Source code for imod.mf6.rch

import numpy as np

from imod.mf6.boundary_condition import BoundaryCondition
from imod.mf6.regridding_utils import RegridderType
from imod.mf6.validation import BOUNDARY_DIMS_SCHEMA, CONC_DIMS_SCHEMA
from imod.schemata import (

[docs]class Recharge(BoundaryCondition): """ Recharge Package. Any number of RCH Packages can be specified for a single groundwater flow model. Parameters ---------- rate: array of floats (xr.DataArray) is the recharge flux rate (LT −1). This rate is multiplied inside the program by the surface area of the cell to calculate the volumetric recharge rate. A time-series name may be specified. 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 recharge 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 recharge 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 recharge 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. """ _pkg_id = "rch" _period_data = ("rate",) _keyword_map = {} _init_schemata = { "rate": [ DTypeSchema(np.floating), IndexesSchema(), CoordsSchema(("layer",)), BOUNDARY_DIMS_SCHEMA, ], "concentration": [ DTypeSchema(np.floating), IndexesSchema(), CoordsSchema( ( "species", "layer", ) ), CONC_DIMS_SCHEMA, ], "print_flows": [DTypeSchema(np.bool_), DimsSchema()], "save_flows": [DTypeSchema(np.bool_), DimsSchema()], } _write_schemata = { "rate": [ OtherCoordsSchema("idomain"), AllNoDataSchema(), # Check for all nan, can occur while clipping AllInsideNoDataSchema(other="idomain", is_other_notnull=(">", 0)), ], "concentration": [IdentityNoDataSchema("rate"), AllValueSchema(">=", 0.0)], } _template = BoundaryCondition._initialize_template(_pkg_id) _auxiliary_data = {"concentration": "species"} _regrid_method = { "rate": (RegridderType.OVERLAP, "mean"), }
[docs] def __init__( self, rate, concentration=None, concentration_boundary_type="auxmixed", print_input=False, print_flows=False, save_flows=False, observations=None, validate: bool = True, repeat_stress=None, ): super().__init__(locals()) self.dataset["rate"] = rate if concentration is not None: self.dataset["concentration"] = concentration self.dataset["concentration_boundary_type"] = concentration_boundary_type self.add_periodic_auxiliary_variable() self.dataset["print_input"] = print_input self.dataset["print_flows"] = print_flows self.dataset["save_flows"] = save_flows self.dataset["observations"] = observations self.dataset["repeat_stress"] = repeat_stress self._validate_init_schemata(validate)
def _validate(self, schemata, **kwargs): # Insert additional kwargs kwargs["rate"] = self["rate"] errors = super()._validate(schemata, **kwargs) return errors