Analysis of groundwater drought using a variant of the Standardised Precipitation Index

Abstract

A new index for standardising groundwater level time series and characterising groundwater droughts, the Standardised Groundwater level Index (SGI), is described. The SGI is a modification of the Standardised Precipitation Index (SPI) that accounts for differences in the form and characteristics of precipitation and groundwater level time series. The SGI is estimated using a non-parametric normal scores transform of groundwater level data for each calendar month. These monthly estimates are then merged to form a continuous index. The SGI has been calculated for 14 relatively long, up to 103 yr, groundwater level hydrographs from a variety of aquifers and compared with SPI for the same sites. The SPI accumulation period which leads to the strongest correlation between SPI and SGI, qmax, varies between sites. There is a positive linear correlation between qmax and a measure of the range of significant autocorrelation in the SGI series, mmax. For each site the strongest correlation between SPI and SGI is in the range 0.7 to 0.87, and periods of low values of SGI coincide with previously independently documented droughts. Hence SGI is taken to be a robust and meaningful index of groundwater drought. The maximum length of groundwater droughts defined by SGI is an increasing function of mmax, meaning that relatively long groundwater droughts are generally more prevalent at sites where SGI has a relatively long autocorrelation range. Based on correlations between mmax, average unsaturated zone thickness and aquifer hydraulic diffusivity, the source of autocorrelation in SGI is inferred to be dependent on aquifer flow and storage characteristics. For fractured aquifers, such as the Cretaceous Chalk, autocorrelation in SGI is inferred to be primarily related to autocorrelation in the recharge time series, while in granular aquifers, such as the Permo-Triassic Sandstones, autocorrelation in SGI is inferred to be primarily a function of intrinsic aquifer characteristics. These results highlight the need to take into account the hydrogeological context of groundwater monitoring sites when designing and interpreting data from groundwater drought monitoring networks.