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DSD-INT 2020 BlueEarth Engine - hydroMT - model builder framework

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Presentation by Dirk Eilander, Deltares, at the BlueEarth User Day: Explain the past, explore the future, during Delft Software Days - Edition 2020. Monday, 16 November 2020.

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DSD-INT 2020 BlueEarth Engine - hydroMT - model builder framework

  1. 1. Dirk Eilander Hélène Boisgontier Mark Hegnauer hydroMT - model builder framework 17-11-2020 BlueEarth Engine Deltares presents
  2. 2. Rationale OSM 2015 2017 • (Good) data becomes more widely available • At higher temporal and spatial resolution • As the data improves, we want to improve our models ➢ Put data at the centre of the model building process
  3. 3. Rationale • Therefore, we need tools that: − Operate on global and local datasets − Are easy to use (for modelling experts (!)) − Support the modellers by doing the “hard” & “boring” work − Support developments in enhancing these datasets − Are modular: methods and workflows can be reused for different models • Hence, hydroMT was born! GISprocessing
  4. 4. Classical approach 1) Collect local data 2) Collect more local data 3) Collect even more local data 4) Analyse data 5) Build a model 6) Throw away 80% of the collected data 1) Month 1-3 2) Month 3-6 3) Month 6 4) Month 7 5) Month 8-12 6) Month 12 6 Model approach before hydroMT Time
  5. 5. Classical approach 1) Collect local data 2) Collect more local data 3) Collect even more local data 4) Analyse data 5) Build a model 6) Throw away 80% of the collected data New approach 1) Build an initial model base on available (global) data 2) Discuss where improvements are required and which data is missing 3) Collect local data 4) Analyse data 5) Improve the model with the new data 7 Model approach with hydroMT
  6. 6. hydroMT 8 Design • High level interface (CLI) • Data oriented • Modular • Scalable (big data) • Extendable (many models) Features • Build • Update • Connect • Clip • Analyze https://deltares.gitlab.io/wflow/hydromt
  7. 7. hydroMT - methods • Generic, reusable and scalable methods for processing GIS data build on xarray • hydromt.rio − IO for raster and vector spatial data − GIS methods: re-project, rasterize, vectorize, clip, snap, etc. • hydromt.flw − DEM & hydrography analysis1 • hydromt.stats − Statistics: objective functions rasterio 1 https://deltares.gitlab.io/wflow/pyflwdir/ pyflwdir
  8. 8. hydroMT - data • Interface to global and local user datasets • yml library file • data_source.get_data()
  9. 9. hydroMT - workflows • Combination of methods to go from input to model data • For example: wflow.setup_basemaps() 11Based on pyflwdr: https://deltares.gitlab.io/wflow/pyflwdir/
  10. 10. Attributes Methods hydroMT - models 12 • API to read/write, build and update models • Attributes: model.staticmaps • Methods: model.setup_component() • Easily exentable ?? …
  11. 11. hydroMT Examples: wflow National scale hydrological model at three resolutions • Large scale model setup • At 3 different resolutions • hydroMT clipping functionality to create sub-models for use in specific projects
  12. 12. hydroMT Examples: SFINCS hydrodynamic model for South-East coast of US • Build SFINCS model(s) (within minutes!) − Reprojection to nearest UTM zone − Preparing elevation & bathymetry − setting up boundary conditions − Setting up configuration file − Ready to run! mask Elevation / bathymetry
  13. 13. hydroMT Examples: wflow + RIBASIM water allocation for IWRM Indonesia • Connect fluxes for serial (offline connections): − Inflow or runoff at specific location − Precipitation for irrigation and reservoir − Potential evapotranspiration for reservoir Overview of the different processes and fluxes in wflow_sbm model grid cell RIB_RSV RIB_TERM RIB_IRR RIB_IRR RIB_PWS RIB_VIF Extract of the RIBASIM model for Serayu basin, Java, Indonesia
  14. 14. hydromt build wflow hydroMT Examples: wflow + RIBASIM water allocation for IWRM Indonesia RIB_RSV RIB_TERM RIB_IRR RIB_IRR RIB_PWS RIB_VIF Existing water allocation model Build corresponding hydrological model hydromt update RIBASIM wflow_connection Connect model schematizations RIB_RSV RIB_TERM RIB_ADVIR RIB_ADVIR RIB_PWS RIB_VIF wflow_VIF wflow_IRRwflow_RSV wflow_IRR hydromt update RIBASIM wflow_forcing Convert hydrologic model outputs
  15. 15. hydroMT Examples: wflow + D-Emission + D-Water Quality TRWP modelling in the Seine • One of the main drivers of emission, fate and transport of pollutants through the landscape and water network is the water movements through a catchment coming from hydrologic, hydraulic processes. wflow_sbm D-Water Quality Surface Runoff Infiltration excess runoff on paved areas Precipitation Emitted TRWP entering the surface water D-Emission Population Road network Tire road wear particles: The wear of tires during driving with your vehicle generates microparticles that are largely polymer based. These particles aggregate with road particles while being emitted to the environment.
  16. 16. hydroMT Examples: wflow + D-Emission + D-Water Quality TRWP modelling in the Seine From wflow schematization and outputs Preparation of TRWP emission data To integrated TRWP emission and transport modelling
  17. 17. 19 </ DEMO >
  18. 18. https://deltares.gitlab.io/wflow/hydromt
  19. 19. Next steps • Add workflows to setup model forcing (ongoing) • Improve model postprocessing (result visualization, statistics, etc.) • Support offline model coupling − make use of generic model interface • Go open source: − License: under discussion − Planning: early next year • We look forward to your feedback and welcome contributions! 21https://deltares.gitlab.io/wflow/hydromt
  20. 20. Contact blueearth.deltares.org blueearth@deltares.nl @deltares @deltares linkedin.com/company/deltares facebook.com/deltaresNL f a c e b o o k . c o m / d e l t a r e s N L l i n k e d i n . c o m / c o m p a n y / d e l t a r e s @ d e l t a r e s @ d e l t a r e s N L

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