import numpy as np
from imod.mf6.pkgbase import BoundaryCondition
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 GeneralHeadBoundary(BoundaryCondition):
"""
The General-Head Boundary package is used to simulate head-dependent flux
boundaries.
https://water.usgs.gov/water-resources/software/MODFLOW-6/mf6io_6.0.4.pdf#page=75
Parameters
----------
head: array of floats (xr.DataArray)
is the boundary head. (bhead)
conductance: array of floats (xr.DataArray)
is the hydraulic conductance of the interface between the aquifer cell and
the boundary.(cond)
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 general head boundary 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 general head boundary 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 general head boundary 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 = "ghb"
_period_data = ("head", "conductance")
_init_schemata = {
"head": [
DTypeSchema(np.floating),
IndexesSchema(),
CoordsSchema(("layer",)),
BOUNDARY_DIMS_SCHEMA,
],
"conductance": [
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 = {
"head": [
OtherCoordsSchema("idomain"),
AllNoDataSchema(), # Check for all nan, can occur while clipping
AllInsideNoDataSchema(other="idomain", is_other_notnull=(">", 0)),
],
"conductance": [IdentityNoDataSchema("head"), AllValueSchema(">", 0.0)],
"concentration": [IdentityNoDataSchema("head"), AllValueSchema(">=", 0.0)],
}
_keyword_map = {}
_template = BoundaryCondition._initialize_template(_pkg_id)
_auxiliary_data = {"concentration": "species"}
[docs] def __init__(
self,
head,
conductance,
concentration=None,
concentration_boundary_type="aux",
print_input=False,
print_flows=False,
save_flows=False,
observations=None,
validate: bool = True,
repeat_stress=None,
):
super().__init__(locals())
self.dataset["head"] = head
self.dataset["conductance"] = conductance
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["head"] = self["head"]
errors = super()._validate(schemata, **kwargs)
return errors
