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Despite the widespread application of landslide susceptibility analyses, there is hardly any information about whether or not the occurrence of recent landslide events was correctly predicted by the relevant susceptibility maps. Hence, the objective of this study is to evaluate four landslide susceptibility maps retrospectively in a landslide-prone area of the Swabian Alb (Germany). The predictive performance of each susceptibility map is evaluated based on a landslide event triggered by heavy rainfalls in the year 2013. The retrospective evaluation revealed significant variations in the predictive accuracy of the analyzed studies. Both completely erroneous as well as very precise predictions were observed. These differences are less attributed to the applied statistical method and more to the quality and comprehensiveness of the used input data. Furthermore, a literature review of 50 peer-reviewed articles showed that most landslide susceptibility analyses achieve very high validation scores. 73% of the analyzed studies achieved an area under curve (AUC) value of at least 80%. These high validation scores, however, do not reflect the high uncertainty in statistical susceptibility analysis. Thus, the quality assessment of landslide susceptibility maps should not only comprise an index-based, quantitative validation, but also an additional qualitative plausibility check considering local geomorphological characteristics and local landslide mechanisms. Finally, the proposed retrospective evaluation approach cannot only help to assess the quality of susceptibility maps and demonstrate the reliability of such statistical methods, but also identify issues that will enable the susceptibility maps to be improved in the future. [ABSTRACT FROM AUTHOR]

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-km 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. [ABSTRACT FROM AUTHOR]

Abstract: A GIS-based model for the assessment of the landslide susceptibility in a selected area of the Jurassic escarpment in the Swabian Alb (SW-Germany) is described, using the weights-of-evidence method. A quantitative model applied to landslides and their causative factors was created and illustrated in susceptibility maps. While previous research work in this area concentrated on large-scale investigations, the present study was carried out at a regional level with a target scale of 1:150,000. The method is based on the assumption that future landslides will occur under the conditions similar or equal to those of past comparable landslides of the same type. Therefore the analysis was limited to one single type of landslides where the causative factors can be assumed as stable over a period of time. Due to uncertainties in the model, mainly because of variances of the weights assigned to the causative factors, the derived probability values, representing the susceptibility for future landslides, have to be considered relative. However, potential susceptible areas can be delineated and landslide indicators can be identified from the available data set. Slopes with angles from 11° to 26°, composed of the Oxford limestone/marls as well as strongly argillaceous and silty colluvial material such as solifluction layers and colluvial cones, are susceptible. The main soil type of the escarpment and the other steep slopes of the Swabian Alb valleys are Rendzinas formed in solifluction layers. Rendzina profiles including rock debris and clay, which are superimposed on marl debris, were also identified as landslide indicators. These findings are in agreement with previous geomorphological studies in the same area. The methodology seems to have widespread applicability beyond this local research area, with the limitation that the knowledge of past landslides input to the model affects the absolute value of the final probability. [Copyright &y& Elsevier]

Landslide databases provide essential information for hazard modeling, damages on buildings and infrastructure, mitigation, and research needs. This study presents the development of a landslide database system named WISL ( W ürzburg I nformation S ystem on L andslides), currently storing detailed landslide data for northern Bavaria, Germany, in order to enable scientific queries as well as comparisons with other regional landslide inventories. WISL is based on free open source software solutions (PostgreSQL, PostGIS) assuring good correspondence of the various softwares and to enable further extensions with specific adaptions of self-developed software. Apart from that, WISL was designed to be particularly compatible for easy communication with other databases. As a central pre-requisite for standardized, homogeneous data acquisition in the field, a customized data sheet for landslide description was compiled. This sheet also serves as an input mask for all data registration procedures in WISL . A variety of “in-database” solutions for landslide analysis provides the necessary scalability for the database, enabling operations at the local server. In its current state, WISL already enables extensive analysis and queries. This paper presents an example analysis of landslides in Oxfordian Limestones in the northeastern Franconian Alb, northern Bavaria. The results reveal widely differing landslides in terms of geometry and size. Further queries related to landslide activity classifies the majority of the landslides as currently inactive, however, they clearly possess a certain potential for remobilization. Along with some active mass movements, a significant percentage of landslides potentially endangers residential areas or infrastructure. The main aspect of future enhancements of the WISL database is related to data extensions in order to increase research possibilities, as well as to transfer the system to other regions and countries. [ABSTRACT FROM AUTHOR]