@misc{HergertHeidbachReiteretal.2015,
  author    = {Hergert, T. and Heidbach, Oliver and Reiter, Karsten and Giger, S. B. and Marschall, P.},
  title     = {Stress field sensitivity analysis in a sedimentary sequence of the Alpine foreland, northern Switzerland},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {522},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-40960},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-409600},
  pages     = {20},
  year      = {2015},
  abstract  = {The stress field at depth is a relevant parameter for the design of subsurface constructions and reservoir management. Yet the distortion of the regional stress field due to local-scale features such as sedimentary and tectonic structures or topography is often poorly constrained. We conduct a stress sensitivity analysis using 3-D numerical geomechanical modelling with an elasto-plastic material law to explore the impact of such site-specific features on the stress field in a sedimentary sequence of the Swiss Alpine foreland. The model's dimensions are 14 x 14 x 3 km(3) and it contains 10 units with different mechanical properties, intersected by two regional fault zones. An initial stress state is established involving a semi-empirical relationship between the ratio of horizontal to vertical stress and the overconsolidation ratio of argillaceous sediments. The model results indicate that local topography can affect the stress field significantly to depths greater than the relief contrasts at the surface, especially in conjunction with horizontal tectonic loading. The complexity and frictional properties of faults are also relevant. The greatest variability of the stress field arises across the different sedimentary units. Stress magnitudes and stress anisotropy are much larger in stiffer formations such as massive limestones than in softer argillaceous formations. The stiffer formations essentially carry the load of the far-field forces and are therefore more sensitive to changes of the boundary conditions. This general characteristic of stress distribution in the stiff and soft formations is broadly maintained also with progressive loading towards the plastic limit. The stress field in argillaceous sediments within a stack of formations with strongly contrasting mechanical properties like in the Alpine foreland appears to be relatively insensitive to changes in the tectonic boundary conditions and is largely controlled by the maximum stiffness contrast with respect to the load-bearing formations.},
  language  = {en}
}
@misc{SunyerHundechaLawrenceetal.2015,
  author    = {Sunyer, M. A. and Hundecha, Y. and Lawrence, D. and Madsen, H. and Willems, Patrick and Martinkova, M. and Vormoor, Klaus Josef and B{\"u}rger, Gerd and Hanel, Martin and Kriaučiūnienė, J. and Loukas, A. and Osuch, M. and Y{\"u}cel, I.},
  title     = {Inter-comparison of statistical downscaling methods for projection of extreme precipitation in Europe},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {512},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-40892},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-408920},
  pages     = {21},
  year      = {2015},
  abstract  = {Information on extreme precipitation for future climate is needed to assess the changes in the frequency and intensity of flooding. The primary source of information in climate change impact studies is climate model projections. However, due to the coarse resolution and biases of these models, they cannot be directly used in hydrological models. Hence, statistical downscaling is necessary to address climate change impacts at the catchment scale. This study compares eight statistical downscaling methods (SDMs) often used in climate change impact studies. Four methods are based on change factors (CFs), three are bias correction (BC) methods, and one is a perfect prognosis method. The eight methods are used to downscale precipitation output from 15 regional climate models (RCMs) from the ENSEMBLES project for 11 catchments in Europe. The overall results point to an increase in extreme precipitation in most catchments in both winter and summer. For individual catchments, the downscaled time series tend to agree on the direction of the change but differ in the magnitude. Differences between the SDMs vary between the catchments and depend on the season analysed. Similarly, general conclusions cannot be drawn regarding the differences between CFs and BC methods. The performance of the BC methods during the control period also depends on the catchment, but in most cases they represent an improvement compared to RCM outputs. Analysis of the variance in the ensemble of RCMs and SDMs indicates that at least 30\% and up to approximately half of the total variance is derived from the SDMs. This study illustrates the large variability in the expected changes in extreme precipitation and highlights the need for considering an ensemble of both SDMs and climate models. Recommendations are provided for the selection of the most suitable SDMs to include in the analysis.},
  language  = {en}
}