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METHODOLOGY OF PREDICTING LANDSLIDE HAZARDS ON A REGIONAL AND LOCAL SCALE: PRINCIPLES AND MODELS

Journal: Visnyk of Taras Shevchenko National University of Kyiv. Geology (Vol.66, No. 3)

Publication Date:

Authors : ;

Page : 55-60

Keywords : landslide hazard; prediction; GIS; stress-stain state;

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Abstract

Assessment of geohazard risks in some areas within man-made systems should be based on an integrated analysis of qualitative and, primar-ily, quantitative data on the geology and geomorphology of the territory and the corresponding causative physiographic factors. The main objective of this paper is to provide the scientific background to locating areas prone to geohazards and modeling their impacts on systems of natural and man-made origin. The methods of deterministic modeling and prediction are used for the purpose. We have analyzed the world experience in re-gional and local landslide hazards prediction based on the integrated approach. Regional landslide hazard prediction involving stochastic and de-terministic approaches yields highly reliable results. Local predictions are a valuable research tool used in order to explore the nature of landslides and to identify their location and interaction with engineering facilities. A forecast-reference model for landslide hazards assessment within the Carpathian polygon has been developed. GIS-analysis has been used to determine the forecast-standard features of landslides, major indicators and triggering factors. The analysis has provided a database for developing a conceptual model of the region with a set of map layers and attrib-utes. There has been carried out a comparative analysis of methods used for predicting local landslide hazards. The stress-strain state of the rock mass has been proved to be one of the most important criteria for evaluating the slope stability. A strategy has been developed for stress-stain assessment and formalization of the calculations for landslide slopes with variable parameters of water saturation.

Last modified: 2015-05-13 18:10:55