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recession_constant(series, bins=300, normalize=False, min_event_length=10, min_n_events=2)[source]#

Recession constant adapted after Kirchner [2009].

  • series (pandas.Series) – Pandas Series with DatetimeIndex and head values.

  • bins (int, optional) – Number of bins to bin the data to.

  • normalize (bool, optional) – normalize the time series to values between zero and one.

  • min_event_length (int, optional) – Minimum length of an event in days. Events shorter than this are discarded.

  • min_n_events (int, optional) – Minimum number of events in a bin. Bins with less events are discarded.


Recession constant in days.

Return type



Recession constant adapted after Kirchner [2009], which is the decay constant of the exponential model fitted to the percentile-wise binned means of the recession segments. The higher the recession constant, the slower the head declines, and vice versa. The following function is fitted to the binned data (similar to the Exponential response function in Pastas):


h(t) = - h_0 * (1 - exp(-t / c))

where h(t) is the head at time t, h_0 is the final head as t goes to infinity, and c is the recession constant.