Pre-defined data catalogs

This page contains a list of (global) datasets which can be used with various HydroMT models and workflows. Below are drop down lists with datasets per pre-defined data catalog for use with HydroMT. The summary per dataset contains links to the online source and available literature.

The deltares_data catalog is only available within the Deltares network. However a selection of this data for a the Piave basin (Northern Italy) is available online in the artifact_data archive and will be used if no data catalog is provided. Local or other datasets can also be included by extending the data catalog with new yaml data catalog files. We plan to provide more data catalogs with open data sources in the (near) future. See the data catalog changelog for recent updates on the pre-defined catalogs.

Using a predefined catalog

From CLI

To use a predefined catalog, you can specify the catalog name with the -d or --data option when running a HydroMT command. For example, to use the deltares_data catalog with the hydromt build command, you can run the following:

hydromt build MODEL -d deltares_data ...

Alternatively, deltares_data can also be accessed with the --dd option:

hydromt build MODEL --dd ...

You can specify a version of the catalog by adding the version number after the catalog name, e.g. deltares_data=v1.0.0.

hydromt build MODEL -d deltares_data=v1.0.0 ...

Once you have set the data catalog you can specify the data source(s) for each method in the HydroMT model workflow file as shown in the example below with the setup_precip_forcing method.

setup_region:
  region:
    bbox: [4.5, 51.5, 6.5, 53.5]

setup_maps_from_rasterdataset:
  raster_fn:
    source: 'eobs'
    version: 'v22.0e'

From Python

To use a predefined catalog in Python, you can specify the catalog name with the data_libs argument when initializing a DataCatalog class. You can specify a data catalog version by adding the version number after the catalog name. You can then get data from the catalog using the DataCatalog.get_rasterdataset() or other :ref: DataCatalog methods.

from hydromt import DataCatalog
data_catalog = DataCatalog(data_libs=["deltares_data"])
# specify a data catalog version
data_catalog = DataCatalog(data_libs=["deltares_data=v2024.2"])
# get data from the catalog
ds = data_catalog.get_rasterdataset("eobs") # get the most recently added
ds = data_catalog.get_rasterdataset("eobs", version="22.0e") # get a specific
version