This session aims to bring together researchers and practitioners from diverse backgrounds to:
1. Foster collaboration and networking across disciplinary boundaries
2. Encourage the exchange of theoretical insights and practical approaches to landslide investigation and mitigation
3. Promote more efficient use of limited resources for landslide risk reduction
We particularly welcome contributions on topics such as:
• Expanding the affordable use of innovative technologies for landslide detection and mapping (e.g., optical and radar satellite remote sensing)
• Advances in subsurface characterization using customized geophysical methods (e.g., electrical resistivity, seismic tomography)
• Integration of remote sensing and ground-based data for improved landslide monitoring
• Engineering geological models as integrative tools for site-specific landslide risk mitigation
• Data availability, quality issues, and handling geological uncertainty in slope stability modeling
• Approaches to slope stability analysis, from empirical methods to advanced numerical models
• Impacts of climate variability on landslide occurrence and engineered slope performance
• Low-cost, reconnaissance-level hazard assessments in data-scarce or disaster-affected regions (e.g., co- and post-seismic landslide events)
• Case histories of slope stabilization and landslide mitigation - including both successful and unsuccessful interventions - to highlight the limitations of “one-size-fits-all” solutions
• Knowledge transfer between scientists and engineers, and effective communication of landslide risk to civil protection authorities, policymakers, media, and the general public
Session sponsored by the International Association of Engineering Geology and the Environment (IAEG – https://iaeg.info)
This study presents the mechanism of a large landslide that has affected the single-track T7 railway tunnel, constructed in 1933 along the Diyarbakır–Fevzipaşa Railway line in Türkiye and predominantly used for freight transportation. Since its construction, the tunnel has suffered from persistent structural and operational problems, requiring repeated temporary remedial measures over nearly a century. The severity of the damage increased markedly following the 6 February 2023 earthquakes, ultimately necessitating a comprehensive reassessment of tunnel stability and long-term serviceability. To identify the causes of the observed damage and develop permanent engineering measures, detailed engineering geological and geotechnical investigations were performed. The investigations included the evaluation of historical documentation, systematic field observations, geotechnical drillings, in-situ and laboratory testing, and monitoring. The results of investigations showed that the tunnel is located within a large landslide mass approximately 220 m wide and 630 m long, characterized by multiple shear and fracture surfaces. The interaction between the landslide and the tunnel was further quantified using Light Detection and Ranging (LiDAR) measurements obtained from the tunnel interior. The results indicate cumulative tunnel displacements reaching up to 250 cm since construction, corresponding to an average long-term deformation rate of approximately 2.7 cm/year. Based on the landslide kinematics and stability assessments, it was concluded that the most effective long-term engineering solution was the relocation of the tunnel 130 m further into the mountain, beyond the landslide-affected zone. The new tunnel alignment was designed and constructed accordingly, and the tunnel was successfully completed at the end of May 2025 without encountering geotechnical or structural difficulties. The findings demonstrate that the long-standing problems of the T7 Tunnel were primarily caused by sustained landslide–tunnel interaction and have now been permanently resolved.
How to cite: Gokceoglu, C., Karahan, S., Posluk, E., and Buyukdemirci, F. B.: Damage Assessment of the T7 Railway Tunnel Associated with a Large Landslide: A Case from Türkiye, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9129, https://doi.org/10.5194/egusphere-egu26-9129, 2026.
Climate variability exerts a fundamental control on the timing and recurrence of rainfall-induced landslides, particularly in tropical regions characterized by deeply weathered soils, pronounced wet–dry seasonality, and sparse ground-based monitoring networks. In this context, climate variability primarily acts as a preparatory factor by regulating antecedent moisture conditions, soil suction, and seasonal hydrological states, while also modulating the frequency and intensity of rainfall events that act as triggers. Although advances have been achieved in climate science, remote sensing, and slope stability modeling, these developments remain only partially incorporated into engineering geological assessments of infrastructure slopes. This study addresses this gap by presenting a climate-informed framework that links large-scale climate variability to local hydro-mechanical slope response in tropical railway environments.
The proposed framework integrates multi-source satellite data with probabilistic and physically based analyses to assess rainfall-induced slope instability. Precipitation data were obtained from CHIRPS (0.05° spatial resolution; 1981–2023), while soil moisture was derived from SMAP products. Topography was represented by the ALOS PALSAR Digital Elevation Model (12.5 m; JAXA, 2021), and vegetation conditions were characterized using NDVI from CBERS-4A imagery acquired on 4 August 2020 (12.5 m). Landslide susceptibility along the railway corridor was mapped using a probabilistic Random Forest model and independently validated with ground deformation data derived from descending-orbit Sentinel-1 SAR images (22 May 2022–26 September 2023) processed using the SqueeSAR InSAR technique. The framework also incorporates hydro-geotechnical characterization, transient numerical modeling, and UAV-based LiDAR surveys.
At the slope scale, the framework emphasizes unsaturated soil behavior, recognizing rainfall infiltration and suction loss as dominant triggering mechanisms in tropical soils. Field and laboratory investigations define soil–water retention characteristics and hydraulic conductivity functions, enabling representation of seasonal moisture dynamics. These parameters are incorporated into coupled transient seepage and slope stability simulations driven by long-term satellite-based rainfall time series. Furthermore, the simulations account for soil–climate interactions by explicitly considering evapotranspiration effects and antecedent moisture conditions, capturing the interactions between climate variability, infiltration processes, and mechanical response.
The susceptibility analysis demonstrates the effectiveness of the Random Forest model in identifying zones prone to shallow landsliding along the railway, with strong agreement between predicted high-susceptibility classes and observed slope instabilities. These results support the selection of critical slopes for detailed numerical investigation. Subsequent coupled seepage and slope stability simulations reveal strong sensitivity of slope stability to rainfall intensity and antecedent moisture conditions, with distinct responses to daily extreme rainfall events and multi-day cumulative rainfall. Seasonal and interannual variability associated with ENSO phases modulates pore-pressure evolution and safety margins, producing periods of increased vulnerability even in the absence of significant long-term precipitation trends.
By coupling climate signals, hydrological processes, and mechanical behavior, the proposed framework provides a practical pathway for integrating climate information into engineering geological assessments. The approach is particularly suited to data-scarce regions such as the Amazon, where satellite observations can partially compensate for limited in situ monitoring, supporting improved slope susceptibility evaluation and climate-informed decision-making.
How to cite: Goulart Fiscina, L. F., Pacheco Silva, F., Pacheco Quevedo, R., Glade, T., and Massao Futai, M.: Climate variability as a driver of slope stability: integrating satellite data and hydro-geotechnical modeling for tropical railway corridors., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21499, https://doi.org/10.5194/egusphere-egu26-21499, 2026.
Earthquake-trigerred landslides (ETLs) cause a significant portion of total earthquake losses in mountainous regions, threatening both financial stability and community sustainability. For nearly 60 years, the Newmark displacement (ND) method has been widely used to estimate earthquake-induced slope deformation. However, most existing ND models are based on regressions developed from specific earthquakes or datasets, which limit their applicability across different tectonic and climatic settings.
To address this gap, we introduce the Site-Adaptable Newmark Displacement (SAND) approach, a flexible, knowledge- and data-driven method designed to work across a wide range of tectonic environments and spatial scales. SAND assumes a quadratic relationship with peak ground acceleration (PGA) and a non-linear relationship with critical acceleration (Ac) and progressively incorporates regional and site-specific factors such as fault focal mechanisms, hanging-wall and footwall effects, topographic amplification, terrain roughness, and climate-related wetness conditions.
We validated the SAND approach against several catastrophic events, including the 2022 Ms 6.8 Luding earthquake (China), the 2010 and 2021 Haiti earthquakes, and major events in Taiwan (1999) and Lushan (2013, 2022). Our comparative analysis shows that older, site-specific equations, such as Miles and Ho (1999), often outperform newer modified versions that overemphasize slope stability at the expense of seismic intensity attenuation. Specifically, in the Luding case, incorporating slope orientation significantly improved predictive power, accounting for the preferential distribution of landslides on E-, SE-, and S-facing slopes.
Overall, SAND consistently performs better than previous regression-based models (e.g. Jin et al., 2019) in predicting landslide locations. Because this method does not require a pre-existing landslide inventory, it can be implemented immediately following an earthquake using only magnitude, epicentre, and focal mechanism data. This can allow for the rapid prediction of shallow ETLs to support emergency rescue efforts and prioritize resource allocation in high-risk zones.
How to cite: Djukem, D. L. W., Fan, X., and Havenith, H.-B.: Effective regional prediction of earthquake-induced landslides: The Site-Adaptable Newmark Displacement (SAND) approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3565, https://doi.org/10.5194/egusphere-egu26-3565, 2026.
Catalogues of landslides show that many slopes in mountainous regions have experienced extensive failures over time, yet their origin remains poorly constrained. This knowledge gap limits our ability to assess present‑day slope hazard levels and to incorporate prehistoric failures into engineering‑geological models used for risk mitigation.
This study builds upon the work of Baroň et al. (2024), who investigated the triggering mechanisms of large landslides, with a focus on distinguishing seismic‑induced failures from those initiated by intense rainfall. We present a newly developed automated morphometric tool for calculating the Index of Potential Trigger (IPT), designed to classify landslides using two input datasets: a digital elevation model (DEM) and a polygonal landslide inventory.
The results show that the automated IPT method closely reproduces the manual classifications reported by Baroň et al. (2024), with a clear distinction between rainfall- and earthquake-triggered landslides. The automated IPT provides a reproducible, low‑cost tool for regional‑scale investigations, supporting more efficient use of resources in landslide risk reduction. By integrating morphometric analysis with established engineering-geological knowledge, the approach contributes to bridging the gap between scientific advances in landslide process understanding and practical tools for engineering geology and risk mitigation.
How to cite: Loche, M., Pisano, L., Bucci, F., and Baroň, I.: The Index of Potential Trigger (IPT): An Automated Morphometric Tool for Classifying Landslide Triggers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4272, https://doi.org/10.5194/egusphere-egu26-4272, 2026.
The Scottish Road Network Landslides Study (SRNLS) was instigated by Transport Scotland in response to a series of rainfall-induced debris flow events that compromised the operation of the Scottish Trunk Road Network (TRN) in August 2004. A fast-paced working group formed a plan that included regional susceptibility and hazard assessment, risk ranking, and the determination of appropriate risk reduction measures, reporting in 2008.
The work programme subsequently evolved to include quantitative risk assessment to determine the fatality risk of road users and users of adjacent recreational areas, economic impact assessment to determine financial impacts of closures/traffic restrictions, the implementation and assessment of innovative monitoring techniques and risk reduction measures and strategies, triggering mechanisms, and protocols for network operation during periods of elevated hazard/risk.
The SRNLS working group was comprised largely of consultants, with the author and the British Geological Survey bridging the gap between practice and academia, a role that might be described as that of a ‘pracademic’. This, against a background of significant UK landslides capability, was considered necessary due to the short duration of the first phase of the project, the lack of significant knowledge gaps, and the continuous input required over sustained periods, all of which were considered better-suited to a consultancy model.
Where interaction and cooperation with academia was fruitful was in the EU FP7 SafeLand project, which helped generate many of the ideas that the author later promulgated to Transport Scotland and formed much of the post-SRNLS work. Successful contributions from academia also included a funded PhD at Northumbria University that contributed to the understanding of event triggers and runout, while subsequent projects in cooperation with Northumbria and Newcastle Universities contributed to innovative monitoring techniques (including GB-SAR, micro-seismic, time-lapse imagery). Projects were funded by both Transport Scotland and UK Research Councils, with some internal university funding also utilised.
There is no doubt that academic contributions to the work of Transport Scotland in the landslides arena have been both significant and beneficial. However, the differing priorities of the academic, consultancy and road authorities should be understood and considered when allocating tasks and commissioning projects. As a result, the projects allocated to academic partners have avoided anything that is urgently needed in order to ensure the continued effective operation of the TRN, but have been carefully selected to supplement and add to the knowledge of, and techniques available to, practitioners involved in such work. As a broad and rather general observation, it is tentatively considered that the most successful projects were those that funded university inputs via more traditional means without the inevitable contractual arrangements involved in contracting to a government body. This seems to reflect the differing demands on the time of academics and practitioners and, in particular, the often-heavy teaching loads of some academics.
The observations made in this short note and the associated presentation are based on the author’s experience of working with academics in the UK, continental Europe, and beyond. No criticism of any individual or group is made, intended or implied.
How to cite: Winter, M.: Academic-Industry Collaboration for Landslides Research and Applications in Scotland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5707, https://doi.org/10.5194/egusphere-egu26-5707, 2026.
Located above the Lütschine Valley, the Grätli landslide endangers parts of the municipality of Gsteigwiler. Since 2021, in situ and remote sensing monitoring has shown frontal acceleration of an unstable rock mass of approximately 500,000 m³.
First, hazard analysis results were obtained using scenario-based process modelling, calculated with RAMMS:debrisflow and three-dimensional depth-resolved MPM simulations. The results indicate that the primary rock avalanche is expected to cause little to no damage to infrastructure. However, subsequent debris flows may impact buildings and critical infrastructure. The modelling results will be integrated into the existing hazard map, potentially affecting land-use planning decisions.
Second, a risk analysis revealed unacceptable risk levels for several properties as well as protection deficits affecting infrastructure. A safety concept involving evacuation following an initial rock avalanche could reduce the risk to an acceptable level. To address economic losses and infrastructure availability, options for structural protection measures are being evaluated in an ongoing study.
This natural hazard mitigation project, commissioned by the municipality, illustrates how the Swiss Integrated Risk Management (IRM) policy can be successfully applied as a framework to prevent major damage from cascading mass movements. Private-sector consultants and communal and cantonal authorities collaborate to address three key questions: (1) What can happen? in terms of hazard analysis; (2) What is allowed to happen? from a policy-based risk perspective; and (3) What needs to be done? by all stakeholders to mitigate unacceptable risks.
How to cite: Raemy, V., Cicoira, A., Brönnimann, C., Hitz, O., and Gaume, J.: Cascading processes from the "Graetli" landslide - a case study of applied Integrated Risk Management in Gsteigwiler (Switzerland), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7252, https://doi.org/10.5194/egusphere-egu26-7252, 2026.
On April 3, 2024, an earthquake of Richter local magnitude (ML) 7.2 struck eastern Taiwan, centered near Shoufeng Township, Hualien County. The maximum intensity reached level 6+, recorded in the Heping area.
The resulting geological instability was subsequently mobilised by the hydrometeorological impacts of Typhoon Wipha in July 2025. On July 25, a massive slope failure—estimated at approximately 290 million m³—occurred in the upper reaches of the Mataian River (TWD97/TM2 zone 121 coordinate system; EPSG:3826; X: 280138, Y: 2621774). This event formed a large-scale landslide-dammed lake with a dam height of 200 m and a potential storage capacity of 91 million m³. The lake was first identified by satellite monitoring on 26 July, prompting an immediate multi-agency emergency response.
During the response, rapid engineering-geomorphological interpretation of the landslide source area and dam morphology was used to define priorities for subsequent monitoring and breach-scenario analysis. We present an integrated GIS-based decision-support framework designed to connect research outputs with time-critical disaster management. The workflow uses multi-temporal Sentinel-1 (SAR) and Sentinel-2 (optical) imagery to track dam–lake evolution and geomorphic change, and it cross-validates remote-sensing interpretation with real-time water-level observations from an in situ gauge installed by a National Cheng Kung University team. For downstream hazard assessment, the PRISM platform (The Indigenous Platform for Risk Information and Safety Management, PRISM) ingests independent hydraulic simulations provided by National Taiwan University and National Yang Ming Chiao Tung University to build plausible breach-inundation scenarios.
By spatially intersecting simulated flood extents with address-level geocoded household data, we identify 1,837 threatened households. In addition, telecom signalling population statistics enable dynamic exposure estimates for 8,000 individuals within the risk zone, supporting evacuation prioritisation and providing a high-fidelity basis for evacuation decisions.
This case study demonstrates how multi-source Earth-observation and population-scale data streams can be operationalised to manage post-earthquake cascading hazards from landslide dams, and highlights the indispensable role of multi-source data integration in mitigating complex, post-seismic cascading hazards.
How to cite: Su, W., Chen, Y., Yang, C., Chang, T., and Chen, H.: Integrating Multi-source Data for Landslide-dammed Lake Emergency Response: From Geomorphic Monitoring to Dynamic Exposure Assessment., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8892, https://doi.org/10.5194/egusphere-egu26-8892, 2026.
Rockfall hazards pose a persistent threat to mountain road safety, particularly along high-risk corridors in regions affected by frequent earthquakes and intense rainfall, where sudden slope failures directly constrain long-term road operations and place road users at risk. In many such corridors, short-term engineering mitigation is not feasible, yet road operations must be sustained over extended periods, making disaster prevention reliant on monitoring, warning, and operational control rather than structural solutions. This study presents the Daman slope, located at 49.8 km along Provincial Highway No. 7 in Taoyuan, Taiwan, as a representative case demonstrating how slope monitoring has evolved into a practical disaster prevention system under these constraints. Early monitoring efforts focused on compiling an event catalog and evaluating rockfall occurrence sensitivity derived from a microtremor system to support operational decisions, such as adjusting traffic access frequency to reduce exposure during periods of elevated activity. While this sensitivity-based approach provided an initial framework for risk management, subsequent experience showed that it was insufficient for operational decision-making when hazards were triggered by earthquakes and intense rainfall, as strong seismic motions exceeded the effective range of the microtremor-based monitoring system, while rainfall-induced conditions were associated with elevated noise levels that reduced signal reliability. Such events are characterized by abrupt onset and severe consequences, particularly when rockfalls occur during active traffic operations, leaving little opportunity for advance intervention. The limitations of prediction became evident during the 3 April 2024 Mw 7.2 Hualien earthquake, when strong ground motion triggered multiple rockfalls during seismic shaking without identifiable precursory signals; similar challenges were also observed for rainfall-related rockfalls, reinforcing the recognition that such hazards cannot be reliably forecast using sensitivity indicators alone. As a result, the monitoring strategy transitioned from an analysis focused on prediction toward a framework centered on warning and disaster prevention. The system was expanded to integrate ground motion and rainfall observations in real time, with an emphasis on identifying hazardous conditions that require immediate operational response. A standardized operating procedure has been established to ensure that monitoring information is consistently translated into warning displays and traffic management actions at the site. In current practice, warning levels displayed in the early morning are determined based on monitoring records from the preceding night, while daytime operations generally allow full access, with warning signals adjusted dynamically when monitored conditions exceed predefined thresholds. Within this framework, the core function of the system remains focused on rapid hazard recognition and warning issuance based on direct monitoring observations and predefined operational thresholds, while artificial intelligence techniques are applied in post-processing as supportive tools to refine event interpretation and improve the accuracy and consistency of the event catalog. This case highlights how slope monitoring can function as an active disaster prevention mechanism by shifting the emphasis from attempting to predict individual failures to reducing exposure and enhancing road user safety through timely warning and operational control when engineering mitigation is constrained.
How to cite: Chou, C.-H., Chang, J.-M., and Chao, W.-A.: An Operational Rockfall Monitoring Framework for Hazard Management: A Case Study of the Daman Slope, Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15758, https://doi.org/10.5194/egusphere-egu26-15758, 2026.
The stability of a slope is governed by a combination of factors, where the hydromechanical properties of the soil are the most prominent ones. The groundwater conditions in such assessments are however, by Swedish practice, generally simplified to a two-dimensional (2D) linear interpolation between measured data, although the three-dimensional (3D) conditions may vary greatly at a site. This can lead to critical areas to be overlooked, especially for sites with variable topography, complex soil stratification or varying soil depth.
This study thereby investigates the integration of a 3D groundwater model into 3D LEM slope stability analysis to account for spatial variations. The groundwater model is generated as a finite difference model via the open-source software MODFLOW and the LEM analysis is performed with PLAXIS 3D LE using the General Limit Equilibrium (GLE) with half-sine function. The PLAXIS 3D LE applies the two-directional 3D-method and the Cuckoo search method, which allow for asymmetrical failure mechanisms and does not require any predefined search area by the user, in contrast to e.g. SCOOPS3D.
The study was applied to a geological site, Skälsbo, located along the Göta River valley. The site consists of thick deposits with soft sensitive clays with eroded slopes facing Göta River. Thorough geotechnical investigations have been performed at the site as a part of the Göta River Commission work to reduce landslide risks along the river.
The results show that the advanced 3D groundwater model can be successfully imported into 3D LEM for a simple, yet computational efficient, uncoupled hydromechanical analysis of the slope stability at regional scale. Comparisons of results from dry 2D analysis shows comparative results between LEM and corresponding finite element analysis. The method has thereby great potential in incorporating future climate scenarios and their effect on regional stability, to detect both migration of critical stability areas and changes in its distribution over time. The method also shows that the user can seamlessly generate 2D models from the regional model for further assessment. The strength of using an advanced groundwater model, such as MODFLOW, is that both historical and future groundwater scenarios can be accounted for and thereby bring a robustness to the stability evaluation. This approach accounts for the complex groundwater situation, to ultimately better predict and optimize the need and extent of mitigation measures for cost- and environmental purposes.
How to cite: Sellin, C., Sundell, J., Abed, A., and Haaf, E.: Integrating Advanced 3D Groundwater Modelling into Slope Stability Assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20761, https://doi.org/10.5194/egusphere-egu26-20761, 2026.
With the increase in the frequency and magnitude of landslides observed in recent years, it is essential to improve risk management tools. To this end, the development of landslides databases must be improved in order to train and refine these tools more efficiently. The GDELT project, a global database that monitors and collects news from around the world, was used to collect news available on the web regarding landslides which occurred between 2015 and 2024 in the city of Petrópolis, the selected study area for the project. The result was compared with the landslide database prepared and provided by the Civil Defense of Petrópolis-RJ. The comparison was made visually, through graphs, and mathematically, through the Pearson correlation coefficient and through Spearman's rank correlation. Moreover, in an attempt to improve the temporal accuracy of the news-based database, keywords referring to periods of the day were identified. The results were compared to the times registered by the Civil Defense, and the news related to the cases in which there was a divergence were studied, in order to assess which result was closer to reality. Finally, seeking to improve spatial accuracy, satellite images were used in order to identify the difference in the vegetation index (in particular, MSAVI2) between before and after the date of a landslide occurrence to ascertain the appearance of slope failures. The news-based database presented a good annual and monthly precision and reasonable weekly precision for identifying landslide events. Moreover, it proved to be useful for identifying the period of the day in which a particular landslide with a significant impact occurred. However, this strategy is less accurate for events involving multiple landslides with a large impact. The Civil Defense database, on the other hand, may be useful in order to consider a larger number of landslides, including those of lesser impact, but it is not prone to highlighting high-impact particular events. Calculating the difference in vegetation index from multispectral images has proven useful for identifying the emergence of landslide scars.
How to cite: Cardoso, C., Michel, G. P., and Zanandrea, F.: Semi-automated landslide database development through online news and satelite images, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-929, https://doi.org/10.5194/egusphere-egu26-929, 2026.
Landslide susceptibility mapping traditionally relies on topographic, hydrological, and geological factors derived from Digital Elevation Models (DEMs). However, conventional parameters may not fully capture geomorphological processes and terrain evolution histories that indicate potential future hazards. This study integrates expert-interpreted geomorphological maps into machine learning models to enhance landslide prediction in Taiwan's mountainous regions. We compared five machine learning models (Logistic Regression, Random Forest, XGBoost, CatBoost, and LightGBM) in the Laku River basin, southern Taiwan. Expert-interpreted geomorphological maps provided four critical features, debris avalanche-prone areas, rockfall zones, alluvial fans, and old landslide locations, representing historical mass movement signatures that DEM-derived parameters cannot discover. Based on testing results, XGBoost outperformed all models, and integrating geomorphological maps significantly improved performance: F1-score increased from 0.8364 to 0.8530, with recall improving by 2.9%. This enhancement was particularly evident in detecting actual landslide occurrences along landslide boundaries, critical for high-risk applications. Furthermore, SHAP analysis revealed that debris avalanche features, NDVI, and rockfall zones were the top three contributing features. Unlike Logistic Regression, which suffered from multicollinearity with geomorphological features, tree-based models effectively leveraged expert knowledge for improved decision-making. This research demonstrates that expert-interpreted geomorphological maps, encoding long-term landscape evolution, significantly enhance machine learning-based landslide susceptibility assessment through improved model interpretability and prediction accuracy.
How to cite: Chu, C.-R., Chan, C.-H., Lin, Y.-C., Lin, S.-C., Chang, C.-H., and Chen, H.: Expert-Interpreted Geomorphological Maps Enhanced Machine Learning for Landslide Susceptibility Mapping in Southern Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17087, https://doi.org/10.5194/egusphere-egu26-17087, 2026.
The Red Beach in Santorini, Greece, is a dynamic landscape formed by the rapid erosion of unstable volcaniclastic cliffs. This study presents a comprehensive, decadal analysis of cliff instability activity using a Multi-Temporal Object-Based Image Analysis (MT-OBIA) framework. Driven by a systematic collection of Unmanned Aerial System (UAS) high-resolution imagery, we developed a time series of high-resolution Digital Surface Models (DSMs) and orthomosaics. Our OBIA workflow was specifically designed to segment and classify features unique to this environment, including scarps/sources, deposits, and cracks. The results quantify a mean annual cliff retreat rate of 0.45 m/year, with significant spatial and temporal variability, including a major collapse event in the winter of 2019 that resulted in over 1 meter of instantaneous retreat. The OBIA-derived inventory, comprising over 1,200 individual objects, reveals a strong seasonal pattern linked to intense storm surges and coastal erosion. This research establishes a robust and transferable methodology for high-frequency geohazard monitoring in coastal environments, providing critical data for the safety management of one of Greece's most visited tourist destinations.
How to cite: Karantanellis, E., Marinos, V., and Vassilakis, E.: A Decade of 4D Object-Based Monitoring of Cliff Hazard Dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17014, https://doi.org/10.5194/egusphere-egu26-17014, 2026.
The Ahr flood 2021 caused 135 fatalities, extreme economic damage as well as drastic geomorphological change in the main valley, its tributaries and adjacent valley slopes. Beside severe erosion and deposition, numerous landslides occurred or have been reactivated. One such landslide, near the town of Müsch in one of the narrowest sections of the valley, is 100 m wide, 200 m long, and of unknown age. It consists of Devonian sandstone, siltstone and slate. Approx. 7000 m³ of the landslide toe were eroded by the 2021 flood, leading to landslide movements, starting months after the hydrological extreme. This reactivation might cause a landslide dammed lake and subsequent flooding of buildings upstream. However, neither the geometric (depth of sliding plane, lateral limits) nor kinetic (deformation rates, possible accelerations, drivers and triggers) properties are known. Thus, a multi-method monitoring program was set up to better understand landslide and cascading hazards at this site.
The monitoring system combines electrical resistivity tomography (ERT) moisture monitoring, borehole data, inclinometer measurements, geodetic surveying and passive seismic instrumentation. Focusing on the ERT monitoring system, which includes three permanent profiles (length: 200 m, electrode spacing 2.5 m, array: gradient), we investigate the internal structure of the slide and the subsurface hydrology. This allows further analysis of the driving factors of slide activity. One longitudinal and one cross profile (both 200m) were measured in monthly intervals from 02/2024-12/2025. An additional cross profile at the borehole locations repeated ERT measurements were performed from 05/2025-12/2025.
Single ERT measurements do not reveal a clear sliding plane, as properties of the landslide material are too similar to the underlying, strongly weathered and tectonically stressed bedrock. ERT time lapse results show major variation in resistivity values in the upper 10-15 m along all three ERT profiles, indicating the depth of the sliding plane more clearly. This is confirmed by inclinometer measurements. Opening and widening of cracks time-correlate with wetter subsurface conditions shown in the ERT data. Our multi-method observations reveal reactivation and continued movement comprising the full slide that continued for several month even when hydro-meteorological conditions became drier.
The interdisciplinary monitoring approach will lead to better geotechnical slope stability model. Scenario analysis will encompass the response of the slope to the potential exacerbation of fluvial undercutting and the occurrence of wetter periods, as evidenced in the early 2000s, when precipitation levels were notably higher than in recent years. Overall, our monitoring facilitates a more profound comprehension of landslide behavior, thereby enabling a more precise evaluation of potential hazards and risks.
How to cite: Schoch-Baumann, A., Bell, R., Dietze, M., Wehinger, A., Hellenkamp, T., Hase, J., and Schrott, L.: The multi-method monitoring system on the Müsch Landslide (Ahr Valley, Germany), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22047, https://doi.org/10.5194/egusphere-egu26-22047, 2026.
Most of the reservoirs located in mountainous areas are exposed to landslides as well as bank slope erosion phenomena, which induces hazard conditions and undermines the integrity and operativity of the reservoir. It is therefore imperative to develop reliable quantitative approaches aimed at assessing landslide susceptibility of the slopes delimiting reservoirs and other slopes within the reservoir basin, so that appropriate preventive and mitigation measures can be explored and implemented accordingly. The main purpose of this study is to extend the application of three-dimensional (3D) limit equilibrium technique for slope stability analysis to the entire reservoir scale in order to conduct landslide susceptibility assessment for both shallow and deep-seated instability processes affecting artificial impoundments, under both different groundwater conditions and other relevant landslide conditioning factors. Based on the available information on the geological settings as well as the soil physical and mechanical data, the approach has been applied to the reservoir basins of the San Pietro Dam and the Occhito Dam, which are both located in Southern Italy. A schematized 3D geotechnical model was created for each of the reservoir basins upon which 3D limit equilibrium analysis of slope stability was carried out, from which safety factor maps were obtained at the entire reservoir basin scale. Different scenarios were run considering both peak and residual geotechnical strength parameters as well as different groundwater depths. In general, the obtained results enabled the identification of slopes highly susceptible to failure within the reservoir basins based on the obtained low safety factor (SF) values. The derived SF maps were validated by comparison with the available landslide inventory maps for the two reservoir basins. This showed that there is good agreement between landslides in the basins and the areas identified as more susceptible to landsliding based on the obtained low SF values confirming that the proposed approach can serve as a valuable tool for basin scale landslide susceptibility assessments. As a quantitative-based approach, the methodology has several advantages for the sake of dam safety, since it provides a clear overview of the slope stability conditions of the entire basin and, hence, can be highly useful in risk management activities.
How to cite: Chikalamo, E., Lollino, P., and Mavrouli, O.: Three-dimensional Landslide Susceptibility Analysis at the reservoir scale by Limit Equilibrium Models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5191, https://doi.org/10.5194/egusphere-egu26-5191, 2026.
Landslides are one of the recurrent precarious geological hazards that may prove fatal to life and property. In the Indian Himalayan region, the primary triggering factor contributing to landslides is rainfall. Recent advancement in rainfall threshold related studies have contributed significantly to a better understanding of the problem and the development of more accurate models at the local, regional and global levels. Although there are well-established studies on role of antecedent rainfalls and its criticality in the initiation of landslides, at present, there is no uniformly accepted method to consider effect of antecedent conditions or rainfall duration on stability of slopes. The antecedent period considers the influence of both soil moisture and groundwater on slope once the rainfall has ceased, since its effect is delayed due to hydrological attributes of the soil. Study from Uttarkashi region indicate that 15-day antecedent rainfall of around 109 mm can activates about 99% landslides in the area, highlighting the need to quantitatively estimate the likelihood of landslide incidents. For the present study, a decadal data on rainfall and landslide were curated from the Uttarkashi district of Uttarakhand state in India which comes under the Garhwal Himalayan region. These data were utilized to assess the influence of daily rainfall and antecedent rainfall on slope stability and to develop an empirical equation that predicts the probability of slope failure. The equation can be used as landslide warning for vulnerable zones if forecast precipitation values are available.
How to cite: Chandna, P., Kumar, G., and Sarkar, S.: Quantifying Antecedent Rainfall Effects on Landslides in the Garhwal Himalayas, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18511, https://doi.org/10.5194/egusphere-egu26-18511, 2026.
Slope movements are among the most widespread and damaging natural hazards in Hungary and worldwide. In recent decades, the occurrence and impact of landslides and related mass movements have markedly increased, a trend commonly linked to ongoing climate change. This study presents a landslide hazard assessment of climate-sensitive slope processes affecting the Danube riverside built structures and houses at the Dunaszekcső high bank, Hungary (Central Europe), focusing on the loess bluff area, where several slope failures and erosional events have been documented in recent decades. The study area is located on the steep Danube-facing slopes of the settlement high bank, composed mainly of Pleistocene loess, loess-derived paleosols, and interbedded sandy and clayey sediments. These lithologies exhibit strong variability in cohesion, permeability, and moisture sensitivity and are covered by shallow soils, resulting in high susceptibility to surface erosion, earth slides, and loess collapses. Steep slopes, locally sparse vegetation, and unfavourable slope exposure further increase landslide hazard. The applied methodology integrates detailed field mapping, geomorphological and engineering geological analysis, and evaluation of long-term and event-based precipitation data. Special attention was given to the identification of active sliding areas and the trigger mechanism. The results indicate that both short, high-intensity convective storms and prolonged rainfall events can initiate landslides. Under current and projected climatic conditions, slope failures and sediment mobilisation are expected, highlighting the urgent need for integrated landslide risk mitigation strategies. These include continuous slope monitoring, rainfall-based early-warning systems, and targeted structural and non-structural protection measures. The paper benefited from the results of GeoNetSee project “An AI/IoT-based system of GEOsensor NETworks for real-time monitoring of unStablE tErrain and artificial structures”, which is financed through the Interreg Danube Region programme, contract DRP0200783.
How to cite: Török, Á., Kis, A., Turák, B., and Rózsa, S.: Climate-Driven Slope Instability: Landslide Hazard at Danube riverside slopes (Hungary), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14824, https://doi.org/10.5194/egusphere-egu26-14824, 2026.
In flysch terrain worldwide, under-dip slopes, which are slopes where the bedding dips more steeply than the ground surface, are traditionally considered kinematically stable. This assumption is challenged by documented toppling failures, which present an apparent mechanical paradox in engineering geology: the required forward rotation of rock slabs seems to oppose gravity by initially lifting their mass, demanding an external energy source. This study introduces and validates a new mechanism, mobilized clay-driven toppling, that resolves this paradox and has direct implications for slope stability assessment. Based on an integrated investigation in the Outer Western Carpathians combining field mapping, LiDAR analysis, and electrical resistivity tomography (ERT), we propose that weathering transforms interbedded claystone into a pressurized viscoplastic medium. Under lithostatic loading, this mobilized clay subsides and extrudes laterally. The resulting pressure forces actively push against and rotates overlying sandstone slabs. This provides the external energy required for paradoxical toppling. A quantitative geometric model links clay subsidence to sandstone rotation and predicts rotation axis depths of 12–26 meters. These depths are independently confirmed by subsurface ERT imaging. This process produces a characteristic, stepped morphology of sink-like depressions upslope of rotated ridges, offering a diagnostic geomorphic signature. These findings necessitate a reevaluation of slope stability concepts in flysch regions. We demonstrate how relatively affordable reconnaissance tools, such as LiDAR and ERT, can identify surface and subsurface indicators that diagnose this mechanism. Our results reveal that under-dip slopes, typically considered low-hazard areas, can undergo active destabilization due to weathering-induced clay mobilization. This bridges a critical gap between process understanding and practical hazard identification in engineering geology. The research was formally supported by the Grant Agency of the Czech Republic (GC22-24206J) and the Taiwanese Ministry of Science and Technology (MOST 111-2923-M-008-006-MY3), the National Science and Technology Council (NSTC) with the Project Numbers NSTC 114-2123-M-008-003-, and by the conceptual development project RVO 67985891 at the Institute of Rock Structure and Mechanics of the Czech Academy of Sciences.
How to cite: Nguyễn, T.-T., Baroň, I., Hartvich, F., Havlík, J., Kociánová, L., Klimeš, J., Černý, J., Šutjak, M., Dušek, V., Lin, C.-H., Tseng, C.-H., Chen, Y.-C., Dong, J.-J., and Melichar, R.: Mobilized Clay-Driven Toppling in Flysch Slopes: Resolving an Apparent Mechanical Paradox and Its Implications for Hazard Reassessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2129, https://doi.org/10.5194/egusphere-egu26-2129, 2026.
Very small-strain stiffness parameters derived from seismic methods are commonly used in landslide investigations to describe subsurface mechanical conditions. In practice, these parameters are often interpreted in terms of slope stability. However, their role in identifying the internal structure of landslide bodies is still not fully recognized, especially in geologically complex flysch terrains.
This study examines the significance of very small-strain shear modulus (G₀) for interpreting the internal structure of deep-seated landslides developed in the Carpathian Flysch. The analysis is based on two slow-moving landslides instrumented with deep inclinometer boreholes and monitored over periods of 9–10 years. Long-term inclinometer records provide information on cumulative deep-seated displacements and their vertical distribution within the landslide bodies.
Seismic surveys were carried out along profiles located within the landslides, and very small-strain stiffness distributions were derived from shear-wave velocity measurements supported by laboratory-based bulk density data. Instead of focusing on the integration methodology, the study compares stiffness profiles directly with long-term displacement patterns and geological information at borehole locations.
The results indicate that variations in very small-strain stiffness reflect differences in lithology, degree of weathering, and structural discontinuities within the landslide bodies. Zones characterized by relatively high stiffness values may correspond to less weathered but strongly fractured flysch units, while lower stiffness values are typically associated with colluvial material or highly disturbed rock masses. Importantly, similar stiffness values can be linked to different kinematic behaviors, highlighting that stiffness parameters alone do not describe landslide activity.
The comparison of geophysical stiffness data with long-term monitoring records demonstrates that very small-strain stiffness is particularly useful for identifying internal structural domains rather than for direct assessment of landslide stability. The study emphasizes the role of long-term inclinometer monitoring as a reference framework that constrains the interpretation of geophysical results. The findings support a more informed use of seismic stiffness parameters in landslide studies and contribute to improved characterization of landslide structure in flysch terrains.
How to cite: Wasilewski, K., Mieszkowski, R., and Mieszkowski, S.: Significance of very small-strain stiffness for interpreting the internal structure of flysch landslides, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14434, https://doi.org/10.5194/egusphere-egu26-14434, 2026.
Identifying slopes most prone to earthquake-induced failure on a regional scale is fundamental for guiding effective damage mitigation strategies in long-term land use planning and for optimizing emergency response during seismic events. Two decades ago, Del Gaudio et al. (2003) proposed an approach for reconnaissance-level assessments of earthquake-induced landslide hazards. This approach relates the slope’s critical acceleration ac, a threshold needed to mobilize co-seismic failures, to the resistance demand imposed by regional seismicity. Based on the simplified Newmark (1965) model of landslide initiation under seismic forcing, this approach estimates the critical acceleration (Ac)x required to limit the probability of Newmark's displacement DN exceeding a predetermined threshold x, which is critical for landslide activation.
With the increasing data availability through civil protection initiatives, such as seismic microzonation studies, involving joint efforts by professionals and researchers and improved data analysis tools, there is an opportunity to refine this approach. This study tested some of these refinements on the landslide-prone Daunia Mountains (southeastern Italy). First, new empirical DN predictive equations specific for the study area were calibrated using over 200 real and synthetic accelerograms representative of seismic scenarios relevant to the Daunia seismic hazard. The results showed that this region-specific model considerably improved the accuracy of DN predictions compared with equations calibrated using data from other regions, although the effect on slope resistance estimates was minor.
Secondly, significant advancements were made in incorporating site response effects on (Ac)x using site-specific, probabilistic estimates of Arias intensity amplification factors. These amplification factors were estimated via site response analyses exploiting seismic microzonation data to i) generate 1D shear-wave velocity models from advanced ambient noise data analyses and ii) simulate site response using sets of relevant accelerograms. Tests demonstrated that incorporating these amplification factors leads to considerably higher resistance demand values compared to those derived using generic assumed amplification factors.
The refined approach proposed here allows the creation of maps showing (Ac)x values that, when compared with GIS-based estimates of actual slope ac values, can pinpoint slopes more likely to experience co-seismic failure. These maps can be used where long-term mitigation measures or emergency rescue operations should be prioritized, thereby enhancing societal resilience to seismic events.
References
Del Gaudio, V., Pierri, P., Wasowski, J., 2003. An Approach to Time-Probabilistic Evaluation of Seismically Induced Landslide Hazard. Bull Seismol Soc Am 93(2):557–569. https://doi.org/10.1785/0120020016.
Newmark, N.M., 1965. Effects of earthquakes on dams and embankments. Geotechnique 15 (2), 139–159.
How to cite: Del Gaudio, V., Capone, P., Fredella, F., and Wasowski, J.: Regional scale evaluation of slope exposure to co-seismic failures: a tool for optimizing land use planning and emergency management , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2378, https://doi.org/10.5194/egusphere-egu26-2378, 2026.
The East Longitudinal Valley is in a high seismicity region of Taiwan, characterized by complex subsurface structures and significant deep geothermal potential. Conventional deep geological borehole drilling provides critical constraints on subsurface structures and geothermal resource distribution but is costly and time-consuming. Recently, the degree of polarization–ellipticity (DOP-E) method for Rayleigh waves has been successfully applied to estimate subsurface depth variations beneath ice sheets and to delineate shear-zone depths in landslide environments. In this study, continuous ambient seismic noise records from three seismic stations co-located with geological boreholes (Station code: WL6G, GW2G, and GW3G) in the Wulu geothermal prospect, eastern Taiwan, were analyzed using the DOP-E method. Rayleigh-wave ellipticity was estimated and applied to invert shear-wave velocity (Vs) profiles. The resulting Vs structures were integrated with three-dimensional Magnetotelluric (MT) models to constrain the geometry of potential geothermal reservoirs. Relationships between Vs structures, borehole core interpretations, and well-logging data were further examined. In addition, the failure of a landslide dam in the upstream MaTaiAn Stream on 23 September 2025 caused severe damage, highlighting the importance of internal stratification in understanding dam failure mechanisms. Temporal seismic array data acquired at the MaTaiAn landslide dam were analyzed using the DOP-E approach to derive two-dimensional Vs profiles. Based on insights from the Wulu site, the internal stratigraphic structure of the dam was characterized. Overall, this study demonstrates that ambient seismic noise observations combined with DOP-E analysis provide robust shear-wave velocity constraints, effectively complementing conventional drilling data. The proposed approach is well suited for geothermal exploration and subsurface structural assessment in remote and topographically challenging environments.
How to cite: Hsu, H.-Y. and Chao, W.-A.: Constraining shear-wave velocity structure using Rayleigh-wave ellipticity: Geothermal site and MaTaiAn landslide dam, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15903, https://doi.org/10.5194/egusphere-egu26-15903, 2026.
After the 2024 Mw 7.4 Hualien earthquake in eastern Taiwan, the Mataian River watershed experienced a catastrophic sequence of cascading geohazards. This study reconstructs the long-term evolution and failure kinematics of the 2025 Mataian giant landslide and its subsequent dam-breach events. By integrating multi-temporal LiDAR-derived topography, satellite imagery, microseismic signal analysis, and high-resolution UAV surveys, we offer a comprehensive geomorphic and kinematic reconstruction of this complex event. Satellite images are identified a 1,200 m-long tension crack developing along the crown of a paleo-landslide after the 2024 earthquake. On 21 July 2025, a massive failure occurred with a maximum scarp retreat of 120 m and a failure depth of 380 m. Multi-temporal LiDAR differencing estimates a total landslide volume of ~308 million cubic meters. Microseismic records captured a distinct two-stage runout process: an initial dominant southeastward motion toward the Wang Creek tributary, followed by a secondary southward runout ~80 s later along the Mataian River mainstream. The resulting landslide dam reached a height of ~200 m and a maximum depositional thickness of ~325 m. On 23 September 2025, the dam catastrophically breached, with the impounded lake volume plummeting from 91 to 1.15 million cubic meters and causing 19 fatalities and 5 missing persons downstream. Post-breach UAV observations of the residual dam exposed a stratified internal structure of fractured greenschist, quartz-mica schist, and marble, overlain by boulder-gravel deposits layer. Notably, subsequent failures on 21 October and 13 November were concentrated on the right bank. Due to the run-up process during the major event, where the colluvial front collided with the opposing slope, forming a steep and mechanically weak interface. A comprehensive dynamic model of the landslide-to-breach sequence is established. Our findings provide critical insights into the post-failure stability of residual dams and important information for subsequent numerical modeling, physical breach experiments, and the hazard mitigation strategies in similar region.
How to cite: Yang, C.-M. and Chao, W.-A.: Cascading Hazards and Dynamic Evolution of the 2025 Mataian Giant Landslide Dam: From Earthquake-Induced Initiation to Catastrophic Breach and Residual Dam Instability, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7434, https://doi.org/10.5194/egusphere-egu26-7434, 2026.
Landslide dams are usually short-lived and it is challenging for decision makers to take response for emergency management of dam breaching hazards. To make a proper decision becomes more difficult due to the high uncertainty for predicting the forming and breaching process of nature damming lake. Since one order of magnitude estimation error of peak flow is common, risk communication plays a vital role for managing the dam breaching hazards. The breaching of Mataian dam with a dam volume of 300 mega cubic meters on 23th Sep. 2025 in Taiwan, which killed 19 people and 5 people still missing, provides a unique case to learn the importance of risk communication and risk management for hazards relating to landslide dam breaching. In this presentation, the uncertainties related to dam forming identification, dam stability evaluation, breaching hydrogram estimation, and downstream flooding prediction are illustrated. This presentation tries to raise an open question: if this event start all over again, can the emergency response be improved and the number of victims can be reduced?
How to cite: Dong, J.-J.: Lesson learned from the breaching of super large, short-lived Mataian landslide dam: The importance of risk communication of a catastrophic and uncertain disaster, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5351, https://doi.org/10.5194/egusphere-egu26-5351, 2026.
