<p>Flash floods resulting from torrential precipitation events cause devastating destruction and loss of human lives, as numerous events in Central Europe have demonstrated in recent years. To assess the damage potential of such events, using hydrodynamic 2D-models is the most accurate method to simulate all hydraulic and hydrological processes at the earth's surface.</p>
<p>Beside infiltration, roughness is the key parameter for hydraulic surface runoff simulations. Particularly roughness for near surface runoff is affected by high uncertainties, as numerous available values are only valid for higher water depths. The choice of the roughness coefficient influences the flow velocity and therefore the accumulation of surface runoff. This potentially leads to an inaccurate planning of flood protection measures.</p>
<p>Based on artificial rainfall experiments on natural hillslopes, available in literature, we estimate the roughness coefficient (Manning&#8217;s <em>n</em>). The experiments have been conducted on a wide range of different sites, whose properties differ in vegetation type (pasture, crops, bare soil), vegetation density (0-100%) and slope (10-30%). A framework evaluating rainfall intensity and surface runoff with the aim to separate the impact of infiltration rate and roughness on the shape of the hydrograph is developed. This avoids complex measurements of flow velocity and water depth during the field experiments.</p>
<p>To verify the validity of the framework, three water depth-dependent formulations of roughness and a constant Manning coefficient are used to simulate the measured hydrograph with an idealized hydraulic 2D-model. This finally results in a robust parameterisation of near surface roughness for a water depth below 1 cm. A strong dependence of the roughness coefficient on the degree of vegetation cover and a correlation between rain intensity and roughness was found. In addition, the temporal change of the infiltration rate during the rainfall experiment could precisely be calculated through the determination of roughness. Therefore, the developed framework also allows a better calibration of infiltration models based on artificial rainfall experiments. In conclusion, this study reduces uncertainties in 2D-hydraulic flash flood modeling by providing empirical near surface roughness coefficients.</p>
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