Monthly Standardised Groundwater level Index (SGI) for observation boreholes across the UK from 1891 to 2015, based on reconstructed groundwater level time series (Bloomfield et al., 2018; https://doi.org/10.5285/ccfded8f-c8dc-4a24-8338-5af94dbfcc16). Standardised groundwater levels have been estimated using a non-parametric normal scores transform of groundwater level data for each calendar month. Probability estimates of an SGI being less than 0, -1, -1.5 and -2 are also provided.
Publication date: 2018-03-12
This dataset is part of the following
Monthly standardised groundwater levels have been estimated using a non-parametric normal scores transform for the data for each calendar month. The normal scores transform assigns a value to observations, in this case monthly reconstructed groundwater levels (Bloomfield et al., 2018; https://doi.org/10.5285/ccfded8f-c8dc-4a24-8338-5af94dbfcc16), based on their rank within a data set, in this case groundwater levels for a given month from a given hydrograph. The normal scores transform is undertaken by applying the inverse normal cumulative distribution function to n equally spaced pi values ranging from 1/(2 n) to 1 − 1/(2 n). The values that result are the SGI values.
The quantification of uncertainty in the reconstructed groundwater levels for a given site is based on the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. Parameter sets are considered to be behavioural if their Nash Sutcliffe Efficiency score exceeds 0.5. For each site, all of the behavioural groundwater level reconstructions are converted to SGI series. The probability of the SGI being within an interval on a particular date is equal to the proportion of these behavioural SGI series that fall within this interval and the probability of SGI being less than 0, -1, -1.5 and -2 is reported.