QUANTATIVE REGIONAL LANDSLIDE HAZARD PREDICTION USING GIS WITHIN SOUTHERN COAST OF CRIMEA

Landslides on the southern coast of Crimea have been an object of long-term research and exploration. However, the existing techniques to identify landslide formation factors and to predict landslides have grown and of date. This is related to the lack of funding of the monitoring work that provides the database required for landslide predicting, as well as to the change of the research direction ? from grand landslide systems to shallow-lying landslides in deluvial-eluvial deposits. The purpose of the study is to introduce and substantiate the relevant method of regional prediction of landslide distribution and activation in surface deposits. Design/methodology/approach. We propose to analyze landslide hazard areas based on regional predicting method with GIS means. As the latter, SINMAP tool, or the method of stability index mapping technique, was selected. Using the slope stability factor as a criterion for determining the landslide hazard and geological-hydrogeological approach to analyze landslide formation factors, this technique permits to perform quantitative, i.e. deterministic spatial and temporal predicting of landslide hazard areas. The south-western landslide sub-area was selected as a test site characterized by the highest percentage of damage by landslide forms and numbering around 600 landslides within it, most of which are specifically shallow-lying landslides the activation or formation of which is caused by joint or separate effect of man-caused load (in the form of slope undercutting, overload or overwatering), erosion and weather conditions (in the form of excessive precipitation). Findings. As a result of the study and calculations a map model has been created constituting the basis for regional zoning of the area according to the landslide hazard degree. The stability index is a probabilistic characteristic of the stability factor, therefore its variation range is from 0 to 1. The sites with the stability index of <1 are characterized as prone to landslides. Around 25 % of the preliminarily identified, examined and mapped landslides are within the landslide hazard areas detected using the GIS tool. Practical value/implications. The obtained results are significant and necessary in economic planning and efficient land use within the territories of the south-western coast. The strongest predictive performance is achieved by the SINMAP using terrain attributes in combination with land use data.