Building a model from scratch
The actual data requirements depend on the application of the Model and the Model type. Both forcing and static data should be provided in netCDF format, with the same grid definition for forcing and static data. The only exception is storage and rating curves for lakes, that should be provided in CSV format, see also Additional settings.
- Forcing data:
- Potential evapotranspiration
- Temperature (optional, only needed for snow and glacier modelling)
The requirements for static data (including model parameters) depend on the Model type. The following data is required for all Model types, but not directly part of a Model component:
- flow direction data (D8)
- river map (location of the river)
- sub-catchment map (model domain)
For the flow direction (D8) data, the PCRaster
ldd convention is used, see also PCRaster ldd. An approach to generate
ldd data is to make use of the Python package pyflwdir:
- to upscale existing flow direction data as the 3 arcsec MERIT Hydro data (Yamazaki et al., 2019)
- or to derive flow directions from elevation data,
see also Eilander et al. (2021) for more information. Pyflwdir is also used by the hydroMT Python package described in the next paragraph. Another approach to generate
ldd data is to make use of PCRaster functionality, see for example lddcreate.
Optionally, but also not directly part of a model component are
gauge locations, that are used to extract gridded data from certain locations.
The following Model types make use of the kinematic wave:
- wflow_sbm + kinematic wave
- wflow_sbm + groundwater flow
and require for the river and overland flow components input data that is described in Surface flow. Reservoirs or lakes can be part of the kinematic wave (optional) and input parameters are described in Reservoirs and Lakes.
Besides the river and overland flow components the wflow_sbm + kinematic wave model consists of the vertical concept SBM and input parameters for this component are described in the SBM section of Model parameters. Finally, the SBM + Kinematic wave model includes the lateral component Subsurface flow routing and parameters that are part of this component are described in the Lateral subsurface flow section of Model parameters. Input parameters for this component of the SBM + Kinematic wave model are derived from the SBM vertical concept and the land slope. One external parameter
khfrac is used to calculate the horizontal hydraulic conductivity at the soil surface
There is also the option to use the local inertial model as part of the
sbm model type:
- for river flow, see also SBM + Local inertial river model.
- for 1D river flow and 2D overland flow combined, see also SBM + Local inertial river (1D) and land (2D) model.
Input parameters for this approach are described in River flow (local inertial), including the optional 1D floodplain schematization, and Overland flow (local inertial) of the Model parameters section.
The HBV model consists besides the river and overland flow components of the HBV vertical concept. Input parameters for this component are described in the HBV section of Model parameters.
The FLEXTopo model consists besides the river and overland flow components of the FLEXTopo vertical concept. Input parameters for this component are described in the FLEXTopo section of Model parameters.
The SBM + Groundwater flow includes besides the river and overland flow components and the vertical SBM concept, the lateral Groundwater flow component. For the unconfined aquifer the input parameters are described in the section Unconfined aquifer of Model parameters. The bottom (
bottom) of the groundwater layer is derived from from the
soilthickness [mm] parameter of
SBM and the provided surface elevation
altitude [m] as part of the static input. The
area parameter is derived from the model grid. Parameters that are part of the boundary conditions of the unconfined aquifer are listed under Constant Head and Boundary conditions of the Model parameters section.
The wflow_sediment model consists of the vertical Soil Erosion concept and the input parameters for this concept are described in the Sediment section of the Model parameters. The parameters of the lateral Sediment Flux in overland flow concept are described in the Overland flow section of the Model parameters. Parameters of this component are not directly set by data from static input. The input parameters of the lateral concept River Sediment Model are listed in River flow of the Model parameters section.
The Model parameters section lists all the parameters per Model component and these Tables can also be used to check which parameters can be part of the output, see also Output NetCDF section and Output CSV section.
Example models can be found in the Example model section.
hydroMT is a Python package, developed by Deltares, to build and analysis hydro models. It provides a generic model api with attributes to access the model schematization, (dynamic) forcing data, results and states.
For the following Wflow models:
- wflow_sbm + kinematic wave
the Wflow plugin hydroMT-wflow of hydroMT can be used to build and analyse these Wflow model types in an automated way.
To learn more about the Wflow plugin of this Python package, we refer to the hydroMT-wflow documentation.
To inspect or modify (for example in QGIS) the netCDF static data of these Wflow models it is convenient to export the maps to a raster format. This can be done as part of the hydroMT-wflow plugin, see also the following example. It is also possible to create again the netCDF static data file based on the modified raster map stack.
- Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H. and Pavelsky, T. M.: MERIT Hydro: A high‐resolution global hydrography map based on latest topography datasets, Water Resour. Res., 2019WR024873, doi:10.1029/2019WR024873, 2019.
- Eilander, D., van Verseveld, W., Yamazaki, D., Weerts, A., Winsemius, H. C., and Ward, P. J.: A hydrography upscaling method for scale-invariant parametrization of distributed hydrological models, Hydrol. Earth Syst. Sci., 25, 5287–5313, https://doi.org/10.5194/hess-25-5287-2021, 2021.