imod.mf6.River#

class imod.mf6.River(*_, **__)[source]#

River package. Any number of RIV Packages can be specified for a single groundwater flow model. https://water.usgs.gov/water-resources/software/MODFLOW-6/mf6io_6.0.4.pdf#page=71

Parameters:

  • stage (array of floats (xr.DataArray)) – is the head in the river.

  • conductance (array of floats (xr.DataArray)) – is the riverbed hydraulic conductance.

  • bottom_elevation (array of floats (xr.DataArray)) – is the elevation of the bottom of the riverbed.

  • concentration (array of floats (xr.DataArray, optional)) – if this flow package is used in simulations also involving transport, then this array is used as the concentration for inflow over this boundary.

  • concentration_boundary_type (({"AUX", "AUXMIXED"}, optional)) – if this flow package is used in simulations also involving transport, then this keyword specifies how outflow over this boundary is computed.

  • print_input (({True, False}, optional)) – keyword to indicate that the list of river information will be written to the listing file immediately after it is read. Default is False.

  • print_flows (({True, False}, optional)) – Indicates that the list of river flow rates will be printed to the listing file for every stress period time step in which “BUDGET PRINT” is specified in Output Control. If there is no Output Control option and PRINT FLOWS is specified, then flow rates are printed for the last time step of each stress period. Default is False.

  • save_flows (({True, False}, optional)) – Indicates that river flow terms will be written to the file specified with “BUDGET FILEOUT” in Output Control. Default is False.

  • observations ([Not yet supported.]) – Default is None.

  • validate ({True, False}) – Flag to indicate whether the package should be validated upon initialization. This raises a ValidationError if package input is provided in the wrong manner. Defaults to True.

  • repeat_stress (Optional[xr.DataArray] of datetimes) – Used to repeat data for e.g. repeating stress periods such as seasonality without duplicating the values. The DataArray should have dimensions ("repeat", "repeat_items"). The repeat_items dimension should have size 2: the first value is the “key”, the second value is the “value”. For the “key” datetime, the data of the “value” datetime will be used. Can also be set with a dictionary using the set_repeat_stress method.

__init__(stage, conductance, bottom_elevation, concentration=None, concentration_boundary_type='aux', print_input=False, print_flows=False, save_flows=False, observations=None, validate: bool = True, repeat_stress=None)[source]#

Methods

__init__(stage, conductance, bottom_elevation)

add_periodic_auxiliary_variable()

assign_dims(arg)

clip_box([time_min, time_max, layer_min, ...])

Clip a package by a bounding box (time, layer, y, x).

copy()

from_file(path, **kwargs)

Loads an imod mf6 package from a file (currently only netcdf and zarr are supported).

get_auxiliary_variable_names()

get_options(predefined_options[, not_options])

get_regrid_methods()

is_regridding_supported()

returns true if package supports regridding.

isel()

mask(domain)

Mask values outside of domain.

period_data()

period_paths(directory, pkgname, ...)

regrid_like(target_grid[, regridder_types])

Creates a package of the same type as this package, based on another discretization.

render(directory, pkgname, globaltimes, binary)

Render fills in the template only, doesn't write binary data

sel()

set_repeat_stress(times)

Set repeat stresses: re-use data of earlier periods.

skip_masking_dataarray(array_name)

to_netcdf(*args, **kwargs)

Write dataset contents to a netCDF file.

write(pkgname, globaltimes, write_context)

writes the blockfile and binary data

write_binary_griddata(outpath, da, dtype)

write_blockfile(pkgname, globaltimes, ...)

write_datafile(outpath, ds, binary)

Writes a modflow6 binary data file

write_netcdf(directory, pkgname[, ...])

Write to netcdf.

write_perioddata(directory, pkgname, binary)

write_text_griddata(outpath, da, dtype)

Attributes

dataset