Suchergebnisse

Abstract. Landslides are widespread phenomena that occur in any terrestrial area with slopes, causing massive property damage and, in the worst-case scenario, loss of human life. This propensity to suffer losses is particularly high for developing countries due to their urban development, population growth and drastic land use changes. Social and economic consequences of landslides can be reduced through detailed planning and management strategies, which can be aided by risk analysis. In this study, we performed a detailed quantitative risk analysis for landslides in the whole of Central Asia (4 000 000 km2). Landslide-induced risk was computed, using a 200 m spatial resolution, in terms of exposed population and expected economic losses to buildings and linear infrastructures (roads and railways). The purpose of our study is to produce the first regional-scale landslide risk assessment for Central Asia in order to inform regional-scale risk mitigation strategies, and it represents an advanced step in the landslide risk analysis for extremely broad areas.

Abstract. Central Asia regions are characterized by active tectonics, high mountain chains with extreme topography with glaciers, and strong seasonal rainfall events. These key predisposing factors make large landslides a serious natural threat in the area, causing several casualties every year. The mountain crests are divided by wide lenticular or narrow, linear intermountain tectonic depressions, which are incised by many of the most important Central Asia rivers and are also subject to major seasonal river flood hazard. This multi-hazard combination is a source of potential damming scenarios, which can bring cascading effects with devastating consequences for the surrounding settlements and population. Different hazards can only be managed with a multi-hazard approach coherent within the different countries, as suggested by the requirements of the Sendai Framework for Disaster Risk Reduction. This work was carried out within the framework of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project as part of a multi-hazard approach with the aim of providing a damming susceptibility analysis at a regional scale for Central Asia. To achieve this, a semi-automated GIS-based mapping method, centered on a bivariate correlation of morphometric parameters defined by a morphological index, originally designed to assess the damming susceptibility at basin/regional scale, was modified to be adopted nationwide and applied to spatially assess the obstruction of the river network in Central Asia for mapped and newly formed landslides. The proposed methodology represents an improvement to the previously designed methodology, requiring a smaller amount of data, bringing new preliminary information on damming hazard management and risk reduction, and identifying the most critical area within the Central Asia regions.

Abstract. Central Asia is an area characterized by complex tectonics and active deformation; the related seismic activity controls the earthquake hazard level that, due to the occurrence of secondary and tertiary effects, also has direct implications for the hazard related to mass movements such as
landslides, which are responsible for an extensive number of casualties
every year. Climatically, this region is characterized by strong rainfall
gradient contrasts due to the diversity of climate and vegetation zones.
The region is drained by large, partly snow- and glacier-fed rivers that
cross or terminate in arid forelands; therefore, it is also affected by a
significant river flood hazard, mainly in spring and summer seasons. The
challenge posed by the combination of different hazards can only be tackled by
considering a multi-hazard approach harmonized among the different
countries, in agreement with the requirements of the Sendai Framework for
Disaster Risk Reduction. This work was carried out within the framework of
the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project as part of a multi-hazard approach and is
focused on the first landslide susceptibility analysis at a regional scale
for Central Asia. To this aim the most detailed landslide inventories,
covering both national and transboundary territories, were implemented in a
random forest model, together with several independent variables. The
proposed approach represents an innovation in terms of resolution (from 30
to 70 m) and extension of the analyzed area with respect to previous
regional landslide susceptibility and hazard zonation models applied in
Central Asia. The final aim was to provide a useful tool for land
use planning and risk reduction strategies for landslide scientists,
practitioners, and administrators.

Abstract. In this work, we apply a physically based model, namely the
HIRESSS (HIgh REsolution Slope Stability Simulator) model, to forecast the
occurrence of shallow landslides at the regional scale. HIRESSS is a physically
based distributed slope stability simulator for analyzing shallow landslide
triggering conditions during a rainfall event. The modeling software is made up of two
parts: hydrological and geotechnical. The hydrological model is based on an
analytical solution from an approximated form of the Richards equation, while
the geotechnical stability model is based on an infinite slope model that
takes the unsaturated soil condition into account. The test area is a portion
of the Aosta Valley region, located in the northwest of the Alpine mountain chain. The
geomorphology of the region is characterized by steep slopes with elevations
ranging from 400 m a.s.l. on the Dora Baltea River's floodplain to
4810 m a.s.l. at Mont Blanc. In the study area, the mean annual
precipitation is about 800–900 mm. These features make the territory
very prone to landslides, mainly shallow rapid landslides and rockfalls.
In order to apply the model and to increase its reliability, an in-depth
study of the geotechnical and hydrological properties of hillslopes
controlling shallow landslide formation was conducted. In particular, two
campaigns of on site measurements and laboratory experiments were performed
using 12 survey points. The data collected contributed to the generation of an input map
of parameters for the HIRESSS model. In order to consider the effect of
vegetation on slope stability, the soil reinforcement due to the presence of
roots was also taken into account; this was done based on vegetation maps and
literature values of root cohesion. The model was applied using back analysis
for two past events that affected the Aosta Valley region between 2008 and
2009, triggering several fast shallow landslides. The validation of the
results, carried out using a database of past landslides, provided good
results and a good prediction accuracy for the HIRESSS model from both a
temporal and spatial point of view.