and the stability of the slope under rainfall conditions were accomplished using the
SEEP/W and SLOPE/W analysis tools, respectively. According to the findings, no
breakthrough into the steel slag was observed inside the GBS. Based upon the changes in the
pore-water pressure and the factor of safety (FOS) versus time graphs, steel slag and recycled
concrete were found to be suitable for use as coarse- and fine-grained layers of the GBS to
minimize slope rainwater infiltration and improve the FOS of a slope with a height of 10 m
and an inclination of 70°, respectively.
Keywords: GeoBarrier system (GBS); rainfall; slope stability; unsaturated soil; waste
materials
How to cite: Abishev, R., Satyanaga, A., Moon, S.-W., and Kim, J.: GeoBarrier System incorporating Recycled Concrete and Steel Slag for Slope Protection, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-616, https://doi.org/10.5194/egusphere-egu25-616, 2025.
Earthen levees are one of the main structural measures against flooding in floodplain areas; however, these structures can fail due to different mechanisms. From the risk point of view, the construction of embarkments might paradoxically increase the overall risk because of a general decrease in flood hazard perception by the exposed population and urban planner (Castellarin et al., 2011). For this reason, ample research has been focused on studying the physical process affecting the levees during a flood event, such as overtopping and seepage/piping (Deverel et al., 2016; Palladino et al., 2019). Specifically, the piping process is very hazardous because it is not openly visible and, therefore, is hard to identify before the failure. Nevertheless, evaluating the vulnerability to seepage for different flood events affecting the earthen levee is fundamental to support territorial planning and risk management in quasi-real-time. In this context, the present work proposes a procedure to calculate the correlation between the probability of levee failure due to seepage process and the probability of occurrence of the flood event affecting the embankment. The vulnerability to seepage is quantified by identifying the saturation line location in the levee through the a two-dimensional numerical model SEEP/W. The analysis is carried out for flood events characterized by a different probability of occurrence estimated by applying a procedure based on stochastic generation of precipitation and temperature time series and continuous hydrological modelling. The proposed procedure is applied to an experimental levee located along the Tatarena stream, in central Italy. The results show that, as expected, the vulnerability increases while the magnitude of the flood increases, i.e. the probability of occurrence decreases, with increments in the range 5-10% for flood duration between 12-24 hours. In particular, 48 hours lasting flood waves are identified as the ones producing a huge increase of the levee vulnerability that is found to rise from 35% to 75%.
Castellarin, A., Di Baldassare, G., Brath. (2011). A floodplain management strategy for flood attenuation in the River Po. River Res. Appl. 27 (8), 1037–1047.
Deverel, S. J, Bachand, S., Brandenberg, S. J, Jones, C. E, Stewart, J. P, & Zimmaro, P. (2016). Factors and Processes Affecting Delta Levee System Vulnerability. San Francisco Estuary and Watershed Science, 14(4). doi: https://doi.org/10.15447/sfews.2016v14iss4art3.
Palladino M.R., Barbetta S., Camici S., Claps P., Moramarco T. (2020). ‘Impact of animal burrows on earthen levee body vulnerability to seepage’, J Flood Risk Management.2020;13 (Suppl. 1): e12559, https://doi.org/10.1111/jfr3.12559.
How to cite: Barbetta, S., Bonaccorsi, B., Ciabatta, L., Dionigi, M., and Aronica, G. T.: On the correlation between earthen levees' vulnerability to seepage and flood events probability of occurrence, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8173, https://doi.org/10.5194/egusphere-egu25-8173, 2025.
In a climate-changing world, flood events represent one of the most impactful natural hazards, causing severe damage to people and infrastructures. Railway systems are critical infrastructures, susceptible to both structural damage and service disruptions. This study leverages a methodology capable of identifying and classifying paths along the railway system that are vulnerable to fluvial flood hazard and debris-flows. The methodology adopted is DEM-based and suitable for large-scale applications. We hereby focus on Italian Railway Network (IRN) and we consider three flood hazard scenarios, H1 (return period, Tr, up to 500 years), H2 (Tr = 100-200 years) and H3 (Tr = 20-50 years), as defined by the EU Flood Directive and the National Flood Risk Management Plans (FRMP). More specifically, the official FRMP data with national coverage and updated to 2020 are here employed. Across Italy, 26%, 19% and 10% of the IRN is exposed to low, medium and high hazard scenarios (H1, H2 and H3, respectively). To analyze this exposure, we discretize the railway system into sections (average length of 2.53 km) and assess their interaction with flood hazard maps. For each flooded stretch, we characterize the upstream basin using key hydrological parameters, including time of concentration, sub-basin area, river slope, and the presence of debris-flows, as influenced by topography-related triggering thresholds. Based on these parameters, we identified three distinct flood types affecting railroad segments: Very Steep River (VSR) portions characterized by steep slopes and fast hydrological response, Rapid River (RR) stretches with fast-responding watercourses, and Slow River (SR) sections. Each type includes a debris-flow classification determined by the contributing basin's morphological characteristics. The analysis of these flood types reveals that RR floods are predominant, representing 67% of the analyzed flood-prone sections, while SR and VSR floods account for 20% and 13%, respectively. A nationwide dataset is compiled, processed and analyzed in order to provide a comprehensive overview of the IRN affected by floods. This analysis represents a significant step forward in enhancing our understanding of flood dynamics and exposure analysis of railway infrastructure, thereby contributing to more informed decision-making processes in flood risk management and disaster mitigation efforts.
How to cite: Lelli, G., Ceola, S., Domeneghetti, A., and Brath, A.: Rail2Flood: A nationwide classification of floodhazard exposure along the Italian Railway Network, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-874, https://doi.org/10.5194/egusphere-egu25-874, 2025.
River crossings are vulnerable to extreme flood events, which pose significant risks to both linear infrastructure functioning and surrounding communities. The proper functioning of bridges is crucial for preventing cascading effects on populations, ensuring the mobility of emergency response teams, and facilitating the evacuation of residents during critical events. As vital links between communities on opposite banks of the river, bridge safety has significant implications for social and economic stability.
Hydraulic phenomena account for over 50% of bridge failures (e.g. Xiong et al., 2023), and scouring around piers and abutments always causes serious damages if adequate foundation depth is not provided in the design. Lacks in scientific and technical knowledges have led in the past to inadequate piers and foundations, and this issue, combined with the increased frequency of hazardous events due to the climate change, amplifies the risk of failure.
A robust prediction of scour evolution up to its maximum depth is fundamental for understanding and forecasting bridge failures, as well as for properly managing infrastructure in the context of climate change. Here, the physical processes governing scour evolution, specifically the temporal behavior of flow field and shear stress, have been thoroughly analyzed by combining physical modeling of sediment-flow-structures interaction with numerical simulations.
The experiments have been developed in a rectangular flume 1 m wide and 15 m long, using quite uniform sands (median grain size d50=0.4 mm) to simulate the riverbed. Experiments of different duration were developed under steady state clear water conditions and adhering to Shields similitude to obtain the scour evolution over time around circular piers. Numerical simulations were developed using 3D CFD software to accurately reproduce the coherent turbulent structures around the pier at scour depths obtained from physical experiments.
This approach, combining and interconnecting physical and numerical experiments, enhances our understanding of how climate change and the consequent increase in flood event frequency impact on the temporal evolution of flow field and shear stresses as the scour progresses. This improved comprehension of the phenomena is crucial for the management of existing bridges that may have been inadequately designed in the past, as well as for the design of new structures.
How to cite: Giaretta, P. and Salandin, P.: Modeling Local Scour Dynamics to Assess Existing Bridge Resilience in the Context of Climate Change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10530, https://doi.org/10.5194/egusphere-egu25-10530, 2025.
Mountainous regions, due to their topographical characteristics, require a high density of bridges to connect road and railway infrastructures that support human activities. Climate change exacerbates the intensity and frequency of extreme events, seriously threatening bridge safety and infrastructure availability.
Among various hazards, debris flows are one of the most destructive phenomena in Alpine regions. Their destructive nature is due to the high velocities they achieve, the large volumes of sediment they mobilize, and the significant impact forces they exert on any obstacles in their path. When debris flows impact bridges, they often result in destruction. The unpredictability of these events, coupled with inadequate early warning systems and the huge amount of materials involved, frequently leads to loss of human life and significant economic damage.
Bridge piers, due to their location in stream beds, are extremely vulnerable to the impulsive nature of sediment flows and are subjected to the most severe impact forces. Understanding the thrust generated by debris flows on bridge structures is essential for designing works capable of withstanding their impact. This knowledge is crucial for defining appropriate design methodologies for bridges, accurately accounting for the dynamic forces exerted on piers.
This study presents a new experimental apparatus designed to provide accurate information on the dynamic thrust of stony debris flows on bridge piers. The debris flow is simulated in a tilted canal measuring 3 m in length and 0.3 m in width. A model bridge pier and associated impulsive force measuring equipment are installed at the channel's end section. Strategically placed sonar sensors along the canal, combined with pressure sensors and load cells, enable a comprehensive characterization of the debris flows that is triggered by suddenly releasing a pre-set water discharge onto a layer of previously saturated erodible material.
The results from the physical model experiments enabled a systematic study of the magnitude of dynamic forces acting on piers of various shapes and how these forces are influenced by the different physical parameters characteristic of debris flows. Analysis of the collected data provided insights that allow for an assessment of the predictive formulas proposed in the literature. This leads to a deeper understanding of the risk of mountain bridge damage, which is increasingly affected by debris flows in the present context of climate change.
How to cite: Cao, A., Giaretta, P., and Salandin, P.: Predicting Mountain Bridge Damage from Increasing Frequency of Debris Flow Dynamic Impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12594, https://doi.org/10.5194/egusphere-egu25-12594, 2025.
The automatic and timely identification of mud pumping is crucial for maintaining the reliability and safety of railway systems. While current prediction models mainly focus on monitoring the dynamic responses of railway tracks, they often overlook vital geotechnical factors, such as hydrological conditions, due to the difficulty of quantifying such information. This limitation reduces the accuracy of predictions. To address this challenge, we propose a novel approach that integrates Geographic Information System (GIS) technology with in-service train vibration data to quantify hydrological variables along railway tracks. Key factors, including elevation, proximity to rivers, rainfall, sink depth, and soil types, are incorporated into a multi-channel neural network, which processes these multi-attribute data separately to enhance prediction accuracy. To improve model interpretability, we apply a Genetic Algorithm (GA) to assess the importance of hydrological factors and their correlation with the likelihood of mud pumping. Tested on real-world data from Chinese railway tracks, the model achieves balanced accuracy, demonstrating the effectiveness of combining GIS and monitoring data to reduce false positives and enhance prediction precision. Our analysis reveals that rainfall is the most influential factor, with groundwater-related variables having a greater impact than surface water. These findings offer valuable insights for infrastructure managers, enabling the identification of vulnerable track sections and facilitating more targeted maintenance and optimized substructure design at the network level.
How to cite: Geng, X.: A Data-Driven Approach for Predicting Mud Pumping in Railway Tracks Using GIS and In-Service Train Vibration Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5111, https://doi.org/10.5194/egusphere-egu25-5111, 2025.
Large-diameter gravity aqueducts play a crucial role in urban water supply, industrial transport, and irrigation, yet they are often subjected to complex flow conditions that can compromise both efficiency and structural integrity. Accurate and real-time flow monitoring is essential for optimizing hydraulic performance and ensuring infrastructure safety. However, conventional techniques like ultrasonic sensing are limited in providing continuous, real-time data on flow states. This study introduces the use of Distributed Acoustic Sensing (DAS) technology for monitoring flow dynamics along a 6 km segment of the 113.1 km Pearl River Delta Water Resources Allocation Project. To handle the large volumes of DAS data, we developed DAS-Water CNN, a convolutional neural network designed to interpret low-frequency acoustic signals and classify different water flow states and velocities. This method enables distributed, real-time monitoring, significantly improving the intelligence and efficiency of urban water management. Our findings demonstrate that DAS, combined with advanced AI algorithms, accurately identifies flow patterns, locations, and velocities, leading to enhanced operational efficiency, reduced maintenance costs, and valuable data support for the advancement of smart water supply systems.
How to cite: Tan, D.-Y., Tang, Z.-Y., Wang, J., and Zhu, H.-H.: Deep Learning-Driven Distributed Acoustic Sensing for Real-Time Flow Dynamics Monitoring in Large-Diameter Aqueducts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2699, https://doi.org/10.5194/egusphere-egu25-2699, 2025.
European Ground Motion Services (EGMS) provides Europe-wide SAR interferometry results, enabling the identification of previously unknown ground motion active areas. In Monóvar, a town in southeastern Spain, an active area has been identified with an approximate length of 450 m and a width of 650 m, affecting an urban area of approximately 6.5 ha. The site exhibits maximum east-west and vertical displacement rates of 23.8 and 64.6 mm/year, respectively, between 2019 and 2024. The geology of the area is characterized by Triassic evaporitic terrains composed of red sandy clays, silts, and marls with gypsum. The western sector of the active area, which is not urbanized, is predominantly marked by massive gypsum reliefs with smooth topography and maximum elevations of 393 m a.s.l. This sector also contains ancient gypsum quarries, exploited artisanally in the past, as well as some landfills. In contrast, the eastern sector, with a maximum elevation of 377 m a.s.l., is mostly urbanized. Borehole data indicate the presence of anthropogenic fill, used for grading and leveling the terrain, with thicknesses exceeding 6 m in certain locations of the eastern sector. The two sectors are separated by an urbanized ravine with a SE-NW orientation. Beneath the fill materials, the underlying strata consist of clays, limestones, and massive gypsum. To the north lies the CV-83 road, with elevations ranging from 375 to 358 m a.s.l. within the affected area, as well as the Charco barranco, a natural ravine crossing the north region from SE to NW. A field campaign conducted in the area identified widespread damage to roads, walls, and buildings. This damage is predominantly concentrated within the urban area, although some tension cracks have also been observed in the gypsum formations in the western sector. Several buildings in the urban area have been underpinned, repaired, or demolished due to ground movement. Based on the available data, the movement is associated with a very slow landslide, termed the Borrasca Landslide, which is divided into two main bodies by the urbanized ravine. The western body exhibits maximum eastward and vertical displacement rates of 14.7 and 64.6 mm/year, respectively, while the eastern body presents maximum rates of 23.8 and 45.5 mm/year, respectively. The failure surface of the landslide develops along the evaporitic terrains, causing significant damage to the urban area and the CV-83 road, including a bridge. Further investigations are needed to enhance understanding of the landslide (e.g., failure surface depth, triggering factors) to inform the local authorities and to develop appropriate corrective measures for its stabilization.
Acknowledgements
This project is funded by the ESA-MOST China DRAGON-6 project (Grant No. 95355) and by the funding scheme of the European Commission, Marie Skłodowska-Curie Actions Staff Exchanges in the frame of the project UPGRADE – GA 101131146.
How to cite: Tomás, R., Pastor, J. L., Riquelme, A., Cano, M., and Navarro-Hernández, M. I.: Preliminary investigation of an urban landslide in evaporitic terrains detected by European Ground Motion Services in Monóvar, SE Spain, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2885, https://doi.org/10.5194/egusphere-egu25-2885, 2025.
The Chanchán River basin, located in the Chimborazo province in the Northern Andes of Ecuador, is affected by several factors contributing to slope instabilities. The high frequency of Landslides results in significant social and economic impacts. Hereby, two extraordinary landslides have occurred recently, being firstly in the Chunchi canton in 2021, affecting 704 people and damaging linear infrastructure such as two bridges and road sections, and secondly in the Alausí canton in 2023, causing even 75 casualties, while damaging first- and second-order roads, and collapsing 427 m of railway. In the present research, landslide geomorphology and ground lithology were studied in the field and using geophysical techniques. Potential triggering factors were also evaluated through the analysis of the rainfall data from the last decade, recent seismic events, and changes in land use within the study area. All these conditions allowed to focus on the similarities between the two catastrophic events.
The results yielded that the Chunchi landslide was a combination of rotational, creep, and flow failure types. In this case, the soils involved were superficial a superficial layer of silty sand and a deeper one of clayey sand, while the water table was detected at a depth of approximately 4 m due to recent rainfall. Conversely, the Alausí landslide was of the rotational type, primarily affecting colluvial soils and secondary volcanic lahars up to 4 m depth, volcanic lahars with blocks of dacitic or andesitic lavas from 4 to 13 m and further below altered volcanic tuffs.
After studying the potential triggering factors, the seismic effect was dismissed in both cases, as no significant seismicity occurred in the areas shortly prior to the landslides. In the Chunchi landslide, the rainfall registered before the event is similar to those of previous years, although the infiltration of water due to the agricultural use of the soil and deforestation may have contributed to the event. Alternatively, the most probable triggering factor of the Alausí landslide was the accumulated rainfall, as an increase of up to 600% was recorded in the three months preceding the event, compared to the average values of recent years.
Extreme climate events are expected to become more intense in the coming years due to factors such as climate change. This, on its own or combined with potential changes in land use, may be able to result in an increase of the frequency of landslide events in the Chanchán River basin.
Acknowledgements
This work is supported by the funding scheme of the European Commission, Marie Skłodowska-Curie Actions Staff Exchanges in the frame of the project UPGRADE – GA 101131146.
How to cite: Macias, L., Pastor, J. L., Bonifaz, H., Quinonez Macias, M., and Toulkeridis, T.: Recent landslides in the Chanchán River basin (Ecuador) – The case study of Chunchi and Alausí., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3804, https://doi.org/10.5194/egusphere-egu25-3804, 2025.
Landslide inventory maps constitute the primary level of information in risk prevention studies and stability analysis. The Dominican Republic, particularly the Barahona province, is exposed to various geological hazards such as slope movements due to its topographic, geological and climatic characteristics, as well as the effect of human activities. These natural phenomena directly and indirectly affect the population and their economic activities, which are essential to their development. The objective of this research is to determine the types of mass movements that directly impact the main roads of Barahona (the Enriquillo Highway and the Barahona-Paraíso Highway), the primary conditioning and triggering factors, and the resulting damage to road infrastructure. Through photointerpretation and fieldwork, a total of 22 slope movements were identified. Of these, 13.64% correspond to landslides, 68.18% to flows, 13.64% to falls, and 4.54% to topples. Most of these movements occur in geological materials of sedimentary origin, such as shales, limestones, marls, sandstones, conglomerates, and alluvial and colluvial deposits. Of the movements identified, 59.09% were classified as suspended, 22.73% as active, and 18.18% as inactive. The factors conditioning the occurrence of landslides are associated with the sedimentary geology that predominantly covers Barahona province, the rugged topography, and changes in land use. Meteorological events such as tropical storms and hurricanes bring intense and prolonged torrential rains. These precipitations, combined with active tectonics, are the main triggering factors. Finally, the damage to road infrastructure results in accumulations of displaced material on the roadway, total or partial collapse of retaining, protective, and drainage structures, differential movements causing irregularities and sinking of the asphalt layer, transverse and longitudinal cracking of the roadway, gullies, and erosion in cut and fill slopes.
How to cite: Tamayo, Á., Duran, F., Pérez, M., and Pastor, J. L.: Inventory and preliminary evaluation of the factors that cause landslides and affect the road infrastructure of the Barahona Province of the Dominican Republic, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7293, https://doi.org/10.5194/egusphere-egu25-7293, 2025.
In recent years, global warming has been associated with an increasing frequency and intensity of extreme meteorological events causing severe damage to land and infrastructure, and potential harm to people. For this reason, it is crucial to develop predictive tools to support land management. In May 2023, two extreme meteorological events struck the Emilia-Romagna region of Italy in succession. The first rainfall event was associated with a limited number of landslides while the following one triggered widespread landslides of various types, leading to extensive damage and forcing the closure of hundreds of roads. The extent of the damage in the affected areas was recorded by satellite imagery captured by Sentinel constellations of the European Space Agency (ESA). By looking for cloud-free pre-event, between-events and post-events images, two study areas were chosen for the development and calibration of a physically-based Bayesian network model, incorporating prior rainfall data and soil spatial variability. The primary objective is to calibrate the model using these training images and subsequently validate it across the entire affected regions utilizing available open-source data on landslide event inventories. With a given weather forecast, the resulting output aims to pinpoint the most hazardous areas in a timely manner. This research stems from a collaboration funded through the MSCA-SE UPGRADE project (GA 101131146).
How to cite: Ceccotto, F., Zhang, S., Geng, X., Mantovani, M., and Bossi, G.: A Physically-based Bayesian Network Model for Landslide Susceptibility Updating, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8243, https://doi.org/10.5194/egusphere-egu25-8243, 2025.
Distributed acoustic sensing (DAS) has emerged as a powerful technology for monitoring seismic events with high spatiotemporal resolution. By using these detailed observations, proactive assessments can significantly enhance resilience through the optimization of management strategies for underground infrastructure and above-ground campus facilities. Recognizing the critical role that underground pipelines play in both subterranean systems and overall campus resilience, this study focuses on their continuous and long-term monitoring at Nanjing University Xianlin Campus, utilizing DAS technology. Our analysis involves the extraction and analysis of key parameters from a 3.8-kilometer-long underground fiber-optic cable array, including flow-induced vibrations, changes in natural frequency, and power spectral density. DAS recordings, which have been collected since February 2023, enable us to assess into the health status of the underground pipelines. The vibrations captured by DAS in response to flow serve as an effective tool for evaluating the drainage system’s capacity, aiding in forecasting flood hazards during extended periods of rainfall. Variations in natural frequency reveal key information about the structural integrity of pipelines, especially under heavy rainfall and seismic activity. Additionally, fluctuations in power spectral density offer both localized and comprehensive spatiotemporal assessments, guiding campus-wide resilience strategies. Key metrics are derived from DAS data to identify patterns of campus activity, informing the decision-making process for optimizing resilience strategies. These results highlight the potential of DAS for long-term, real-time monitoring, supporting enhanced resilience at scales ranging from individual campuses to entire urban environments.
How to cite: Wang, J., Zhu, H.-H., and Tan, D.-Y.: Enhancing campus resilience monitoring with distributed acoustic sensing: a case study, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10151, https://doi.org/10.5194/egusphere-egu25-10151, 2025.
Posters virtual: Wed, 30 Apr, 14:00–15:45 | vPoster spot 3
EGU25-3505 | ECS | Posters virtual | VPS13
Vulnerability quantification of roads caused by future debris flows in mountainous areasWed, 30 Apr, 14:00–15:45 (CEST) | vP3.21
Quantifying the vulnerability of roads caused by debris flows is crucial for regional hazard mitigation in remote areas. However, the changing climate has increased the uncertainties in providing reliable vulnerability assessment due to the altered pattern of rainfall. Such change has induced the increased frequency and magnitude of debris flows, impacting the safe operation of highways. In this case, a reliable method was developed to help on the improvement of vulnerability quantification with the involvement of AI and Flo-2D simulation techniques before applying this proposed framework to a case study in the Gyirong Zangbo Basin, Tibet, China. In detail, a deep learning model was developed to estimate the physical vulnerability of roads in the event of a future debris flow with the consideration of a series of factors, including spatial locations of roads to the debris-flow channel, debris-flow catchment area (Ac), length of main channel (L), topographic relief (R), mean slope of main channel (J), and rainfall (P). After that, debris-flow simulations were performed to validate the physical vulnerability assessment results, which can further benefit the accurate quantification of economic loss on a regional scale. Here, in addition to the direct loss of the damaged roads, the indirect loss caused by the damaged roads was also estimated using a complex network theoretical approach that account for regional socioeconomic development and the time needed for road restoration. Overall, this study can form part of an early warning system to assist on the effective management of debris flows on a regional scale in mountainous areas.
How to cite: Qiu, C.: Vulnerability quantification of roads caused by future debris flows in mountainous areas, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3505, https://doi.org/10.5194/egusphere-egu25-3505, 2025.
EGU25-15456 | ECS | Posters virtual | VPS13
Numerical study of 2018 Baige landslides induced geohazards chain and dynamic proessesWed, 30 Apr, 14:00–15:45 (CEST) | vP3.22
Geohazard chains in watersheds often involve a series of interconnected events, such as landslides that propagate along slopes, intrude into river channels, form landslide dams, and result in dam breaches and outburst flooding. Because the sub-processes within a geohazard chain are coupled, one or more of these events can trigger subsequent ones, leading to larger spatial and temporal scales than isolated disasters. This results in more destructive power and a wider impact area. In this study, a numerical case study focuses on the most recent geohazard chain event: the 2018 Baige landslide in Sichuan Province, China. This event can be divided into several sub-processes based on the coupling order within the chain. The first landslide formed a landslide dam, followed by another landslide at the same location, which overlapped with the first, creating a higher dam. This ultimately led to a larger-scale dam breach and outflow.
To simulate this sequence, a series of validated depth-averaged models for geohazard chains was employed, along with a standard LxF central differencing scheme to retain high resolution and avoid Riemann characteristic decomposition. The landslide propagation was modeled using a visco-inertial friction law. The numerical predictions were verified against field measurements from the literature, demonstrating the feasibility of using μ(K) visco-inertial rheology to simulate large-scale landslides and landslide dam formations. The overtopping failure of the two overlapping landslide dams and the subsequent outburst flooding were successfully simulated using the proposed model. Maximum discharge results indicate the model's capability to capture the interaction between dam breaches and outburst floods. The numerical findings, validated by existing literature, provide a reliable assessment for emergency relief and hazard mitigation. This modeling framework is expected to contribute to improved mitigation strategies for geohazard chains.
How to cite: Xie, Y., Zhou, G., Cui, K. F. E., Lu, X., and Li, N.: Numerical study of 2018 Baige landslides induced geohazards chain and dynamic proesses, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15456, https://doi.org/10.5194/egusphere-egu25-15456, 2025.
