Joint BGS/Environment Agency dataset of aquifer designations for England and Wales at 1:50 000. The dataset identifies different types of aquifer - underground layers of water-bearing permeable rock or drift deposits from which groundwater can be extracted. These designations reflect the importance of aquifers in terms of groundwater as a resource (drinking water supply) but also their role in supporting surface water flows and wetland ecosystems. The maps are split into two different type of aquifer designation: superficial - permeable unconsolidated (loose) deposits (for example, sands and gravels), and bedrock - solid permeable formations e.g. sandstone, chalk and limestone.

Matlab m-file code to generate a probabilistic model of aquifer-body occurrence in the subsurface of the Indo-Gangetic foreland basin, northwestern India. The accompanying ArcGIS ASCII matrix files give aquifer-body percentages in successive 10 m depth slices for use within the model. File xxx_01.txt is for depths 0-10 m, file xxx_02.txt for depths 10-20 m, etc.

Thicknesses of aquifer units in the subsurface of the Indo-Gangetic foreland basin, northwestern India. Data are organised by borehole and indicate the thickness of aquifer units, separated by non-aquifer material.

The borehole is located at the UK Centre for Ecology and Hydrology (UKCEH), screened between 2 and 4.5 m in the Thames gravels, and drilled to a total depth of 4.8m. It is located on an actively managed grass verge with popular and sycamore trees within 10 m. The stilling well is positioned 420 m west of the borehole in the River Thames. Both stage and groundwater level were monitored at 1-minutre frequency to investigate hydrological fractal scaling of high frequency data between 2012 and 2016. An automatic weather station is present between the borehole and stilling well and the data are available separately from UKCEH (stetur@ceh.ac.uk). Further site description is provided in: Habib, A. et al. 2017. Journal of Hydrology, 549, 715-730. Habib, A. et al. 2022. Hydrological Sciences Journal

Monthly anomalies (August 2002 to July 2016) of total terrestrial water storage (TWS), soil moisture storage (SMS), surface water storage (SWS), snow water storage (SNS), groundwater storage (GWS) derived from an ensemble mean of 3 gridded GRACE products (CSR, JPL-Mascons and GRGS) and an ensemble mean 4 land surface models (CLM, NOAH, VIC and MOSAIC), provided by the NASA’s Global Land Data Assimilation System (GLDAS). Monthly precipitation (CRU) data, derived from the Climatic Research Unit (CRU), were aggregated over each aquifer system. GRACE, GLDAS and CRU datasets are publicly available at the global scale. (NERC grant NE/M008932/1)

This dataset consists of reconstructions of daily groundwater levels for eight boreholes in Burkina Faso. Data for each borehole is provided in an individual csv file, with reconstructed groundwater level time series reported in metres above sea level (GWL, mASL). The groundwater level reconstructions were derived in 2019 as a part of the BRAVE project (NE/M008827/1 and NE/M008983/1) to develop an improved understanding of temporal variability in groundwater levels in sub-Saharan Africa. The reconstructions were derived using the lumped conceptual groundwater model AquiMod. Observed groundwater level time series for the eight boreholes were modelled using AquiMod, and the calibrated models were used with historic precipitation and potential evapotranspiration data to derive the reconstructions. The length of the time series of reconstructed groundwater levels varies between the boreholes due to differences in the length of the precipitation time series used to derive the reconstructions. Full details of this dataset are reported by Ascott et al. (2020). Ascott, M.J., Macdonald, D.M.J., Black, E., Verhoef, A., Nakohoun, P., Tirogo, J., Sandwidi, W.J.P., Bliefernicht, J., Sorensen, J.P.R., Bossa, A.Y., 2020. In Situ Observations and Lumped Parameter Model Reconstructions Reveal Intra-Annual to Multidecadal Variability in Groundwater Levels in Sub-Saharan Africa. Water Resour. Res., 56(12): e2020WR028056. DOI:https://doi.org/10.1029/2020WR028056

This dataset was generated with a novel process-based stochastic modelling approach to investigate the productivity and sustainability of groundwater abstractions in the Precambrian basement aquifer in Ghana. The statistical distribution of the generated synthetic yield data was found in very good agreement with observed yield data from the same Ghanaian aquifer. The dataset includes more than 40,000 simulated values of maximum allowable yield and corresponding transmissivity values for different realisations of aquifer heterogeneity, net recharge values, and borehole depth. Further details about the dataset and the method of generation and collection can be found in the article by Bianchi et al. (2020) "Investigating the productivity and sustainability of weathered basement aquifers in tropical Africa using numerical simulation and global sensitivity analysis" published in the Water Resources Research journal. This research was supported by the UKRI British Geological Survey NC-ODA grant NE/R000069/1 and NE/M008827/1.

(I) Handpump Vibration Data For each handpump, data is organized in one CSV file per day. These files are grouped together over batches, where each batch approximately corresponds to three months. (II) Borehole Water Level Data Water level data at the borehole of each handpump is recorded in one CSV file per handpump. Both uncompensated (raw) and compensated (with respect to atmospheric pressure) data are available. (III) Data Time Logs A separate Excel file lists the locations of the monitoring sites and the time logs corresponding to both (I) and (II) per handpump. References: [1] P. Thomson, R. Hope, and T. Foster, “GSM-enabled remote monitoring of rural handpumps: a proof-of-concept study,” Journal of Hydroinformatics, vol. 14, no. 4, pp. 829–839, 05 2012. [Online]. Available: https://doi.org/10.2166/hydro.2012.183 [2] F. Colchester, “Smart handpumps: a preliminary data analysis,” IET Conference Proceedings, pp. 7–7(1). [Online]. Available: https://digital-library.theiet.org/content/conferences/10.1049/cp.2014.0767 [3] H. Greeff, A. Manandhar, P. Thomson, R. Hope, and D. A. Clifton, “Distributed inference condition monitoring system for rural infrastructure in the developing world,” IEEE Sensors Journal, vol. 19, no. 5, pp.1820–1828, March 2019. [4] F. E. Colchester, H. G. Marais, P. Thomson, R. Hope, and D. A. Clifton, “Accidental infrastructure for groundwater monitoring in africa,” Environmental Modelling Software, vol. 91, pp. 241 – 250, 2017. [Online]. Available:http://www.sciencedirect.com/science/article/pii/S1364815216308325 [5] A. Manandhar, H. Greeff, P. Thomson, R. Hope, and D. A. Clifton, “Shallow Aquifer Monitoring Using Handpump Vibration Data,” In-review, 2019.

The Superficial Aquifer Productivity Scotland dataset forms part of the BGS Hydrogeological Maps of Scotland data product. This product is comprised of three datasets: Bedrock Aquifer Productivity Scotland; Superficial Aquifer Productivity Scotland; and Groundwater Vulnerability Scotland. Aquifer productivity is a measure of the potential of aquifers to sustain a borehole water supply. The Superficial Aquifer Productivity Scotland dataset version 2 (2015) indicates the location and productivity of superficial aquifers across Scotland, and their groundwater flow characteristics. Developed as a tool to support groundwater resource management, the dataset provides a guide to aquifer characteristics at a regional scale, and may be useful to anyone interested in learning more about, assessing or managing groundwater resources across Scotland. The dataset is delivered at 1: 100 000 scale; the resolution of the dataset being 50 m and the smallest detectable feature 100 m.

These maps provide an overview, at the national scale, of the spatial relationships between principal aquifers and some of the major shale and clay units in England and Wales. The data comprises a series of occurrence maps shows the distribution of rock units that form the principal aquifers and some major shale and clay units in England and Wales. In addition, a series of separation maps show the vertical separation between pairs of shales or clays and overlying aquifers. If shale gas resources are to be developed in the UK, the implications for groundwater will need to be considered as part of any risk assessment. A step in such an assessment will be to understand and quantify the spatial relationships between the potential shale gas source rocks (including both shales and some clay units) and overlying aquifers. The datasets used to produce the aquifer maps, the shale and clay occurrence maps and the separation maps are available to download for your own use. As with other BGS data sets available for download, this will enable you to work offline to develop your own systems and methodologies using BGS data. The data used to produce the aquifer, shale and clay maps are available below as ESRI GIS and KML files.