, Volume 12, Issue 2, pp 321–334 | Cite as

Landslide cost modeling for transportation infrastructures: a methodological approach

  • Martin Klose
  • Bodo Damm
  • Birgit Terhorst
Original Paper


This paper presents a new methodology for ex post assessment of direct landslide costs for transportation infrastructures. The methodology includes tools to compile, model, and extrapolate landslide losses on different spatial scales over time. A landslide susceptibility model enables regional cost extrapolation by means of a cost figure obtained from local cost compilation for a representative case study area. On a local level, cost survey is closely linked with cost modeling, a toolset for cost estimation based on landslide databases. Cost modeling uses landslide disaster management process models (LDMMs) and cost modules to simulate and monetize cost factors for certain types of landslide damage. The landslide susceptibility model provides a regional exposure index and updates the cost figure to a cost index which describes the costs per kilometer of traffic route at risk of landslides. Both indexes enable the regionalization of local landslide losses. The methodology is applied and tested in a cost assessment for highways in the Lower Saxon Uplands, NW Germany, in the period 1980 to 2010. In this 7,400-km2 large mountain region, 77 km of highway is located in landslide hazard area. Annual average costs of US$52,000 per km of highway at risk of landslides are identified as cost index for a local case study area. The cost extrapolation results in annual average costs for highways in the Lower Saxon Uplands of US$4.02 million. This test application as well as a validation of selected modeling tools verifies the functionality of this methodology.


Landslide losses Cost modeling Transportation infrastructures Landslide susceptibility Exposure index Cost extrapolation 



This research was funded by the Ministry of Science and Culture of Lower Saxony (MWK Niedersachsen 11.2-76202-10-1/07). The funding of the project is gratefully acknowledged. The authors thank the Lower Saxony Department of Transportation (NLStBV) for the pleasant collaboration and the excellent data support. Thanks are also due to Lynn Highland (USGS) for her valuable suggestions and discussions. This work benefited from a grant for a research visit at the USGS Geologic Hazards Science Center given by the German Academic Exchange Service (DAAD, D/12/45096). We are grateful to both institutions for the support.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.University of Vechta, ISPAVechtaGermany
  2. 2.Institute of Geography and GeologyUniversity of WürzburgWürzburgGermany

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