Abstract
This paper is representing a successful application and comparison of heuristic and deterministic landslide hazard assessment modelling. The advantages of deterministic model, which quantify hazard more plainly and more transparently, are herein emphasized, as they are usually better accepted by potential end users, i.e., decision makers. However, applying deterministic model on large scale is always challenging due to data shortage and uncertainty. Presented example appears to be applicable in road management, i.e. assessment of landslide hazard exposure of the road network. The case study involved Polog region in North Macedonia, modeled for two types of landslides by two different models. The first included shallow translational sliding mechanism and implementation of SINMAP model, while the second included flow mechanism and implementation of RAMMS model. Both models resulted in concurrent map products, suitable for further use in road network decision making. The latter was identified particularly useful when it can be back analyzed on the basis of recent real flow example with sufficient documentation, such as examples from Polog region in 2015 when massive failures occurred following rainstorm and flooding. In comparison to conventional heuristic map which was created in previous research for the same area, the new maps were more difficult to parameterize, with sufficient certainty, so back analysis is a very useful convenience of this particular case study. In conclusion, regional scale deterministic landslide assessment is desirable tool for standard applications in planing and decision making, but it is also recommendable to use it in combination with expert-driven heuristic outputs.
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References
Haque U, Blum P, da Silva FP, Andersen P, Pilz J, Chalov SR, Malet J-P, Jemec Auflič M, Andres N, Poyiadji E, Lamas PC, Zhang W, Peshevski I, Pétursson HG, Kurt T, Dobrev N, García-Davalillo JC, Halkia M, Ferri S, Gaprindashvili G, Engström J, Keellings D (2016) Fatal landslides in Europe. Landslides 13(6):1545–1554
Hussin HY, Quan Luna B, van Westen CJ, Christen M, Malet J-P, van Asch ThWJ (2012) Parameterization of a numerical 2-D debris flow model with entrainment: a case study of the Faucon catchment, Southern French Alps. Nat Hazards Earth Syst Sci 12:3075–3090
Marjanović M (2014) Conventional and machine learning methods for landslide assessment in GIS. Palacký University, Department of Geoinformatics, Olomouc, 204 p. ISBN 978-80-244-4169-6
Mutter JC (2015) The disaster profiteers: how natural disasters make the rich richer and the poor even poorer. St. Martin’s Press, New York, 288 p. ISBN 978-1137278982
Pack RT, Tarboton DG, Goodwin CN (2001) Assessing terrain stability in a GIS using SINMAP. In: 15th annual GIS conference, GIS 2001, Vancouver, 19–22 Feb 2001, pp 1–9
Peshevski I, Jovanovski M, Abolmasov B, Papic J, Đurić U, Marjanović M, Haque U, Nedelkovska N (2019) Preliminary regional landslide susceptibility assessment using limited data. Geol Croat 72(1):81–92
Acknowledgements
This paper was supported by the project of Ministry of Education of Republic of Serbia TR36009. The entire research was performed under the framework of World Bank project P148023.
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Marjanović, M., Abolmasov, B., Peshevski, I., Reeves, J., Georgievska, I. (2021). Regional Slope Stability Analysis in Landslide Hazard Assessment Context, North Macedonia Example. In: Guzzetti, F., Mihalić Arbanas, S., Reichenbach, P., Sassa, K., Bobrowsky, P.T., Takara, K. (eds) Understanding and Reducing Landslide Disaster Risk. WLF 2020. ICL Contribution to Landslide Disaster Risk Reduction. Springer, Cham. https://doi.org/10.1007/978-3-030-60227-7_29
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