Regionalisation of groundwater droughts using hydrograph classification

Bloomfield, J.P. ORCID: https://orcid.org/0000-0002-5730-1723; Marchant, B.P.; Bricker, S.H.; Morgan, R.B.. 2015 Regionalisation of groundwater droughts using hydrograph classification. Hydrology and Earth System Sciences Discussions, 12 (6). 5293-5341. 10.5194/hessd-12-5293-2015

Before downloading, please read NORA policies.

Preview

Text hessd-12-5293-2015.pdf - Published Version Available under License Creative Commons Attribution. Download (6MB) | Preview

Abstract/Summary

Groundwater drought is a spatially and temporally variable phenomenon. Here we describe the development and application of a method to regionalize and quantify groundwater drought based on categorisation of Standardised Groundwater level Index (SGI) time series. The categorisation scheme uses non-hierarchical k-means cluster analysis. This has been applied to 74 SGI time series for the period January 1983 to August 2012 for a case study from Lincolnshire, UK. Six SGI time series clusters have been identified. For each cluster a correlation can be established between the mean SGI and a mean Standardised Precipitation Index (SPI) associated with an optimal SPI accumulation period, qmax. Based on a comparison of SPI time series for each cluster and SPI estimated for the whole study area, it is inferred that the clusters are largely independent of heterogeneity in the diving meteorology across the study region and are primarily a function of catchment and hydrogeological factors. This inference is supported by the observation that the majority of sites in each cluster are associated with one of three principal aquifers in the study region. The groundwater drought characteristics of the three largest clusters (CL1, CL2 and CL4 that constitute ~80% of the sites) have been analyzed. There is a common linear relationship between drought magnitude and duration for each of three clusters. However, there are differences in the character of the groundwater drought events between the three clusters as a function of autocorrelation of the mean SGI time series for each cluster. For example, CL1 has a relatively short period of significant SGI autocorrelation compared with CL2 (15 and 23 months respectively); CL1 has more than twice the number of drought episodes (39 episodes) than CL2 (15 episodes), and the average and maximum duration of droughts in CL1 (4.6 and 27 months) are less than half those of CL2 (11.3 and 61 months). The drought characteristics of CL4 are intermediate between those of CL1 and CL2. Differences in characteristics between the three clusters are also seen in their response to three major multi-annual droughts that occurred during the analysis period. For example, sites in CL2 with the longest SGI autocorrelation experience the greatest magnitude droughts and are the slowest to recover from drought, with groundwater drought conditions typically persisting at least six months longer than at sites in the other two clusters. Membership of the clusters reflects differences in the autocorrelation of the SGI time series that in turn is shown to be related to unsaturated zone thickness at individual boreholes. This last observation emphasises the importance of catchment and aquifer characteristics as (non-trivial) controls on groundwater drought hydrographs.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.5194/hessd-12-5293-2015
ISSN:	1812-2116
Additional Keywords:	GroundwaterBGS, Groundwater, Groundwater drought
Date made live:	06 Jul 2015 13:59 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/511250

Actions (login required)

View Item

Document Downloads

More statistics for this item...