Параметри
Susceptibility Modelling of Landslides in Central Nepal
Випуск :
4(107)
ISSN :
1728-3817
Початкова сторінка :
5
Кінцева сторінка :
12
Дата випуску :
20 грудня 2024 р.
Автор(и) :
Лаве Жером
2CRPG, CNRS, Université de Lorraine
Петрушенко Едуард
Анотація :
Background. Landslide processes in the Himalayas represent a major hazard threatening both humans lives and the socio-economic development of the region. The main goal of the present study is to examine the main factors influencing landslides in Central Nepal, to understand their relative importance and connections, and demonstrate the potential of the integrated technique for the assessment of landslide hazards at the regional scale.
Methods. The workflow used in this study consists of the following steps: (1) collection of the data for analysis (numerical topographies, remote sensing data, geological data, inventory of landslides); (2) identification of the main causes of landslides, determination of input parameters for modelling; (3) lineament extraction by using manual and automated approaches; and (4) susceptibility mapping and spatial modelling of landslides.
Results. Based on the overlay analysis of geological and geomorphological data, the susceptibility modelling of landslides in Central Nepal helps to identify the landslide-prone areas (high to low). The analysis confirms the essential role of lineaments in the landslide formation and their relation with tectonic and erosion processes. Therefore, in the regional classification of landslides in the Central Nepal it is necessary to add the landslides associated with weak zones of various nature and orientations.
Conclusions. The susceptibility modeling and landslide forecasting at the regional level are the main stage of the landslide risk evaluating and management. The results concern the general impact of geological-geomorphological and landscape factors on the formation of landslide phenomena in Central Nepal. Carrying out an analysis of landslides and studying their dynamics and regime is only possible with detailed studies and identifying the priority of the influence of each factor on the landslide formation. This study also aims to provide valuable insights for disaster preparedness, risk reduction, and sustainable land use practices in the region.
Methods. The workflow used in this study consists of the following steps: (1) collection of the data for analysis (numerical topographies, remote sensing data, geological data, inventory of landslides); (2) identification of the main causes of landslides, determination of input parameters for modelling; (3) lineament extraction by using manual and automated approaches; and (4) susceptibility mapping and spatial modelling of landslides.
Results. Based on the overlay analysis of geological and geomorphological data, the susceptibility modelling of landslides in Central Nepal helps to identify the landslide-prone areas (high to low). The analysis confirms the essential role of lineaments in the landslide formation and their relation with tectonic and erosion processes. Therefore, in the regional classification of landslides in the Central Nepal it is necessary to add the landslides associated with weak zones of various nature and orientations.
Conclusions. The susceptibility modeling and landslide forecasting at the regional level are the main stage of the landslide risk evaluating and management. The results concern the general impact of geological-geomorphological and landscape factors on the formation of landslide phenomena in Central Nepal. Carrying out an analysis of landslides and studying their dynamics and regime is only possible with detailed studies and identifying the priority of the influence of each factor on the landslide formation. This study also aims to provide valuable insights for disaster preparedness, risk reduction, and sustainable land use practices in the region.
Цитування :
Ivanik, O., Lavé, J., Hadiatska, K., Kravchenko, D., & Petrushenko, E. (2025). Susceptibility Modelling of Landslides in Central Nepal. Visnyk of Taras Shevchenko National University of Kyiv. Geology, 4(107), 5-12.
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5.17 MB
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