Abstract:
Abstract
The simulation of floods with conceptual rainfall-runoff models is a frequently used method for various ap -
plications in flood risk management. In mountain areas, the identification of the optimum model parameters
during the calibration is often difficult because of the complexity and variability of catchment properties and
hydrological processes. Central European mountain ranges are typically covered by Pleistocene periglacial
slope deposits. The hydraulic conductivity of the cover beds shows a high degree of anisotropy, so it is impor -
tant to understand the role of this effect in flood models of mesoscale mountain watersheds. Based on previ -
ous field work, the study analyses the sensitivity of the NASIM modeling system to a variation of vertical and
lateral hydraulic conductivity for the Upper Flöha watershed (Ore Mountains, Germany). Depending on the
objective function (Nash-Sutcliffe coefficient, peak discharge), two diametric parameter sets were identified
both resulting in a high goodness-of-fit for total discharge of the flood events, but only one reflects the hydro-
logical process knowledge. In a second step, the knowledge of the spatial distribution of the cover beds is used
to investigate the potential for a simplification of the model parameterisation. The soil types commonly used
for the spatial discretisation of rainfall-runoff models were aggregated to one main class (periglacial cover
beds only). With such a simplified model, the total flood discharge and the runoff components were simulated
with the same goodness of fit as with the original model. In general, the results point out that the anisotropy in
the unsaturated zone, which is intensified by periglacial cover beds, is an important element of flood models.
First, a parameter set corresponding to the hydraulic anisotropy in the cover beds is essential for the optimum
reproduction of the flood dynamics. Second, a discretisation of soil types is not necessarily required for flood
modeling in Central European mountain areas
