from dataclasses import field, make_dataclass
from typing import Dict, Sequence, Tuple, Union
from pydantic import Field, field_validator, model_validator
from pydantic.dataclasses import dataclass
from pymbolic.primitives import Variable
import ravenpy.config.processes as p
from ravenpy.config import commands as rc
from ravenpy.config import options as o
from ravenpy.config.base import Sym, SymConfig
from ravenpy.config.commands import (
HRU,
PL,
LandUseClasses,
LandUseParameterList,
SoilClasses,
SoilParameterList,
SoilProfiles,
VegetationClasses,
)
from ravenpy.config.defaults import nc_attrs
from ravenpy.config.rvs import Config
P = dataclass(
make_dataclass(
"Params",
[(f"X{i:02}", Sym, field(default=Variable(f"X{i:02}"))) for i in range(1, 35)],
),
config=SymConfig,
)
# Bug: RavenC tries to write two variables with the same name `Snow Melt (Liquid) [mm]` to netCDF.
[docs]
class OrganicHRU(HRU):
hru_id: int = 1
land_use_class: str = "FOREST"
veg_class: str = "FOREST"
soil_profile: str = "SOILP_ORG"
aquifer_profile: str = "[NONE]"
terrain_class: str = "[NONE]"
[docs]
class BedRockHRU(HRU):
hru_id: int = 2
land_use_class: str = "FOREST"
veg_class: str = "FOREST"
soil_profile: str = "SOILP_BEDROCK"
aquifer_profile: str = "[NONE]"
terrain_class: str = "[NONE]"
[docs]
class HRUs(rc.HRUs):
"""HRUs command for CanadianShield."""
root: Tuple[OrganicHRU, BedRockHRU]
[docs]
class CanadianShield(Config):
"""The Canadian Shield model is a useful configuration of Raven for
Canadian shield basins characterized by shallow soils atop rock,
with ample exposed rock and lakes. It is a custom model for this
type of region, but there is no reference to it in the literature.
"""
params: P = P()
hrus: HRUs = Field([OrganicHRU(), BedRockHRU()], alias="HRUs")
netcdf_attribute: Dict[str, str] = {"model_id": "CanadianShield"}
sub_basins: rc.SubBasins = Field([rc.SubBasin()], alias="SubBasins")
write_netcdf_format: bool = Field(True, alias="WriteNetcdfFormat")
time_step: Union[float, str] = Field(1.0, alias="TimeStep")
calendar: o.Calendar = Field("PROLEPTIC_GREGORIAN", alias="Calendar")
land_use_classes: LandUseClasses = Field(
[rc.LU(name="FOREST", impermeable_frac=0.0, forest_coverage=0.02345)],
alias="LandUseClasses",
)
routing: o.Routing = Field("ROUTE_NONE", alias="Routing")
catchment_route: o.CatchmentRoute = Field(
"ROUTE_TRI_CONVOLUTION", alias="CatchmentRouting"
)
evaporation: o.Evaporation = Field(
o.Evaporation.HARGREAVES_1985, alias="Evaporation"
)
ow_evaporation: o.Evaporation = Field(
o.Evaporation.HARGREAVES_1985, alias="OW_Evaporation"
)
sw_canopy_correct: o.SWCanopyCorrect = Field(
o.SWCanopyCorrect.STATIC, alias="SWCanopyCorrect"
)
rain_snow_fraction: o.RainSnowFraction = Field(
o.RainSnowFraction.DINGMAN, alias="RainSnowFraction"
)
potential_melt_method: o.PotentialMeltMethod = Field(
o.PotentialMeltMethod.DEGREE_DAY, alias="PotentialMeltMethod"
)
precip_icept_frac: o.PrecipIceptFract = Field(
o.PrecipIceptFract.LAI, alias="PrecipIceptFrac"
)
soil_model: rc.SoilModel = Field(3, alias="SoilModel")
monthly_interpolation_method: o.MonthlyInterpolationMethod = Field(
o.MonthlyInterpolationMethod.LINEAR_MID, alias="MonthlyInterpolationMethod"
)
hydrologic_processes: Sequence[Union[rc.Process, p.Conditional]] = Field(
[
p.SnowRefreeze(algo="FREEZE_DEGREE_DAY", source="SNOW_LIQ", to="SNOW"),
p.Precipitation(algo="PRECIP_RAVEN", source="ATMOS_PRECIP", to="MULTIPLE"),
p.CanopyEvaporation(
algo="CANEVP_MAXIMUM", source="CANOPY", to="ATMOSPHERE"
),
p.CanopySublimation(
algo="CANEVP_MAXIMUM", source="CANOPY_SNOW", to="ATMOSPHERE"
),
p.SnowBalance(algo="SNOBAL_TWO_LAYER", source="MULTIPLE", to="MULTIPLE"),
p.Abstraction(algo="ABST_FILL", source="PONDED_WATER", to="DEPRESSION"),
p.OpenWaterEvaporation(
algo="OPEN_WATER_EVAP", source="DEPRESSION", to="ATMOSPHERE"
),
p.Infiltration(algo="INF_HBV", source="PONDED_WATER", to="MULTIPLE"),
p.Interflow(algo="INTERFLOW_PRMS", source="SOIL[0]", to="SURFACE_WATER"),
p.Baseflow(algo="BASE_POWER_LAW", source="SOIL[1]", to="SURFACE_WATER"),
p.Conditional(kind="HRU_TYPE", op="IS", value="SOIL_ORG"),
p.Baseflow(algo="BASE_POWER_LAW", source="SOIL[2]", to="SURFACE_WATER"),
p.Percolation(algo="PERC_GAWSER", source="SOIL[0]", to="SOIL[1]"),
p.Conditional(kind="HRU_TYPE", op="IS", value="SOIL_ORG"),
p.Percolation(algo="PERC_GAWSER", source="SOIL[1]", to="SOIL[2]"),
p.Conditional(kind="HRU_TYPE", op="IS", value="SOIL_ORG"),
p.Percolation(algo="PERC_GAWSER", source="SOIL[0]", to="SOIL[2]"),
p.Conditional(kind="HRU_TYPE", op="IS", value="SOIL_BEDROCK"),
p.SoilEvaporation(algo="SOILEVAP_ROOT", source="SOIL[0]", to="ATMOSPHERE"),
],
alias="HydrologicProcesses",
)
soil_classes: SoilClasses = Field(
[{"name": "TOPSOIL"}, {"name": "VADOSE"}, {"name": "FRACBEDROCK"}],
alias="SoilClasses",
)
soil_profiles: SoilProfiles = Field(
[
{"name": "LAKE"},
{"name": "ROCK"},
{
"name": "SOILP_ORG",
"soil_classes": ("TOPSOIL", "VADOSE", "FRACBEDROCK"),
"thicknesses": (P.X01, P.X02, P.X03),
},
{
"name": "SOILP_BEDROCK",
"soil_classes": ("TOPSOIL", "VADOSE", "FRACBEDROCK"),
"thicknesses": (P.X01, 0, P.X03),
},
],
alias="SoilProfiles",
)
vegetation_classes: VegetationClasses = Field(
[{"name": "FOREST", "max_ht": 5, "max_lai": 5, "max_leaf_cond": 5}],
alias="VegetationClasses",
)
global_parameter: Dict = Field(
{
"SNOW_SWI": P.X15,
"SNOW_SWI_MIN": P.X16,
"SNOW_SWI_MAX": P.X17,
"SWI_REDUCT_COEFF": P.X18,
"RAINSNOW_TEMP": P.X19,
"RAINSNOW_DELTA": P.X20,
"MAX_SWE_SURFACE": P.X21,
"TOC_MULTIPLIER": P.X22,
}
)
soil_parameter_list: SoilParameterList = Field(
{
"parameters": (
"POROSITY",
"HBV_BETA",
"BASEFLOW_COEFF",
"BASEFLOW_N",
"MAX_INTERFLOW_RATE",
"FIELD_CAPACITY",
"SAT_WILT",
"MAX_PERC_RATE",
"PET_CORRECTION",
),
"pl": [
PL(
name="TOPSOIL",
values=(1.0, P.X07, 0.0, 0.0, P.X12, P.X06, P.X05, P.X13, P.X04),
),
PL(name="VADOSE", values=(1.0, 0.0, P.X08, P.X10, 0, 0, 0, P.X14, 0)),
PL(name="FRACBEDROCK", values=(1.0, 0.0, P.X09, P.X11, 0, 0, 0, 0, 0)),
],
},
alias="SoilParameterList",
)
land_use_parameter_list: LandUseParameterList = Field(
{
"parameters": (
"FOREST_SPARSENESS",
"MELT_FACTOR",
"DD_MELT_TEMP",
"REFREEZE_FACTOR",
"DEP_MAX",
"OW_PET_CORR",
),
"pl": [PL(name="FOREST", values=(0, P.X25, P.X24, P.X23, P.X26, P.X27))],
},
alias="LandUseParameterList",
)
vegetation_parameter_list: rc.VegetationParameterList = Field(
{
"parameters": (
"SVF_EXTINCTION",
"SAI_HT_RATIO",
"RAIN_ICEPT_FACT",
"SNOW_ICEPT_FACT",
"MAX_CAPACITY",
"MAX_SNOW_CAPACITY",
),
"pl": [PL(name="FOREST", values=(0.5, 1, P.X28, P.X29, P.X30, P.X31))],
},
alias="VegetationParameterList",
)
seasonal_relative_lai: rc.SeasonalRelativeLAI = Field(
rc.SeasonalRelativeLAI(), alias="SeasonalRelativeLAI"
)
seasonal_relative_height: rc.SeasonalRelativeHeight = Field(
rc.SeasonalRelativeHeight(), alias="SeasonalRelativeHeight"
)
hru_state_variable_table: rc.HRUStateVariableTable = Field(
[
rc.HRUState(
hru_id=1,
data={
"SOIL[0]": P.X01 * 500,
"SOIL[1]": P.X02 * 500,
"SOIL[2]": P.X03 * 500,
},
),
rc.HRUState(
hru_id=2,
data={
"SOIL[0]": P.X01 * 500,
"SOIL[1]": P.X02 * 500,
"SOIL[2]": P.X03 * 500,
},
),
],
alias="HRUStateVariableTable",
)
[docs]
@field_validator("hrus", mode="before")
@classmethod
def equal_area(cls, hrus):
if len(hrus) != 2:
raise ValueError(
f"CanadianShield must have two HRUs, one organic and one bedrock, has {len(hrus)}."
)
areas = []
for hru in hrus:
if isinstance(hru, dict):
areas.append(hru["area"])
else:
areas.append(hru.area)
if len(set(areas)) > 1:
raise ValueError(f"HRUs must have equal areas: {areas}")
return hrus
_nc_attrs = field_validator("netcdf_attribute")(nc_attrs)
_initialized: bool = False
@model_validator(mode="after")
def _init(self):
if not self._initialized:
hrus = self.hrus.root
hrus[0].area *= self.params.X34
hrus[1].area *= 1 - self.params.X34
if self.gauge:
for gauge in self.gauge:
gauge.rain_correction = self.params.X32
gauge.snow_correction = self.params.X33
self._initialized = True
return self