40a80d95-5a8a-4586-aa24-d6c87f9968b6
English
ISO/IEC 8859-1 (also known as Latin 1)
dataset
dataset
Environmental Information Data Centre
Lancaster Environment Centre, Library Avenue, Bailrigg
Lancaster
LA1 4AP
UK
info@eidc.ac.uk
pointOfContact
2021-10-04T14:11:20
UK GEMINI
2.3
WGS 84
Groundwater monitoring data following 2016-2017 extreme rainfall and floods in the Gaborone catchment, Upper Limpopo basin, Botswana
2021-09-07
publication
https://catalogue.ceh.ac.uk/id/40a80d95-5a8a-4586-aa24-d6c87f9968b6
10.5285/40a80d95-5a8a-4586-aa24-d6c87f9968b6
doi:
Petros, A., Comte, J.-C. (2021). Groundwater monitoring data following 2016-2017 extreme rainfall and floods in the Gaborone catchment, Upper Limpopo basin, Botswana. NERC EDS Environmental Information Data Centre 10.5285/40a80d95-5a8a-4586-aa24-d6c87f9968b6
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
Petros, A.
Botswana Department of Water and Sanitation
apetros@gov.bw
author
Comte, J.-C.
University of Aberdeen
jc.comte@abdn.ac.uk
author
Dr. Jean-Christophe Comte
University of Aberdeen
jc.comte@abdn.ac.uk
pointOfContact
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
publisher
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
custodian
University of Aberdeen
jc.comte@abdn.ac.uk
owner
Environmental Monitoring Facilities
theme
GEMET - INSPIRE themes, version 1.0
2008-06-01
publication
Groundwater
Hydrogeology
Borehole
Water table
Physico-chemical parameters
Timeseries
Temperature
pH
Electrical conductivity
Total dissolved solids
otherRestrictions
no limitations
otherRestrictions
This resource is available under the terms of the Open Government Licence
otherRestrictions
If you reuse this data, you should cite: Petros, A., Comte, J.-C. (2021). Groundwater monitoring data following 2016-2017 extreme rainfall and floods in the Gaborone catchment, Upper Limpopo basin, Botswana. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/40a80d95-5a8a-4586-aa24-d6c87f9968b6
textTable
100
English
utf8
environment
2017-05-18
2018-06-09
25.25
25.981
-25.296
-24.677
Comma-separated values (CSV)
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
distributor
https://data-package.ceh.ac.uk/data/40a80d95-5a8a-4586-aa24-d6c87f9968b6
Download the data
Download a copy of this data
download
https://data-package.ceh.ac.uk/sd/40a80d95-5a8a-4586-aa24-d6c87f9968b6.zip
Supporting information
Supporting information available to assist in re-use of this dataset
information
dataset
dataset
Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services
2010-12-08
Manual water table depth measurements during the near-monthly campaigns were done in situ using a standard groundwater dipmeter. Manual groundwater pH, temperature, electrical conductivity and total dissolved solids measurements (Strategy 1) were obtained on pumped grab groundwater samples from borehole taps.
Automatic loggers immersed in a selection of three boreholes provided high-temporal resolution (5-min) groundwater level, temperature, electrical conductivity data (Strategy 2). Raw groundwater levels were provided in meter equivalent freshwater head above the logger, later converted in depth in Excel through two sequential processing steps: (1) barometric compensation, from a barometric sensor installed; (2) depth correction using the manual depth measurements (Strategy 1) and applying linear interpolation between measurement dates.
Datasets were post-process through removal of obvious measurement errors, including human errors when writing up values on field notebook and anomalous datalogger records associated to sensor extraction from the well.