from dataclasses import field, make_dataclass
from typing import Dict, Sequence, Union
from pydantic import Field, field_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, 22)],
),
config=SymConfig,
)
# Bug: RavenC tries to write two variables with the same name `Snow Melt (Liquid) [mm]` to netCDF.
[docs]
class LandHRU(HRU):
land_use_class: str = "FOREST"
veg_class: str = "FOREST"
soil_profile: str = "DEFAULT_P"
aquifer_profile: str = "[NONE]"
terrain_class: str = "[NONE]"
[docs]
class HRUs(rc.HRUs):
"""HRUs command for GR4J.
Pydantic is able to automatically detect if an HRU is Land or Lake if `hru_type` is provided.
"""
root: Sequence[LandHRU]
[docs]
class SACSMA(Config):
"""Sacramento - Soil Moisture Accounting model
References
----------
Sorooshian, S., Duan, Q., and Gupta, V. K. (1993), Calibration of rainfall-runoff models:
Application of global optimization to the Sacramento Soil Moisture Accounting Model,
Water Resour. Res., 29( 4), 1185– 1194, doi:10.1029/92WR02617.
"""
params: P = P()
hrus: HRUs = Field([LandHRU()], alias="HRUs")
netcdf_attribute: Dict[str, str] = {"model_id": "SACSMA"}
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")
routing: o.Routing = Field("ROUTE_NONE", alias="Routing")
catchment_route: o.CatchmentRoute = Field(
"ROUTE_GAMMA_CONVOLUTION", alias="CatchmentRouting"
)
evaporation: o.Evaporation = Field(o.Evaporation.OUDIN, alias="Evaporation")
rain_snow_fraction: o.RainSnowFraction = Field(
o.RainSnowFraction.DATA, alias="RainSnowFraction"
)
potential_melt_method: o.PotentialMeltMethod = Field(
o.PotentialMeltMethod.DEGREE_DAY, alias="PotentialMeltMethod"
)
soil_model: rc.SoilModel = Field(7, alias="SoilModel")
hydrologic_processes: Sequence[Union[rc.Process, p.Conditional]] = Field(
[
p.SnowBalance(algo="SNOBAL_SIMPLE_MELT", source="SNOW", to="PONDED_WATER"),
p.Precipitation(algo="RAVEN_DEFAULT", source="ATMOS_PRECIP", to="MULTIPLE"),
p.SoilEvaporation(
algo="SOILEVAP_SACSMA", source="MULTIPLE", to="ATMOSPHERE"
),
p.SoilBalance(algo="SOILBAL_SACSMA", source="MULTIPLE", to="MULTIPLE"),
p.OpenWaterEvaporation(
algo="OPEN_WATER_RIPARIAN", source="SURFACE_WATER", to="ATMOSPHERE"
),
],
alias="HydrologicProcesses",
)
soil_classes: SoilClasses = Field(
[
{"name": "UZT"},
{"name": "UZF"},
{"name": "LZT"},
{"name": "LZFP"},
{"name": "LZFS"},
{"name": "ADIM"},
{"name": "GW"},
],
alias="SoilClasses",
)
vegetation_classes: VegetationClasses = Field(
[{"name": "FOREST", "max_ht": 4, "max_lai": 5, "max_leaf_cond": 5}],
alias="VegetationClasses",
)
land_use_classes: LandUseClasses = Field(
[rc.LU(name="FOREST", impermeable_frac=P.X13, forest_coverage=1.0)],
alias="LandUseClasses",
)
soil_profiles: SoilProfiles = Field(
[
{"name": "LAKE"},
{
"name": "DEFAULT_P",
"soil_classes": ("UZT", "UZF", "LZT", "LZFP", "LZFS", "ADIM", "GW"),
"thicknesses": (P.X04, P.X05, P.X06, P.X08, P.X07, 100, 100),
},
],
alias="SoilProfiles",
)
soil_parameter_list: SoilParameterList = Field(
{
"parameters": (
"POROSITY",
"SAC_PERC_ALPHA",
"SAC_PERC_EXPON",
"SAC_PERC_PFREE",
"BASEFLOW_COEFF",
"UNAVAIL_FRAC",
),
"pl": [
PL(
name="[DEFAULT]",
values=(1.0, P.X11, P.X10, P.X09, 0, 0),
),
PL(
name="UZF",
values=(1.0, P.X11, P.X10, P.X09, P.X03, 0),
),
PL(
name="LZFP",
values=(1.0, P.X11, P.X10, P.X09, P.X01, P.X16),
),
PL(
name="LZFS",
values=(1.0, P.X11, P.X10, P.X09, P.X02, 0),
),
],
},
alias="SoilParameterList",
)
land_use_parameter_list: LandUseParameterList = Field(
{
"parameters": (
"GAMMA_SHAPE",
"GAMMA_SCALE",
"MELT_FACTOR",
"STREAM_FRACTION",
"MAX_SAT_AREA_FRAC",
"BF_LOSS_FRACTION",
),
"pl": [
PL(
name="[DEFAULT]",
values=(
P.X18,
P.X19,
P.X17,
P.X15,
P.X14,
P.X12,
),
)
],
},
alias="LandUseParameterList",
)
vegetation_parameter_list: rc.VegetationParameterList = Field(
{
"parameters": ("RAIN_ICEPT_PCT", "SNOW_ICEPT_PCT"),
"pl": [PL(name="[DEFAULT]", values=(0, 0))],
},
alias="VegetationParameterList",
)
hru_state_variable_table: rc.HRUStateVariableTable = Field(
[
rc.HRUState(
hru_id=1,
data={
"SOIL[0]": P.X04 * 1000,
"SOIL[2]": P.X06 * 1000,
},
),
],
alias="HRUStateVariableTable",
)
_nc_attrs = field_validator("netcdf_attribute")(nc_attrs)
def __init__(self, **data):
super().__init__(**data)
if self.gauge:
for gauge in self.gauge:
gauge.rain_correction = self.params.X20
gauge.snow_correction = self.params.X21