The dataset contains borehole groundwater levels and physico-chemical parameters for the period May 2017 to June 2018 including; (1) near-monthly measurements of water table depth, groundwater temperature, pH, electrical conductivity and total dissolved solids obtained from manual sampling of 22 boreholes; and (2) higher temporal resolution (5-min time-step) timeseries of water table depth, groundwater temperature and electrical conductivity obtained from automatic dataloggers in 3 of the abovementioned boreholes. Full details about this dataset can be found at https://doi.org/10.5285/40a80d95-5a8a-4586-aa24-d6c87f9968b6

Future Flows Hydrology (FF-HydMod-PPE) is an 11-member ensemble projections of river flow and groundwater levels time series for 283 catchments and 24 boreholes in Great Britain. It is derived from Future Flows Climate, an 11-member 1-km bias-corrected and downscaled climate projection products based on the SRES A1B emission scenario. River Flows data are at a daily time step: Groundwater Levels data are at a monthly time step. Future Flows Hydrology span from 1951 to 2098. The development of Future Flows Hydrology was made during the partnership project 'Future Flows and Groundwater Levels' funded by the Environment Agency for England and Wales, Defra, UK Water Research Industry, NERC (Centre for Ecology & Hydrology and British Geological Survey) and Wallingford HydroSolutions. Full details about this dataset can be found at https://doi.org/10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b

This dataset includes weekly data from monitoring of stream, rainfall and groundwater hydrochemistry in the Vyrnwy research catchment between 1994 and 2001. Data for over 50 chemical determinands are presented alongside data for some in-situ measurements such as water temperature. Full descriptions of the analytical methods used for each determinand is included. Intensive and long-term monitoring within the catchments underpins a wealth of hydrological and hydro-chemical research; other linked datasets include river flow, meteorology and a variety of detailed spatial datasets representing the topography, soils and rivers of the catchments. Monitoring is funded by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/68f4a12f-740d-4705-9c27-6a7fb7127046

The dataset contains a scaled, semi-quantitative conceptual hydrogeological model of the Gaborone catchment along a general WSW-ENE direction including; (1) the geographic coordinates of the extremities of each segment of the polyline transect; (2) the raster, scaled image of the conceptual hydrogeological cross-section. Full details about this dataset can be found at https://doi.org/10.5285/4731c4da-91fc-4762-9c17-74c8749d4227

Enhanced Future Flows and Groundwater (eFLaG) is an 12-member ensemble projection of river flow, groundwater level, and groundwater recharge time series for 200 catchments, 54 boreholes and 558 groundwater bodies in Great Britain and Northern Ireland. It is derived from the UKCP18 dataset, specifically the 'Regional' 12km projections, to which a bias correction is applied. River flows, groundwater level and groundwater recharge data are at a daily time step. To be consistent with the driving meteorological dataset, eFLaG data use a simplified 360-day year, consisting of twelve 30-day months. eFLaG data span from 1981 to 2080. The development of eFLaG was made during the partnership project funded by the Met Office-led component of the Strategic Priorities Fund Climate Resilience programme under contract P107493 (CR19_4 UK Climate Resilience). Full details about this dataset can be found at https://doi.org/10.5285/1bb90673-ad37-4679-90b9-0126109639a9

This dataset contains the anonymised results of a survey of customers who buy groundwater for consumption in Kisumu, Kenya. Data includes information on the amount of water bought and ways in which this water was used and handled, as well as their use of water from other sources. Data about assets and services, including access to food, are also included. The surveys were carried out during February and March 2014 and include data from 137 well customers. The data were collected as part of the Groundwater2030 project, which aims to reduce the health problems that result from consumption of contaminated groundwater in urban areas of Africa. The project was co-ordinated by the University of Southampton, with partners at the University of Surrey, the Victoria Institute of Research on Environment and Development (VIRED) International, and the Jaramogi Oginga Odinga University of Science and Technology. The project was funded by the Natural Environment Research Council and the Department for International Development as part of the Unlocking the Potential of Groundwater for the Poor (UPGro) programme. Full details about this dataset can be found at https://doi.org/10.5285/6f3f1d06-4e6b-435e-a770-af7549993b88

This dataset contains the results of a sanitary risk inspection for different groundwater sources in Kisumu, Kenya. A total of 70 groundwater sources were surveyed between February and March 2014. The survey took the form of an observation checklist that identified contamination hazards at well heads and in their immediate surroundings. Data on well depth, electro-conductivity, pH and temperature were also collected. The data were collected as part of the Groundwater2030 project, which aims to reduce the health problems that result from consumption of contaminated groundwater in urban areas of Africa. The project was co-ordinated by the University of Southampton, with partners at the University of Surrey, the Victoria Institute of Research on Environment and Development (VIRED) International, and the Jaramogi Oginga Odinga University of Science and Technology. The project was funded by the Natural Environment Research Council and the Department for International Development as part of the Unlocking the Potential of Groundwater for the Poor (UPGro) programme. Full details about this dataset can be found at https://doi.org/10.5285/bc1a979b-7cc9-4c9d-9fe4-a8510cd62f8e

This dataset contains free residual chlorine, turbidity, nitrate, chloride, sulphate, fluoride, phosphate and thermatolerant coliform concentrations in groundwater from a variety of sources within two neighbourhoods of Kisumu, Kenya. A total of 73 groundwater sources were tested between February and March 2014. The data were collected as part of the Groundwater2030 project, which aims to reduce the health problems that result from consumption of contaminated groundwater in urban areas of Africa. The project was co-ordinated by the University of Southampton, with partners at the University of Surrey, the Victoria Institute of Research on Environment and Development (VIRED) International, and the Jaramogi Oginga Odinga University of Science and Technology. The project was funded by the Natural Environment Research Council and the Department for International Development as part of the Unlocking the Potential of Groundwater for the Poor (UPGro) programme. Full details about this dataset can be found at https://doi.org/10.5285/4062e6d9-2e90-4775-87f1-179dea283ef1

This datasets contains the anonymised results of a survey of well owners in Kisumu, Kenya. Data includes information on the amount of water abstracted daily from the well and ways in which this water was used and handled, information on other sources of water (e.g. piped utility water and rainwater) and how this is used, and the assets and services that the well owner has access to. Answers from questions to assess food poverty are also included. The surveys were carried out during February and March 2014 and include data from 51 well owners. The data were collected as part of the Groundwater2030 project, which aims to reduce the health problems that result from consumption of contaminated groundwater in urban areas of Africa. The project was co-ordinated by the University of Southampton, with partners at the University of Surrey, the Victoria Institute of Research on Environment and Development (VIRED) International, and the Jaramogi Oginga Odinga University of Science and Technology. The project was funded by the Natural Environment Research Council and the Department for International Development as part of the Unlocking the Potential of Groundwater for the Poor (UPGro) programme. Full details about this dataset can be found at https://doi.org/10.5285/4ca855a3-752c-4492-8e26-3438652dd35c