WellModel#

class WellModel(stress, rfunc, name, distances, up=False, cutoff=None, settings='well', sort_wells=True, metadata=None)[source]#

Convolution of one or more stresses with a single scaled response function.

Parameters:

stress (list) – list containing the stresses time series.
rfunc (pastas.rfunc instance) – this model only works with the HantushWellModel response function.
name (str) – Name of the stressmodel.
distances (array_like) – list of distances to oseries, must be ordered the same as the stresses.
up (bool, optional) – whether a positive stress has an increasing or decreasing effect on the model, by default False, in which case positive stress lowers e.g., the groundwater level.
cutoff (float, optional) – This argument is deprecated since 0.23. Directly provide this to directly to the response function instance (e.g., ps.Gamma(cutoff=0.999).
settings (str, list of dict, optional) – settings of the time series, by default “well”.
sort_wells (bool, optional) – sort wells from closest to furthest, by default True.
metadata (Optional[list]) –

Notes

This class implements convolution of multiple series with the same response function. This can be applied when dealing with multiple wells in a time series model. The distance(s) from the pumping well(s) to the monitoring well have to be provided for each stress.

Warning

This model only works with the HantushWellModel response function.

Attributes#

nparam

Methods#

`__init__`
`dump_stress`	Method to dump all stresses in the stresses list.
`get_distances`
`get_nsplit`	Determine in how many time series the contribution can be split.
`get_parameters`	Get parameters including distance to observation point and return as array (dimensions = (nstresses, 4)).
`get_settings`	Method to obtain the settings of the stresses.
`get_stress`	Returns the stress(es) of the time series object as a pandas DataFrame.
`set_init_parameters`	Set the initial parameters (back) to their default values.
`simulate`
`to_dict`	Method to export the WellModel object.
`update_stress`	Method to update the settings of the all stresses in the stress model.
`variance_gain`	Calculate variance of the gain for WellModel.