Urban flood modeling using shallow water equations with depth-dependent anisotropic porosity

Özgen, Ilhan; Zhao, Jiaheng; Liang, Dongfang; Hinkelmann, Reinhard

doi:10.1016/j.jhydrol.2016.08.025

Title: Urban flood modeling using shallow water equations with depth-dependent anisotropic porosity

Journal Article · Sat Oct 01 00:00:00 EDT 2016 · Journal of Hydrology

DOI:https://doi.org/10.1016/j.jhydrol.2016.08.025· OSTI ID:1482512

Özgen, Ilhan ^[1]; Zhao, Jiaheng ^[1]; Liang, Dongfang ^[2]; Hinkelmann, Reinhard ^[1]

Technische Univ. Berlin (Germany). Chair of Water Resources Management and Modeling of Hydrosystems
Univ. of Cambridge (United Kingdom). Dept. of Engineering

The shallow water model with anisotropic porosity conceptually takes into account the unresolved subgrid-scale features, e.g. microtopography or buildings. This enables computationally efficient simulations that can be run on coarser grids, whereas reasonable accuracy is maintained via the introduction of porosity. This article presents a novel numerical model for the depth-averaged equations with anisotropic porosity. The porosity is calculated using the probability mass function of the subgrid-scale features in each cell and updated in each time step. The model is tested in a one-dimensional theoretical benchmark before being evaluated against measurements and high-resolution predictions in three case studies: a dam-break over a triangular bottom sill, a dam-break through an idealized city and a rainfall-runoff event in an idealized urban catchment. The physical processes could be approximated relatively well with the anisotropic porosity shallow water model. The computational resolution influences the porosities calculated at the cell edges and therefore has a large influence on the quality of the solution. The computational time decreased significantly, on average three orders of magnitude, in comparison to the classical high-resolution shallow water model simulation.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1482512

Journal Information:: Journal of Hydrology, Vol. 541, Issue PB; ISSN 0022-1694

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 43 works

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