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 http://youtu.be/QwhKiOGjHs
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