Hawkins, C.E et al
High resolution water quality and flow monitoring data coupled with daily and storm samples from the Loddon catchment (Sept 2017-Sept 2018)
Cite this dataset as:
Hawkins, C.E; Kelly, T.J.; Loewenthal, M.; Smith, R.; Dudley, A.; Leggatt, A.; Dowman, S.; Oliver, R.G.; Collins, C.D.; Clark, J.M. (2019). High resolution water quality and flow monitoring data coupled with daily and storm samples from the Loddon catchment (Sept 2017-Sept 2018). NERC Environmental Information Data Centre. https://doi.org/10.5285/331659d7-da72-48a2-9b52-63c003557990
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This dataset is available under the terms of the Open Government Licence
https://doi.org/10.5285/331659d7-da72-48a2-9b52-63c003557990
This data set comprises of hourly water quality monitoring and flow data of a site within the River Loddon catchment, UK, from September 2017 to September 2018. Parameters measured were temperature, conductivity, pH, ammonium, turbidity, dissolved oxygen, UV-Vis spectral scan from 197-720nm. Daily samples were also taken at 9am GMT and occasional storm samples were taken hourly and then analysed in the laboratory for pH, conductivity, turbidity, total suspended solids, non-purgeable organic carbon, UV-Vis spectral scan from 200-800nm and 12 pesticide concentrations: 2-4-D, Bentazone, Carbendazim, Carbetamide, Chlorotoluron, Clopyralid, MCPA, Mecoprop, Metaldehyde, Propyzamide, Quinmerac and Metazachlor.
This data was created as part of the TWENTY65 project, funded by the Engineering and Physical Sciences Research Council (Grant number: EP/N010124/1) and with some additional funding from Affinity Water and Syngenta.
This data was created as part of the TWENTY65 project, funded by the Engineering and Physical Sciences Research Council (Grant number: EP/N010124/1) and with some additional funding from Affinity Water and Syngenta.
Publication date: 2019-04-03
View numbers valid from 01 June 2023 Download numbers valid from 20 June 2024 (information prior to this was not collected)
Format
Comma-separated values (CSV)
Spatial information
Study area
Spatial representation type
Tabular (text)
Spatial reference system
WGS 84
Temporal information
Temporal extent
2017-09-08 to 2018-09-08
Provenance & quality
Water quality and flow data from the Bow Brook, a headwater tributary to the River Loddon. These data were collected via automatic sampling methods and then analysed either by on-site high frequency analysers or via laboratory analysis at the University of Reading and Affinity Water Limited laboratory (Staines-upon-Thames). The daily samples were usually collected weekly, and hourly storm samples were collected as soon as possible, and taken to the laboratory for analysis. Samples were stored in the fridge at 4°C on return to the laboratory and filtered within 48 hours of collection. For more details please see the supporting documentation.
Licensing and constraints
This dataset is available under the terms of the Open Government Licence
Cite this dataset as:
Hawkins, C.E; Kelly, T.J.; Loewenthal, M.; Smith, R.; Dudley, A.; Leggatt, A.; Dowman, S.; Oliver, R.G.; Collins, C.D.; Clark, J.M. (2019). High resolution water quality and flow monitoring data coupled with daily and storm samples from the Loddon catchment (Sept 2017-Sept 2018). NERC Environmental Information Data Centre. https://doi.org/10.5285/331659d7-da72-48a2-9b52-63c003557990
© Engineering and Physical Sciences Research Council
Citations
Zhang, H., Zhang, L., Wang, S., & Zhang, L. (2022). Online water quality monitoring based on UV-Vis spectrometry and artificial neural networks in a river confluence near Sherfield-on-Loddon. Environmental Monitoring and Assessment, 194(9) https://doi.org/10.1007/s10661-022-10118-4
Correspondence/contact details
Authors
Hawkins, C.E
University of Reading
Loewenthal, M.
Environment Agency
Smith, R.
Environment Agency
Dudley, A.
University of Reading
Leggatt, A.
Affinity Water
Dowman, S.
Affinity Water
Oliver, R.G.
Syngenta
Other contacts
Custodian
NERC EDS Environmental Information Data Centre
info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
info@eidc.ac.uk
Additional metadata
Keywords
Funding
Engineering and Physical Sciences Research Council Award: EP/N010124/1
Last updated
08 February 2024 17:34