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Levy, P.E.

Daily soil moisture maps for the UK (2016-2023) at 2 km resolution

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This dataset is available under the terms of the Open Government Licence

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https://doi.org/10.5285/5aa8c5b4-4485-4954-b5c3-18d937a418f7
The data consist of daily maps of volumetric soil moisture predicted by a model based on a network of cosmic-ray neutron sensors (COSMOS-UK), the National River Flow Archive (NRFA) and remotely-sensed data. Maps cover the UK and Ireland at 2-km resolution in the Ordnance Survey National Grid (OSGB) projection. Maps are produced in near-real time, lagging by about one week. Data are available from early 2016 to 2023, on a daily basis. The model was calibrated on a network of cosmic-ray neutron sensors (COSMOS-UK) and remotely-sensed soil moisture data. A key parameter was estimated from the national-scale spatial pattern in the catchment response to rainfall seen in the National River Flow Archive (NRFA) data. Precipitation and humidity data to drive the model came from the Met Office High Resolution Numerical Weather Prediction model (NWP-UKV) which incorporates the C-band rainfall radar network. The maps have a variety of uses in hydrology and elsewhere, for example as inputs to ecosystem models of greenhouse gas exchange, where soil moisture affects numerous processes. The modelling was carried out as part of UK-SCAPE Virtual Survey Lab, and the NERC project "Detection and Attribution of Regional Emissions (DARE-UK)". There are some gaps in the time series of meteorological and remote sensing inputs, and data are unavailable for these days. The NRFA data are only available for Great Britain, so estimates in Ireland and continental Europe will be less accurate.
Publication date: 2024-05-08
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More information

View numbers valid from 08 May 2024 Download numbers valid from 20 June 2024 (information prior to this was not collected)

Format

TIFF

Spatial information

Study area
Spatial representation type
Raster
Spatial reference system
OSGB 1936 / British National Grid

Temporal information

Temporal extent
2016-01-01    to    2023-12-31
Temporal resolution
1 day

Provenance & quality

We developed a statistical model of soil moisture, calibrated on a network of cosmic-ray neutron sensors in the UK. We found that applying an exponentially-weighted moving-average filter effectively linearised the effect of precipitation, so we could form a simple linear model. With this, we integrated remotely-sensed soil moisture data. To extrapolate across the whole country, we inferred information on the soil water retention properties from daily water balance data from ~1200 catchments with wide coverage. We used a Bayesian approach to allow the uncertainty from the calibration at 40 sites to be propagated through the extrapolation on a grid covering the whole UK. The Met Office High Resolution Numerical Weather Prediction model (NWP-UKV), which incorporates the C-band rainfall radar network, provides very detailed data on the variation in precipitation which arises from the sporadic nature of rainfall events and interactions with orography in near-real time, to predict small-scale, short-term variation in soil moisture.

Licensing and constraints

This dataset is available under the terms of the Open Government Licence

Cite this dataset as:
Levy, P.E. (2024). Daily soil moisture maps for the UK (2016-2023) at 2 km resolution. NERC EDS Environmental Information Data Centre. https://doi.org/10.5285/5aa8c5b4-4485-4954-b5c3-18d937a418f7

Correspondence/contact details

Levy, P.E.
UK Centre for Ecology & Hydrology
Lancaster Environment Centre, Library Avenue, Bailrigg
Lancaster
Lancashire
LA1 4AP
UNITED KINGDOM
 enquiries@ceh.ac.uk

Author

Levy, P.E.
UK Centre for Ecology & Hydrology

Other contacts

Rights holder
UK Centre for Ecology & Hydrology
Custodian
NERC EDS Environmental Information Data Centre
 info@eidc.ac.uk
Publisher
NERC EDS Environmental Information Data Centre
 info@eidc.ac.uk

Additional metadata

Topic categories
environment
INSPIRE theme
Soil
Keywords
ASCAT , atmospheric precipitation , catchment , hydrological modelling , hydrology , Hydrology , mapping , Mapping , modelling , NRFA , rainfall , rainfall radar , remote sensing , SCAT-SAR , soil , Soil , soil moisture , soil water , soil water retention curves , UK
Funding
Natural Environment Research Council Award: NE/R016429/1
Natural Environment Research Council Award: NE/S003614/2
Last updated
20 May 2024 09:04