This paper focuses on the studying of landslides in the hinterland area of the Koroška Bela settlement, NW Slovenia. Research has shown that these landslides have the potential to mobilize the ...material into a debris flw. The area of interest is located on the Karavanke mountain ridge, above the settlement of Koroška Bela, which lies on the outskirts of the town of Jesenice. In order to recognize and understand the kinematics of landslides and their triggering mechanisms, a multidisciplinary approach using engineering-geological and geotechnical investigations was applied. Thus, landslide source areas were determined based on engineering-geological mapping. Furthermore, landslide boundaries, types of landslides and sediments that are involved in processes of sliding were mapped in detail. Geotechnical monitoring is benefiial in evaluating rates of movement and failures in the ground under real conditions in the fild. Current investigations as well as historical evidence and previous research prove that the hinterland of Koroška Bela is prone to various types of landslides that together form a source area that has the potential to mobilize into larger debris flw.
Mathematical modelling is a common approach when assessing debris-flow hazards. In this study on the mathematical modelling of debris flows, we applied the widely used Flo2D model. The high accuracy ...of the input parameters is essential for obtaining acceptable results. The numerimi grid in the area of the debrisflow movement is generated from topographic data. The aim of our research was to assess the usefulness of public data for debrisflow-modelling and to compare this data to the LiDAR-derived data. In Slovenia, DEM 5 and DEM 12.5 are publicly available data. However, the morphological accuracy of these dataseis is questionable because of their development methods and their low morphologic resolution. A better solution is LiDAR-derived data with higher resolutions and a multiple options for further improvements with different methods and algorithms. The results with LiDAR data are more accurate-, the torrential channel is better expressed. One downside of LiDAR data is its high price, which prevents wider usage of more precise data. Another downside is the much longer computational times of the model. More precise data means a more agitated surface of the computational grid, which results in shorter computational steps to ensure numerical stability. Methods for LiDAR-derived DEMs improvements are proposed in this study. With modified data, computational times are much shorter and results are even more precise than with non-modified DEMs.
PDF
