eml_urban_hydro_model package

Subpackages

• eml_urban_hydro_model.type_models package
  • Submodules
    • eml_urban_hydro_model.type_models.area_parameters module
      • AreaParameters
      • get_percent_paved()
      • set_percent_paved()
    • eml_urban_hydro_model.type_models.model_input module
      • ModelInput
    • eml_urban_hydro_model.type_models.model_output module
      • ModelOutput
    • eml_urban_hydro_model.type_models.model_parameters module
      • ModelParameters
    • eml_urban_hydro_model.type_models.preprocessing_parameters module
      • PreprocessingParameters
    • eml_urban_hydro_model.type_models.rho_parameters module
      • RhoParameters
    • eml_urban_hydro_model.type_models.soil_parameters module
      • SoilParameters
    • eml_urban_hydro_model.type_models.vegetation_parameters module
      • VegetationParameters
  • Module contents

Submodules

• eml_urban_hydro_model.area_parameters module
• eml_urban_hydro_model.model module
  • model_st()
• eml_urban_hydro_model.preprocessing module
  • preprocess()
• eml_urban_hydro_model.rho module
  • rho()
• eml_urban_hydro_model.soil_parameters module
• eml_urban_hydro_model.vegetation_parameters module

Module contents

class eml_urban_hydro_model.AreaParameters(*, omegaSoil: Annotated[float, Gt(gt=0)], omegaRoad: Annotated[float, Ge(ge=0)], omegaRoof: Annotated[float, Ge(ge=0)], runoff_coeff_soil: Annotated[float, Ge(ge=0), Le(le=1)] = 0.5, runoff_coeff_roads: Annotated[float, Ge(ge=0), Le(le=1)] = 0.9, runoff_coeff_roofs: Annotated[float, Ge(ge=0), Le(le=1)] = 0.95)

Bases: BaseModel

Container for area parameters.

_abc_impl = <_abc._abc_data object>

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

omegaRoad: float

omegaRoof: float

omegaSoil: float

runoff_coeff_roads: float

runoff_coeff_roofs: float

runoff_coeff_soil: float

class eml_urban_hydro_model.ModelInput(*args, **kwargs)

Bases: DataFrameModel

DataFrame model for the model’s input data.

class Config

Bases: Config

name: str | None = 'ModelInput'

name of schema

precp: Series[float] = 'precp'

time: Series[Timestamp] = 'time'

class eml_urban_hydro_model.ModelOutput(*args, **kwargs)

Bases: DataFrameModel

DataFrame model for the model’s output data.

class Config

Bases: Config

name: str | None = 'ModelOutput'

name of schema

Qirr: Series[float] = 'Qirr'

Qout: Series[float] = 'Qout'

Qroad: Series[float] = 'Qroad'

Qroof: Series[float] = 'Qroof'

Qsoil: Series[float] = 'Qsoil'

Qtank: Series[float] = 'Qtank'

Vflush: Series[float] = 'Vflush'

soil_mois: Series[float] = 'soil_mois'

time: Series[Timestamp] = 'time'

v_tank: Series[float] = 'v_tank'

class eml_urban_hydro_model.ModelParameters(*, k: float = 84, frac_rt2s: float = 0.5, frac_rt2tk: float = 0.5, vegetation_params: VegetationParameters = VegetationParameters(Z_root=140.0), E_max: float = 0.5, E_w: float = 0.0625, heavy: float = 9.166666666666667e-05, soil_params: SoilParameters = SoilParameters(Ks=100.0, n=0.42, beta=12.7, sh=0.08, sw=0.11, ss=0.31, sfc=0.52), area_params: AreaParameters, Vmax: float = 10, lag: int = 0, resolution: int = 5, Qirr: float | None = None, flushing_frequency: float = 2)

Bases: BaseModel

Container for model’s parameters.

E_max: float

E_w: float

Qirr: float | None

Vmax: float

_abc_impl = <_abc._abc_data object>

area_params: AreaParameters

flushing_frequency: float

frac_rt2s: float

frac_rt2tk: float

heavy: float

k: float

lag: int

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

resolution: int

soil_params: SoilParameters

vegetation_params: VegetationParameters

class eml_urban_hydro_model.PreprocessingParameters(*, ic: float = 0.2, T: int = 50, resolution: int = 5)

Bases: BaseModel

Container for preprocess function parameters.

T: int

_abc_impl = <_abc._abc_data object>

ic: float

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

resolution: int

class eml_urban_hydro_model.SoilParameters(*, Ks: float, n: float, beta: float, sh: float, sw: float, ss: float, sfc: float)

Bases: BaseModel

Container for soil parameters.

Ks: float

_abc_impl = <_abc._abc_data object>

beta: float

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

n: float

sfc: float

sh: float

ss: float

sw: float

class eml_urban_hydro_model.VegetationParameters(*, Z_root: float)

Bases: BaseModel

Container for vegetation parameters.

Z_root: float

_abc_impl = <_abc._abc_data object>

model_config: ClassVar[ConfigDict] = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

eml_urban_hydro_model.get_percent_paved(params: AreaParameters) → float

Calculates the percentage of paved area based on the area parameters.

Parameters:

params (AreaParameters) – The area parameters containing omega values.

Returns:

The percentage of paved area (0-100).

Return type:

float

eml_urban_hydro_model.model_st(df: DataFrame[ModelInput], params: ModelParameters) → DataFrame[ModelOutput]

eml_urban_hydro_model.preprocess(original_rainfall: DataFrame[ModelInput], params: PreprocessingParameters = PreprocessingParameters(ic=0.2, T=50, resolution=5)) → DataFrame[ModelInput]

Modify rainfall intensity using a memory term with heavyside equation.

eml_urban_hydro_model.set_percent_paved(params: AreaParameters, percent_paved: float) → AreaParameters

Adjusts the omega* parameters based on the percent_paved value.

Parameters:

• params (AreaParameters) – The original area parameters.

• percent_paved (float) – The desired percentage of paved area (0-100).

Returns:

Updated area parameters with adjusted omega values.

Return type:

AreaParameters