Cross-border risk assessment of earthquake-induced landslides in Central Asia

Central Asia is one of the most challenging places in the world where various natural hazards can heavily injury populations and resources. Among these hazards, landslides pose a serious threat to human life and human facilities. The large variability of local geological materials, together with the difficulties in forecasting heavy precipitation locally and in quantifying the level of ground shaking, call for harmonized procedures to better quantify the hazard and the negative impact of slope failures across the Central Asian countries. Furthermore, the increase of population and the expansion of urban settlements towards landslide-prone slopes, exacerbate negative consequences associated to slope failures. Especially in less developed countries which are particularly suffering for appropriate resources, there is the urgent need to address landslide research in order to support disaster management and planning activities at the regional level. Under conditions of data scarcity as well as of geographic remoteness – which are of particular concern to Central Asian countries - a sound statistical approach is presented that is able to quantify landslide hazard and risk, which also allows for the inference of information about landslide potential and expected damage for areas where no data coverage is available. With these premises, the main objective of the work is to provide a cross-border risk map of earthquake-induced landslides in Central Asia. To this scope, the main components of risk are evaluated and two main questions are addressed: 1) where are earthquake-induced landslides more likely to occur in future, 2) how is it possible to quantify damages to exposed assets. A first essential step of any landslide hazard and risk assessment is the preparation of a landslide susceptibility map with the objective to identify areas where the potential for landslide activation exists. For the purposes of this research, a landslide susceptibility analysis is performed by exploiting new advances in Geographic Information System (GIS) technology, together with concepts from Bayesian statistics, and promoting the use of open-source tools. Specifically, a range of conditioning factors and their potential impact on landslide occurrence are quantitatively assessed on the basis of the spatial distribution of landslides by applying weights-of-evidence modelling based on (1) a landslide inventory of past events, (2) terrain-derived variables of slope, aspect and curvature, (3) a geological map, (4) a distance from faults map, and (5) a seismic intensity map. A spatial validation of the proposed method is performed, indicating sufficient measures of significance to predicted landslide susceptibility results, which present an overall level of accuracy greater than 70%. Secondarily, the evaluation of expected damage to exposed population is achieved at a transnational level. A physically-based procedure, applicable over the entire Central Asian region, is adopted 1) to identify landslide source areas, 2) to define downhill trajectories of mass movements, and 3) to finally retrieve their impact velocities. By incorporating such dynamic concepts, a landslide hazard map is prepared allowing for a better quantification of the natural phenomenon. For the finally landslide risk task, the expected destructiveness due to landslide activation is calculated by integrating the distribution of population density with the hazard map. Results show that a relatively high level of risk is expected for large cities, i.e., those located in the Fergana Valley, in the proximity of Tashkent in Uzbekistan and Jalal-Abad in Kyrgyzstan, being highly dense populated areas. On the other hand, there is a general medium level of risk extensively expected over the entire Central Asia region, primarily due to the presence of small settlements (having a population density in the order of 1000 persons/km²) exposed to relatively high landslide hazard.

Author dc:creator

• Saponaro, Annamaria

Advisor dc:contributor.advisor

• Parolai, Stefano

Licence dc:rights.uri

• http://rightsstatements.org/vocab/InC/1.0/

Language dc:language.iso

en

Identifier URI

http://dx.doi.org/10.14279/depositonce-6662

OAI identifier oai:identifier

oai:depositonce.tu-berlin.de:11303/7412