Kasvillisuuden karakterisointi virtausmalleissa laserkeilauksen avulla

Kasvillisuuden karakterisointi
virtausmalleissa laserkeilauksen
avulla
Johanna Jalonen, Juha Järvelä
Mallinnusseminaari 1.4.2015
LUKE
How to model depth and velocities in
vegetated rivers?
•
For the purpose of, e.g.
– Flood prediction
– nutrient and sediment processes
– Ecohydraulics and habitat hydraulics
Q, v, h ?
Modelling problem
• Drag of foliated and defoliated trees of different scales
– Flume studies usually conducted with twigs or small trees
– > direct drag force measurements of trees of H = 1 - 3.5 m
• Characterization of herbaceous and woody vegetation
from point clouds obtained with terrestrial laser scanning
(TLS)
Flow resistance caused by vegetation:
drag force approach
• Drag force F on a rigid object
1
FD  ρC D Ac uc2
2
where ρ = fluid density, CD = drag coefficient,
Ac = reference area (frontal projected area Ap), uc = approach velocity
• For rigid objects AP and CD are constant, but for flexible
vegetation streamlining alters CD and AP values
• One way to account for the reconfiguration is the Vogel
exponent:
Modelling of flexible woody vegetation
• Järvelä (2004):
Determination of flow resistance caused
by non-submerged woody vegetation,
Int. J. River Basin Manage.
′′
4
unitgroundarea
,
The friction factor can be
expressed in terms of FD
• Jalonen & Järvelä (2014)
Estimation of drag forces caused by natural
woody vegetation of different scales.
Journal of Hydrodynamics
1
2
Where
is the characteristic
reference area,
is drag
coefficient, is reconfiguration
parameter,
is the scaling term,
is the mean velocity
Measured parameters for trees of H = 1 – 3.5 m
Bulk χ ≈ - 0.81
χ = 0 for
rigid objects
1
2
0.048
Stem χS ≈ - 0.64
,
0.38
Terrestrial laser scanning of vegetation
properties in the field
1 m2 sampling quadrates:
• 6 samples
• All vegetation harvested
• Manually measured Atot
• Ground level DTM laser scanned after
vegetation removal
Different analyzing methods for
herbaceous and woody vegetation
Highest elevations:
1 cm, 5 cm and 10 cm grid
Voxelization of point clouds:
1 cm, 5 cm and 10 cm voxel grid
Concluding remarks
Implications for modelling:
1) Drag force approach can be
used to model resistance of
complex vegetation
2) Remote sensing can be used
to obtain the parameter -values
TLS-based Atot/AB in 30×30 cm
grid in a floodplain area with
grasses and willows (~1 m tall)
Grasses
Willows
Grasses
Thank you!
More information:
Jalonen, J., Järvelä, J., Virtanen, J.-P., Vaaja, M., Kurkela, M. & Hyyppä, H. 2015.
Determining characteristic vegetation areas by terrestrial laser scanning for
floodplain flow modeling. Water 7(2): 420-437. DOI: 10.3390/w7020420
Jalonen, J., Järvelä, J. 2014. Estimation of drag forces caused by natural woody
vegetation of different scales. Journal of Hydrodynamics 26(4):608-623.
Jalonen, J., Järvelä, J., Koivusalo, H. & Hyyppä, H. 2014. Deriving floodplain
topography and vegetation characteristics for hydraulic engineering applications by
means of terrestrial laser scanning. Journal of Hydraulic Engineering 140(11):
04014056.
Jalonen, J., Jarvelä, J., Aberle, J. 2013. Leaf Area Index as Vegetation Density
Measure for Hydraulic Analyses. Journal of Hydraulic Engineering, 139(5), 461-469.
Funded by: Academy of Finland, Maaja vesitekniikan tuki ry
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