Regionalisation of groundwater droughts using hydrograph classification

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

Regional analysis of groundwater droughts using hydrograph classification

Groundwater drought is a spatially and temporally variable phenomenon. Here we describe the development of a method to regionally analyse and quantify groundwater drought. The method uses a cluster analysis technique (non-hierarchical k-means) to classify standardised groundwater level hydrographs (the standardised groundwater level index, SGI) prior to analysis of their groundwater drought characteristics, and has been tested using 74 groundwater level time series from Lincolnshire, UK. Using the test data set, six clusters of hydrographs have been identified. For each cluster a correlation can be established between the mean SGI and a mean standardised precipitation index (SPI), where each cluster is associated with a different SPI accumulation period. Based on a comparison of SPI time series for each cluster and for the study area as a whole, it is inferred that the clusters are independent of the driving meteorology 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 the principal aquifers in the study region. The groundwater drought characteristics of the three largest clusters, which constitute ~ 80 % of the sites, have been analysed. There are differences in the distributions of drought duration, magnitude and intensity of groundwater drought events between the three clusters as a function of autocorrelation of the mean SGI time series for each cluster. In addition, there are differences between the clusters in their response to three major multi-annual droughts that occurred during the analysis period. For example, sites in the cluster with the longest SGI autocorrelation experience the greatest-magnitude droughts and are the slowest to recover from major droughts, with groundwater drought conditions typically persisting at least 6 months longer than at sites in the other clusters. Membership of the clusters 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. The method of analysis is flexible and can be adapted to a wide range of hydrogeological settings while enabling a consistent approach to the quantification of regional differences in response of groundwater to meteorological drought

Spatio-temporal modelling of the status of groundwater droughts

An empirical (geo)statistical modelling scheme is developed to address the challenges of modelling the severity and distribution of groundwater droughts given their spatially and temporally heterogeneous nature and given typically highly irregular groundwater level observations in space and time. The scheme is tested using GWL measurements from 948 observation boreholes across the Chalk aquifer (UK) to estimate monthly groundwater drought status from 1960 to 2013. For each borehole, monthly GWLs are simulated using empirical mixed models where the fixed effects are based on applying an impulse response function to the local monthly precipitation. Modelled GWLs are standardised using the Standardised Groundwater Index (SGI) and the monthly SGI values interpolated across the aquifer to produce spatially distributed monthly maps of SGI drought status for 54 years for the Chalk. The mixed models include fewer parameters than comparable lumped parameter groundwater models while explaining a similar proportion (more than 65%) of GWL variation. In addition, the empirical modelling approach enables confidence bounds on the predicted GWLs and SGI values to be estimated without the need for prior information about catchment or aquifer parameters. The results of the modelling scheme are illustrated for three major episodes of multi-annual drought (1975–1976; 1988–1992; 2011–2012). They agree with previous documented analyses of the groundwater droughts while providing for the first time a systematic, spatially coherent characterisation of the events. The scheme is amenable to use in near real time to provide short term forecasts of groundwater drought status if suitable forecasts of the driving meteorology are available

Reconstruction of multi-decadal groundwater level time-series using a lumped conceptual model

Multi-decadal groundwater level records, which provide information about long-term variability and trends, are relatively rare. Whilst a number of studies have sought to reconstruct river flow records, there have been few attempts to reconstruct groundwater level time-series over a number of decades. Using long rainfall and temperature records, we developed and applied a methodology to do this using a lumped conceptual model. We applied the model to six sites in the UK, in four different aquifers: Chalk, limestone, sandstone and Greensand. Acceptable models of observed monthly groundwater levels were generated at four of the sites, with maximum Nash–Sutcliffe Efficiency scores of between 0.84 and 0.93 over the calibration and evaluation periods, respectively. These four models were then used to reconstruct the monthly groundwater level time-series over approximately 60 years back to 1910. Uncertainty in the simulated levels associated with model parameters was assessed using the Generalized Likelihood Uncertainty Estimation method. Known historical droughts and wet period in the UK are clearly identifiable in the reconstructed levels, which were compared using the Standardized Groundwater Level Index. Such reconstructed records provide additional information with which to improve estimates of the frequency, severity and duration of groundwater level extremes and their spatial coherence, which for example is important for the assessment of the yield of boreholes during drought period

Illustrative components of the geological environment

In this chapter we provide an account of the contribution made by the Geosphere, in particular bedrock geological materials (part of the lithosphere), groundwater and hydrochemistry to the development of a GDF. In order to put this in context we provide a brief account of the general requirements of these attributes, particularly in respect of the post closure safety and, to a lesser extent, the construction phase of the GDF. We also provide a brief summary of the international approach to using bedrock geological materials and go on to describe the summary properties from a range of bedrock geological materials (lithologies and formations) in England, Wales and Northern Ireland, illustrated from well-documented examples

Groundwater drought forecasting using lumped conceptual models

For fractured aquifers, such as the Cretaceous Chalk, autocorrelation in SGI (Bloomfield & Marchant, 2013) has been 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 saturated flow and storage properties of aquife

Characterising variations in the salinity of deep groundwater systems: A case study from Great Britain (GB)

Study region The study region is Great Britain (GB), a small non-continental island landmass in North West Europe Study focus Data for Total Dissolved Solids (TDS) from groundwater samples can be used to characterise regional-scale variations in the quality of deep groundwater systems. Combined with information about typical well-depths, TDS data can be used to identify the presence of currently undeveloped fresh or brackish groundwater at depth that may require protection. This study considers the distribution of TDS with depth relative to sea level in the main GB aquifers and selected other key hydrogeological units, and demonstrates how useful insights can be obtained from data-led analyses of depth variations in groundwater chemistry if the regional context of hydrogeological systems is taken into account. New hydrogeological insights In GB, TDS varies over about five orders of magnitude, up to about 330,000 mg/L, with a general increase in mineralisation with depth. Overall, there is a transition from fresh 10,000 mg/L groundwater at about 700 m. Given that the 95 %tile depth of water wells is about 200 m, it is evident that there is currently undeveloped fresh groundwater at depth across large parts of the study area that may require protection, although it is inferred that TDS is not the only factor limiting exploitation and use of these deeper resources. As in this study, previous data-led analyses of fresh groundwater at depth have typically analysed TDS as depth below surface. However, if TDS data is analysed relative to sea level and in the context of regional hydrogeological information or models, additional insights can be gained on the distribution and controls on fresh groundwater at depth. Projecting TDS data into a 3D hydrogeological model of the study area shows that fresh groundwater at depth exhibits spatial coherence and is generally associated with relatively dee

Combined impacts of future land-use and climate stressors on water resources and quality in groundwater and surface waterbodies of the upper Thames river basin, UK

It is widely acknowledged that waterbodies are becoming increasingly affected by a wide range of drivers of change arising from human activity. To illustrate how this can be quantified a linked modelling approach was applied in the Thames river basin in southern UK. Changes to river flows, water temperature, river and reservoir quality were predicted under three contrasting future “storylines”; one an extension of present day rates of economic development, the others representing more extreme and less sustainable visions. Modelling revealed that lower baseflow conditions will arise under all storylines. For the less extreme storyline river water quality is likely to deteriorate but reservoir quality will improve slightly. The two more extreme futures could not be supported by current management strategies to meet water demand. To satisfy these scenarios, transfer of river water from outside the Thames river basin would be necessary. Consequently, some improvement over present day water quality in the river may be seen, and for most indicators conditions would be better than in the less extreme storyline. However, because phosphorus concentrations will rise, the invoked changes in water demand management would not be of a form suitable to prevent a marked deterioration in reservoir water quality

Towards improved global estimates and model representations of water storage in the unsaturated zone

The unsaturated zone is a globally important, dynamic water store, which affects water resources, agriculture and pollutant transport. Despite this, the magnitude of unsaturated zone water storage remains highly uncertain. This work provides the first global estimates of the magnitude of this store (1.0 x105 km3) in comparison to recent estimates of global modern groundwater (3.5x105 km3), before presenting a roadmap for improved representation of the unsaturated zone in global hydrological models