hydroflows.methods.coastal.coastal_tidal_analysis

Derive tide and surge from waterlevel timeseries based on a tidal analysis.

class hydroflows.methods.coastal.coastal_tidal_analysis.CoastalTidalAnalysis(waterlevel_nc: Path, data_root: Path = PosixPath('data/input'), **params)

Derive tide and surge from waterlevel timeseries based on a tidal analysis.

Implements hatyan package to do tidal analysis. Uses 94 tidal constituents to estimate tidal signal.

Parameters:

• waterlevel_timeseries (Path) – Path to waterlevel timeseries to derive tide and surge from.

• data_root (Path, optional) – Folder root where output is stored, by default “data/input/forcing/waterlevel”

See also

CoastalTidalAnalysis Input CoastalTidalAnalysis Output CoastalTidalAnalysis Params

pydantic model hydroflows.methods.coastal.coastal_tidal_analysis.Input

Input parameters for the CoastalTidalAnalysis method.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Fields:

• waterlevel_nc (pathlib.Path)

field waterlevel_nc: Path [Required]

Path to water level time series in NetCDF format whici is used to derive tide and surge.

model_post_init(context: Any, /) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self – The BaseModel instance.

• context – The context.

pydantic model hydroflows.methods.coastal.coastal_tidal_analysis.Output

Output parameters for the CoastalTidalAnalysis method.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Fields:

• surge_timeseries (pathlib.Path)

• tide_timeseries (pathlib.Path)

field surge_timeseries: Path [Required]

Path to output surge timeseries.

field tide_timeseries: Path [Required]

Path to output tide timeseries.

model_post_init(context: Any, /) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self – The BaseModel instance.

• context – The context.

pydantic model hydroflows.methods.coastal.coastal_tidal_analysis.Params

Params for the CoastalTidalAnalysis method.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Fields:

• data_root (pathlib.Path)

• plot_fig (bool)

field data_root: Annotated[Path, AfterValidator(func=outputdirpath_validator)] = PosixPath('data/input')

field plot_fig: bool = True

Make tidal component and timeseries plots. Note: the timeseries difference plot is -1*surge timeseries

model_post_init(context: Any, /) → None

This function is meant to behave like a BaseModel method to initialise private attributes.

It takes context as an argument since that’s what pydantic-core passes when calling it.

Parameters:

• self – The BaseModel instance.

• context – The context.