@article{DoblerBuergerStoetter2013,
  author    = {Dobler, C. and B{\"u}rger, Gerd and St{\"o}tter, J.},
  title     = {Simulating future precipitation extremes in a complex Alpine catchment},
  series = {Natural hazards and earth system sciences},
  volume    = {13},
  journal   = {Natural hazards and earth system sciences},
  number    = {2},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1561-8633},
  doi       = {10.5194/nhess-13-263-2013},
  pages     = {263 -- 277},
  year      = {2013},
  abstract  = {The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.},
  language  = {en}
}
@article{WinterSchneebergerDungetal.2019,
  author    = {Winter, Benjamin and Schneeberger, Klaus and Dung, N. V. and Huttenlau, M. and Achleitner, S. and St{\"o}tter, J. and Merz, Bruno and Vorogushyn, Sergiy},
  title     = {A continuous modelling approach for design flood estimation on sub-daily time scale},
  series = {Hydrological sciences journal = Journal des sciences hydrologiques},
  volume    = {64},
  journal   = {Hydrological sciences journal = Journal des sciences hydrologiques},
  number    = {5},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {0262-6667},
  doi       = {10.1080/02626667.2019.1593419},
  pages     = {539 -- 554},
  year      = {2019},
  abstract  = {Design flood estimation is an essential part of flood risk assessment. Commonly applied are flood frequency analyses and design storm approaches, while the derived flood frequency using continuous simulation has been getting more attention recently. In this study, a continuous hydrological modelling approach on an hourly time scale, driven by a multi-site weather generator in combination with a -nearest neighbour resampling procedure, based on the method of fragments, is applied. The derived 100-year flood estimates in 16 catchments in Vorarlberg (Austria) are compared to (a) the flood frequency analysis based on observed discharges, and (b) a design storm approach. Besides the peak flows, the corresponding runoff volumes are analysed. The spatial dependence structure of the synthetically generated flood peaks is validated against observations. It can be demonstrated that the continuous modelling approach can achieve plausible results and shows a large variability in runoff volume across the flood events.},
  language  = {en}
}