from typing import Optional
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 EvapotranspirationRegridMethod
from imod.mf6.validation import BOUNDARY_DIMS_SCHEMA, CONC_DIMS_SCHEMA
from imod.schemata import (
AllInsideNoDataSchema,
AllNoDataSchema,
AllValueSchema,
CoordsSchema,
DimsSchema,
DTypeSchema,
IdentityNoDataSchema,
IndexesSchema,
OtherCoordsSchema,
)
from imod.util.spatial import unstack_dim_into_variable
SEGMENT_BOUNDARY_DIMS_SCHEMA = (
BOUNDARY_DIMS_SCHEMA
| DimsSchema("segment", "time", "layer", "y", "x")
| DimsSchema("segment", "layer", "y", "x")
| DimsSchema("segment", "time", "layer", "{face_dim}")
| DimsSchema("segment", "layer", "{face_dim}")
# Layer dim not necessary, as long as there is a layer coordinate present.
| DimsSchema("segment", "time", "y", "x")
| DimsSchema("segment", "y", "x")
| DimsSchema("segment", "time", "{face_dim}")
| DimsSchema("segment", "{face_dim}")
)
[docs]
class Evapotranspiration(BoundaryCondition, IRegridPackage):
"""
Evapotranspiration (EVT) Package.
Any number of EVT Packages can be specified for a single groundwater flow
model. All single-valued variables are free format.
https://water.usgs.gov/water-resources/software/MODFLOW-6/mf6io_6.0.4.pdf#page=86
Parameters
----------
surface: array of floats (xr.DataArray)
is the elevation of the ET surface (L). A time-series name may be
specified.
rate: array of floats (xr.DataArray)
is the maximum ET flux rate (LT −1). A time-series name may be
specified.
depth: array of floats (xr.DataArray)
is the ET extinction depth (L). A time-series name may be specified.
proportion_rate: array of floats (xr.DataArray)
is the proportion of the maximum ET flux rate at the bottom of a segment
(dimensionless). A time-series name may be specified. (petm)
proportion_depth: array of floats (xr.DataArray)
is the proportion of the ET extinction depth at the bottom of a segment
(dimensionless). A timeseries name may be specified. (pxdp)
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.
fixed_cell: array of floats (xr.DataArray)
indicates that evapotranspiration will not be reassigned to a cell
underlying the cell specified in the list if the specified cell is
inactive.
print_input: ({True, False}, optional)
keyword to indicate that the list of evapotranspiration 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 evapotranspiration 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 evapotranspiration 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 = "evt"
_init_schemata = {
"surface": [
DTypeSchema(np.floating),
IndexesSchema(),
CoordsSchema(("layer",)),
BOUNDARY_DIMS_SCHEMA,
],
"rate": [
DTypeSchema(np.floating),
IndexesSchema(),
CoordsSchema(("layer",)),
BOUNDARY_DIMS_SCHEMA,
],
"depth": [
DTypeSchema(np.floating),
IndexesSchema(),
CoordsSchema(("layer",)),
BOUNDARY_DIMS_SCHEMA,
],
"proportion_rate": [
DTypeSchema(np.floating),
IndexesSchema(),
CoordsSchema(("layer",)),
SEGMENT_BOUNDARY_DIMS_SCHEMA,
],
"proportion_depth": [
DTypeSchema(np.floating),
IndexesSchema(),
CoordsSchema(("layer",)),
SEGMENT_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 = {
"surface": [
OtherCoordsSchema("idomain"),
AllNoDataSchema(), # Check for all nan, can occur while clipping
AllInsideNoDataSchema(other="idomain", is_other_notnull=(">", 0)),
],
"rate": [IdentityNoDataSchema("surface")],
"depth": [IdentityNoDataSchema("surface")],
"proportion_rate": [IdentityNoDataSchema("surface")],
"proportion_depth": [
IdentityNoDataSchema("surface"),
AllValueSchema(">=", 0.0),
AllValueSchema("<=", 1.0),
],
"concentration": [IdentityNoDataSchema("surface"), AllValueSchema(">=", 0.0)],
}
_period_data = ("surface", "rate", "depth", "proportion_depth", "proportion_rate")
_keyword_map = {}
_template = BoundaryCondition._initialize_template(_pkg_id)
_auxiliary_data = {"concentration": "species"}
_regrid_method = EvapotranspirationRegridMethod()
[docs]
@init_log_decorator()
def __init__(
self,
surface,
rate,
depth,
proportion_rate,
proportion_depth,
concentration=None,
concentration_boundary_type="auxmixed",
fixed_cell=False,
print_input=False,
print_flows=False,
save_flows=False,
observations=None,
validate: bool = True,
repeat_stress=None,
):
if ("segment" in proportion_rate.dims) ^ ("segment" in proportion_depth.dims):
raise ValueError(
"Segment must be provided for both proportion_rate and"
" proportion_depth, or for none at all."
)
dict_dataset = {
"surface": surface,
"rate": rate,
"depth": depth,
"proportion_rate": proportion_rate,
"proportion_depth": proportion_depth,
"concentration": concentration,
"concentration_boundary_type": concentration_boundary_type,
"fixed_cell": fixed_cell,
"print_input": print_input,
"print_flows": print_flows,
"save_flows": save_flows,
"observations": observations,
"repeat_stress": repeat_stress,
}
super().__init__(dict_dataset)
self._validate_init_schemata(validate)
def _validate(self, schemata, **kwargs):
# Insert additional kwargs
kwargs["surface"] = self["surface"]
errors = super()._validate(schemata, **kwargs)
return errors
def _get_options(
self, predefined_options: dict, not_options: Optional[list] = None
):
options = super()._get_options(predefined_options, not_options=not_options)
# Add amount of segments
if "segment" in self.dataset.dims:
options["nseg"] = self.dataset.dims["segment"] + 1
else:
options["nseg"] = 1
return options
def _get_bin_ds(self):
bin_ds = super()._get_bin_ds()
# Unstack "segment" dimension into different variables
bin_ds = unstack_dim_into_variable(bin_ds, "segment")
return bin_ds
