Implications of hydraulic anisotropy in periglacial cover beds for flood simulation in low mountain ranges (Ore Mountains, Germany)

The simulation of floods with conceptual rainfall-runoff models is a frequently used method for various applications 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 important to understand the role of this effect in flood models of mesoscale mountain watersheds. Based on previous 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 hydrological 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

How can we model subsurface stormflow at the catchment scale if we cannot measure it?

Subsurface stormflow (SSF) can be a dominant run‐off generation process in humid mountainous catchments (e.g., Bachmair & Weiler, 2011; Blume & van Meerveld, 2015; Chifflard, Didszun, & Zepp, 2008). Generally, SSF develops in structured soils where bedrock or a less permeable soil layer is overlaid by a more permeable soil layer and vertically percolating water is deflected, at least partially, in a lateral downslope direction due to the slope inclination. SSF can also occur when groundwater levels rise into more permeable soil layers and water flows laterally through the more permeable layers to the stream (“transmissivity feedback mechanism”; Bishop, Grip, & O'Neill, 1990). The different existing terms for SSF in the hydrological literature such as shallow subsurface run‐off, interflow, lateral flow, or soil water flow reflects the different underlying process concepts developed in various experimental studies in different environments by using different experimental approaches at different spatial and temporal scales (Weiler, McDonnell, Tromp‐van Meerveld, & Uchida, 2005). Intersite comparisons and the extraction of general rules for SSF generation and its controlling factors are still lacking, which hampers the development of appropriate approaches for modelling SSF. But appropriate prediction of SSF is essential due to its clear influence on run‐off generation at the catchment scale (e.g., Chifflard et al., 2010; Zillgens, Merz, Kirnbauer, & Tilch, 2005), on the formation of floods (e.g., Markart et al., 2013, 2015) and on the transport of nutrients or pollutants from the hillslopes into surface water bodies (Zhao, Tang, Zhao, Wang, & Tang, 2013). However, a precise simulation of SSF in models requires an accurate process understanding including, knowledge about water pathways, residence times, magnitude of water fluxes, or the spatial origin of SSF within a given catchment because such factors determine the transport of subsurface water and solutes to the stream. But due to its occurrence in the subsurface and its spatial and temporal variability, determining and quantifying the processes generating SSF is a challenging task as they cannot be observed directly. Therefore, it is logical to ask whether we can really model SSF correctly if we cannot measure it well enough on the scale of interest (Figure 1). This commentary reflects critically on whether current experimental concepts and modelling approaches are sufficient to predict the contribution of SSF to the run‐off at the catchment scale. This applies in particular to the underlying processes, controlling factors, modelling approaches, research gaps, and innovative strategies to trace SSF across different scales