import numpy as np
from imod.logging import init_log_decorator
from imod.mf6.boundary_condition import BoundaryCondition
from imod.mf6.interfaces.iregridpackage import IRegridPackage
from imod.mf6.regrid.regrid_schemes import RechargeRegridMethod
from imod.mf6.validation import BOUNDARY_DIMS_SCHEMA, CONC_DIMS_SCHEMA
from imod.schemata import (
AllInsideNoDataSchema,
AllNoDataSchema,
AllValueSchema,
CoordsSchema,
DimsSchema,
DTypeSchema,
IdentityNoDataSchema,
IndexesSchema,
OtherCoordsSchema,
)
[docs]
class Recharge(BoundaryCondition, IRegridPackage):
"""
Recharge Package.
Any number of RCH 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=79
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.
fixed_cell: ({True, False}, optional)
indicates that recharge will not be reassigned to a cell underlying the
cell specified in the list if the specified cell is inactive.
"""
_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 = RechargeRegridMethod()
[docs]
@init_log_decorator()
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,
fixed_cell: bool = False,
):
dict_dataset = {
"rate": rate,
"concentration": concentration,
"concentration_boundary_type": concentration_boundary_type,
"print_input": print_input,
"print_flows": print_flows,
"save_flows": save_flows,
"observations": observations,
"repeat_stress": repeat_stress,
"fixed_cell": fixed_cell,
}
super().__init__(dict_dataset)
self._validate_init_schemata(validate)
def _validate(self, schemata, **kwargs):
# Insert additional kwargs
kwargs["rate"] = self["rate"]
errors = super()._validate(schemata, **kwargs)
return errors
