hydromt_wflow.WflowSedimentModel.setup_reservoirs#

WflowSedimentModel.setup_reservoirs(reservoirs_fn: str | Path | GeoDataFrame, min_area: float = 1.0, trapping_default: float = 1.0, output_names: Dict = {'reservoir_area__count': 'reservoir_area_id', 'reservoir_location__count': 'reservoir_outlet_id', 'reservoir_surface__area': 'reservoir_area', 'reservoir_water_sediment~bedload__trapping_efficiency': 'reservoir_trapping_efficiency'}, geom_name: str = 'reservoirs', **kwargs)[source]#

Generate maps of reservoir areas and outlets.

Also generates well as parameters with average reservoir area, and trapping efficiency for large particles.

The data is generated from features with min_area [km2] (default is 1 km2) from a database with reservoir geometry, IDs and metadata.

Adds model layers:

• reservoir_area_id map: reservoir IDs [-]

• reservoir_outlet_id map: reservoir IDs at outlet locations [-]

• reservoir_area map: reservoir area [m2]

• reservoir_trapping_efficiency map: reservoir trapping efficiency coefficient [-]

Parameters:

• reservoirs_fn (str) –

  Name of data source for reservoir parameters, see data/data_sources.yml.

  • Required variables: [‘waterbody_id’, ‘Area_avg’]

  • Optional variables: [‘reservoir_trapping_efficiency’]

• min_area (float, optional) – Minimum reservoir area threshold [km2], by default 1.0 km2.

• trapping_default (float, optional) – Default trapping efficiency coefficient for large particles [between 0 and 1], by default 1 to trap 100% of large particles (sand to gravel) for example for gravity dam. For the others the natural deposition in waterbodies from Camp is used.

• output_names (dict, optional) – Dictionary with output names that will be used in the model netcdf input files. Users should provide the Wflow.jl variable name followed by the name in the netcdf file.

• geom_name (str, optional) – Name of the reservoirs geometry in the staticgeoms folder, by default “reservoirs” for reservoirs.geojson.

• kwargs (optional) – Keyword arguments passed to the method hydromt.DataCatalog.get_rasterdataset()