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Research paper

Three-dimensional numerical modelling of floods in river corridor with complex vegetation quantified using airborne LiDAR imagery

, , , , &
Pages 88-108 | Received 28 Sep 2021, Accepted 19 Jul 2022, Published online: 28 Nov 2022
 

Abstract

Excessive flood flow over the historic diversion weir in the vegetated Asahi River in Okayama Prefecture, Japan, was recently recorded for the first time after its renovation work. Fluvial researchers analysed the diversion discharge for flood mitigation measures through laboratory studies and conventional two-dimensional (2-D) depth-averaged simulations. The existing model was insufficient for simulation of certain phenomena such as flow resistance caused by vegetation branches and leaves and vertical flow distribution around the river corridor. Therefore, we developed a three-dimensional (3-D) vegetation resistance porous model by estimating topography, land cover, and vegetation distribution from airborne light detection and ranging (LiDAR) topo-bathymetry (ALB) data. Results show that the water level and flow regime were more reproducible than by referenced 2-D calculations when compared to space-time image velocimetry (STIV) data and field measurements. The diversion discharge designed using the proposed model is feasible with the current riverbed and vegetation conditions.

Acknowledgements

The authors thank the Chugoku Regional Development Bureau, Ministry of Land, Infrastructure, Transport and Tourism, Japan, for offering necessary data recorded along the Asahi and Hyakken rivers. The authors express their gratitude to the anonymous reviewers for their useful suggestions on the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplemental data

Supplemental data for this article can be accessed here https://dx.doi.org/10.1080/00221686.2022.2106596.

Notation

CD=

drag coefficient (–)

Cfk, C=

coefficients related to the vegetation resistance (–)

Cμ, σk, σϵ, Cϵ1, Cϵ2=

turbulent constants (–)

Fi=

component of vegetation resistance in the i direction (m s−2)

g=

acceleration due to gravity (m s−2)

h=

flow depth (m)

H=

water level (m)

i=

subscripts; 1, 2, 3 (–)

j=

dummy indices; 1, 2, 3 (–)

k=

turbulent kinetic energy (m2 s−2)

n=

number of time steps (–)

p=

pressure (kg m−1 s−2)

p0n=

static pressure (kg m−1 s−2)

p'n=

anomaly pressure (kg m−1 s−2)

pn=

known pressure defined in the cell centre (kg m−1 s−2)

p'n+1=

new anomaly pressure (kg m−1 s−2)

Q=

river discharge (m3 s−1)

t=

time (s)

u*=

shear velocity (m s−1)

ub(wb)=

presumed velocity on the cell boundary (m s−1)

ubn+1(wbn+1)=

new velocity on the cell boundary (m s−1)

uc(wc)=

presumed velocities in the cell centre (m s−1)

ui=

flow velocity component in the xi direction (m s−1)

un(wn)=

known velocities in the cell centre (m s−1)

un+1(wn+1)=

new velocities in the cell centre (m s−1)

x=

longitudinal direction for a main river flow (m)

x1, x2, x3=

x, y, z in Cartesian coordinates (m)

y=

cross-sectional direction for a main river flow (m)

z’=

distance from the riverbed in the vertical upward direction (m)

z=

vertical direction for a main river flow (m)

α, β and γ=

ALB-derived proportion of herbaceous, woody and bamboo species, respectively, in each flow computational mesh (–)

γ(i)=

fractional area ratio in the xi direction (%)

γv=

fractional volume ratio or vegetation porosity in a calculation grid (%)

Δ=

distance from the solid wall boundary to the nearest calculation point (m)

δ=

Kronecker's delta (–)

Δt=

calculation time step (s)

Δx, Δy=

horizontal grid sizes (m)

Δz=

vertical grid size (m)

ϵ=

turbulent energy dissipation rate (m2 s−3)

κ=

von Karman constant (–)

λ=

vegetation density (m−1)

λa=

average vegetation density in each numerical mesh (m−1)

λb, λh and λw=

constant density assigned to bamboo, herbaceous and woody species, respectively (m−1)

ν=

coefficient of kinematic viscosity (m2 s−1)

νt=

coefficient of eddy viscosity (m2 s−1)

ρ=

fluid density (kg m−3)

Additional information

Funding

This study was supported in part by the Wesco Scientific Promotion Foundation, the Yakumo Foundation for Environmental Science Grant and the Chugoku Kensetsu Kousaikai.

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