pastas.stats.sgi.sgi

pastas.stats.sgi.sgi(series: pandas.Series, timescale_months: int = 1) → pandas.Series

Method to compute the Standardized Groundwater Index (SGI) Bloomfield and Marchant [2013].

Parameters:

• series (pandas.Series or Pandas.DataFrame) – Pandas time series of the groundwater levels for which the SGI is to be determined

• timescale_months (integer, optional) – Length of the aggregation period in months (default: 1; allowed: 1, 2, 3)

Returns:

sgi_series – Pandas time series of the groundwater levels. Time series index should be a pandas DatetimeIndex.

Return type:

pandas.Series or Pandas.DataFrame

Notes

The Standardized Groundwater Index (SGI) is a non-parametric method to standardize groundwater levels. The SGI is calculated for each aggregation period within the year separately. The data within that period in all years in the series are used to determine the reference for which the index is calculated for each value in that period. The SGI is a dimensionless index and is used to compare groundwater levels across different wells. It may be useful to resample the time series to a monthly interval before computing the SGI.