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DSD-INT 2019 Delft3D FM model for Hong Kong-Groenenboom

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Presentation by Julien Groenenboom, Deltares, at the Delft3D - User Days (Day 2: Hydrodynamics), during Delft Software Days - Edition 2019. Tuesday, 12 November 2019, Delft.

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DSD-INT 2019 Delft3D FM model for Hong Kong-Groenenboom

  1. 1. D e l t a r e s – D e l f t S o f t w a r e D a y s – 1 2 N o v e m b e r 2 0 1 9 Delft3D FM model for Hong Kong Julien Groenenboom, Firmijn Zijl, Theo van der Kaaij and João de Lima Rego
  2. 2. Content of this presentation • Background of this study • Model setup • Model calibration • Model validation • Conclusions Delft3DFMmodelforHongKong 2/24 Victoria Harbour
  3. 3. Background of this study • Area description • Deltares is involved in Hong Kong modelling studies for more than 20 years • Aim of this study • Setup of a 3D hydrodynamic model that is suitable for water quality modelling Delft3DFMmodelforHongKong 3/24 Hong Kong SAR
  4. 4. Model setup – Model coverage and grid generation Delft3DFMmodelforHongKong • Compared to previous model (shown in red), we applied an extended model domain with the aim to: • Improve the modelled residual currents and their variability • Improve the modelled surge • Courant grid approach • The resolution of the network increases with decreasing water depths 4/24 Grid resolution in Hong Kong waters ≤ 300 m
  5. 5. Model setup – Model coverage and grid generation Delft3DFMmodelforHongKong • Fine resolution where needed (physics and area of interest) • Previous model (in red): structured grid • New model (in blue): unstructured grid • Compared to previous grid, the resolution has increased substantially! 5/24
  6. 6. Model setup – Dry points and thin dams • Dry points and thin dams are added to capture the coastline and blockage of flow • Automatic procedure to create dry points • Several manual checks performed as well Delft3DFMmodelforHongKong 6/24
  7. 7. Model setup – Scenario modelling • Grids adjustments can easily be made using Delft3D Flexible Mesh • Possible future reclamations Delft3DFMmodelforHongKong 7/24
  8. 8. Model setup – Grid generation – Convergence tests Delft3DFMmodelforHongKong Convergence tests to determine required resolution • 150 m resolution 8/24
  9. 9. Model setup – Grid generation – Convergence tests Delft3DFMmodelforHongKong Convergence tests to determine required resolution • 150, 75 m resolution 9/24
  10. 10. Model setup – Grid generation – Convergence tests Delft3DFMmodelforHongKong Convergence tests to determine required resolution • 150, 75, 37.5 m resolution Conclusion: Discharges through cross-sections converged already after applying a resolution of 75 m 10/24
  11. 11. Model setup – Grid generation – Convergence tests Delft3DFMmodelforHongKong • Final grid • Courant-grid approach • Curvilinear at selected locations • Time-step limiting cells • Resolution: Hong Kong waters ≤ 300 m Hong Kong coastal zones ≤ 75 m 11/24
  12. 12. Model setup – Grid generation – Workflow Main steps: 1. Base rectangular grid (coarsest resolution) 2. Using polygons to increase resolution by factor 2 (repeat) 3. Using land-sea-boundaries to delete cells that are completely on land • Cell with cell center on land > dry point (scripting) 4. Delete rectangular grid in selected areas 5. Fill deleted parts by triangular or curvilinear grids 6. Check runtimes, time-step limiting cells and model results This is an iterative process Delft3DFMmodelforHongKong 12/24
  13. 13. Model setup – Bathymetry • GEBCO 2014 • Hong Kong local data Delft3DFMmodelforHongKong 13/24
  14. 14. Model setup – Boundary conditions Simulation period • Four-year period (first year is considered spin-up) Open boundaries • Water level (astronomical components) • FES2012 • Inverse Barometer Correction (IBC) • Salinity and temperature • WOA2013 Discharge-points • River discharges • eartH2Observe Delft3DFMmodelforHongKong 14/24
  15. 15. Model setup – Meteorological forcing ECMWF’s ERA5 dataset • Spatially- and time-varying meteorological conditions from ECMWF’s ERA5 dataset. • Hourly interval • On a 0.25˚ by 0.25˚ resolution grid Wind and pressure forcing • Wind speed (u- and v-direction), the atmospheric pressure and the Charnock coefficient from ERA5 Heat-flux model and forcing • Composite heat-flux model • Dew point temperature, cloud coverage and air temperature (in addition to the wind speed) are used as input for this heat-flux model. Delft3DFMmodelforHongKong 15/24
  16. 16. Model setup – Model characteristics Horizontal grid • About 110.000 computational cells • Resolution varies from approx. 5 km at open boundaries to about 75 m • Curvilinear grid in selected area and rivers Vertical grid • 20 equidistant sigma-layers Runtime • 20 partitions (5 nodes with 4 partitions per node) • Intel quad-core e3-1276 v3 processor (4 cores per node with 3.6 GHz per core) • 3.1 days per simulation-year (= 12.3 minutes per simulation-day) Delft3DFMmodelforHongKong 16/24
  17. 17. Model calibration • Spatially uniform bottom roughness → tidal amplitudes • Horizontal/vertical viscosity and diffusivity → horizontal spreading and vertical mixing of salinity and temperature • Using the Smagorinsky sub-grid parameterisation • Solar annual constituent SA and the solar semiannual constituent SSA → seasonal variation in the water level Delft3DFMmodelforHongKong 17/24
  18. 18. Model validation – Water levels • The tidal part of the total water level was derived by performing a harmonic analysis • “Surge” = “total water level” minus “tide” • Good agreement between observed and modelled tide and water levels Delft3DFMmodelforHongKong Cheung Chau 18/24
  19. 19. Model validation – Transport patterns • According to literature and common knowledge, there is a residual offshore current … • … to the southwest during the winter monsoon (dry season) • … to the northeast during the summer monsoon (wet season) Delft3DFMmodelforHongKong 19/24
  20. 20. Model validation – Transport patterns – Dry season Delft3DFMmodelforHongKong 20/24 Bed – Zoomed-out Surface – Zoomed-out Bed – Zoomed-in Surface – Zoomed-in
  21. 21. Model validation – Transport patterns – Wet season Delft3DFMmodelforHongKong Bed – Zoomed-out Surface – Zoomed-out Bed – Zoomed-in Surface – Zoomed-in 21/24
  22. 22. Model validation – Timeseries of salinity Delft3DFMmodelforHongKong 22/24
  23. 23. Model validation – Timeseries of temperature Delft3DFMmodelforHongKong 23/24
  24. 24. Conclusions • Presented how 3D hydrodynamic model can be set up • Using Delft3D FM’s unstructured grid, we were able to cover a large model domain • Resolution in area of interest and where needed • Capture more physics in enlarged model domain • The model is forced by both “tidal”- and “non-tidal”-forcing • Using available data from open sources (FES2012, ERA5, WOA2013) • High spatial and temporal varying meteo-forcing • The model validation shows very satisfactory results • Next step: Water quality modelling • Online-coupling between D-Flow FM and D-Water Quality Delft3DFMmodelforHongKong 24/24
  25. 25. D e l t a r e s – D e l f t S o f t w a r e D a y s – 1 2 N o v e m b e r 2 0 1 9 Delft3D FM model for Hong Kong Julien Groenenboom, Firmijn Zijl, Theo van der Kaaij and João de Lima Rego

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