Historic reconstructions of daily groundwater levels for eight boreholes in Burkina Faso (NERC Grant NE/M008827/1)
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
dataset
https://webapps.bgs.ac.uk/services/ngdc/accessions/index.html#item169011
name: Data
function: download
https://doi.org/10.5285/c9262369-4db1-48e1-9660-3ef8667ab19b
name: Digital Object Identifier (DOI)
function: information
http://data.bgs.ac.uk/id/dataHolding/13607829
eng
geoscientificInformation
publication
2008-06-01
Groundwater
Aquifers
Climatology
Simulation
NGDC Deposited Data
revision
2022
NERC_DDC
-5.5100
2.4000
15.1000
9.4100
revision
2009
BF
revision
2009
BFA
creation
1979
BURKINA FASO [id=626000]
2019-10-01
2019-12-31
creation
2021-10-12
notApplicable
Observed groundwater level time series for each of the boreholes were modelled using the lumped conceptual model AquiMod. The models were calibrated using Monte Carlo sampling, which resulted in a series of parameter sets which produced behavioural models. The top ten behavioural models were then used for groundwater level reconstruction by applying historic rainfall and potential evapotranspiration data as inputs. The results of the best fit behavioural model are presented here. For full details of the methodology please see Ascott et al. (2020).
publication
2011
false
See the referenced specification
publication
2010-12-08
false
See http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2010:323:0011:0102:EN:PDF
.csv
The copyright of materials derived from the British Geological Survey's work is vested in the Natural Environment Research Council [NERC]. No part of this work may be reproduced or transmitted in any form or by any means, or stored in a retrieval system of any nature, without the prior permission of the copyright holder, via the BGS Intellectual Property Rights Manager. Use by customers of information provided by the BGS, is at the customer's own risk. In view of the disparate sources of information at BGS's disposal, including such material donated to BGS, that BGS accepts in good faith as being accurate, the Natural Environment Research Council (NERC) gives no warranty, expressed or implied, as to the quality or accuracy of the information supplied, or to the information's suitability for any use. NERC/BGS accepts no liability whatever in respect of loss, damage, injury or other occurence however caused.
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British Geological Survey
Maclean Building, Crowmarsh Gifford
WALLINGFORD
OX10 8BB
United Kingdom
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01491 692345
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British Geological Survey
Maclean Building, Crowmarsh Gifford
WALLINGFORD
OX10 8BB
United Kingdom
01491 838800
01491 692345
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British Geological Survey
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British Geological Survey
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2024-04-18