Geomorphological Hazards and Risk Management


Geomorphological Hazards and Risk Management
Conveners: Bianca Carvalho Vieira, Helene Petschko, Ana Luiza Coelho-Netto, Tavares Alexandre Oliveira
| Mon, 12 Sep, 14:30–16:30, 17:00–19:00|Room Sala Almedina-C2D, Tue, 13 Sep, 09:00–10:30, 11:00–16:30|Room Sala Almedina-C2D
| Attendance Tue, 13 Sep, 10:45–11:00 | Display Mon, 12 Sep, 09:00–Tue, 13 Sep, 19:00|Poster area, Attendance Tue, 13 Sep, 16:45–17:00 | Display Mon, 12 Sep, 09:00–Tue, 13 Sep, 19:00|Poster area

Orals: Mon, 12 Sep | Room Sala Almedina-C2D

Chairpersons: Ana Luiza Coelho-Netto, Tavares Alexandre Oliveira, Maria Carolina Villaça Gomes
Tsunami hazards
Giovanni Scicchitano, Salvatore Gambino, Giovanni Scardino, Giovanni Barreca, Felix Gross, Giuseppe Mastronuzzi, and Carmelo Monaco

The disastrous earthquake that affected south-eastern Sicily in 1693 caused over 60,000 causalities and the total destruction of several villages and towns along the coastline between Siracusa, Ragusa, and Catania. During the aftermath of the earthquake, a tsunami struck the Ionian coasts of Sicily and the Messina Strait and was probably recorded even in the Aeolian Islands and Malta. Over the course of the past decades, the event has been highly debated regarding the location of the seismogenic source and the possible cause of the associated tsunami. The marine event has been correlated to both, a submarine landslide and a coseismic displacement at the seafloor. To better defining the most reliable sources and dynamics of the tsunami, we couple high-resolution marine seismic survey data with hydrodynamic modelling to simulate various scenarios of tsunami generation and propagation. Results from the simulations have been compared with geomorphological evidences of past tsunami impacts, described in previous work along the coast of south-eastern Sicily, and within historical chronicles and reports. The most reliable scenario considers the 1693 event composed by two different tsunami waves: a first wave generated by the coseismic fault displacement at the seafloor and a second wave generated by a submarine landslide, triggered by the earthquake shaking. Distinct tsunami modelling runs showed that a simultaneous movement between fault displacement and submarine mass movement could determine a destructive interference on the tsunami waves, with a reduction of wave height. For this reason, the second tsunami wave was probably generated with a maximum delay of few minutes after the one generated by the earthquake and induced a higher flooding. The double-source model could explain the observation why in the course of other destructive earthquakes which occurred in south-eastern Sicily, like that of 1169 AD, the associated tsunami caused less damages. This implies the need to better map, define and evaluate the coastal hazards offshore eastern Sicily accounting to this kind of tsunami events.

How to cite: Scicchitano, G., Gambino, S., Scardino, G., Barreca, G., Gross, F., Mastronuzzi, G., and Monaco, C.: The enigmatic 1693 AD tsunami in the eastern Mediterranean Sea: new insights on the triggering mechanisms and propagation dynamics, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-29, https://doi.org/10.5194/icg2022-29, 2022.

Maria Teresa Ramirez-Herrera, Néstor Corona, Héctor Nava, David Romero, Hamblet Torija, and Felipe Hernández Maguey

The 23 June 2020 La Crucecita earthquake occurred at 10:29 hr on the coast of Oaxaca in a Mw 7.4 megathrust event at 22.6 km depth and triggered a tsunami recorded at tide gauge stations and a DART off the coast of Mexico. We describe here details of the rapid response survey of vertical coseismic deformation, tsunami, geologic effects, ecological damage to coral reef ecosystems, and lessons from working in the field during the COVID-19 crisis. Moreover, ecological damage caused by earthquakes and tsunamis is an important problem barely addressed in recent studies. Coral reefs are some of the world’s most fragile ecosystems, they are highly sensitive to environmental changes. These communities had suffered a significant impact by both coseismic coastal uplift and the tsunami. We surveyed 44 km along the coast of Oaxaca. Because of the COVID-19 pandemic, some local communities enforced rules of confinement. They closed the access roads to their villages prohibiting the passage of outsiders to their community. We assessed coseismic coastal uplift by means of mortality caused by vertical displacement of intertidal organisms, bleaching of coral communities, resurveying of benchmarks, and measured tsunami runup. Our results show coastal uplift of 0.53 m near the epicenter, decreasing farther away from it, and up to 0.8 m, the latest related to exposure of the coast. Our values of coastal uplift, ca. 0.53 m fit well with 0.55 m of uplift reported by tide gauge data at Huatulco. These amounts of coastal uplift left coral communities exposed and not covered by seawater even at high tide, causing the death of these communities. Coastal uplift and low tide at the time of the event limited the tsunami inundation and runup on the Oaxaca coast. Nevertheless, we found tsunami inundation evidence at four confined coastal sites reaching a maximum runup of 1.5 m.  The enclosed morphology of these sites determined higher runup and tsunami inundation. Local coastal morphology effects are not detected in tsunami models lacking detailed bathymetry and topography. This issue needs to be addressed during tsunami hazard assessments. 

How to cite: Ramirez-Herrera, M. T., Corona, N., Nava, H., Romero, D., Torija, H., and Hernández Maguey, F.: Coseismic uplift and coral mortality caused by the 23 June 2020, Mw 7.4 La Crucecita, Oaxaca, Mexico earthquake and tsunami, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-444, https://doi.org/10.5194/icg2022-444, 2022.

Landslide susceptibility, hazard and risk assessment
Michele Amaddii, Giorgio Rosatti, Daniel Zugliani, Lorenzo Marzini, and Leonardo Disperati

Mountain environments are naturally exposed to debris flows, a mass movement which represents one of the major geomorphological hazard sources for urbanized alluvial fan. In the last decades, climate change has contributed to extreme precipitations increase, making debris flows both larger and more frequent than in the past. The assessment and management of the risk associated with these events, according to UE Flood Directive, is feasible and desirable by using appropriate practices and the best available technology that do not imply excessive costs.
In line with the above-mentioned European Directive, we present a multidisciplinary approach for the numerical modelling of the debris flow event that occurred on July 27-28, 2019 in Abbadia San Salvatore, a  village located in a catchment of the Mt. Amiata area (Southern Tuscany, Italy). Debris flow was triggered by an extreme rainfall of 110 mm/1 h causing a channelled erosive process, and the subsequent obstruction of a culvert at the entrance to the village, flooding and damaging it.
Mt. Amiata is an extinct Pleistocene volcano mainly consisting of trachidacitic lavas characterized by a pervasive saprolite weathering, resulting in a large amount of residual loose debris resting on the hillslopes and along the hydrographic network. Specific geological and engineering-geological field investigations were carried out to assess the availability of debris material and its hydrological behaviour, providing more constraints for numerical modelling. 
The Green-Ampt model, implemented in the FLO-2D software, was used for the evaluation of discharge values in the hydrographic network. Subsequently, the debris flow modelling was conducted applying the WEEZARD system, composed of a previously developed advanced two-phase debris-flow model (TRENT2D), re-coded as a web service. The mass movement was simulated to quantify erosive and depositional processes that occurred during the event. In addition, a specific approach was implemented to model the effect of the culvert that was clogged during the event.
Despite the challenging modelling aspects, the results in terms of debris volume, erosion rates, flooded area and timing of the culvert obstruction, are in agreement with observed data. 
The WEEZARD system has therefore proved to be an effective tool, in line with the indications of the European Directive. Moreover, the reconstruction was obtained using most of the a priori parameters setting. This shows that the used modelling approach has a good predictive capacity and can therefore be reasonably used to support further predictive hazard mapping analyses. Finally, another important element to be highlighted is that an accurate input model based on the integration of detailed geological-geomorphological investigations is necessary to obtain reliable modelling results.

How to cite: Amaddii, M., Rosatti, G., Zugliani, D., Marzini, L., and Disperati, L.: Back-analysis of the Abbadia San Salvatore (Mt. Amiata, Italy) debris flow of July 27-28, 2019 using the WEEZARD system, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-305, https://doi.org/10.5194/icg2022-305, 2022.

Marco Loche, Gianvito Scaringi, and Luigi Lombardo

The effect of temperature on the stability of slopes in temperate climates is poorly constrained. Experiments demonstrate a clear thermo-hydro-mechanical (THM) response in expansive soils, and evidence of thermally-induced activity exists for some landslides. However, building a representative thermal variable suitable for catchment or regional-scale studies is challenging, owing to heterogeneities in materials and stress histories and the complexity of THM processes. We performed a landslide susceptibility modelling of the portion of Italian territory featuring clay deposits. We utilised the geo-lithological map of Italy and the Italian National Inventory (IFFI), that differentiates among landslide types, and we focused on slow flows, often associated with creep movements. We relied, as one of the inputs, on a ten-year series of Land Surface Temperature (LST) data from MODIS, freely available in Google Earth Engine, and implemented a slope unit-based Generalized Additive Model (GAM) approach to account for nonlinearities in the possible temperature-slope stability relationship. We produced a susceptibility map for clay deposits over the entire Italian territory, and observed a positive dependence of landslide abundance on LST on warmer and gentle slopes, where creep phenomena are common. Higher temperatures are in fact associated with decreased soil and water viscosity and hence enhanced shear creep rates in clays.

How to cite: Loche, M., Scaringi, G., and Lombardo, L.: Land Surface Temperature Controls Stability in Gentle Clay Slopes, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-411, https://doi.org/10.5194/icg2022-411, 2022.

Raoul Merlin Ndonbou, David Guimolaire Nkouathio, Ghislain Zangmo Tefogoum, Christian Suh Guedjeo, and Paul Tematio

Mass movements are phenomena which, due to their random nature, generate very significant risks, affecting the human heritage. The Southern Escarpment of the Bamileke Plateau (ESPB) is a region with a rugged relief. This relief, associated with climatic bad weather, is the seat of numerous instabilities linked to mass movements. This study aims to establish a relationship between geomorphological factors and mass movements along the Southern Escarpment of the Bamileke Plateau. The methodological approach used in this work is based on the inventory of mass movements from field campaigns and the exploitation of satellite images as well as the mapping of geomorphological factors. The geomorphological map, the slope map and the slope direction map are the factor maps that were used to assess the occurrence and susceptibility to mass movements in the region. Based on the field observations and satellite images, a spatial distribution map of mass movement was obtained. This map reveals that landslides are the most significant mass movement in the study area with a representativeness rate of 90% compared to subsidence and rock falls which represent respectively 5% of recorded mass movements.  The steepest slopes are the areas with the highest concentration of landslides in the region. The susceptibility map obtained from the geomorphological factor maps reveals that 16.95% represent low probability areas, 43.39% represent moderate probability areas, 29.77% represent high probability areas and 9.89% represent very high probability areas. The superimposition of the susceptibility map on the spatial distribution map of mass movements allows the relevance of this susceptibility map to be validated and assessed. The information obtained on the regional geomorphology clearly explains the special distribution of recorded mass movements, especially landslides.

How to cite: Ndonbou, R. M., Nkouathio, D. G., Zangmo Tefogoum, G., Guedjeo, C. S., and Tematio, P.: Involvement of geomorphological factors on the occurrence of mass movements along the Southern Escarpment of the Bamileke Plateau (West-Cameroon), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-669, https://doi.org/10.5194/icg2022-669, 2022.

Evaluation of the frequency and morphometric parameters of shallow landslides in Serra do Mar Paulista
Camilla Capella, Bianca Vieira, and José Bonini
Giorgio Paglia, Vania Mancinelli, Gianluca Esposito, Enrico Miccadei, Jacopo Cinosi, Valerio Piattelli, and Massimiliano Fazzini

Abruzzo Region (Central Italy) is largely affected by landslide phenomena, widespread from the mountainous to the coastal areas. The area is located in the central-eastern part of the Italian peninsula. It is framed in a complex geological and geomorphological framework, closely connected to the combination of endogenous (morphotectonics) and exogenous processes (slope, fluvial, karst, and glacial processes). Landslide phenomena are linked to the interaction of geological, geomorphological, and climatic factors (instability factors) in response to trigger mechanisms, mostly represented by heavy rainfall events, seismicity, or human action. This work illustrates the results of multidisciplinary analyses carried out in recent years in different physiographic and geomorphological-structural contexts (chain, foothills, fluvial, and coastal areas). These analyses are based on the combination of classic and advanced methods, including morphometric analysis of the topography and hydrography, detailed geological-geomorphological field mapping, geostructural analysis, photogeological analysis, and numerical modeling. Selected case studies are chosen as representative of the main active geomorphological processes affecting different geomorphological/morphostructural environments, with reference to the predisposing and/or triggering factors. The main landslide cases analyzed and discussed in this work consist of: debris flow and rockfalls in a mountain area, widely altered by wildfire events (Montagna del Morrone case); complex landslides systems in the foothills, characterized by a very rough topography documenting the activity of long-term landslide phenomena (Ponzano and San Martino sulla Marrucina cases); sliding and complex landslides (topples and rockfalls) in hilly-piedmont areas, following a heavy snow precipitation event and a moderate seismic sequence (Castelnuovo di Campli case) and induced by episodic and localized cliff recession processes combined with wave-cut and gravity-induced slope processes (Abruzzo rock coast cases). The work outlines the importance of combining geological and geomorphological approaches with detailed field and laboratory data analysis to characterize morphologies, bedrock features, structural features and jointing, superficial continental deposits, and landforms distribution. This allows supporting large-scale analyses to evaluate hazards and risks posed by different landslides with different magnitudes in different environments. This work could represent a practical integrated approach in geomorphological studies for landslide hazard modeling at different spatial scales, readily available to interested stakeholders. Furthermore, it could provide a scientific basis for implementing sustainable territorial planning, emergency management, and loss-reduction measures.

How to cite: Paglia, G., Mancinelli, V., Esposito, G., Miccadei, E., Cinosi, J., Piattelli, V., and Fazzini, M.: Landslide hazard in the Abruzzo Region (Central Italy): landslides case studies in different geomorphological/morphostructural environments, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-148, https://doi.org/10.5194/icg2022-148, 2022.

Coffee break and poster session
Chairpersons: Maria Carolina Villaça Gomes, Ana Luiza Coelho-Netto, Tavares Alexandre Oliveira
Chiara Martinello, Claudio Mercurio, Chiara Cappadonia, Viviana Bellomo, Andrea Conte, Giampiero Mineo, Grazia Azzara, and Edoardo Rotigliano

Landslide susceptibility assessment implemented by statistical methods relies on a basic concept according to which past and future landslides depends on the same causes of past failures. As a consequence, statistical inference can explore the relationships between past phenomena and geo-environmental variables to spatially recognize landslide-prone areas. Coherently, the quality and the prediction skill of the model and the relative prediction image heavily depend on the completeness of the landslide scenario exploited. However, landslide archives are frequently biased due to more or less limits we face in reconstructing reliable and complete landslide maps. In this sense, exploiting public available archives compiled from local administration is a goal in landslides susceptibility evaluation. In fact, usually, these types of archives are multitemporal and collect potentially or real destructive phenomena based on direct observation of failures. The use of these types of archives allows obtaining immediately available landslides inventories, saving time and resources from mapping.

On the other hand, public landslide inventory may be wealthy close to urban areas while, usually, failures in the agricultural lands are sporadic or under-represented.

In this study, starting from the available slide (56 cases) and flow (115 cases) inventories of the Torto River basin (420 km2, central-northern Sicily), which were prepared by the “Dipartimento Regionale dell’Autorità di Bacino del Distretto Idrografico Sicilia”, and a set of twelve geo-environmental predictors, two basin susceptibility models (for slides and flows, respectively) were prepared by applying Multivariate Adaptive Regression Splines (MARS). Good performance for the basin-scale models was then assessed according to cross-validation validation strategies. Then, in a randomly selected small sub-catchment (Sciara stream, 21.5 km2), the prediction images produced at a basin-scale were validated in recalling the landslides of two local systematic and multitemporal remotely recognized inventories. Despite the high performance of the basin-scale models, the results at the local scale showed a poor capacity of the models in detecting the two systematic archives, with a non-acceptable sensitivity (0.67 and 0.57 for slide and flow, respectively). The AUC (Area Under the Curve) values are non-acceptable (0.47 and 0.65 for slide and flow, respectively) also.

In order to “boost” the basin-scale susceptibility models, by exploiting a score weighted random selection of 30% of the mapping units of the Sciara stream sub-catchment, a stable/unstable status concerning slide and flow phenomena of the selected cases was assigned by intersecting with the remotely sensed inventories.

Two new basin-scale models were implemented by using these new “hybrid” archives. The two prediction images compared with the systematic inventories of the Sciara sub-catchment reveal an increment of the models’ performance, with high accuracy in predicting positive cases both for slide and local flow types. At the same time, persistent precision in detecting stable cases for local flow arises (~0.8), while a decrease in specificity due to an increment of False Positives suggests potentially new future activations for slide phenomena. However, the important increment of the AUC values (from 0.79 to 0.94 and from 0.8 to 0.94, for slide and local flow, respectively) testifies to a general improvement of the main models.

How to cite: Martinello, C., Mercurio, C., Cappadonia, C., Bellomo, V., Conte, A., Mineo, G., Azzara, G., and Rotigliano, E.: Incomplete landslide archive in landslide susceptibility assessment: a nested strategy for improving results., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-648, https://doi.org/10.5194/icg2022-648, 2022.

Mihai Micu

Vrancea seismic region, corresponding to the Curvature sector of the SE (Romanian) Carpathians, represents a very active geomorphic region, marked by a wide variety of fluvial, slope gravitational and seismic processes. The morpho-litho-structural traits, the active neotectonic movements, the climatic regime and the human influence are controlling a complex multi-hazard environment. Accordingly, numerous landslide hazard evaluation attempts have been developed during the last decade, and several landslide inventories were used to calibrate and validate statistic and probabilistic susceptibility models. However, comparing various results, it was seen that fine-tuned regional susceptibility models, performing properly from a statistical point of view, resulted in differently-distributed susceptibility classes, potentially inducing confusions among stakeholders and end-users. It is the purpose of this presentation to outline the geomorphic complexity of landslides typology in the study-area, and the induced epistemic uncertainties. Different landslide inventories (based on field mapping, optical remote sensing imagery, radar interpherometry) and bi/multivariate statistical approaches are being discussed, and slope sensitivity, geomorphic complexity of landslides, their evolution, frequency-magnitude relationship, triggering thresholds, morphodynamic sectors and connectivity are evaluated as potential sources of epistemic uncertainties. The presentation concludes with a series of recommendations meant to support the development of more robust and highly predictive susceptibility models and hazard evaluation. By enriching such methodology for evaluating the past, present and future behavior of such processes, the geomorphologists may foster numerous stakeholders to develop the optimal proactive measures for risk prevention and preparedness and the most suitable reactive actions for response and recovery.

Key words: Vrancea seismic region, Romania, Carpathians, landslides typology, epistemic uncertainty

How to cite: Micu, M.: Epistemic uncertainties induced by landslides typology in Vrancea seismic region (SE Carpathians, Romania) and their implication in hazard evaluation, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-731, https://doi.org/10.5194/icg2022-731, 2022.

Mario Valiante and Domenico Guida

Landslide susceptibility assessment is a key topic for land-use planning and for the overall safeguard of human activities. In this perspective, a wide range of methods and techniques have been proposed for the evaluation of landslide susceptibility, ranging from statistical methods to the latest deep learning technologies. Besides, Slope-Area plots are also exploited for the evaluation of surficial processes domains and the increasing availability of digital terrain models with higher resolution allows much detailed analyses.

On these premises, we compared slope-area plots produced with high resolution Lidar data with a landslide dataset produced following the LOOM data structure. The analysis has been carried out using only surficial phenomena like flows and falls. Moreover, such landslides have been decomposed into their principal components such as detachment, transit, and accumulation zones in order to perform an accurate evaluation of the geomorphic signature of such features. Each landslide has been also compared with the corresponding reference hillslope, defined as the set of enveloping Morse regions computed using Surface Network.

The plot of slope-area values of the training landslides and their reference hillslopes allows thresholding of the slope values at different contributing area bins, resulting in the mapping of those values exceeding the defined thresholds. Preliminary results show how such defined thresholds based on a proper training dataset could be a valid contribution to the overall topic of landslide susceptibility assessment based on geomorphological criteria at least for surficial landslide types like flow- and fall-like movements.

How to cite: Valiante, M. and Guida, D.: Geomorphic landslide susceptibility assessment using Slope-Area plots, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-665, https://doi.org/10.5194/icg2022-665, 2022.

Laura Paola Calderon-Cucunuba, German Vargas-Cuervo, and Christian Conoscenti

In this study, the ability of stochastic models to predict landslide susceptibility in the southern sector of the “Via al Llano” highway (Colombia) was assessed. To this aim, an inventory of landslides occurred in the area was prepared by analyzing images available in Google Earth. Multivariate Adaptive Regression Splines (MARS) was employed to model the spatial distribution of the following five data sets of unstable cells selected within each landslide: i) the highest cell (data set MAX), ii) the highest 10% of cells (data set SUP), iii) the lowest cell (data set MIN), iv) the lowest 10% of cells (data set INF), and v) the entire landslide area (data set BODY). The goal of our experiment was to identify which of the calibration data set produces the best prediction of the landslide areas (BODY data set). The data sets were divided into calibration and validation groups of cells by randomly selecting 75% and 25% of the mapped landslides, respectively. In order to evaluate the robustness of the results, ten calibration and validation samples were extracted for each instability data set. The analysis revealed that the most important predictors were Normalized Difference Vegetation Index (NDVI), slope steepness, vertical distance to channel network, elevation and aspect. The receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC), calculated for each of the five instability data sets, indicated that calibrating the models with the lowest landslide pixels (MIN or INF data sets) allows to obtain the most accurate prediction of the validation landslide bodies (BODY data set), achieving AUC values ranging between 0.80 and 0.85.

How to cite: Calderon-Cucunuba, L. P., Vargas-Cuervo, G., and Conoscenti, C.: Stochastic assessment of landslide susceptibility by using five different instability datasets: a case study from the southern sector of the “Via al Llano” highway (Colombia), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-316, https://doi.org/10.5194/icg2022-316, 2022.

Stefan Steger, Mateo Moreno, Alice Crespi, Peter James Zellner, Robin Kohrs, Jason Goetz, Stefano Luigi Gariano, Maria Teresa Brunetti, Massimo Melillo, Silvia Peruccacci, Lotte de Vugt, Thomas Zieher, Martin Rutzinger, Volkmar Mair, and Massimiliano Pittore

Shallow landslides are frequently caused by an interplay of static predisposing factors (e.g., topography), mid-term preparatory factors (e.g., prolonged rainfall, seasonal changes of vegetation, snow melt), and short-term triggers (e.g., heavy rainfall). For large-area assessments, statistical analyses and data-driven approaches are often used to model landslide susceptibility based on spatial environmental variables or to derive critical landslide-triggering rainfall conditions through the definition of empirical rainfall thresholds. Attempts to integrate the spatial and temporal domains in the context of quantitative regional-scale landslide prediction are still rare.

This contribution focuses on the landslide-prone area of South Tyrol, northern Italy (7,400 km²) and presents a novel data-driven modelling procedure that integrates spatial predisposing factors and dynamic preparatory and triggering factors to predict the probability of landslide occurrence in space and time. The approach is based on time-stamped landslide inventory data from 2000 to 2021, high-resolution gridded daily precipitation observations for the same period, and a set of relevant static environmental variables (e.g., including topographic indices, lithology). Data preparation included an initial filtering of rainfall-induced landslide presence observations and a rule-based stratified sampling of landslide absence observations at landslide locations and at non-landslide locations. Cross-validation was implemented in the model developing stage to select optimal time windows to represent pre-landslide preparatory and triggering cumulative rainfall conditions. Modelling was based on a binomial Hierarchical Generalized Additive Model (HGAM) that considered the non-linear influence and interactions (i.e., via tensor products) of static and dynamic environmental variables on landslide occurrence (presence vs. absence) while simultaneously accounting for the nested data structure (i.e., multiple considerations of each location) and seasonal effects. The study also considered different biases inherent in the input data, such as the known underrepresentation of landslide data in locations far from infrastructure or potential reporting biases across years, by averaging-out associated random effect variables. The results were validated quantitatively (spatial and temporal cross-validation) and qualitatively (geomorphic plausibility) and visualized as maps and probability surface plots.

The assessment and validation confirmed the high generalizability and predictive performance of the model. A closer look at the derived relationships allowed to uncover the effects of predisposing, preparatory and triggering factors on landslide occurrence as well as the associated season-dependent variations. From our perspective, this new approach represents a good compromise between the high model flexibility for landslide prediction purposes and the high interpretability for understanding the underlying relationships.

The research leading to these results is related to the PROSLIDE project that received funding from the research program Research Südtirol/Alto Adige 2019 of the Autonomous Province of Bozen/Bolzano – Südtirol/Alto Adige.

How to cite: Steger, S., Moreno, M., Crespi, A., Zellner, P. J., Kohrs, R., Goetz, J., Gariano, S. L., Brunetti, M. T., Melillo, M., Peruccacci, S., de Vugt, L., Zieher, T., Rutzinger, M., Mair, V., and Pittore, M.: Applying a hierarchical Generalized Additive Model to integrate predisposing, preparatory and triggering factors for landslide prediction, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-388, https://doi.org/10.5194/icg2022-388, 2022.

Victor Buleo Tebar, Federica Lucà, Mauro Bonasera, Michele Licata, Giandomenico Fubelli, and Gaetano Robustelli

Landslide susceptibility is generally defined as the likelihood of a landslide occurring in a certain area on the basis of local terrain conditions. The aim of susceptibility assessment is to estimate the areas where landslides are likely to occur, based on the assumption that landslides will likely occur under the same conditions under which they occurred in the past.

The purpose of this study is assessing shallow landslide for Negrone and Tanarello catchments which are the upper basins of Tanaro river, a mountainous area within the Palaeo-European Continental Margin of the Alpine External Belt (External Briançonnais sucessions) and the Ligurian units of Maritime Alps of the Alpine Axial Belt (Pennidic Domain). The lithology is composed of silicate and to a minor extent carbonate rocks.

In the last decades, the study area has repeatedly been affected by slope instability events, mainly related to debris flows, characterized by extremely rapid movements. By integrating a detailed (1:5.000) geological and geomorphological field survey with ortophoto interpretation and existing information provided by Arpa Piemonte, landslide inventories have been produced. Only focusing on source areas, susceptibility assessment to debris flow have been performed by using a logistic regression approach, considering as covariates lithology, land use and morphometric factors derived from a digital elevation model (DEM) with a 5 m resolution. Source area pixel have been split into training and validation subsets by adopting a random partition. A certain number of pixels equal to the training set has been randomly extracted among stable cells, to prepare the dataset for logistic regression. The best set of covariates in controlling the spatial distribution of debris flows have been identified by iteratively adding one variable at a time and comparing the results. Susceptibility model fitting and prediction skill have been assessed based on validation subsets. The role of the considered factors in predisposing debris flow failures has been evaluated, discussing differences in the outcomes.

How to cite: Buleo Tebar, V., Lucà, F., Bonasera, M., Licata, M., Fubelli, G., and Robustelli, G.: Landslide susceptibility assessment at a local scale: logistic regression analysis for upper Tanaro catchments, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-274, https://doi.org/10.5194/icg2022-274, 2022.

Dr. Aadil Manzoor Nanda, Prof. Pervez Ahmed, and Prof. Tasawoor Ahmad Kanth

The present study endeavours to explore the efficacy of machine learning models in landslide predictions triggered by extreme rainfall events along Highway from Bandipora to Gurez, J&K, India. Random Forest (RF) and Logistic Regression (LR) Models were employed on account of their technical utility and logical procedure to transform the decision making into a series of algorithm steps that eventually culminate in low variance and minimum bias. The crux of these models was to find the optimal parameters for targeted feature i.e. landslide prediction. Hyper-parameter tuning was used to optimize the performance of the respective models. These models were evaluated for accuracy using the receiver operating characteristics, area under the curve (ROC-AUC) and false negative rate (FNR). When antecedent rainfall data is incorporated in the prediction models, both (LR and RF) performed better with an AUC of 0.825 and 0.843 respectively. The results reveal a positive correlation between antecedent precipitation and landslide occurrence rather than between single-day landslide and rainfall events. In case of FNR, LR and RF improved to14.32% and 15.92% respectively, when antecedent rainfall was included in the analysis. Comparing the two models, LR model’s performance is well within the acceptable limits of FNR and therefore could be preferred for landslide prediction and early warning over RF. LR model’s incorrect prediction rate is 8.48% without including antecedent precipitation data and 5.84% including antecedent precipitation data. Our study calls for wider use of Machinery Learning Models for developing early warning systems of landslides.

Keywords: -Rainfall Triggered; Machine Learning Models; Area Under Curve; False Negative Rate.

How to cite: Nanda, Dr. A. M., Ahmed, P. P., and Kanth, P. T. A.: Prediction of Rainfall Induced Landslides Using Machine Learning Models along Highway-Bandipora to Gurez Road, J&K, India, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-390, https://doi.org/10.5194/icg2022-390, 2022.

Claudio Mercurio, Chiara Martinello, Abel Alexei Argueta-Platero, Grazia Azzara, Edoardo Rotigliano, and Christian Conoscenti

On January 13th, 2001, El Salvador was hit by an earthquake of magnitude 7.7 which triggered thousands of landslides, causing 1259 fatalities and extensive damage to infrastructures. The analysis of aerial images provided by the CNR (Centro Nacional de Registros de El Salvador), which were taken a few days after the event, allowed us to map 1005 seismically-induced landslides that occurred in a study area extended for 92 km2. The objective of this experiment was to verify whether it is possible to predict the spatial distribution of these landslides through a stochastic approach that combines a rainfall-induced landslide susceptibility (SUSC) model, which is based on preparatory factors, and an earthquake-triggered landslide predictive (TRIGGER) model, which is based on seismic parameters such as peak ground acceleration (PGA) and distance to the epicenter (ED). The SUSC model was calibrated by using an inventory of 5609 landslides that occurred in November 2009 in the area of the San Vicente volcano, due to the simultaneous action of low-pressure system 96E and Hurricane Ida. The TRIGGER model was instead trained with the 20% of the earthquake-triggered landslides, whereas the remaining 80% was used to validate both the SUSC and TRIGGER models, as well as an ensemble model obtained by using as predictors PGA, ED and the landslide probability calculated by the SUSC model. In order to evaluate the robustness of the results, ten calibration and validation samples were randomly extracted from the 2001 landslide inventory. Multivariate adaptive regression splines (MARS) was used as modelling technique. The predictive performance of the models was evaluated by using receiver operating characteristics (ROC) curves and the area under the ROC curve (AUC).

The validation results revealed a slightly better performance of the SUSC model (average AUC = 0.719; AUC st.dev. = 0.008) with respect to the TRIGGER model (average AUC = 0.707; AUC st.dev. = 0.009). Moreover, the analysis highlighted that the best predictive ability is achieved by the ensemble model (average AUC = 0.743; AUC st.dev. = 0.006). These results suggest that, in the event that only some of the landslides triggered by an earthquake are known, as usually happens shortly after the event, it is possible to use the approach proposed in this study to identify those sites where the other landslides are more likely to have occurred.

This work is a part of the CASTES project, which is funded by the Italian Agency for Development Cooperation (AICS) and focuses on promoting research and training activities in the field of earth sciences in El Salvador (CA).

How to cite: Mercurio, C., Martinello, C., Argueta-Platero, A. A., Azzara, G., Rotigliano, E., and Conoscenti, C.: Predicting earthquake-induced landslides by using a stochastic modeling approach which combines preparatory and triggering factors: a case study of the co-seismic landslides occurred on January 2001 in El Salvador (CA), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-543, https://doi.org/10.5194/icg2022-543, 2022.

Orals: Tue, 13 Sep | Room Sala Almedina-C2D

Chairpersons: Susana Pereira, Grace Alves, Tavares Alexandre Oliveira
Roberta Silva, Ana Luiza Coelho Netto, Willy Lacerda, and Flávio Nunes

Several methodologies are described in the literature for the classification of terrain susceptibility to landslides, including probabilistic analysis based on landslide inventories and diagnoses based on the crossing of thematic maps. The latter approach prevails in Brazil, where thematic information has privileged geological maps and some geotechnical and geomorphological information. Other relevant categories, such as vegetation and land use are scant. This study poses a functionally based methodology of pertinent geological-geotechnical, geomorphological, vegetation cover and land use categories to assess terrain susceptibility to shallow planar landslides by following the geo-hydroecological approach. The D’Antas Creek basin (53 km2) located in Nova Friburgo, Rio de Janeiro state (SE-Brazil), was chosen as a pilot-area, as it was severely affected by 327 landslides in January 2011, 85% of which were triggered as shallow planar landslides with the slip surface around 1,5m + 0.5 m/deep. The geo-hydroecological approach follows empirical-analytical and integrative procedures of morphological, functional and historical knowledge, in a systemic view of the geographic space and articulating different hierarchical levels of the geo-ecosystem, as summarized in Coelho Netto et al. (2020). This approach is based on relevant functional parameters, indexes and categories affecting shallow planar landslides, all of which were synthetized in three cartographic bases: hydro-geomorphological; geological-geotechnical and vegetation-land use. Human-made activities were used to ponder their interferences to increase or to reduce the terrain susceptibility. The use of GIS (Geographic Information System) and multi-criteria analysis (i.e. Analytic Hierarchy Process - AHP) were incorporated into the geo-hydroecological approach. Soil geotechnical parameters increased the ability of the susceptibility model to identify potential areas for landslides. Integrated hydro-geomorphological conditions presented a more significant impact with the susceptibility classes. Vegetation and land use cover were reclassified on the basis of their ecological, hydrological and mechanical functionality, allowing a simplification of its classes. The final landslide susceptibility map included four categories (very high; high; medium; and low); areas classified as very high and high susceptibility overlaps with > 75% of the 2011 landslide scars. These results highlight the relevance of the geo-hydroecological approach to the definition of terrain susceptibility. Its systemic foundation and the organization of the database in a GIS environment remains open for updates, as new functional parameters are identified as relevant, favouring updated diagnoses to guide territorial ordering aimed at prevention, mitigation and/or adaptation of human occupation. This approach reaffirms the idea that the assessment of terrain susceptibility is a continuous process that must be constantly updated, according to the dynamics of landscape changes over space and time.

How to cite: Silva, R., Coelho Netto, A. L., Lacerda, W., and Nunes, F.: TERRAIN SUSCEPTIBILITY TO TRIGGER SHALLOW PLANAR LANDSLIDE ON STEEP SLOPES: a geo-hydroecological approach at D'Antas creek basin, Nova Friburgo (RJ - Brazil)., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-493, https://doi.org/10.5194/icg2022-493, 2022.

Pedro Lima, Stefan Steger, Helene Petschko, Jason Goetz, Michael Bertagnoli, Joachim Schweigl, and Thomas Glade

Many examples of regional scale statistical landslide susceptibility assessments can be found in scientific literature. A real-life application of these maps for spatial planning decisions is less common. As result of the MoNOE research project (Method development for landslide susceptibility modelling in Lower Austria), a landslide susceptibility map has been created. Since 2014, this map is constantly used by provincial spatial planners and geologists to guide strategic settlement development in Lower Austria (approx. 19200 km²). Resulting from a multi-temporal inventory of 12,889 slides, a generalized additive model (GAM) was applied to predict the landslide susceptibility using a variety of meaningful morphological and geo-environmental predictors. These easily-applicable, local-scale (1:25,000) landslide susceptibility maps consist of three susceptibility classes. The three classes correspond to low landslide susceptibility (covering 78% of all pixels within the study area), moderate (16% of all pixels) and high (6% of all pixels). Although well accepted by the stakeholders, a few important questions recently arise: a) Is this map able to correctly predict new landslide events that occurred after the implementation of this map? b) With the inclusion of these new samples, is the terrain susceptibility still the same? c) If the terrain susceptibility has changed with the inclusion of the unused (partly recently mapped) samples, why and to what extent?

By aiming to answer these questions, a review project named MoNEW is currently in place, which has the overall objective to quantify the accuracy of the MoNOE spatial predictions. The new landslides were obtained from two main different sources: 1) recently occurred damage related landslides from a cadaster of landslide events (in German: “Baugrundkataster"), and 2) landslides mapped from hillshades of a high-resolution LiDAR DTM. Based on these new landslides, the final quality of MoNOE will be explored and the landslide susceptibility recalculated to identify potential differences. Therefore, the identical MoNOE methodological design will be applied to ensure comparability and quality control. Changes in the spatial prediction will be quantified and deeply explored.

First exploratory analysis has demonstrated that most of the new landslides occurred within the highest landslide susceptibility class, indicating an apparent good ability of the past MoNOE susceptibility model to predict these landslides. Depending on the inventory source, 34 to 64% of the landslides occurred within the higher susceptibility class (this percentage was 70% by design in the original MoNOE project). This variation might be explained by the positional accuracy and mapping methodologies of the new landslides. Additionally, it was observed that most of the new landslides occurring in other less susceptible classes (i.e., “low” and “moderate”) were actually located in close proximity to the highest susceptibility class. Given the applicability scale of the MoNOE landslide susceptibility map (1:25,000), these (mostly very low) quantified distances between the landslide locations and the high susceptibility pixels might be inside of the new landslide mapping accuracy. However, how much the landslide susceptibility of the terrain might change with the addition of these new samples is currently under analysis.

How to cite: Lima, P., Steger, S., Petschko, H., Goetz, J., Bertagnoli, M., Schweigl, J., and Glade, T.: How well do landslide susceptibility maps hold up over time? Reviewing the accuracy of maps implemented for spatial planning in Lower Austria, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-154, https://doi.org/10.5194/icg2022-154, 2022.

Martin Mergili and Jan-Thomas Fischer

First approaches to analyze the propagation of hazardous, extremely rapid, landslides go back at least to the 1930s, when data-driven approaches such as angles of reach were used to estimate runout distances. Various much more sophisticated tools for the simulation of flow-type landsides including debris flows or rock avalanches, or cascading effects involving more than one type of phenomenon, have been developed since then, particularly throughout the last two decades. They build on increasingly complex physical-mathematical models, starting from comparatively simple and straightforward, depth-averaged Voellmy-type mixture models, moving to still depth-averaged two- and three-phase models able to simulate the interaction of landslides with water bodies, and currently proceeding to highly complex and highly flexible full 3D models. Phenomena such as erosion, entrainment, deposition, phase separation, or non-hydrostatic effects are increasingly well understood and incorporated into operational mass flow simulation tools.

However, this trend of increasing model complexity, supported by increasing physical process understanding and enhanced computational capacities, is not necessarily in line with the demand by natural hazard practitioners, who need capable but easy-to-handle simulation tools for their work. Besides the computational costs, it is mainly the multitude of often unknown, rather conceptual model parameters representing a barrier for practitioners towards using the more or even the most advanced approaches. Further, more complex models do not necessarily provide more accurate results than simpler ones, this always depends on the scope, purpose, and phenomenon. If only estimates of runout distances or impact areas are needed, very simple data-driven models may do the work. Even when it comes to flow thicknesses, velocities, or impact pressures, ordinary debris flows may still be better represented by comparatively simple mixture models than by parameter-hungry two- or three-phase models. Yet, more complex models are needed for more complex processes such as landslide-lake interactions or other types of process chains with dynamically changing material composition. Therefore, intelligent approaches have to be found to find an appropriate balance between simplicity and complexity.

Mainly based on seven years of experience with the depth-averaged multi-phase mass flow simulation framework r.avaflow, we will discuss the main challenges and ideas to find a useful balance between simplicity and complexity in the simulation of landslide runout.

How to cite: Mergili, M. and Fischer, J.-T.: Simplicity vs. complexity – a long-standing challenge in the simulation of landslide runout, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-474, https://doi.org/10.5194/icg2022-474, 2022.

Laurie Kurilla and Giandomenico Fubelli

It is widely accepted that climate changes will affect slope instability, and the presence and  prevalence of landslides are expected to be exacerbated.   Many areas of the world are experiencing increases in minimum, mean, and maximum temperatures and more frequent heavy precipitation.  Due to both climate change and projected population and urban growth, it is reasonable to assume the impact of debris flow  hazards will increase.  

With climate change and increasing temperatures, the likelihood of increased forest fires leads to an increased likelihood in post-fire debris flow frequency in those burn areas where other debris flow predisposing factors exist and rainfall amounts required to induce debris flows decrease. 

Future debris flow susceptibility models (RCP 2.6 and RCP 8.5) were developed and augmented with future wildfire probability, and areas of potential glacier retreat, both of which can subsequently act as amplifiers to global debris flow susceptibility.  The resulting debris flow susceptible areas are projected against future population and urbanization centers for a spatial view on human vulnerability.


How to cite: Kurilla, L. and Fubelli, G.: Future global debris flow susceptibility considering climate change, wildfire probability, and glacier retreat, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-69, https://doi.org/10.5194/icg2022-69, 2022.

Fils Makanzu Imwangana, Blaise Kamosi Zola, Joyce Mbiya Kangudia, and Serge Pangu Sanghy

The catchments draining the small plateau of Kimwenza in Kinshasa's south (DR Congo) are undergoing rapid and extensive peri-urbanization with limited planning. In this research, we study gully erosion processes that are associated with several infrastructure. The goal is to identify and characterize the primary erosion sites, to understand the factors of gully erosion, as well as to develop appropriate and effective methods for reducing gully erosion. To achieve this, we proceeded as follows: characterize the morphometry of the catchments, describe the surface water flow network, assess the runoff rates and propose an adequate drainage to collect runoff. Following the proliferation of street-gullies and the absence of water retention devices, it appears that these basins have a high drainage density ranging from approximately 1800 to more than 11000 m/km2, with a general average of approximately 6570 m/km2 following the field and laboratory investigations. Furthermore, all of the basins in this area have a somewhat rounded shape and a modest extension. This means they're more likely to have a quick rainwater concentration-time and, as a result, a quick response time. As a result, runoff flows can only be torrential, especially since the majority of this sector (80 percent) has slopes of more than 8%. The peak flow rate of surface flows can surpass 650 l/s/ha, according to an analysis of active showers and their intensities. Due to the soil's incoherent structure, which primarily consists of sands, 30 gullies were mapped, with an average length of 560 meters, a width of 27 meters, and a depth of 10 meters. Under these conditions, attenuating the gully phenomenon necessitates a significant reduction in runoff flows.

How to cite: Imwangana, F. M., Zola, B. K., Kangudia, J. M., and Sanghy, S. P.: Gully erosion associated with peri-urbanization: focus on the catchments in the south of Kinshasa, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-265, https://doi.org/10.5194/icg2022-265, 2022.

Yenny Alejandra Jiménez Donato, Pedro Lima, Maria Arango, and Thomas Glade

Landslides have caused significant losses in terms of lives and economic damage across the globe. Understanding their triggering factors, dynamics and potential impact is fundamental to implement more comprehensive disaster risk reduction measures to strengthen communities´ resilience. However, the lack of baseline data and impact information remains challenging. In order to improve our knowledge and to fill existing gaps between practitioners, disaster risk reduction institutions and other stakeholders, risk assessment and risk management projects can be appropriate starting points. Here, we present the results of a risk assessment analysis of three selected locations in Lower Austria.

The region of Lower Austria is particularly affected by landslides due to its complex geology and anthropogenic impact. The present research focuses on three earth mass movements with rotational characteristics in the regions of Erla, Behamberg, and Kreisbach. We developed different physical-based models to visualize different scenarios of potential runout areas and fluxes. Then, we performed an analysis of the cascading risk to estimate the potential economic damage in these regions to be able to propose adequate disaster risk reduction measures that could contribute to the region´s resilience.

How to cite: Jiménez Donato, Y. A., Lima, P., Arango, M., and Glade, T.: Risk assessment of earth mass movements in Lower Austria. Case study: NoeMotion Project, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-616, https://doi.org/10.5194/icg2022-616, 2022.

Coffee break
Chairpersons: Grace Alves, Susana Pereira, Tavares Alexandre Oliveira
Raquel Melo, José Luís Zêzere, Sérgio C. Oliveira, Ricardo A. C. Garcia, and Sandra Oliveira

The Lisbon Metropolitan Area (LMA) is a Portuguese administrative region that encompasses 18 municipalities and is characterized by a high risk of landsliding as a consequence of the high susceptibility and exposure of people and assets. Therefore, this work aimed to assess the evolution of exposure levels to landsliding in each municipality of LMA, based on three timesteps (1995, 2011 and 2018), through the following summarized steps: 1) Landslide susceptibility modelling for LMA using an inventory that contains 1268 landslides, mostly rotational and translational slides; 2) Assessment of the relationship between the number of existing buildings and the urban area represented in the official land use map in 2011; 3) Assessment of the population exposed to landslides in 2011 (using Census data) within and outside the urban areas, based on the dasymetric distribution approach; 4) Backward and forward projection of population exposure to landsliding in the years of 1995 and 2018, for which official land use maps are available. Projections are based on relations found in 2) and 3). Overall, the results show that population exposure to landsliding has increased over time in LMA, but differently depending on the municipality considered. The relations found allow to estimate future population and assets exposure based on scenarios of urban expansion and population growth.

S.C. Oliveira was financed by the Portuguese Foundation for Science and Technology, I.P., under the framework of the project BeSafeSlide Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017). Ricardo A. C. Garcia was financed by the project Riskcoast - Development of tools to prevent and manage geological risks on the coast linked to climate change (SOE3/P4/EO868, Interreg Sudoe). CEG Research Unit UID/GEO/00295/2019.

How to cite: Melo, R., Zêzere, J. L., Oliveira, S. C., Garcia, R. A. C., and Oliveira, S.: Assessing exposure changes to landsliding in Lisbon Metropolitan Area, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-625, https://doi.org/10.5194/icg2022-625, 2022.

Extreme climate events and food security – a study case in the highlands of Rio de Janeiro, Brazil
Ana Paula Turetta and Ana Luiza Coelho Netto
Ana Luiza Coelho Netto, Manoel Fernandes, Flavio Nunes, Guilherme Bertassoni, Letícia Bolsas, Ana Carolina Facadio, Isadora Mefano e Silva, Aydam De Paula, Tomas Duek, Gabriel Thaumaturgo, and Luna Moreno

In the top of the Serra do Mar, at Rio de Janeiro state, the historic city of Petropolis has a long history of disasters related to extreme rainfall induced landslides and floods, which have become increasingly impactful in association with disorderly urban growth. The last critical event occurred on February 15, 2022, causing 236 deaths and major economic losses. A total number of 149 landslide scars were mapped with the support of a World View 3 satellite image from February 17th. These landslides reached a total area of 37 km2, being more concentrated in the central part of the city, especially in the neighborhoods of Alto da Serra (Morro da Oficina), Chácara Flora (Morro do Turco) and Vila Felipe. The critical rains were spatially non-uniform, varying between 100 and 260 mm, in just 3 hours (between 16:00 and 19:00 hours); the highest number of landslides occurred when rainfall exceeded 180 mm (77.2%). Taking into account the geometry of the slopes, it was observed that 52% of these landslide scars occurred on slopes of converging water flows; 37% on divergent slopes and only 17% on planar slopes. Two types of landslide mechanisms prevailed: shallow planar slides and debris flows, which increased flooding in the rivers that drain the city. These rivers were artificially narrowed throughout the city's history, since the 19th century. The forest remnants, although highly degraded, functioned as natural dams for many landslides (45%), reducing the spread of sediment to the valley bottom.

How to cite: Coelho Netto, A. L., Fernandes, M., Nunes, F., Bertassoni, G., Bolsas, L., Facadio, A. C., Mefano e Silva, I., De Paula, A., Duek, T., Thaumaturgo, G., and Moreno, L.: The most recent disaster related to extreme rainfall induced landslides and floods: Petropolis, Rio de janeiro state, SE-Brazil., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-628, https://doi.org/10.5194/icg2022-628, 2022.

Flood hazard and risk assessment
Niki Evelpidou, Anna Karkani, Maria Tzouxanioti, Evangelos Spyrou, Theodore Gavalas, Giannis Saitis, and Alexandros Petropoulos

Greece, as the rest of the Mediterranean countries, faces wildland fires every year. Besides their short-term socioeconomic impacts, the ecological destruction and the loss of human lives, forest fires also increase the burnt areas’ susceptibility to floods, as the vegetation, which acted in a protective way against runoff and soil erosion, is massively removed. Among the most severe wildland fire events in Greece were those of summer 2021, which were synchronous to very severe heat waves that hit the broader area of the Balkan Peninsula. More than 3,600 Km2 of land were burnt and a significant amount of natural vegetation was removed. Four of the burnt areas are examined in this work, namely Attica, Northern Euboea, the Peloponnese, and Rhodes in order to assess their susceptibility to future flood events. The burnt areas were mapped, and their geological and geomorphological features were studied, while flood risk assessment was accomplished through logical rules applied in G.I.S. In this work we present the results of the flood risk assessment.

How to cite: Evelpidou, N., Karkani, A., Tzouxanioti, M., Spyrou, E., Gavalas, T., Saitis, G., and Petropoulos, A.: Assessment of fire effects to flood susceptibility: the case of the summer 2021 forest fires in Greece, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-278, https://doi.org/10.5194/icg2022-278, 2022.

Sayantan Das, Pritam Kumar Santra, Abhijit Das, Sajal Mondal, Sunando Bandyopadhyay, and Kalyan Rudra

The Ganga–Brahmaputra–Meghna Delta (GBMD) at the northern apex of the Bay of Bengal, is the world’s largest in respect of area (c. 120 × 103 km2) as well as annual discharge of sediments (c. 109 t). Contributed by the Ganga River and its numerous distributaries, the southwestern part of the GBMD is known as the Ganga Delta which spans over a number of districts in Bangladesh and West Bengal (India). The Indian state of West Bengal occupies the western portion of the GBMD, where the delta plains drained by the Ganga and its distributaries measure 42,371 km2. The estimated population residing in this region in 2021 is about 76 million. The Ganga Delta is completely enveloped by the alluviums deposited by the floods and channel deposits in the last 10,000 years. Nearly every major river in the region is embanked on their both flanks to prevent overspilling during the high stages in the monsoon season (June–September). Floods occur nonetheless in years of exceptionally high rainfalls, often brought about by tropical cyclones, when these embankments are breached or overtopped by the river water.

This study aims to delineate the flood-prone zones of the Gangetic West Bengal (GWB) based on the highest floods that occurred between 1995 and 2020, and to extract data on extension, land use and resident population of the flood-susceptible area on different administrative levels.

Using five highest-magnitude flood events for five overlapping zones, it is found that 33% of the GWB is susceptible to inundation by floodwater. Overlying the inundation area over 226 administrative blocks of 14 districts of the region reveals that 51 highly populated blocks located close to the principal rivers are susceptible to flooding. The deepest flood localities of the east–central GWB noticeably coincides with the blocks with highest percentage of inundated area (>50%) and also with the blocks having fairly large population size. 77 out of 226 blocks are susceptible to inundation of 50% or more of their total area. On a higher level, if the distribution of flood inundation across the districts constituting the GWB is considered, the districts of Nadia and Murshidabad are found to have relatively more inundation area, with almost 16% of the total flood-susceptible area of the GWB lying within each of these districts, followed by Purba Medinipur (13%) and Malda (11%). The study connotes that floods and the region’s cultural landscape—consisting of farmlands, habitations, and lines of communications—are closely related. Floods occur despite all human endeavours to prevent them, affecting approximately 14,500 km2 area and 18 million people.

How to cite: Das, S., Santra, P. K., Das, A., Mondal, S., Bandyopadhyay, S., and Rudra, K.: Demarcation of Flood-Prone Zones in the Indian Part of the Ganga Delta Based on the Highest Floods between 1995 and 2020, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-654, https://doi.org/10.5194/icg2022-654, 2022.

Fluvial Hazard Zone (FHZ) Mapping for Stream Corridor Management
Michael Blazewicz
Lunch break
Chairpersons: Ana Luiza Coelho-Netto, Tavares Alexandre Oliveira, Susana Pereira
Giovanni Forte, Melania De Falco, Nicoletta Santangelo, and Antonio Santo

A flash flood is a very quick increase in the discharge of a stream, generally caused by short duration and high intensity rainfalls. This phenomenon is very frequent in Europe and in Italy too, where generally occurs in small catchments with short response time, causing many damages in the outlet zones. In historical times, numerous flash flood events occurred in Campania Region (Southern Italy), with an increase in frequency in the last decades, associated with the present trend of climate change. 
This note summarizes the results of the last ten years studies on the flood events occurred in the torrential basin-fan systems of the Campania region, aiming to contribute to the assessment of the hazard and risk condition. In these watersheds flash flood events resulted in a series of phenomena, passing from debris flow to debris flood and water flood, which produced serious damage to urban centers and cultivated areas. Unfortunately, these catchments are often not monitored and the lack of information on rainfall and flow data makes more difficult to apply hydrological and hydraulic models to evaluate hazard and risk. Hence, in these settings, geomorphological study and post-event field campaign have been useful to identify the flooding prone areas and the magnitude of the occurred events. The latter has been achieved by the estimate of the maximum water heights of the flow, of the thickness of eroded and/or deposited material and of the relative particle size of the deposits and finally of the volumes. The acquisition of remotely sensed images by means of UAV (drones) enhanced the field surveys to obtain these data. More in detail, the integration of morphometric analysis in GIS, with field and remotely sensed data permitted to draw several thematic maps, that together with the identification of the damage states have been exploited to produce empirical vulnerability curves for these events. 
Collecting such data represents a fundamental issue for calibrating hydraulic flow models for the hazard evaluation, while the development of vulnerability tools can be adopted to assess the risk and define the best mitigation strategies.


How to cite: Forte, G., De Falco, M., Santangelo, N., and Santo, A.: Geomorphological approach to flash flood hazard and vulnerability evaluation in torrential basin-fan systems in Campania (South Italy), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-146, https://doi.org/10.5194/icg2022-146, 2022.

Eric Fouache, Stéphane Desruelles, Christian Gorini, Nicoletta Bianchi, and Adrien Marchiel

The passage of the storm Alex favored on October 2, 2020 the triggering of very intense rainfall in the coastal valleys of the Alpes-Maritimes, including that of the Roya, which caused many devastating hydro-geomorphological processes, mainly floods and landslides. The destruction, which has affected modern and ancient infrastructures, has been considerable, with dramatic social and economic consequences. The processes have also unearthed archaeological remains dating from the Bronze Age to the modern era.

Meteorological analyses confirm the exceptional character of this Mediterranean episode, while marine sedimentary records made in the deltas of the Var crossed with C14 dating of ancient torrential deposits identified in the Roya watershed indicate a return time of about half a millennium.

The major difficulty in the case of the Roya is that the reactivation of the entire late glacial active band has upset the geometry of the river's major bed compared to what it was before Storm Alex. In the areas of torrential deposits, there is a widening of the bed of the order of 1 to 10 and a rise of several meters in the height of the alluvial table. This major modification implies that before defining the new risk zones and deciding on the reconstruction of the infrastructures, the impact of the floods recorded in the past should be modeled according to this new geometry of the bed. Moreover, in the context of global warming, it is not excluded that we observe a higher recurrence of events such as storm Alex. We present the preliminary results of our research program (STORY: "Risks and societies in the Roya basin: multidisciplinary and multi-temporal analysis, from the slopes to the sea") and discuss the difficulties in reconciling the perceptions of the different actors, the necessary time of research not always easy to articulate with the urgency of reconstruction and the vital need to open up sectors that otherwise risk being permanently abandoned by the populations.

Keywords: Holocene, flash floods, climate change, risk management


How to cite: Fouache, E., Desruelles, S., Gorini, C., Bianchi, N., and Marchiel, A.: Evaluation of the return time of flash floods generated in the Roya Valley (Alpes Maritime, France) on October 2, 2020: What challenges does this type of event pose for risk management?, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-7, https://doi.org/10.5194/icg2022-7, 2022.

Lukáš Michaleje and Miloš Rusnák

The flood hazard is affected by several natural factors, such as impermeable soil, depressions and unsuitable land cover. Human impact is also not negligible in the river basin. We can observe inappropriate tillage accelerating erosion or storage of various materials and waste in the immediate proximity and directly in watercourses. The size of the inundation area is affected by the capacity of the watercourse and its ability to transmit a flood wave.

Our medium-term goal is to enrich the preliminary flood hazard assessment with watercourse channel properties such as flow, depth and capacity. We want to determine these parameters quickly for large areas using detailed data. The sub-goal on which this paper is focused is the detection of the watercourse channel as an area. Hence we are focused on detecting the right and left bank of the channel. We test our methodology in a selected area of Slovakia with an area of 320 km2. The input is LiDAR data with an average density of 32 points per m2 and average height accuracy of 0.05 m. From the above data, we created a digital elevation model (DEM) with a cell size of 1 m and derived layers such as slope, topographic position index, topographic wetness index, and topographic openness. Subsequently, we used these layers in the machine learning random forest (RF) tool for the supervised classification of the spatial limits of the channels represented by the banks. We adjusted the classification output from other depressions or potential misclassification based on proximity analysis and a morphometric approach. For validation, we use a manually edited layer of channel lines based on detailed orthophoto from 2017 and DEM.

Keywords: LiDAR, channel detection, channel morphology, banks, random forest


How to cite: Michaleje, L. and Rusnák, M.: Semi-automatic channel detection based on detailed LiDAR data for preliminary flood hazard assessment, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-593, https://doi.org/10.5194/icg2022-593, 2022.

Shreya Bandyopadhyay and Sunil Kumar De

Nagavali river has come into the limelight since 2005 because the Govt of India had announced for constructing ten hydro-powers projects in the river basin. Nagavali river is flood-prone. The river flows through a complex structural longitudinal valley between eastern and western ridges in Orissa and Andhra Pradesh before meeting with the Bay of Bengal. Out of those ten project sites, two sites, i.e., at Hathipahar region in Rayagada, Orissa and the Thotapalli village in Vizianagaram District, Andhra Pradesh, have been selected for the risk assessment.  The Hathipahar region is situated over a piedmont slope of the eastern ridge (formed of Khandelite-granite), and the Thotapalli site is located over a rolling plain. In July 2006, due to torrential rainfall and flash flood, the under constructed dam at Hathipahar collapsed. The valley experienced vast changes in channel shifting (about 550 meters), headword erosion, valley incision and soil loss. The Thotapalli site was not affected, and thus, the construction was completed in 2010. Consequent flood events of   2011 and 2015 caused massive erosion and enlargement of the reservoir from 2.1 sq. km. to 9.16 sq. km, and the upstream course of the river merged with the reservoir.

The present research aims at estimating damage and assessing socio-environmental risk along with these two sites. For assessing flood risk, the SCS-CN model has been used and validated with real-time discharge data, land use-land cover change, spatio-temporal variations in channel width-depth, and sedimentology. Google Earth and SRTM DEM have been used for detecting such changes. Field surveys have been carried out to prepare a micro-level elevation model, damage estimation and lithological formation of the area. The research also focuses on assessing the possibility of continuing the proposed hydro-power sites since the existing sample sites are already experiencing massive erosions and destructions.

Keywords: piedmont slope, flash flood; hydro-power project; SCS-CN model; risk assessment

How to cite: Bandyopadhyay, S. and De, S. K.: Risk Assessments of Hydro-Power Projects along the Nagavali River, Odisha-Andhra Pradesh, India, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-222, https://doi.org/10.5194/icg2022-222, 2022.

Anselme Muzirafuti, Giovanni Randazzo, and Stefania Lanza

Coastal erosion worldwide affects seaside resorts, linear infrastructures (promenades, railways, and coastal roads), small entrepreneurs’ activities, and local economies. On the other hand, the development of these human activities often leads to coastal dynamics and coastal erosion in general. With ever-changing environmental conditions due to both climate change and human activities, coastal area and particularly sandy beaches are being subjected to phenomenon of different kinds.  Local authorities and scientific communities have been working and searching for solutions to contrast these processes. Different solutions have been adopted regarding beach protection including hard engineering structures, seawalls, and beach nourishment. However, these solutions have been proven not to be cost effectives and sometimes they have been inefficient in terms of sustainability and resiliency. Within the last 50 years, the pocket beach of San Vito lo Capo located on the Northwestern coast of Sicily has undergone repetitive modifications in terms of beach morphology and grain sediment sizes. Moreover, this beach has been identified as an important tourist destination and contributes efficiently on local economic development.

The aim of this study is to conduct a comprehensive geomorphological and sedimentological analyzes in order to determine its natural resilience and eventually propose solutions to increase its protection and its sustainable management.

To achieve this objective, emerged and submerged sediments have been sampled and analyzed, single beam echo sounding and AUV photogrammetry surveys have been performed for morpho-topographic analyses, and a morpho-dynamic shoreline analysis has been conducted based on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite images acquired from 2001 to 2017.

The results indicate that the sediments tend to move along the coastline generally from center to the western part of the beach with no loss of the sediments for the beach. Furthermore, wave penetration and wind analyses revealed the presence of non-destructive wave with maximum penetration reaching the urban area.  Such ability of the beach to dissipate the wave energy can be enhanced by using sever beaches to dissipate the winter waves. While morpho-dynamic evolution of the beach can be managed by establishing a seasonal re-equilibrium of internal sediment distribution.


How to cite: Muzirafuti, A., Randazzo, G., and Lanza, S.: A Resilient Solution for Management of Beach Tourist Destination (NW Sicily, Italy), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-288, https://doi.org/10.5194/icg2022-288, 2022.

Galina Pryakhina, Valeriia Rasputina, and Sergey Popov

Catastrophic outburst floods are formed due to the destruction of moraine dams of the periglacial lakes. Outburst floods are dangerous hydrological phenomena that cause the large material damage and often lead to human losses. These dangerous hydrological phenomena are sudden and fleeting due to this the organization of observations is extremely difficult and unsafe. To study these hydrological phenomena the methods of mathematical modelling and physical modelling are most often used. This paper presents a methodology developed by the authors for calculating the outburst flood hydrograph, which is formed during the destruction of an earth dam due to water overflow through the crest. The methodology was verified using the results of physical experiments carried out on a special experimental setup and in natural conditions. The quantitative characteristics of outburst floods obtained as a result of physical experiments were used for comparison with the data obtained in mathematical modelling. Comparison of the simulated outburst flood hydrographs with obtained hydrographs as a result of physical experiments showed their convergence. The paper also presents the results of numerical experiments, which allowed to obtain the dependence of the discharge on the initial size of the breach, the specific gravity of the material from which the dam is built, the percentage of clay in this material and the roughness coefficient value. The results of the work were considered satisfactory and demonstrated the efficiency of the calculation method.

The work was supported by the RFBR grant No. 20-05-00343 A "Identification of the features of the outburst process of lakes of oases of Antarctica based on field research data and mathematical modeling."

How to cite: Pryakhina, G., Rasputina, V., and Popov, S.: Modelling of the outburst flood hydrograph due to the moraine lakes outbursts, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-73, https://doi.org/10.5194/icg2022-73, 2022.

Karabi Das and Kanailal Das

Abstract: Vulnerability not only establishes the relationships people have with their environment but also links the social forces and institutions and the cultural values that sustain them. Physiographically, a deltaic plain, the Sundarban region is a dynamic ecosystem which frequently witnesses physical and social vulnerability brought about by natural hazards like tropical cyclones resulting in saltwater flooding. The Bay of Bengal basin records the highest number of tropical cyclones globally. About 8 storms with sustained wind speeds more than 63 km/hr form in the Bay of Bengal, of which, 2 become tropical cyclones. Cyclone Yaas was identified as a very severe cyclonic storm, originally formed as a tropical disturbance identified by the India Meteorological Department (IMD) on 23rd May 2021. Yaas made it’s landfall at Dhamra of Orissa state of India, on 26th May 2021, coinciding with spring tide. Coastal flooding was reported from Maipith, Bhubaneswari village panchayats along the rivers Matla, Thakuran and Nimania of Kultali community development block, Dhaspara, Sumatinagar, Kastala, Kochuberia, Mahishamari, Muriganga, Shilpara village panchayats of Sagar community development block, Amrabati, Lakshmipur, Fraserganj of Namkhana community development block, Gobardhanpur, Mridangabhanga, Krishnadaspur, East Chintamanipur, Kumarpur of Patharpratima community development block. Within the last 7 years, capacity building in the form of concrete houses under Indira Awas Yojana, cyclone shelters, metalled roads has increased. However, in the time of disasters even the settled portions get submerged in water as the settled portions are located at a lower height than the high water level. The local demand of concrete embankments is debatable and in some places the use of brick pitching, brick block pitching, porcupine mesh and Aila bandh have not been successful in preventing breaching and consequent saltwater inundation. Vulnerability is severe in case of Basanti, Gosaba, Kultali, Namkhana, Patharpratima community development blocks and high in case of Kakdwip, Sagar and Hingalganj community development blocks (Sahana et al, 2019). This paper takes all these phenomena into account and provides certain probable mitigation strategies which include the mapping of erosion accretion sites by comparative analyses of toposheets and satellite images, site specific mangrove aforestation, improved construction of embankments following expert and local opinions, revival of the decayed creeks to prevent waterlogging at times of disaster and rehabilitation of people from sites of continuous erosion to community shelters located at elevated areas alongwith tidal river management as practiced in Bangladesh where the rivers are temporarily allowed their spill areas.



How to cite: Das, K. and Das, K.: Vulnerabilities in Post Yaas Environment and Probable Mitigation Strategies: Case Studies from Selected Sites, Sundarban, India, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-341, https://doi.org/10.5194/icg2022-341, 2022.

Eusébio Reis, Jorge Rocha, Andreia Silva, Jorge Trindade, José Luís Zêzere, Susana Pereira, Sérgio Oliveira, Ricardo Garcia, and Pedro Santos

All populations are, at some level, directly or indirectly affected by climate change. Sea level rise (SLR) changes can have strong effects in population exposure conditions in coastal areas, being one of the most critical environmental threats in 21st century.

Portugal, like most coastal countries, have high concentrations of settlements, population and activities near the coast, situation that has been intensified from the second half of the 20th century and during the 21st century. Despite of mitigation and adaptation measures based on SLR scenarios, Portugal already faces the expansion of SLR hazard zones, with a rising rate of 2.1±0.1 mm/year between 1977 and 2000 [1], and an increasing exposure and vulnerability to coastal flooding. Moreover, the IPCC/NASA SSP5 scenario for 2100 estimates values between 0.74m e 0.81m for the Portuguese coastline [1]. In addition, an increasing frequency of extreme sea level events is expected, namely associated to the SSP5-8.5 [2]. Despite 30 years of regulatory land use planning that incorporates hazard preventive measures and restrictions, Portuguese coastal communities have long before occupied SLR hazard zones in an ongoing process. In this context, knowledge of processes and impacts in the past is fundamental to assess future conditions and consequences, based on SLR scenarios.

The main goal of this work is the diagnosis of land use land cover (LULC) changes focused on built-environments spatiotemporal dynamics (1995 to 2018) in a SLR context. The results will support exposure assessment for 2040, 2070 and 2100 scenarios for the Portuguese mainland coastal zone at a sub-municipality level.

This work uses a validated SLR hazard baseline [1] as reference to measure the recent and actual exposure of the potentially elements at risk. For LULC one used the official cartography (1995 to 2018), produced by the General Directorate for Territorial Development in Portugal.

To assess the amount and patterns of LULC changes, memoryless stochastic methods are used, extracting two categories of data:  i) the persistence, gain, loss, total change, absolute value of net change, and swapping tendency, as well several ratios; ii)   measurement of systematic and random LULC changes by using the off-diagonal entries of the transition matrix for the significant inter-class transitions detection.



[1] https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool.

[2] IPCC (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. V. Masson-Delmotte, P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, B. Zhou (eds.), Cambridge University Press.



To project HighWaters (EXPL/GES-AMB/1246/2021). Pedro P. Santos is financed by FCT I.P. (CEECIND/00268/2017). This work was financed by the Research Unit UIDB/00295/2020 and UIDP/00295/2020.

How to cite: Reis, E., Rocha, J., Silva, A., Trindade, J., Zêzere, J. L., Pereira, S., Oliveira, S., Garcia, R., and Santos, P.: Spatial and temporal changes in urban fabric exposure to Sea Level Rise, from 1995 to 2018, in mainland Portugal, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-495, https://doi.org/10.5194/icg2022-495, 2022.

Display time: Mon, 12 Sep 09:00–Tue, 13 Sep 19:00

Poster: Tue, 13 Sep, 10:45–11:00 | Poster area

Chairpersons: Ana Luiza Coelho-Netto, Tavares Alexandre Oliveira, Maria Carolina Villaça Gomes
Avalanche hazard
Flood hazard and risk assessment
Landslide susceptibility, hazard and risk assessment
Neha Chauhan, Yaspal Sundriyal, Anil D. Shukla, and Vipin Kumar

Alaknanda River valley in the NW Himalaya has been subjected to frequent landslides of different types and sizes owing to its geographical position and topography that receive extreme rainfall from Indian Summer Monsoon and Western Disturbance. Such landslides, mainly debris flow, pose a growing risk to the rapidly growing human population and result in huge sediment influx into river valleys that contribute to fluvial regime changes.

In this study, we have simulated runout characteristics of four debris-flow landslides based on inputs from field observation and high-resolution satellite imagery analysis. These landslides are situated along the river valley and accommodate villages/towns near the crown/toe of landslides. Hillslopes constituting these landslides are mostly made up of schist/quartzite/gneissic rock mass, and regional thrust fault passes in the vicinity, contributing to shearing. A Voellmy-Salm fluid-flow continuum model was used to perform debris flow simulations. Frictional, turbulence, and cohesion parameters are probabilistic to eliminate uncertainty, caused mainly by selective input values.

Results indicated that debris flow from these landslide slopes might reach up to 250 m upstream and downstream along the river during extreme rainfall events, contributing to sediment influx, with a flow velocity and height of 5-10 m/sec and 6-13 m, respectively. Further, the human population residing near the crown/toe of these landslides might be subjected to ground instability and subsequent failure due to shear strength loss. Such predictive studies contribute to the effective evaluation of growing hazards associated with hillslopes during extreme rainfall events. 

Keywords: Debris flow; Rainfall; Himalaya

How to cite: Chauhan, N., Sundriyal, Y., Shukla, A. D., and Kumar, V.: Ascertaining potential debris-flow landslides and associated hazards, NW Himalaya, India, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-10, https://doi.org/10.5194/icg2022-10, 2022.

Pablo Valenzuela, Teresa Vaz, María José Domínguez-Cuesta, Susana Pereira, José Luís Zêzere, Victoria Rivas, Juan Remondo, Jaime Bonachea, Alberto González-Díez, Txomin Bornaetxea, Javier Sánchez-Espeso, Eliezer San Millán, and Lucía Francos

Landslides, common and widespread phenomena in the north of the Iberian Peninsula, represent a relevant cause of geomorphological hazard, in particular in some mountainous and densely populated areas of Portugal and Spain. Rainfall is the most relevant landslide-triggering factor in these territories within the Iberian Atlantic Arc, characterized by an Oceanic climate with some areas of Mediterranean influence and average annual precipitation in the range 900-1900 mm.

Since the 1980s, several research groups have been developing work lines focused on the study of the temporal occurrence of landslides and its relationship with different precipitation patterns by calculating empirical rainfall thresholds. Their computation is mainly based on the statistical analysis of individual or multiple rainfall events which caused landslides in the past. A wide variety of approaches considering different data sets, methodologies and spatio-temporal scales have been conducted. However, some results have not been greatly disseminated or have remained unpublished, hampering the overall analysis of research carried out up to date.

The present work aims to review the literature related to empirical rainfall thresholds in the north and northwest of the Iberian Peninsula with the objectives of (i) synthesizing existing data, (ii) establishing comparison criteria that consider the different characteristics of each study area, data set, and methodology used, and (iii) addressing a joint analysis. The study zones are located the north of Portugal (Oporto, Vila Real-Douro Valley and Casal Soeiro areas) and in the north of Spain (Asturias, Cantabria and Guipuzcoa and Vizcaya provinces within the Basque Country).

The review revealed that over 80 landslide rainfall thresholds have been compiled, most of them defined through equations. To describe the critical rainfall-triggering conditions, 75% of the thresholds considered the accumulated precipitation during a specific period, while the remaining 25% considered the precipitation intensity. Critical accumulated rainfall in 24 hours showed appreciable variations in the range 20-140 mm in Spain and 20-80 mm in Portugal. Almost 70% of the thresholds showed regional representativeness; the remaining rest showed local representativeness.

How to cite: Valenzuela, P., Vaz, T., Domínguez-Cuesta, M. J., Pereira, S., Zêzere, J. L., Rivas, V., Remondo, J., Bonachea, J., González-Díez, A., Bornaetxea, T., Sánchez-Espeso, J., San Millán, E., and Francos, L.: Empirical rainfall thresholds for the triggering of landslides in northern Portugal and Spain: a preliminary overview, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-143, https://doi.org/10.5194/icg2022-143, 2022.

Nabanita Sarkar, Angela Rizzo, and Mauro Soldati

The adverse effects of ongoing global warming on coastal areas are quite evident worldwide and the Mediterranean region is a perfect example of this scenario, being considered as a hotspot of climate change since in this area the short- and long- term impacts are expected to be stronger than in other areas of the world. In fact, the recent published “Assessment Report on Climate and Environmental Change in the Mediterranean” highlights that this region is warming 20% faster than the global average and that the current changes and future climate scenarios will point to a significant increase in climate-related risks during the next decades. In this context, the Mediterranean coastal areas are particularly prone to be affected by direct and indirect climate-related impacts including an increase in sea surface temperatures and ocean acidity, northward migration of marine species, changes in phytoplankton communities, and losses of ecosystem services. Many of these expected phenomena are related to coastal processes such as erosion, flooding, and saltwater intrusion, which, in turn, are strongly affected by increase in mean sea level, the most important slow-onset consequence of climate change. In the last decades, several studies have been focused on the evaluation of climate change impacts on coastal areas at the global and regional scale and, in particular, on the assessment of vulnerability and risk levels using different methodological approaches. On one hand, index-based methods are widely used being easy to be computed and providing stakeholders and planning authorities with useful and easy-to-read maps.  On the other hand, model-based approaches provided more detailed results but are less efficient in terms of time and computational efforts. With the aim of providing an updated state of art of the studies related to the assessment of both long- and short- term effects of climate change on coastal Mediterranean areas, with special reference to the methods and techniques applied for the evaluation of coastal vulnerability and risk, this work explores the available literature by searching Google scholar and Scopus platforms. In particular, the literature review was based on a number of keywords defined in the context of coastal hazard, vulnerability, and disaster risk reduction. The publications in close connection with the searched topics were selected and analysed. The results are shown in the form of graphs and maps, in order to highlight at the Mediterranean scale i) the most analysed coastal sectors, ii) the most common parameters used in the vulnerability and risk indices definition. Through this literature review, it becomes clear, how a sustainable management of coastal stretches would be possible through applying a holistic approach of risk assessment, which cannot ignore the interactions between multiple physical factors, related to social aspects, subaerial and marine processes. The key findings of the research emphasize how technological improvements and development of innovative methods for analysing the causes and effects of coastal risks sensitize local authorities to adopt relevant adaptation measures for coastal risk governance in the Mediterranean region. 

How to cite: Sarkar, N., Rizzo, A., and Soldati, M.: A literature review on the methods for climate related coastal risk assessment in the Mediterranean region, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-144, https://doi.org/10.5194/icg2022-144, 2022.

Francis Gauthier, Jacob Laliberté, and Tom Birien

Rockfalls are major natural hazard for road users and infrastructures in northern Gaspésie (Eastern Canada) where nearly 25 kilometers of road runs along 10 to 100 m high flysch rockwall. The Ministère des Transports du Québec (MTQ) has recorded more than 17 500 rockfalls that have reached the roadway since 1987, which represents a nearly permanent danger for users. In the late 90s, protective berms were erected to reduce the number of rocks reaching the roadway. Despite the efficiency of these infrastructures, more than a hundred events are still recorded each year. Based on previous studies showing that rock instabilities in this type of geology is strongly correlated with meteorological events, we used different machine learning methods (logistic regression, classification tree, random forest, neural network) to design the best operational rockfall prediction model. Three event variables based on different rockfall frequency and magnitude thresholds were created. 94 weather variables were used to explain and predict events. Results show that 24h to 120h mean daily temperature above 0oC and thawing degree-days are the most effective variables explaining the occurrence of winter and spring rockfall events. In summer, rainfall intensity is the most effective explanatory variable. The performance of the models has been optimized using a testing data set and then tested in an operational context using Environment Canada 24h and 48h HRDPS (high resolution deterministic prediction system) weather forecast model. A rockfall danger scale based on the probability of occurrence of medium and large magnitude rockfalls is proposed. These models can be used operationally as decision support tools to predict days with high event probability.

How to cite: Gauthier, F., Laliberté, J., and Birien, T.: Rockfall forecasting models along the roads of northern Gaspésie (Eastern Canada), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-174, https://doi.org/10.5194/icg2022-174, 2022.

Julio Garrote, Daniel Vazquez-Tarrio, Andrés Díez-Herrero, Miguel Gómez-Heras, and Javier Martínez

The occurrence of flash-floods affecting the Sta. María de Huerta Medieval Monastery is a recurrent process over time. The most recent examples date from 2015 and 2018, but evidences of previous historical flood episodes are available in documentary record (three flood events between 1761 and 1772). Although the Sta. María de Huerta Monastery is closed to the Jalón River, a tributary of Ebro River, flash-flood occurrence is mostly linked to a small tributary (Torrehermosa ravine) with a drainage basin smaller than 5 km2. During the afternoon of September 9th (2018), high intensity rainfall related to a summer convective cell caused a cumulative rainfall volume of roughly 100 l m-2. Rainfall duration was less than two hours and caused a flash-flood breaking the brick-wall in the south boundary of the monastery, so the flood finally affected the main monastery building. A wave of water and suspended sediment load (mainly silt and clay in size) penetrated through the entrance doors into the building, reaching a height above one meter in some of the rooms (church, cloister, refectory). The flash-flooding event finally only caused tangible damage that required cleaning of walls and furniture, as well as the replacement of some glass panes. However, if the occurrence of the flash-flood had coincided with the celebration of liturgical events, the damage to the attendees could have been significant.

For the detailed hydromorphological analysis of the September 9th 2018 flash-flood event, the first step was the incorporation of the monastery building structure (outdoor and indoor building walls, rooms doors…) with their related flat grounds, and surroundings (perimeter wall, secondary buildings…) into a detailed LiDAR derived DEM. Then, the hydrological module of Iber hydrodynamic software was used for hydrograph and sedimentograph simulation. The outcomes of this hydrological simulation were subsequently used in hydraulic modeling, where suspended sediment transport was into consideration. For the hydraulic analysis, two independent scenarios were considered: the first linked to the initial situation (the one existing on September 9th, 2018); and the second considering a proposal of measures for flood hazard mitigation including the installation of flood gates in the monastery doors.

Results for the scenario representing conditions existing on September 9th 2018 show a flooding extension covering the full monastery building with flow depths ranging from 0.25 meters until more than 1.0 meters, depending on the considered return period. Flow velocity values into the monastery do not increase flood hazard. These results, and specifically those located at the position of the entrance doors, were used to design the minimum dimensions of the flood doors. The results of the second scenario show only residual flows into the monastery building that are in the same range as model uncertainties. These results show how detailed hydromorphological analysis approaches can be applied to flood risk reduction in cultural heritage buildings, improving the design of mitigation measures.

Funded by spanish National Research Agency, research project PID2020-116896RB-C22 “Innovación en la respuesta preventiva a eventos direccionales hidrometeorológicos extremos en el patrimonio cultural”

How to cite: Garrote, J., Vazquez-Tarrio, D., Díez-Herrero, A., Gómez-Heras, M., and Martínez, J.: Hydromorphological modelling of the September 9th 2018 flash flood event at Medieval Sta. María de Huerta Monastery (Soria, Spain). A detailed hazard analysis for flood risk mitigation proposal., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-211, https://doi.org/10.5194/icg2022-211, 2022.

Jacopo Cinosi, Valerio Piattelli, Gianluca Esposito, Vania Mancinelli, Giorgio Paglia, and Enrico Miccadei

Earthquakes and consequent phenomena represent a major issue for human activities planning and fulfilment; within this framework, Earthquake-Induced Landslides (EILs) constitute major hazards, being often responsible for the greatest damages up to overshadowing those caused by the solely ground motion. Due to its geomorphological dynamics and strong seismicity, the Abruzzo Region (Central Italy) is severely affected by EILs, whose distribution results from the interaction between the seismic shaking and the local physiographic and geological-structural setting of the area. In this context, the present work focuses on the realisation of an EILs susceptibility map, following a heuristic approach combined with a statistical analysis, integrated using GIS technology. This approach leads to the identification of nine instability factors, including morphometric, lithological, geomorphological, and tectonic elements. These factors are analysed and assigned proper expert-based weights after the critical evaluation of literature data and available landslide inventories. Subsequently, they are combined into a preliminary susceptibility map wherein high/low numerical values correspond to a high/low propensity of the slope to fail. A statistical analysis is then executed on these values to derive the optimal number of classes by performing an unsupervised classification of preliminary susceptibility values. The total Within Clusters Sum of Squares (WCSS) and the Between Clusters Sum of Squares (BCSS) are hence computed, and the optimal number is derived by applying the elbow method. An absolute susceptibility scale is then introduced, with values ranging from the minimum to the maximum potential values of the area. Subsequently, statistics of clusters are analysed through violin plot diagrams and compared to classes of the absolute scale; in this phase, an algorithm is also applied to achieve the best differentiation among classes. The final map is created by grouping preliminary values in seven susceptibility classes ranging from very low to very high. The stepwise approach here presented has been applied to the whole Abruzzo Region, with ongoing specific site investigations in the areas severely affected by the 2009 L’Aquila earthquake and the 2016-2017 Central Italy seismic sequence. The applied methodology could constitute a scientific tool to better define situations that potentially lead to hazards following an earthquake and, consequently, to develop sustainable territorial management, loss-reduction measures, and post-earthquake reconstruction plans.

How to cite: Cinosi, J., Piattelli, V., Esposito, G., Mancinelli, V., Paglia, G., and Miccadei, E.: Earthquake-induced landslides susceptibility assessment of the Abruzzo Region (Central Italy): a geomorphological approach., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-255, https://doi.org/10.5194/icg2022-255, 2022.

Nino Krvavica, Bojana Horvat, Ante Šiljeg, Ivan Marić, Silvija Šiljeg, Fran Domazetović, Lovre Panđa, and Rajko Marinović

Flood hazard prediction is a critical component of flood risk assessment, flood risk management plans, and implementation of flood mitigation measures. In the EU, there is currently a growing interest in floods caused by extreme heavy rainfall, commonly known as pluvial floods. Due to the rapid development of computational and remote sensing technology, as well as the public availability of high-resolution spatial data, pluvial floods are now simulated using integrated hydrological-hydraulic approaches consisting of time-dependent 2D numerical models and so-called rain-on-grid approaches with spatially variable infiltration. In this paper, we will present the recent progress and methodological framework for pluvial flood hazard assessment in the city of Poreč in the northern coastal part of Croatia, focusing on the interpretation and modification of spatial input data, precipitation data processing, and numerical modelling of pluvial flooding. We show what spatial data were collected and improved, what spatial data were generated, how the precipitation data were processed for this purpose, and discuss some modelling aspects specific to pluvial flooding in urban areas. Finally, we present the results of the pluvial flood hazard assessment for the city of Poreč and its catchment area and provide some recommendations for further research.

How to cite: Krvavica, N., Horvat, B., Šiljeg, A., Marić, I., Šiljeg, S., Domazetović, F., Panđa, L., and Marinović, R.: Pluvial flood hazard mapping in coastal areas of Croatia, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-269, https://doi.org/10.5194/icg2022-269, 2022.

José Luís Zêzere, Eusébio Reis, Susana Pereira, Pedro Santos, Sérgio Oliveira, Ricardo Garcia, Raquel Melo, and Ana Rita Morais

This work aims to assess the landslide hazard, nowadays and at the end of the 21st century, considering the SSP2-4.5 and SSP5-8.5climate change scenarios. The exposure of residential buildings, roads and strategic equipment to landslide hazard is also assessed. The study area is a small alpine orogenic chain – the Arrábida - characterised by a complex geomorphology, developing along 35 km in the southern part of the Lisbon Metropolitan Area.

The landslide susceptibility was assessed using a statistical method (Information Value), using seven landslide predisposing factors: slope, aspect, slope curvature, topographic position index, topographic humidity index, lithology, and land use. These factors were crossed with a landslide inventory containing 4047 rainfall-triggered landslides occurred in 19 municipalities belonging to the Lisbon and Tagus Valley region, which includes the study area.

The obtained susceptibility model was cross-checked with 197 rainfall-triggered landslides that were inventoried in the Arrábida in 2012, based on aerial photo interpretation and fieldwork. The date of occurrence of most landslides is unknown, but we assume that the morphological maintenance of landslides in the landscape is less than 20 years.

The landslide susceptibility map was classified based on the slope breaks of the prediction-rate curve, and the current landslide probability was computed for each grid cell within each landslide susceptibility class.

Landslides in the Arrábida have been typically associated with intense rainfall episodes lasting a few days (5 to 15 days). The estimation of the future landslide probability considered the critical rainfall thresholds established for the Lisbon region by Vaz et al. (2018): (regression threshold, R= 5.5D +124.6; minimum threshold, R= 4.4D + 56.5, where R is the critical rainfall, and D is the number of consecutive days).

In a recent work, Araújo (2021) projected the critical rainfall thresholds for landsliding in the Lisbon region for the end of the 21st century, in the context of climate change (SSP2-4.5 and SSP5-8.5 scenarios) and considering 4 accumulated rainfall time scales (1 day, 10 days, 30 days and 60 days). The projections for the duration of 10 days are of special interest for the case study, indicating an increase of 5% in frequency in the case of SSP2-4.5 scenario, and a reduction of 10%in frequency in the case of SSP5-8.5 scenario (Araújo, 2021). These features are considered to compute landslide probability per pixel for the end of the century.



Araújo, J. R. (2021). Impact of extreme rainfall events on landslide events in Portugal under climate change scenarios. Dissertação de Mestrado, Faculdade de Ciências da Universidade de Lisboa.

Vaz, T., Zêzere, J. L., Pereira, S., Oliveira, S. C., Garcia, R. A., & Quaresma, I. (2018). Regional rainfall thresholds for landslide occurrence using a centenary database. Natural Hazards and Earth System Sciences, 18(4), 1037-1054.



This work is part of the project Riskcoast - Development of tools to prevent and manage geological risks on the coast linked to climate change (SOE3/P4/EO868, Interreg Sudoe), and uses data from the Local Climate Change Adaptation Plans - Arrábida (PLAAC-Arrábida, EAAGrants). Pedro Pinto Santos is funded by FCT - Fundação para a Ciência e a Tecnologia, I.P. (reference CEEIND/00268/2017).


How to cite: Zêzere, J. L., Reis, E., Pereira, S., Santos, P., Oliveira, S., Garcia, R., Melo, R., and Morais, A. R.: Landslides in a changing climate: assessment of hazard and exposure in the Arrábida (Portugal), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-311, https://doi.org/10.5194/icg2022-311, 2022.

Ana Rita Morais, Sérgio C. Oliveira, Susana Pereira, and José Luís Zêzere

On November 18, 1983, a heavy and short-duration rainfall event (164 mm/24 hours ) occurred, particularly, in the northern Lisbon metropolitan area, associated with an atmospheric  depression, localised southwest of the Azores islands, which evolved into a cut-off depression. This rainfall event triggered a large number of landslides, with evident regional importance, which remained little explored until now.

Event-based landslide inventories identify the location of landslides caused by a single trigger, which is crucial to understand the predisposition factors and to assess landslide susceptibility for different types of landsides occurring in the study area. The purpose of this study is to elaborate a complete event-based landslide inventory for this rainfall-triggered event, which is used  to model landslide susceptibility at the regional scale, helping to understand the combined action of the trigger and the landslide predisposing factors.

The landslide inventory is built based on the interpretation of high-resolution analogic aerial photographs (1:15,000 scale), obtained after the event, between the 8th and the 13th December 1983. Recent orthophotomaps covering the complete study area were used as the baseline image for the process of geo-referencing the aerial photos. In addition, it was necessary to perform local correction of deformations, resulting from the conic projections of aerial photographs, to improve the geometry of landslide limits. The landslide inventory allows to identify the landslide event spatial extension as well as to characterize the landslide typology, landslide morphometric parameters and event magnitude.

The landslide susceptibility is assessed using the event-based landslide inventory and a set of geo-environmental landslide predisposing factors that are modelled with the statistical method of the Information Value. The obtained results are interpreted taking in account the combination of landslide predisposing factors, but also of the spatial distribution of the rainfall that triggered the landslide event.



This work is part of the project Riskcoast - Development of tools to prevent and manage geological risks on the coast linked to climate change (SOE3/P4/EO868, Interreg Sudoe). Sérgio C. Oliveira is funded by FCT - Portuguese Foundation for Science and Technology, I.P., through the project BeSafeSlide - Landslide Early Warning soft technology prototype to improve community resilience and adaptation to environmental change (PTDC/GES-AMB/30052/2017) and by the Research Unit UIDB/00295/2020, UIDP/00295/2020.

How to cite: Morais, A. R., Oliveira, S. C., Pereira, S., and Zêzere, J. L.: The rainfall-triggered landslide event of November 1983 in the Lisbon Region: a contribution for the knowledge of regional slope instability, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-317, https://doi.org/10.5194/icg2022-317, 2022.

Philipp Marr, Margherita Stumvoll, Robert Kanta, Yenny Alejandra Jimenez Donato, and Thomas Glade

The occurrence of landslides poses a significant threat to communities and infrastructure worldwide. Detailed knowledge of the triggering factors and process mechanisms of this geomorphic hazard still remains challenging. To reduce landslide risks, negative societal impacts and to deepen our understanding of the preparatory and triggering factors for landslide initiation, long-term monitoring approaches can be helpful. However, long-term monitoring projects required to study slow-moving landslides with varying periods of activity are rare due to financial and/or project time constraints. Here, we present the results of a long-term monitoring system, that includes a variety of methods to monitor the surface and subsurface of a slow-moving landslide, at the Hofermühle, in Lower Austria.

The region of Lower Austria is heavily affected by landslides. Therefore, the present research focuses on a small, retrogressive, slow-moving (cm-dm/a) earth slide-earth flow system of ~0.15 km2 at Konradsheim, Waidhofen/Ybbs in Lower Austria, which is representative of thousands of landslides in the region. It is located in a complex geological transition zone, of which the Flyschzone is known to be prone to shallow and deep landslides. It is characterized by high clay contents and the advanced weathering stage of the lithology. In addition, anthropogenic influences such as drainage mechanisms and land-use changes complicate the situation at the study site. Movements at the Hofermühle have been reported since the 1970s. In 2013, sliding processes increased in speed and magnitude, with heavy precipitation being the main trigger. As a result, monitoring systems were continuously established in 2014 and have been in operation since then. In this study, hydrometeorological data and remote sensing, such as UAV and TLS, combined with subsurface and geophysical data (e.g., inclinometers, TDR-probes, ERT) provide meaningful insights into the dynamics of slow-moving landslides.

How to cite: Marr, P., Stumvoll, M., Kanta, R., Jimenez Donato, Y. A., and Glade, T.: Insights from a long-term monitoring system of a slow-moving landslide at Hofermühle, Lower Austria., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-338, https://doi.org/10.5194/icg2022-338, 2022.

Francesco Seitone, Mauro Bonasera, Victor Buleo Tebar, Giandomenico Fubelli, and Michele Licata

The geomorphological and geotechnical assessment of a large landslide should be always carried out to plan the best solution for monitoring and risk mitigation works. Too many times monitoring and works were realised following standard procedures without preventively comprehending the morphoevolution of the landslide system. This work aims to offer a full and multidisciplinary analysis in an anthropized area to supply strategic support for civil protection activities, to deepen the local natural hazard and try to reduce them.

We investigate a complex landslide system located in San Vito Romano, Central Italy, 40 km east from Rome. It has a spatial extent of about 1 km2. The geological context is characterised by a Tortonian sequence of turbidite deposits, characterised by marls and arenaceous intercalations, forming a monocline with 15-20° dip-direction eastward, parallel to slope inclination. Moreover, a complex hydrogeological system characterises the groundwaters.

A field survey has been carried out to recognize the geomorphological features and elements as crowns, scarps, tension cracks and all other geomorphic evidence. The survey also focused on building damages. A geomorphological-technical model has been realised interpreting boreholes, piezometers, inclinometers, high precision GPS stations and cracks digital metres, geotechnical and geophysical investigations, coupled with detailed digital elevation models analysis through GIS software. In this way the San Vito Romano landslide has been interpreted as a large rock translational slide in the upper part of the slope turning into a rotational slide in its accumulation zone. Data have been used for experimental slope stability analysis to find the main critical areas of the slope and correlate water table changes and landslide movements. Even though data model is still developing and calibrating, preliminary data provide realistic results. The individuation and characterization of most critical areas allow to plan where locate further instrumentations choosing the most appropriate ones for the two different detected portions of the landslide. Based on it, the suggested work consists in a drainage trench system upstream the main scarp to canalize the surface running waters avoiding infiltration in recharging area, and a large drainage borehole, for the purpose of limiting the water table changes downstream in the accumulation zone.

How to cite: Seitone, F., Bonasera, M., Buleo Tebar, V., Fubelli, G., and Licata, M.: Large landslide system full characterization in central Italy: relevance of geomorphological and geotechnical models to plan monitoring and risk mitigation works., 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-364, https://doi.org/10.5194/icg2022-364, 2022.

Di Lu and Takashi Oguchi

The impact caused by landslides can be determined by both landslide occurrence probability and the runout distance of landslides. This study aims to evaluate the potential damage caused by landslides in urbanized areas using two different methods: the Artificial Neural Networks (ANNs) method produces a landslide susceptibility map, and the constrained random walk method deals with landslide runout distance. These methods are applied to the study area in King County, Washington, USA. The landslide inventory data used include 2331 historical landslides. We divided each landslide area into the source, transportation, and deposition areas. We also selected 13 conditioning factors for landslide occurrence in the source areas: elevation, slope gradient, slope aspect, plan curvature, profile curvature, lithology, Stream Power Index (SPI), Topographic Wetness Index (TWI), Sediment Transport Index (STI), land cover, distance to roads, distance to railways, and population density. The value of the Area Under the Curve (AUC) of landslide susceptibility assessment using these factors is 0.927, showing the high performance of the applied model. Analysis of the transportation and deposition areas using the random walk model has provided additional insights into landslide hazards.

How to cite: Lu, D. and Oguchi, T.: GIS-based machine learning models for assessing landslide impact: A case study in King County, State of Washington, USA, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-397, https://doi.org/10.5194/icg2022-397, 2022.

Poster: Tue, 13 Sep, 16:45–17:00 | Poster area

Chairpersons: Susana Pereira, Grace Alves, Tavares Alexandre Oliveira
Alessandra Ascione, Manuela Palumbo, Stuart N. Lane, Nicoletta Santangelo, Antonio Santo, and Ettore Valente

Flash floods occur quickly and instantly with respect to triggering rainfall and are particularly frequent in river basins of limited extent. In the Mediterranean area, flash floods are acknowledged as the most widespread geo-hydrological hazard. They may have a particularly catastrophic character due to combination of intense precipitation and strong orographic forcing (cumulative rainfall values in the order of hundreds of mm in a few hours) with the widespread presence of steep, small river basins, referred to as Small Mediterranean Catchments. The natural susceptibility associated with Small Mediterranean Catchments eventually results in high hydrogeological risk notably for densely-urbanized and populated alluvial fans at catchment outlets. Therefore, the evaluation of sediment budgets of flash-flood prone, torrential catchments is important for the assessment of flood susceptibility and hazard in piedmont areas.

Our study addresses the evaluation of the sediment volume that has the potential to be entrained and delivered downstream during flash floods in torrential catchments. With the final aim of developing an approach useful to the definition of the order of magnitude of future flash flood events in terms of debris loads, our goal is to obtain reliable quantification of sediment storage through the geomorphological analysis of high-resolution topographic data.

We developed and tested a predictive, quantitative geomorphological technique for estimating the magnitude of debris flows related to flash floods triggered by extreme rainfall events. We applied our method to steep torrential catchments that (i) are underlain by resistant rocky bedrock, therefore not prone to large landslides, and (ii) allowed testing of our technique through quantification of the effects of recently-occurred flash floods. The three study catchments are located in southern Italy and experienced flash flood-related debris flows triggered by a rainstorm with a recurrence interval > 200 yrs. We estimated the sediment volumes stored in the investigated mountainous catchments prior to the flash flood and compared our results with the sediment volumes entrained by the debris flows. The latter volumes were estimated by post-event data collected by means of both field surveys and remote sensing (drone surveys). The results were mutually consistent so supporting our approach. The approach can be applied extensively, even in the absence of field data and measurements, to ungauged catchments similar to those we analysed for flash flood hazard assessment and planning of mitigation strategies.

How to cite: Ascione, A., Palumbo, M., Lane, S. N., Santangelo, N., Santo, A., and Valente, E.: A new geomorphological method for the evaluation of debris flow magnitude: a case study from the southern Apennines (Italy), 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-404, https://doi.org/10.5194/icg2022-404, 2022.

Mircea Voiculescu, Marcel Torok-Oance, and Diana Bodea

Snow avalanches are a denudational process and natural hazard that can severely damage tourist infrastructure, roads and forests and lead to injury and loss of life. Political and socio-economic changes in mountain landscapes also affect avalanche activity. This study was carried out in the Făgăraş Mountains, a representative mountain unit in the Southern-Romanian Carpathians, which is dominated by glacial and periglacial relief, high altitudes, high snow cover thickness, snow persistence of about 8-9 months per year and high occurrence of avalanche hazards.

Our analysis of the location, spatial extent and number of avalanche events was based on extensive documentation using old photographs, maps, papers and statistics from Mountain Rescuer Public Services databases. We also used dendrogeomorphological data with a 130-year chronology, from which we extracted the frequency, magnitude and spatial extent, satellite images and event simulations using the RAMMS avalanche module in the most affected area of the Fagaras Mountains, the Balea-Capra glacier sector. The study data were collected between 1880 and 2020, in three different periods, each with political and socio-economic peculiarities: the Romanian Kingdom Period (1880-1945), the Communist Period (1946-1989) and the Post-Communist Period (1990-present). In the first period, the tourist infrastructure was modest with no tourist traffic and the avalanche danger was not recognized. Only three avalanche events with human casualties were recorded. In the communist period 23 avalanche events were recorded. In the post-communist period, 75 avalanche events were recorded. Avalanche activity has strongly interfered with the emergence of new elements of tourist infrastructure such as huts, alpine refuges and the Transfăgărășan highway but also with the increasing exposure of tourists especially in the last 20 years. This is why the Făgăraş Mountains are a real avalanche hot spot in the Romanian Carpathians, accounting for 51.2% of fatalities and 57.4% of injuries/burials.

Studies carried out in the Romanian Carpathians have shown that climate warming is more evident between 1,000 and 1,500 m than at higher altitudes where most avalanches have been recorded. In this context, it is difficult to determine that the frequency and spatial extent of avalanches is determined by global change.


How to cite: Voiculescu, M., Torok-Oance, M., and Bodea, D.: A 130-year history of avalanche risk in the Fagaras Mountains, Romanian Carpathians deduced from interference with human activities, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-433, https://doi.org/10.5194/icg2022-433, 2022.

Ana Cardoso, Susana Pereira, Tiago Miguel Ferreira, José Luís Zêzere, Raquel Melo, Teresa Vaz, Sérgio C. Oliveira, Ricardo A. C. Garcia, Pedro Pinto Santos, Eusébio Reis, and Paulo B. Lourenço

This work aims to assess the physical vulnerability of buildings (PVB) exposed to landslides that can be triggered by rainfall and earthquake in the Lisbon metropolitan area (LMA).

Susceptibility to landslides triggered by rainfall was assessed with a statistical model (Information Value), using seven predisposing factors: slope, aspect, geology, curvature, land use, and topographic wetness and position (TPI) indexes. A landslide inventory containing 4k landslides identified in the Lisbon and Tagus Valley region was used. The ROC curve of this model produced an AUC of 0.92. In this approach, the area defined as most susceptible was selected to assess the PVB for each exposed building to landslides with a slip surface depth of 1 m and an accumulated material height of 0.5 m.

Susceptibility to landslides triggered by earthquakes was assessed with an Analytic Hierarchy Process to achieve the relative weights based on the Saaty’s scale of influence using six predisposing factors: slope, curvature, TPI, geology, PGA and distance to faults. The results of this model were compared with a historical inventory of landslides triggered by earthquakes in the LMA obtained from documental sources (Vaz and Zêzere, 2016). The area most susceptible to landslides (8th and 9th deciles) was selected to assess the PVB for each exposed building to landslides with a slip surface depth of 3 m and an accumulated material height of 1 m.

In both cases, the PVB assessment considered all exposed buildings with a residential function surveyed in the 2011 Census (Georeferenced Buildings Database - BGE), including the following parameters: construction material, presence of reinforced structure, number of floors, conservation status, and need for repairs in the structure and finishes. Each parameter was divided into a set of building classes obtained from BGE. A score was given to each building class and the respective parameter. Both scores and parameters’ weights are based on expert opinion and dedicated literature (Guillard-Gonçalves et al., 2016; Pereira et al., 2020).

The analysis allowed us to observe meaningful regional multi-hazard potential interactions between earthquake and rainfall triggered landslides which can generate, in space and time, a complex level of damages scenarios for residential buildings. Additionally, it contributes to identifying risk hotspots and possible risk adaptation and mitigation measures.



To MIT-RSC - Multi-risk Interactions Towards Resilient and Sustainable Cities (MIT-EXPL/CS/0018/2019), Portuguese Foundation for Science and Technology (FCT I.P.), MIT-Portugal program; RISKCOAST (SOE3/P4/EO868), Interreg-SUDOE program. Pedro Pinto Santos financed through FCT I.P contract CEECIND/00268/2017. CEG Research Unit UID/GEO/00295/2019



Guillard-Gonçalves, C., Zêzere, J. L., Pereira, S., & Garcia, R. A. (2016). Assessment of physical vulnerability of buildings and analysis of landslide risk at the municipal scale: application to the Loures municipality, Portugal. Natural Hazards and Earth System Sciences, 16(2), 311-331.

Pereira, S., Santos, P. P., Zêzere, J. L., Tavares, A. O., Garcia, R. A. C., & Oliveira, S. C. (2020). A landslide risk index for municipal land use planning in Portugal. Science of the Total Environment, 735, 139463.

Vaz, T., & Zêzere, J. L. (2016). Landslides and other geomorphologic and hydrologic effects induced by earthquakes in Portugal. Natural Hazards, 81(1), 71–98.

How to cite: Cardoso, A., Pereira, S., Ferreira, T. M., Zêzere, J. L., Melo, R., Vaz, T., Oliveira, S. C., Garcia, R. A. C., Pinto Santos, P., Reis, E., and Lourenço, P. B.: On the physical vulnerability of buildings exposed to landslide hazard: application to the Lisbon Metropolitan Area, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-557, https://doi.org/10.5194/icg2022-557, 2022.

Mateo Moreno, Stefan Steger, Luigi Lombardo, Lotte de Vugt, Thomas Zieher, Martin Rutzinger, Massimiliano Pittore, Volkmar Mair, and Cees van Westen

Landslides of the slide-type movement represent a potential threat to people and infrastructure in mountain areas all over the world. At regional scales, data-driven models are typically used to assess landslide susceptibility, i.e., to map where landslides are more or less likely to occur. Such assessments frequently serve as basic input for landslide risk assessment, applications in spatial planning, and landslide early warning. Data-driven landslide susceptibility models strongly rely on the quality of the landslide inventory data, and therefore, their explanatory power depends on various errors associated with the underlying landslide data collection process. Previous research has highlighted how ignoring systematic errors inherent in the landslide data can lead to erroneous model inference and landslide susceptibility maps with limited practical applicability. In this context, this study aims to counteract the challenge of spatial landslide-inventory biases (e.g., incomplete landslide mapping far from infrastructure) by testing several possibilities to consider information on Effectively Surveyed Areas (ESA). The concept of ESA was introduced in previous research as the areas which were explicitly surveyed during the preparation of the landslide inventory, and hence, landslides occurring outside these areas are not usually reflected in the inventory data. Consequently, accounting for ESA may lead to landslide susceptibility maps more suitable for practical applications.

In this contribution, we carried out a comparative analysis of three different landslide susceptibility models that focus on different strategies to handle information on ESA. The analyses focused on the Italian province of South Tyrol (7,400 km²) and built upon landslide data from 2000 to 2020. This data relates to damage-causing and infrastructure-threatening landslide events and therefore ignores slope instability far from the elements at risk. The first tested strategy focused on accounting for the ESA during model fitting while averaging out its effect for the prediction into space. The second strategy builds upon the first strategy but additionally excludes easy-to-classify “trivial” terrain (e.g., alluvial plains, rock faces, water bodies). The third strategy does not account for the ESA during model fitting but considers its information during the preceding sampling process (i.e., the sampling of stable and unstable mapping units is based on an ESA mask).

The workflow comprised the delineation of slope units, the derivation of the ESA, and the spatial aggregation of the predisposing factors (e.g., lithology, land cover, topographic indices). The subsequent exploratory data analysis was conducted to explore the association of each factor with landslide occurrence data. Generalized Additive Models were implemented to derive linear or non-linear relationships between shallow landslide occurrence and the predisposing factors and to assess relative variable importance. The results were validated through random cross-validation, spatial cross-validation, and geomorphic plausibility checks.

The findings confirmed the importance and benefits of accounting for the ESA. The various results showed how not accounting for the ESA can lead to a misleading depiction of landslide susceptibility in certain areas. This study was framed within the PROSLIDE project, that has received funding from the research program Research Südtirol/Alto Adige 2019 of the Autonomous Province of Bozen/Bolzano – Südtirol/Alto Adige.

How to cite: Moreno, M., Steger, S., Lombardo, L., de Vugt, L., Zieher, T., Rutzinger, M., Pittore, M., Mair, V., and van Westen, C.: Comparing different strategies to incorporate the effectively surveyed area into landslide susceptibility modeling, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-563, https://doi.org/10.5194/icg2022-563, 2022.

Mónica Silva, Mário Quinta Ferreira, and Pedro Santarém


Climate change is a global concern, directly interfering with the local geology, causing changes, affecting the geomorphological structures and the stability of the rock masses.

The phenomena that occur due to changes in the geological materials, such as in coastal areas or abandoned quarries, significantly affect the behavior of the rock masses located in these areas, as they suffer the action of abrasion and erosion due to the dynamics of the sea or strong winds, which can provide an early instability of existing cliffs or slopes, endangering the surrounding environment, such as roads or buildings.

Knowing that storms are increasingly recurrent and stronger, the damages they can cause presents greater consequences, requiring a more objective analysis of the geological materials behavior when exposed to severe weather events, such as torrential rainfall or long lasting rainfall.

The geomechanical classifications e.g. Rock Mass Rating (RMR) and Slope Mass Rating (SMR), are crucial as the behavior of the rock masses can be foreseen when the values of the geotechnical parameters are suitably defined. Complementarily, it is useful to use geophysical methods allowing to obtaining more detailed information in a less invasive, but reliable way, including the degree of fracturing of the rock masses, provided that access and the characterization of the sites are feasible. Currently the geomechanical classifications are reliable at a small scale, failing to convey the geomechanical behavior of the rock masses as a whole, but rather in restricted locations. Realizing this difficulty, it is relevant to find a work methodology allowing the existing classifications to be used, so that the final results are a continuous evaluation of the rock mass behavior and not only in delimited sections or test sampling points.

Considering the goal of a continuous characterizing of the rock mass behavior through the results obtained, it is pertinent to present solutions, which should contribute, whenever possible, to greater sustainability.

Therefore, it is intended that geomorphology and geology, in association with the geotechnical studies should be used as a basis for the characterization of rock masses, allowing to identify the problems and instability causes and subsequently to present the solutions allowing to enhance profitability, sustainability and efficiency in the stabilization of the rock masses.

How to cite: Silva, M., Quinta Ferreira, M., and Santarém, P.: Contribution to a Suitable Rehabilitation of Rock Masses, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-595, https://doi.org/10.5194/icg2022-595, 2022.

Pedro Pinto Santos, Eusébio Reis, José Luís Zêzere, Susana Pereira, Sérgio Cruz Oliveira, Ricardo A. C. Garcia, Maria Xofi, José Carlos Domingues, Paulo Lourenço, and Tiago Miguel Ferreira

This work aims to assess the spatial relationships between buildings and the flood risk areas identified in the Floods Directive. The assessment considers the physical vulnerability of the buildings (from seven parameters regarding their physical properties and implantation), the flood hazard (considering the flood height and the runoff velocity) and the geomorphological context of the building's implantation areas. The test sites are the areas of significant potential flood risk (ASPFR) existing in the Lisbon Metropolitan Area (LMA), and being evaluated in the 2nd implementation cycle of the Floods Directive, which includes flooding of the fluvial, estuarine and coastal type:

- V.F. Xira-Tagus estuary: fluvial, estuarine and coastal flooding affecting the Tagus river, its estuary, to the oceanic shoreline of the Cascais and Almada municipalities;

- Loures-Odivelas: fluvial flooding in the Trancão river, a tributary of the Tagus river;

- Cova do Vapor-Fonte da Telha: coastal flooding in the Almada municipality;

- Seixal: fluvial and estuarine flooding in the Judeu river, affecting the Seixal municipality;

- Setúbal: fluvial flooding in the Livramento stream, affecting the Setúbal municipality;

The assessment of the physical vulnerability of buildings (PVB) to flooding considered all the buildings with residential function surveyed in the 2011 Census survey (Georeferenced Buildings Database). The assessment considers six building parameters, namely the period of construction, number of storeys, material of external cladding, material of structural system, building exposure, building condition, and one defined by the spatial framing of the building in the soil/lithological substrate. A score between 10 and 100 is given to each building according to its characteristics expressed in four classes. Both scores and parameters’ weights are based on expert opinion and dedicated literature.

This analysis aims at verifying to what extent: (i) the buildings’ characteristics make them adapted to the characteristics of the hazards to which they are exposed; and (ii) those features are related with the geomorphological context of flooding – coastal, estuarine, and fluvial (flash or slow on-set) flood.

A clustering analysis was run as part of an unsupervised learning algorithm, taking each building as the statistical individual, which is characterized by the on-site flood height and velocity, physical vulnerability and type of flooding.

The analysis produced relationships between flood hazard and the geomorphological context, which were related to the characteristics of the buildings, identifying the higher risk hotspots and informing decision-makers in territorial planning and civil protection emergency planning as to the priority situations related to climate change adaptation and mitigation measures.


The MIT-Portugal project MIT-RSC - Multi-risk Interactions Towards Resilient and Sustainable Cities (MIT-EXPL/CS/0018/2019) is funded by the Portuguese Foundation for Science and Technology (FCT I.P.), under the MIT-Portugal program. RISKCOAST - Development of tools to prevent and manage geological risks on the coast linked to climate change (SOE3/P4/EO868) is funded by the Interreg SUDOE program. Pedro Pinto Santos is financed through FCT I.P., under the contract CEECIND/00268/2017. CEG Research Unit UID/GEO/00295/2019.

How to cite: Santos, P. P., Reis, E., Zêzere, J. L., Pereira, S., Oliveira, S. C., Garcia, R. A. C., Xofi, M., Domingues, J. C., Lourenço, P., and Ferreira, T. M.: Physical vulnerability of buildings exposed to different flood hazards in the Lisbon Metropolitan Area, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-607, https://doi.org/10.5194/icg2022-607, 2022.

Hydrological and hydraulic study of the Ceira river and its contribution to the flood peak discharge in Coimbra (Portugal)
João Pardal, Lúcio Cunha, Alexandre Oliveira Tavares, Pedro Pinto Santos, and Luís Leitão
Renato Liscar, Mário Quinta-Ferreira, and Pedro Santarém Andrade

A geotechnical characterization of the gypsum quarry of Sogerela and its slope stability assessment, were carried out. The quarry is located at Avarela, in the municipality of Óbidos (western Portugal). For the evaluation of rock mass quality, the characteristics of the discontinuities were defined, which correspond to an important factor in the stability and behavior of the fractured gypsum rock mass affected by diapiric deformations. Laboratory characterization tests were performed, determining several parameters such as: apparent density, open porosity, slake durability index, Schmidt hammer rebound hardness, point load strength index and mineral identification with X-Ray Diffraction (XRD). Results obtained from field survey and the laboratory tests allowed to define the values of the geotechnical parameters and to perform the characterization and classification of the rock mass, using the Rock Mass Rating (RMR) and Geotechnical Strength Index (GSI).

The data obtained was used in the geomechanical simulation for slope stability analysis using SLIDE2 V9.0 and RocFall V8.0 software programs. The quarry slope stability was assessed with the definition of the possibility of slope failure considering the raise of the water table and in the eventual occurrence of an earthquake. The results allowed to verify that that the actual conditions seem to be stable, concerning global failure of the excavation slopes, despite the frequent fall of gypsum fragments adjacent to the quarry walls during and after rainy periods.

How to cite: Liscar, R., Quinta-Ferreira, M., and Santarém Andrade, P.: Geotechnical characterization and slope stability evaluation of the gypsum quarry of Sogerela, Óbidos, Portugal, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-690, https://doi.org/10.5194/icg2022-690, 2022.

Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya Narayan Mishra, Douglas Maraun, and Alexander Brenning

With changing environmental conditions, the risk of landslides will also change. For the Styrian basin, Austria, we investigate how storylines of climate and land use/land cover change may affect future landslide susceptibility (2071-2100). Our analysis is based on two extreme rainfall events in Styria in 2009 and 2014, which triggered more than three thousand landslides causing a major threat to the local population and significant damage to settlements and infrastructure.

Furthermore, while the number of studies analysing the impact of climate and land use change on landslide dynamics is rising, the assessment of their uncertainties is still often neglected. However, the quantification of uncertainties is not only essential for the development of business strategies and policy interventions, but also for increasing transparency and confidence in scientific analysis. Therefore, we additionally analyse the joint contribution of climate change uncertainty and landslide model uncertainty for the developed storylines of landslide susceptibility.

We found for the worst-case storyline (4 K warming scenario) a substantial increase in highly susceptible areas due to much heavier rain. However, the estimated prediction uncertainties were generally high in all storylines. We discovered that the parametric landslide model uncertainty was of the same order as the climate scenario uncertainty, while uncertainties due to internal climate model variability were negligible. With an improved availability of event-based landslide inventories and high-resolution ground data, uncertainties in storylines of landslide susceptibility may be reduced.

How to cite: Knevels, R., Petschko, H., Proske, H., Leopold, P., Mishra, A. N., Maraun, D., and Brenning, A.: Future storylines of landslide susceptibility in the Styrian Basin, Austria. Accounting for environmental change and uncertainties, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-716, https://doi.org/10.5194/icg2022-716, 2022.

Zhihao Wang, Jason Goetz, and Alexander Brenning

Landslide susceptibility modelling is an effective way to assist decision-makers in minimizing landslide risk. Developing landslide inventories for susceptibility model training and testing can be of high cost and effort. Previous studies have pointed out that landslide inventories from different areas are able to provide informative knowledge of landslides. However, training models for target areas using data from different regions at different times is challenging due to differences in feature space and/or the data distribution. Traditional machine learning techniques assume that target and source areas have the same data distribution. Therefore, when the data distribution is different, their performance can be degraded. Transfer learning can solve new problems using knowledge extracted from previous experiences. Case-based reasoning (CBR) is a transfer learning method that determines the similarity between source and target areas by considering various attributes (e.g., topography, geology, data structure). The resulting most similar or a weighted combination of models from similar source areas are applied to model susceptibility in the target area. Instead of applying the similarity obtained by CBR, domain adaptation (DA) transfers the knowledge by considering the data distribution between source and target areas. These two techniques are rarely used in landslide assessment studies, yet they have excellent potential to enhance spatial model transfers.

We evaluated the performance of transfer learning using CBR, DA and a CBR-DA combination for landslide susceptibility modelling. Our assessment is based on ten study areas with various spatial resolutions (1 m, 10 m and 25 m) located in Austria, Ecuador and Italy. We explored two modelling scenarios: only one source area available (single-source learning) and multiple source areas (multi-source learning) and compared them to benchmark situations, that is, landslide susceptibility models that are applied to the target area without using transfer learning techniques. Our results clearly showed CBR strategies using single-source learning and multi-source learning were robust and effective in developing highly transferable landslide susceptibility models without any a prior knowledge of landslides in target area. Since-source CBR was the most effective method for model transferring. The proposed method can alleviate the burden of collecting and labelling data, resulting in a more expedited preparation of landslide susceptibility maps for large and data-scarce regions.

How to cite: Wang, Z., Goetz, J., and Brenning, A.: Predicting the unknown: using transfer learning techniques for landslide susceptibility modelling, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-718, https://doi.org/10.5194/icg2022-718, 2022.

Evaluation of exposure to mass movement processes using UAV-acquired aerial imagery: insights after the 2021 El Chiquihuite hill disaster, Estado de Mexico, Mexico
Ricardo Garnica-Peña and Irasema Alcántara-Ayala
Marina Tamaki de Oliveira Sugiyama, Maria Carolina Villaça Gomes, Bianca Carvalho Vieira, and Vivian Cristina Dias

The UNESCO Caminhos dos Cânions do Sul Geopark, located in Southern Brazil, is an extensive territory marked by the presence of a great escarpment (Serra Geral), which is commonly affected by high magnitude mass movements. However, susceptibility studies related to such processes are scarce. As an area of geotouristic interest, it is essential to use simple  methods to support the risk and disaster management plans Thus, this work aims to compare two different methodologies The first methodology used (MI) was developed to evaluate the criticality of the basins to the development of debris flows based on five morphometric parameters (basin area, percentage of area above 30°, relief, slope of the main channel and circularity index); while the second (MII) is applied to determine basin susceptibility and the magnitude of the events triggered based on the use of nine morphometric parameters (longitudinal profile, roughness index, relief ratio, relief, melton, percentage of area above 25°, drainage density, drainage confluence and drainage hierarchy). For both methods was used an inventory based on debris flows triggered in 1995 and 2012. The application of MI resulted in the classification of 12% of the basins as Very High susceptibility, 40% as High, 20% as Medium, 20% as Low and 20% as Very Low susceptibility. MII resulted in 14% High Susceptibility basins, 36% Medium, 44% Low and 2% Very Low. Out of the basins classified as Very High and high susceptibility by MI (51%), 42% were affected by debris flows. On the other hand, out of the basins classified as Low susceptibility (20%), 50% were affected by debris flows, which is equivalent to 10% of all basins studied. Out of the basins classified as Very High and High susceptibility by MII (14.6%), 33.3% were affected by debris flow. In addition, from the medium susceptibility basins (36%), there were decries flows in 60% of them. While MI overestimates areas of greatest susceptibility, M2 classifies into the Low Susceptibility class an expressive number of basins which present recorded occurrences. These results can be related to weights and class intervals established by MI and MII, which were not developed to the Serra Geral escarpment context. Despite their limitations, these methods can be recalibrated from a morphometric evaluation of areas already affected by debris flows.

How to cite: de Oliveira Sugiyama, M. T., Villaça Gomes, M. C., Carvalho Vieira, B., and Dias, V. C.: Regional Scale Mapping of Debris-Flow Susceptibility in the Caminhos dos Cânions do Sul GeoPark, Southern Brazil, 10th International Conference on Geomorphology, Coimbra, Portugal, 12–16 Sep 2022, ICG2022-720, https://doi.org/10.5194/icg2022-720, 2022.