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Distributed Hydrological Modeling and Model Adaption in High Alpine Karst at Regional Scale (Berchtesgaden Alps, Germany)

  • Gabriele KrallerEmail author
  • Michael Warscher
  • Ulrich Strasser
  • Harald Kunstmann
  • Helmut Franz
Chapter
Part of the Environmental Earth Sciences book series (EESCI)

Abstract

Distributed hydrological modeling in karst dominated catchments is challenging as various unknown underground flow conditions and flow directions lead to unknown storage quantities. Missing parameterization in karst catchments at regional scale prevents reliable hydrological modeling of subsurface (unsaturated and saturated) water fluxes; and consequently, climate impact modeling in karst dominated catchments is until today insufficient. The deterministic hydrological model WaSiM-ETH by Schulla and Jasper was applied in the Alpine catchment of the river Berchtesgadener Ache to describe the water balance and to determine and quantify karst impact on hydrological processes at different time and space scales in the watershed. The study area is situated in the northern limestone Alps, characterized by a huge carbonate stratum, which is exposed to karstfication processes since Alpine lift. It is assumed, that subsurface flow channels and heterogeneous storage effects lead to groundwater redistribution through mountain ranges and influence hydrological processes of neighboring valleys. In a first step, former karst research in the area is evaluated to draw the main subsurface flow directions within or in between sub-basins. Based on this, the water balance of the sub-basins is examined to obtain further information on the regional hydrology. This is done by analyzing model results of the hydrological model. A systematic mismatch between modeled and measured runoff (over and underestimation) was detected in three high Alpine karst dominated sub-basins, indicating hydrological subsurface processes at sub-basin scale. The comparison of monthly sums of modeled and measured water storage indicates subsurface water inflow, outflow or redistribution in sub-basins and enables quantification of those processes. Based on these outcomes, a method to predict future water storage in the Berchtesgaden karst is developed and groundwater modeling is adapted in WaSiM-ETH, which was developed to improve the hydrological model for karst-dominated catchments.

Keywords

Alpine karst Distributed hydrological modeling Artificial neural network Water balance 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Gabriele Kraller
    • 1
    Email author
  • Michael Warscher
    • 2
  • Ulrich Strasser
    • 3
  • Harald Kunstmann
    • 2
    • 4
  • Helmut Franz
    • 5
  1. 1.Department of Geoinformatics-Z_GISUniversity of SalzburgSalzburgAustria
  2. 2.Institute for Meteorology and Climate Research (IMK-IFU)Karlsruhe Institute of Technology (KIT)Garmisch-PartenkirchenGermany
  3. 3.Institute for GeographyUniversity of InnsbruckInnsbruckAustria
  4. 4.Institute for GeographyUniversity of AugsburgAugsburgGermany
  5. 5.Berchtesgaden National Park AdministrationBerchtesgadenGermany

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