Near surface roughness estimation: A parameterization derived from artificial rainfall experiments and two-dimensional hydrodynamic modelling for multiple vegetation coverages

Roughness is the key parameter for surface runoff simulations. This study aims to determine robust Manning resistance coefficients (n) on basis of consecutive artificial rainfall experiments natural hillslopes available in literature, obtained at 22 different sites with degrees vegetation cover and type. The coefficient particularly important context two-dimensional (2D) hydraulic heavy Since there a wide range possible values leading significantly results regarding accumulation runoff, especially shallow water depths. planning flood protection structures directly affected by these uncertainties. work also improves knowledge between roughness shape hydrograph allowing better calibration infiltration models. As flow velocity, depth, rate were not observed during experiments, only outflow test field rain intensity are known. For this purpose, framework was developed parameterize depth (<1 cm) -dependent coefficients. To robustness framework, three formulations depth-dependent constant used comparing measured discharge under intensities simulations 2D-hydraulic model. We identified strong dependency Manning’s n degree -type as well an influence events. finally leads more parameterization near hydrodynamic modelling, which simulation