Daily soil moisture maps for the UK (2016-2023) at 2 km resolution
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Identification info
- Metadata Language
- English (en)
- Character set
- utf8
- Dataset Reference Date ()
- 2024-05-08
- Identifier
- doi: / 10.5285/5aa8c5b4-4485-4954-b5c3-18d937a418f7
- Other citation details
- Levy, P.E. (2024). Daily soil moisture maps for the UK (2016-2023) at 2 km resolution. NERC EDS Environmental Information Data Centre 10.5285/5aa8c5b4-4485-4954-b5c3-18d937a418f7
- GEMET - INSPIRE themes, version 1.0 ()
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- Soil
- GEMET - Concepts, version 4.1.3
- Keywords
- Limitations on Public Access
- otherRestrictions
- Other constraints
- Registration is required to access this data
- Use constraints
- otherRestrictions
- Use constraints
- otherRestrictions
- Other constraints
- If you reuse this data, you should cite: 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
- Spatial representation type
- grid
- Distance
- 2000 urn:ogc:def:uom:EPSG::9001
- Topic category
-
- Environment
![](https://data-search.nerc.ac.uk/geonetwork/srv/api/regions/geom.png?geomsrs=EPSG:4326&geom=POLYGON((1.768%2049.864,1.768%2060.861,-8.648%2060.861,-8.648%2049.864,1.768%2049.864)))
- Begin date
- 2016-01-01
- End date
- 2023-12-31
Distribution Information
- Data format
-
-
TIFF
()
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TIFF
()
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Supporting information
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Supporting information
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- Quality Scope
- dataset
- Other
- dataset
Report
- Dataset Reference Date ()
- 2010-12-08
- Statement
- 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.
Metadata
- File identifier
- 5aa8c5b4-4485-4954-b5c3-18d937a418f7 XML
- Metadata Language
- English (en)
- Character set
- ISO/IEC 8859-1 (also known as Latin 1)
- Resource type
- dataset
- Hierarchy level name
- dataset
- Metadata Date
- 2024-05-20T09:04:09
- Metadata standard name
- UK GEMINI
- Metadata standard version
- 2.3