As the effects of climate change become more and more evident in high-mountain regions, investigating the relation between climatic anomalies and geomorphic hazards becomes increasingly critical to predict the risk associated with such hazards and to develop reliable models. To do so, researchers often adopt statistical-based methods to detect climate anomalies at multiple time scales associated with the occurrence of different types of landslides. However, the in-situ observations commonly adopted for such studies may misrepresent some of these climatic variables in high mountain areas, sometimes leading to questionable results. For example, no daily precipitation anomaly is often reported for events such as debris flows, which are mainly triggered by short-duration precipitation. Additionally, collecting and quality-controlling in-situ observations is an extremely time-consuming task that prevents wide-scale applications of these methods. In this work, we exploit a consolidated statistical-based method to compare the results obtained from carefully controlled in-situ observations with the ones obtained from freely available quasi-global gridded datasets of (a) daily temperature observations from ENSEMBLES OBServation (E-OBS) and (b) half-hourly precipitation estimates from the Integrated Multi-Satellite Retrievals from GPM (IMERG). We focus on an extended database of 483 geomorphic hazards, including landslides, rockfalls and debris flows, occurred across the Italian Alps in the period 2000-2020. Our results show that the integrated use of open and free products is beneficial in different ways. Statistical tests indicate that E-OBS gridded temperature anomalies as well as multi-day IMERG precipitation anomalies provide as much information as in-situ observations, and can thus be used as easily available surrogates. More importantly, thanks to the ability of satellites to measure precipitation at the triggering locations, IMERG proved able to detect daily precipitation anomalies for many debris flows events for which in-situ data reported no precipitation. Examining the sub-daily variability of the triggering precipitation, we show that the anomalies missed by in-situ observations tend to be associated with events with high temporal, and hence spatial, variability such as the convective storms that usually trigger debris flows in the Alps. The use of quasi-global open datasets in place of in-situ observations can greatly speed-up the data retrieval and even provides an added value over in-situ observations. These results represent an important step ahead in the analysis of climate anomalies related to geomorphic hazards in high mountainous regions as they open the way to more accurate wide-scale applications.  

How to cite: Paranunzio, R. and Marra, F.: Multi-source climate data to investigate the nexus between climate anomalies and landslides in high-mountain regions in the Alps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1704, https://doi.org/10.5194/egusphere-egu23-1704, 2023.

Due to the impact of climate change, the increasing frequency of extreme rainfall events, with concentrated rainfalls, commonly cause landslide hazard in the mountain areas of Taiwan. The extraordinary rainfall behavior is critical for the landslide hazard, therefore, it certainly affects the landslide resilience as well.

This study employs rainfall frequency analysis together with the atmospheric general circulation model (AGCM) downscaling estimation to understand the temporal rainfall trends, distributions, and intensities in the adopted study area in Central Taiwan. Beside the landslide susceptibility, the landslide resilience was quantitatively defined and analyzed. The upstreams of Tachia River, Wu River, and Chuoshui River were adopted as the study area. The results of predictive landslide susceptibility and resilience analysis can be applied for risk prevention and management in the study area.

How to cite: Shou, K.-J.: Landslide Susceptibility and Resilience Changing Climate– for the Case in Taiwan, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1949, https://doi.org/10.5194/egusphere-egu23-1949, 2023.

The influence of meteorological (pre-) condition on landslide probability in the German low mountain regions is assessed and effects arising from climate change are investigated. The landslide events analysed for this study are taken from the landslide database for Germany (Damm and Klose, 2015) and from an event inventory from the German railway company (Deutsche Bahn). We follow two different approaches in order to determine the influence of atmospheric conditions on hillslope failure.

The first approach is based on weather types. Each day is assigned one of 28 Lamb-style weather types. The meteorological variables used to classify the weather types are sea level pressure and anomalies of the atmospheric water content. We were able to identify 4 patterns associated with a statistically significant increase for landslide frequency. The climate change signal of the frequency for the occurrence for these weather types is investigated in a multi-model ensemble of regional climate simulations (EURO CORDEX). The majority of the models shows a decrease in the frequency of those relevant patterns under RCP8.5 scenario conditions. In most models this decrease is, however, not statistically significant.
 
The second approach is based on logistic regression. The logistic regression model was fitted using meteorological observations close to the landslide sites. Conditions at the day of the event as well as the pre-conditions from the days leading up to the event were considered. In order to select the best statistical model we tested a large number of physically plausible combinations of meteorological predictors. Each model was checked using cross-validation. The decision on the final model was based on the value of the logarithmic skill score and on expert judgement. As relevant predictors we identified daily precipitation, frost, and a soil moisture proxy determined from multi-day accumulated precipitation and potential evapotranspiration. 
The climate change signal is determined by applying the statistical model to the output of a multi-model ensemble of climate scenario simulations. 

Damm, B. and Klose, M. (2015): The landslide database for Germany: Closing the gap at national level, Geomorphology, 249, 82-93, https://doi.org/https://doi.org/10.1016/j.geomorph.2015.03.021.

How to cite: Nissen, K., Wilde, M., Ulbrich, U., and Damm, B.: Landslide probability in the German low mountain regions under climate change conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7471, https://doi.org/10.5194/egusphere-egu23-7471, 2023.

Temperature significantly affects the hydraulic and mechanical properties of geomaterials on a slope. However, results from the laboratory show the change in material behaviour depends on the slip rates and the type of minerals present. Active clays are observed to be the most sensitive to temperature oscillations in mechanical deformations. In this research, the temperature change effects will be addressed in laboratory experiments on natural soils. We will deploy laboratory samples to obtain the frictional coefficient as a function of temperature (20-50 degrees). Further, reconstituted samples will be tested under different shear rates to understand the dependencies on temperature. Temperature-sensitive parameters (such as the internal friction angle) will be incorporated in a physically-based modelling framework analysing effects for a sloping unit. The factor of safety will be calculated based on spatial grids representative of the sampling location. In the second part of this research, the frictional coefficient obtained from the laboratory as a function of temperature will be synchronised with projected climate change (surface temperature, hydro-meteorological forcing) and will be simulated to a catchment scale multihazard modelling. This model will incorporate measured data and geostatistical interpolation of remotely sensed data to fulfil the dataset to run the physically based equations. The final output will be the comparison of hazard intensities (e.g., debris flow impact pressure, inundation heights, solid velocity and depth) for the projected future years.

How to cite: Dhakal, O. P., Scaringi, G., Loche, M., Dahal, R. K., and Bout, B. V. D.: Physically based slope stability analysis: future scenarios due to changing surface temperature, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5774, https://doi.org/10.5194/egusphere-egu23-5774, 2023.

Open bedrock fracture networks are characteristic structural features in unstable rock slopes. They affect the subsurface bedrock temperature field due to fracture ventilation and temporary water infiltration. The ground thermal conditions are a key factor influencing slope stability. Ascending air circulating through fracture networks during winter (the so-called chimney effect) facilitates the cooling of the ground and leads in some cases to the development of extra-zonal permafrost. In addition, fracture networks exposed to the atmosphere have an impact on gas exchange processes at the Earth-atmosphere interface. Natural ventilation of the underground compartments can thus lead to increased gas exhalation to the surface. Especially the radioactive gas radon (²²²Rn) has been used in Earth science and environmental studies of natural ventilation systems and has due to its relatively long half-life great potential to characterize the subsurface bedrock fracture systems.

We present a case study of a natural ventilation system from the Stampa rock slope instability (Aurland, Norway). The area above the slide scar is characterized by a relatively low slope angle and bedrock lineaments, which correspond to morphological depressions and open subsurface fractures. Natural ventilation through these fractures has been observed at several locations at Stampa, where air flows out or in. Such chimney ventilation depends upon outside air temperature compared to subsurface temperature but also on locality and other atmospheric conditions such as wind and air pressure. Rock-surface and air temperature loggers in open fracture systems can provide information about both subaerial temperature and the subsurface temperature field, which can be use to model the chinmey ventilation. Instruments continuously monitoring air flow and radon concentration at selected vents, in addition to sporadic alpha track radon surveys are used to identify the extent and connectivity beween individual ventilation systems and verify ventilation patterns. In situ measurements are combined with UAV surveys using both optical and thermal imaging. We found that air ventilation through several individual systems of open bedrock fractures leads to cooling of the ground and to the development of sporadic extrazonal permafrost far below the regional permafrost limit. Radon concentration of outflowing air is depending on the air flow rate and the rock-atmosphere contact area which, in turn, depends on ground water level and the extent of ice in subsurface fractures. The subsurface bedrock reaches its highest temperatures in late autumn/early winter which coincides with enhanced slope deformation. 

How to cite: Scheiber, T., Snook, P., Haanes, H., Maschler, A., and Schild, L.: Natural ventilation through open bedrock fracture systems and its influence on rock slope stability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9596, https://doi.org/10.5194/egusphere-egu23-9596, 2023.

The majority of landslide-prone areas spread in mountainous areas with abundant rainfall. However, when high altitudes make areas prone to significant snowfall, the amount of such snowfall, as well as environmental temperature and humidity, should be taken into account to determine its effect on the condition of landslide stability. To pursue this aim, the present study focuses on the quantification of snow accumulation on the slope through approaches based on image analysis and on the prediction of surface displacements of the slope using a two-steps LSTM (Long short-term memory) algorithm. The main LSTM algorithm aims at forecasting the landslide displacement in the future 12 hours using as input the past 5 days data of rainfall, snowfall and movements of the slope, plus the weather prediction of the next day. The necessity of estimation of the trend of the snow condition makes it necessary to implement a secondary LSTM algorithm for estimating if the snow coverage is going to accumulate or melt in next 12 hours, again basing on the past 5 days environmental measurements (temperature and humidity) and a forecast of the future condition of the site. Both the algorithms are trained basing on the historical measurements of temperature, humidity, rainfall, snowfall and landslide displacement. The main code also includes a training based on the surficial movements of the slope measured by a topographical monitoring system. Within this model, the presence and the trend of the snow is evaluated by means of some image-processing algorithms aiming at evaluating the cover square percentage of white content in the RGB image, filtering out noises and false signals. The presented procedure is applied to the case of the Sant’Andrea landslide, located in Perarolo di Cadore (North Italy, Province of Belluno), whose bedrock is composed by dolomitic lithology and folded layers rich in anhydrides and gypsum easily erodible by water infiltration in the subsoil. The two-steps LSTM model implementation achieves the forecasting of the landslide displacements, focusing in particular on the effects of snow melting in the stability condition of the slope.

How to cite: Liu, Y., Brezzi, L., Nava, L., Liang, Z., and Cola, S.: Forecasting the surficial displacements of a landslide triggered by snow melting basing on LSTM and image processing algorithms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12239, https://doi.org/10.5194/egusphere-egu23-12239, 2023.

Landslides are more widespread than any other geological events on Earth. Due to their steep topography and contrasted weather conditions, volcanic regions are especially prone to water-triggered landslides. Indeed, examples of volcanic slope failures abound. Regions endowed with volcanic soils are often densely populated and landslides are causing devastating impacts including loss of human lives, damage to critical infrastructure and disruption to livelihoods. There is growing concern that the intensifying effects of climate change on the hydrological cycle – changing the amount and frequency of rainfall and meltwater input – will exacerbate shallow-seated landslide susceptibility. Soil is the weakest material involved in landslide-related disasters, and soil properties are pivotal in determining the susceptibility of a slope to mass movement. Volcanic soils have unique, but hitherto poorly constrained, hydraulic and mechanical properties. Depending on the volcanic parent materials and weathering conditions, these soils can display clay fractions of different mineralogical composition which likely influence their hydraulic and mechanical properties.

Our study aims to advance understanding of the relationships between the hydraulic and mechanical properties of volcanic soils. We sampled undisturbed volcanic soils in Tenerife (Spain) and Ecuador characterized by different mineralogies in order to measure their microstructural and hydraulic properties (particle size distribution ; pore size distribution ; hydraulic conductivity ; water retention curve). We also determined the mechanical properties (shear strength) of these soils and quantified the effect of soil water content on these properties conducting triaxial tests at different moisture level. The mineralogical analysis performed reveal clay fractions either enriched in allophanes or halloysites for the different sampled sites. The allophanic soils display large porosities and water retention values, whereas halloysites-rich soils are less efficient to retain water but seem to conduct it faster. Halloysites-rich soils also show higher, but more water content dependent shear strengths. Indeed, maximum shear stresses reached during triaxial tests are largely increased with drying while allophanic soils’ shear strength are less impacted by a decreased water content. This could be explained by the aggregation of allophane particles in clumps during drying, causing a reduction of shear strength offsetting the classic increasing shear strength due to the increased capillary effects. 

How to cite: Delvoie, M., Delmelle, P., Rattez, H., Pereira, J.-M., and Tang, A. M.: Hydraulic and mechanical behaviour of volcanic soils and implications for evaluating slope stability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7534, https://doi.org/10.5194/egusphere-egu23-7534, 2023.