This paper provides insights into a new landslide hazards project which is part of a national research program on safe and sustainable transport in Germany funded by the Federal Ministry of Transport and Digital Infrastructure (BMVI). Here we report on a work in progress and present selected results of a pilot study conducted prior to the launch of the research program in 2016. The main goal of the landslide hazards project is to assess the future landslide hazard potential for the federal transport system under the influence of climate change. A federal road-related pilot study with focus on developing an approach to this type of hazard assessment was a first step in this direction. The developed approach is based upon a Geographic Information System (GIS) as mapping tool to combine a landslide susceptibility map with spatial datasets of regional climate change projections. Here we present the basic framework of this approach only, and provide information on landslide activity and climate change. This information refers to findings from three example landslide sites in Germany. The purpose of this paper is to introduce these landslide projects of German transport research against the backdrop of the existing national strategy of climate change adaptation.
In the framework of a DEUFRAKO (German/French cooperation) project on the Prediction and Propagation of Rolling Noise (P2RN), it has been proposed to rank the different German and French road pavements with respect to noise for different long distance configurations representative of real road topographies, ground characteristics and meteorological situations. After identification of those typical 30 configurations, the attenuations between a reference point in the near field and several receiving points in the far field have been computed according to the most relevant and adapted modelling methods currently available. The main goal being the accuracy of the prediction and not the computation time, analytical (ray tracing) and numerical (BEM, Parabolic Equation) approaches have been implemented. In the following, a technique permitting to estimate day and night LAeq and Lden has been used to classify the various pavements for the whole configurations. All those results have been gathered in a common database (DEUFRABASE) which will be directly available on the website of the authors' Institutes. The paper deals with the description of the ranking procedures, how the database is implemented on the web and how to use it for road traffic noise prediction.
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