Source code for imod.mf6.rch

from copy import deepcopy
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.dis import StructuredDiscretization
from imod.mf6.interfaces.iregridpackage import IRegridPackage
from imod.mf6.regrid.regrid_schemes import RechargeRegridMethod
from imod.mf6.utilities.imod5_converter import convert_unit_rch_rate
from imod.mf6.utilities.regrid import RegridderWeightsCache, _regrid_package_data
from imod.mf6.validation import BOUNDARY_DIMS_SCHEMA, CONC_DIMS_SCHEMA
from imod.prepare.topsystem.allocation import ALLOCATION_OPTION, allocate_rch_cells
from imod.schemata import (
    AllInsideNoDataSchema,
    AllNoDataSchema,
    AllValueSchema,
    CoordsSchema,
    DimsSchema,
    DTypeSchema,
    IdentityNoDataSchema,
    IndexesSchema,
    OtherCoordsSchema,
)
from imod.typing import GridDataArray
from imod.typing.grid import (
    enforce_dim_order,
    is_planar_grid,
)


[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
[docs] @classmethod def from_imod5_data( cls, imod5_data: dict[str, dict[str, GridDataArray]], target_dis: StructuredDiscretization, regridder_types: Optional[RechargeRegridMethod] = None, regrid_cache: RegridderWeightsCache = RegridderWeightsCache(), ) -> "Recharge": """ Construct an rch-package from iMOD5 data, loaded with the :func:`imod.formats.prj.open_projectfile_data` function. .. note:: The method expects the iMOD5 model to be fully 3D, not quasi-3D. Parameters ---------- imod5_data: dict Dictionary with iMOD5 data. This can be constructed from the :func:`imod.formats.prj.open_projectfile_data` method. target_dis: GridDataArray The discretization package for the simulation. Its grid does not need to be identical to one of the input grids. regridder_types: RechargeRegridMethod, optional Optional dataclass with regridder types for a specific variable. Use this to override default regridding methods. regrid_cache: RegridderWeightsCache, optional stores regridder weights for different regridders. Can be used to speed up regridding, if the same regridders are used several times for regridding different arrays. Returns ------- Modflow 6 rch package. """ new_idomain = target_dis.dataset["idomain"] data = { "rate": convert_unit_rch_rate(imod5_data["rch"]["rate"]), } new_package_data = {} # first regrid the inputs to the target grid. if regridder_types is None: regridder_settings = Recharge.get_regrid_methods() new_package_data = _regrid_package_data( data, new_idomain, regridder_settings, regrid_cache, {} ) # if rate has only layer 0, then it is planar. if is_planar_grid(new_package_data["rate"]): if "layer" in new_package_data["rate"].dims: planar_rate_regridded = new_package_data["rate"].isel( layer=0, drop=True ) else: planar_rate_regridded = new_package_data["rate"] # create an array indicating in which cells rch is active is_rch_cell = allocate_rch_cells( ALLOCATION_OPTION.at_first_active, new_idomain == 1, planar_rate_regridded, ) # remove rch from cells where it is not allocated and broadcast over layers. rch_rate = planar_rate_regridded.where(is_rch_cell) rch_rate = enforce_dim_order(rch_rate) new_package_data["rate"] = rch_rate return Recharge(**new_package_data, validate=True, fixed_cell=False)
@classmethod def get_regrid_methods(cls) -> RechargeRegridMethod: return deepcopy(cls._regrid_method)