This dataset contains a summary of the weekly volumetric output of pumps monitored using Smart Handpump sensors for 2014 and 2015. Grants that permitted the data collection include: Groundwater Risk Management for Growth and Development project (NE/M008894/1) funded by NERC/ESRC/DFIDs UPGro programme; New mobile citizens and waterpoint sustainability in rural Africa (ES/J018120/1) ESRC-DFID; Groundwater Risks and Institutional Responses for Poverty Reduction in Rural Africa (NE/L001950/1) funded by NERC/ESRC/DFIDs UPGro programme Notes: 1. The accuracy of these volume figures should be considered to be +/- 20%. 2. The dataset has gaps due to variable signal, and some attrition due to damage and vandalism. 3. Not all pumps in the study area were under monitoring. References:  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. 829839, 05 2012. [Online]. Available: https://doi.org/10.2166/hydro.2012.183  Behar, J., Guazzi, A., Jorge, J., Laranjeira, S., Maraci, M.A., Papastylianou, T., Thomson, P., Clifford, G.D. and Hope, R.A., 2013. Software architecture to monitor handpump performance in rural Kenya. In Proceedings of the 12th International Conference on Social Implications of Computers in Developing Countries, Ochos Rios, Jamaica. pp. 978 (Vol. 991).
This data contains high-resolution XRF data scanned from IODP cores recovered from Expedition 369, IODP Sites U1513, U1514 and U1516. Sietske Batenburg was responsible for scanning the Cenomanian-Turonian interval at Sites U1513 and U1516, and the lower half of the Eocene at U1514. Data is available from IODP database: http://web.iodp.tamu.edu/LORE/
(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:  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. 829839, 05 2012. [Online]. Available: https://doi.org/10.2166/hydro.2012.183  F. Colchester, Smart handpumps: a preliminary data analysis, IET Conference Proceedings, pp. 77(1). [Online]. Available: https://digital-library.theiet.org/content/conferences/10.1049/cp.2014.0767  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.18201828, March 2019.  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  A. Manandhar, H. Greeff, P. Thomson, R. Hope, and D. A. Clifton, Shallow Aquifer Monitoring Using Handpump Vibration Data, In-review, 2019.
The dataset consists of daily rainfall data for 23 manual rain gauge stations installed by Gro for GooD project within and about the study area. The installed stations covering four river catchments name Ramisi River, Mukurumudzi River, Mtawa River and Mwachema River in Kwale County. The dataset period is from January 2016 to November 2018. Gro for GooD: Groundwater Risk Management for Growth and Development
The dataset consist of daily rainfall data for 22 manual rain gauge stations installed by Gro for GooD project within and about the study area. The installed stations covering four river catchments name Ramisi River, Mukurumudzi River, Mtawa River and Mwachema River in Kwale County. The dataset period is from January 2016 to September 2017. Gro for GooD: Groundwater Risk Management for Growth and Development
The file contain groundwater level/depth (WL), Groundwater and Surface Water Quality data (EC (micro-siemens per centimetre or µS/cm), Temperature (degrees C) and pH) for 49 points under fortnightly monitoring relevant to Gro for GooD research project in Kwale County, Kenya. Blank - Data not available. Note this is same dataset as NGDC record number 118189 with extended time series. Gro for GooD: Groundwater Risk Management for Growth and Development
Neodymium (Nd) isotope data measured from fossil fish debris and sediment leaches collected from IODP Sites U1512, U1513, U1514 and U1516.
Here, we provide data corresponding to the experimental conditions used, the results gained via electron microprobe for natural and experimental volcanic samples. Mass balance calculations and a compilation of monitoring data for recent explosive eruptions.
Dataset of material characterisation (X-ray diffraction) analyses to constrain the nature of materials produced during Fe(II)-silicate precipitation experiments from seawater in the presence of various metals.
Geological observations during field walks, with coordinates, photographs and descriptions of rocks/geological materials and features at the various stops.