hydroMT is a model builder framework developed by Deltares to facilitate building and updating hydrological models. It operates on global and local datasets and supports modelers through automating data processing tasks. hydroMT contains reusable methods for processing spatial data and interfaces with hydrological models to build, update, and connect their components. Examples shown include using hydroMT to setup models at different scales and resolutions, build hydrodynamic models quickly, and connect hydrological and water allocation models.

1. Dirk Eilander
Hélène Boisgontier
Mark Hegnauer
hydroMT - model builder framework
17-11-2020
BlueEarth Engine
Deltares presents

4. 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

5. 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

6. 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

7. 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

8. 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

9. 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

10. hydroMT - data
• Interface to global and local user datasets
• yml library file
• data_source.get_data()

11. 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/

12. Attributes
Methods
hydroMT - models
12
• API to read/write, build and update
models
• Attributes: model.staticmaps
• Methods: model.setup_component()
• Easily exentable
?? …

13. 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

14. 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

15. 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

16. 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

17. 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.

18. 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

19. 19
</ DEMO >

20. https://deltares.gitlab.io/wflow/hydromt

21. 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

22. Contact
blueearth.deltares.org
blueearth@deltares.nl
@deltares
@deltares
linkedin.com/company/deltares
facebook.com/deltaresNL
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