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

Feldmann, David 1,2; Laux, Patrick ORCID iD icon 1,2; Heckl, Andreas; Schindler, Manfred; Kunstmann, Harald 1,2
1 Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU), Karlsruher Institut für Technologie (KIT)
2 Zukunftscampus (CAMPUS), Karlsruher Institut für Technologie (KIT)

Abstract:

Roughness is the key parameter for surface runoff simulations. This study aims to determine robust Manning resistance coefficients (𝑛) on the basis of consecutive artificial rainfall experiments on natural hillslopes available in literature, obtained at 22 different sites with different degrees of vegetation cover and type. The Manning resistance coefficient is particularly important in the context of two dimensional (2D) hydraulic heavy rainfall simulations. Since there is a wide range of possible resistance values available leading to significantly different results regarding the accumulation of surface runoff, especially for shallow water depths. The planning of flood protection structures is directly affected by these uncertainties. This work also improves the knowledge between roughness and the shape of the hydrograph allowing a better calibration of infiltration models. As flow velocity, water depth, and infiltration rate were not observed during the rainfall experiments, only the outflow of the test field and rain intensity are known. For this purpose, a framework was developed to parameterize shallow water depth (< 1 cm) -dependent roughness coefficients. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000154015
Veröffentlicht am 04.01.2023
Originalveröffentlichung
DOI: 10.1016/j.jhydrol.2022.128786
Scopus
Zitationen: 5
Web of Science
Zitationen: 4
Dimensions
Zitationen: 5
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 02.2023
Sprache Englisch
Identifikator ISSN: 0022-1694, 1879-2707
KITopen-ID: 1000154015
HGF-Programm 12.11.33 (POF IV, LK 01) Regional Climate and Hydrological Cycle
Erschienen in Journal of Hydrology
Verlag Elsevier
Band 617
Heft Part A
Seiten Art.-Nr.: 128786
Vorab online veröffentlicht am 01.12.2022
Schlagwörter Depth-dependent roughness coefficients, Flow resistance, Artificial rainfall experiments, Hydraulic rainfall-runoff modelling, Surface runoff, Flash floods
Nachgewiesen in Dimensions
Web of Science
Scopus
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