Formation of Clay-Rich Layers at The Slip Surface of Slope Instabilities: The Role of Groundwater

Some landslides around the world that have low-angle failure planes show exceptionally poor mechanical properties. In some cases, an extraordinarily pure clay layer has been detected on the rupture surface. In this work, a complex landslide, the so-called Diezma landslide, is investigated in a low-to moderate-relief region of Southeast Spain. In this landslide, movement was concentrated on several surfaces that developed on a centimeter-thick layer of smectite (montmorillonite-beidellite) clay-rich level. Since these clayey levels have a very low permeability, high plasticity, and low friction angle, they control the stability of the entire slide mass. Specifically, the triggering factor of this landslide seems to be linked to the infiltration of water from a karstic aquifer located in the head area. The circulation of water through old failure planes could have promoted the active hydrolysis of marly soils to produce new smectite clay minerals. Here, by using geophysical, mineralogical, and geochemical modelling methods, we reveal that the formation and dissolution of carbonates, sulfates, and clay minerals in the Diezma landslide could explain the elevated concentrations of highly plastic secondary clays in its slip surface. This study may help in the understanding of landslides that show secondary clay layers coinciding to their low-angle failure planes.This study was supported by the research projects PID2019-107138RB-I00 funded by the Spanish Ministry of Science and Innovation and P18-RT-3632 funded by the Junta de Andalucí

Assessment of shallow landslide risk mitigation measures based on land use planning through probabilistic modelling

On October 25, 2011 an extreme rainfall event affected a wide area along the coasts of Cinque Terre (eastern Liguria, northern Italy). Particularly, in the Vernazza catchment, the event triggered hundreds of shallow landslides and a debris flood that caused three casualties. Investigation of slope stability after the event was carried out aiming at defining the most effective mitigation measures which may be adopted in future land use planning. To this objective a susceptibility model was produced and a series of scenarios were simulated using probabilistic methods. The susceptibility model has provided information about landslide conditioning factors on which to act for reducing landslide occurrence and therefore the associated risk. The simulations have taken into consideration the following alternative types of mitigation measures: (1) restoration of abandoned terraces, (2) reforestation of abandoned terraces, (3) use of local structural measures over stretches of potentially unstable hillsides and (4) avoidance of any intervention. The advantages and the disadvantages of proposed mitigation measures for shallow landslide risk are discussed considering the results of the simulations and taking into account their complex interaction with environmental, historical, cultural and socio-economic aspects. The results show that the most effective mitigation strategy for reducing landslide risk at short-term consists of applying structural measures over potentially unstable slopes. However a long-term program promoting the development of agricultural practices on terraced slopes is necessary. In fact, the simulations indicate if no measures are applied to avoid the degradation of the terraced areas, landslide areal frequency would inevitably increase

InSAR-Based Mapping to Support Decision-Making after an Earthquake

It has long been recognized that earthquakes change the stress in the upper crust around the fault rupture and can influence the behaviour of neighbouring faults and volcanoes. Rapid estimates of these stress changes can provide the authorities managing the post-disaster situation with valuable data to identify and monitor potential threads and to update the estimates of seismic and volcanic hazard in a region. Here we propose a methodology to evaluate the potential influence of an earthquake on nearby faults and volcanoes and create easy-to-understand maps for decision-making support after large earthquakes. We apply this methodology to the Mw 7.8, 2016 Ecuador earthquake. Using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and continuous GPS data, we measure the coseismic ground deformation and estimate the distribution of slip over the fault rupture. We also build an alternative source model using the Global Centroid Moment Tensor (CMT) solution. Then we use these models to evaluate changes of static stress on the surrounding faults and volcanoes and produce maps of potentially activated faults and volcanoes. We found, in general, good agreement between our maps and the seismic and volcanic events that occurred after the Pedernales earthquake. We discuss the potential and limitations of the methodology.This work is supported by the European Commission, Directorate-General Humanitarian Aid and Civil Protection (ECHO) under the SAFETY (Sentinel for Geohazards regional monitoring and forecasting) project (ECHO/SUB/2015/718679/Prev02) and by the Spanish Ministry of Economy and Competitiveness under INTERGEOSIMA (CGL2013-47412) and ACTIVESTEP (CGL2017-83931-C3), QUAKESTEP (1-P) + 3GEO(2-P) + GEOACTIVA (3-P) projects

InSAR-Based Mapping to Support Decision-Making after an Earthquake

It has long been recognized that earthquakes change the stress in the upper crust around the fault rupture and can influence the behaviour of neighbouring faults and volcanoes. Rapid estimates of these stress changes can provide the authorities managing the post-disaster situation with valuable data to identify and monitor potential threads and to update the estimates of seismic and volcanic hazard in a region. Here we propose a methodology to evaluate the potential influence of an earthquake on nearby faults and volcanoes and create easy-to-understand maps for decision-making support after large earthquakes. We apply this methodology to the Mw 7.8, 2016 Ecuador earthquake. Using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and continuous GPS data, we measure the coseismic ground deformation and estimate the distribution of slip over the fault rupture. We also build an alternative source model using the Global Centroid Moment Tensor (CMT) solution. Then we use these models to evaluate changes of static stress on the surrounding faults and volcanoes and produce maps of potentially activated faults and volcanoes. We found, in general, good agreement between our maps and the seismic and volcanic events that occurred after the Pedernales earthquake. We discuss the potential and limitations of the methodology

Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe

Stream Length-gradient Hotspot and Cluster Analysis (SL-HCA) to fine-tune the detection and interpretation of knickzones on longitudinal profiles

This work presents a new approach for fine-tuning the analysis of stream longitudinal profiles. We show that applying Hotspot and Cluster Analysis (HCA), based on the Getis-Ord Gi* statistic, to the stream length-gradient (SL) index improves the visualization of anomalous values, assisting in the identification of tectonic structures and large landslides. High positive Gi* values indicate the clustering of SL anomalies (hotspots), and mirror the occurrence of knickzones on the stream long-profiles. We applied this methodology to a mountainous sector of the eastern Emilia-Romagna region, in northern Italy. Remote sensing and field surveys conducted on hotspot sites indicate that large landslides are the main process associated to over-steepened long-profile segments along streams connected to the valley slopes. Along-stream changes in bedrock resistance accounts for the main anomalies within sectors where hillslopes and valley floors are disconnected. We demonstrate that specific relationships between geometry and intensity of SL hotspots are indicative of the process responsible for the knickzone formation and, in particular that tectonic structures generally provide the longest and highest anomalies. The results of this work suggest that SL-HCA maps are more advantageous for detecting and interpreting knickzones compared with traditional SL maps, since: i) they need less input data to be computed, thus making them useful to investigate regions poorly covered by detailed geological data and/or where field surveys are difficult to be carried out and ii) the hotspot geometry can help discriminate the knickzones attributable to gravitational mass movements from litho-structural ones

Spatial analysis of stream length-gradient (SL) index for detecting hillslope processes: A case of the Gállego River headwaters (Central Pyrenees, Spain)

A morphometric analysis of drainage networks and relief using geomorphic indices and geostatistical analyses of topographical data are useful tools for discussing the morphoevolution of a given area Among the geomorphic indices, the stream length-gradient (SL) index represents a practical tool to highlight anomalous changes in river gradients. Perturbations of SL are usually indicative of (1) differences in the resistance of outcropping lithological units to erosion, (2) sub-surface processes, such as active faulting, and (3) slope failures that directly reach the stream channels, particularly in small catchments. In this work, the SL index was calculated for the upstream sector of the Gallego River basin in the central Spanish Pyrenees to test its accuracy and sensitivity for detecting the imprints of different surface processes. A geostatistical procedure is proposed to obtain SL index maps through the interpolation and filtering of the values estimated along the drainage network. This method allows computing of SL, validation and assessing of its spatial distribution with robust statistical accuracy, and objectively defining the anomalies in SL The anomalies in the SL map of the study area, which coincide with knickpoints and knickzones, were analyzed in detail. The results indicate (1) perturbation in the drainage network caused by differences in the resistance to erosion of outcropping lithological units and (2) hillslopes affected by large landslides, earth flows, and rock falls directly reaching the stream bed. This study indicates that the SL index has strong potential to solve geomorphological problems in different geological settings, especially in detecting the role of active, large-scale features that influence landscape evolution. (C) 2014 Elsevier B.V. All rights reserved

Integration of multi-criteria and nearest neighbour analysis with kernel density functions for improving sinkhole susceptibility models: the case study of Enemonzo (NE Italy)

The significance of intra-mountain valleys to infrastructure and human settlements and the need to mitigate the geo-hazard affecting these assets are fundamental to the economy of Italian alpine regions. Therefore, there is a real need to recognize and assess possible geo-hazards affecting them. This study proposes the use of GIS-based analyses to construct a sinkhole susceptibility model based on conditioning factors such as land use, geomorphology, thickness of shallow deposits, distance to drainage network and distance to faults. Thirty-two models, applied to a test site (Enemonzo municipality, NE Italy), were produced using a method based on the Likelihood Ratio (λ) function, nine with only one variable and 23 applying different combinations. The sinkhole susceptibility model with the best forecast performance, with an Area Under the Prediction Rate Curve (AUPRC) of 0.88, was that combining the following parameters: Nearest Sinkhole Distance (NSD), land use and thickness of the surficial deposits. The introduction of NSD as a continuous variable in the computation represents an important upgrade in the prediction capability of the model. Additionally, the model was refined using a kernel density estimation that produced a significant improvement in the forecast performance

Monitoring unstable urbanized slopes in Granada coast through InSARanalysis of Sentinel-1 images

EGU General Assembly 2019, Vienna (Austria) 7-12 April 201

Deterministic and Probabilistic Slope Stability Models Forecast Performance at ~1:5000-Scale

Deterministic methods are appropriate for analyzing specific slopes at site-scale where geotechnical parameters are better known. Probabilistic techniques provide better results than deterministic methods at regional scales (1:10,000–1:50,000). However, the performances of deterministic and probabilistic methods at large scales (e.g. 1:5000-scale) are not well-known. We applied GIS-based deterministic (WEDGEFAIL, SAFETYFACTOR, SHALSTAB) and probabilistic (Likelihood ratio) methods to a mountain road of 14 km in the Alpujarras region (S Spain) to investigate the behavior of these models at detailed scales. The studied road stretch was affected by 111 landslides (7–8 landslides/km) during the 2009–2010 winter in a period of high precipitation. These landslides cut off the road in several points and disconnected the central region of Alpujarras from the main transport infrastructures. We delimited a small study area with only 4 km2 restricted to the slopes that cross the road where we gathered as much data as possible. Our results show that deterministic methods have less prediction capability at ~1:5000-scale than probabilistic methods and it seems that the needed effort to improve their results is not worthwhile. However, it must take into account that probabilistic methods need an inventory and they could not have been applied before the analyzed landslide event. As our results indicate, the deterministic methods, such as the SHALSTAB model, are reliable tools to make an evaluation of the stability of cut slopes in a roadway at project-scale