Trill, E.; Robotham, J.; Old, G.; Rameshwaran, P.; Bishop, J.

High-resolution time-series of flood storage area water levels and estimated stored volumes in the Littlestock Brook, Thames Basin, England, 2018-2022

https://doi.org/10.5285/cf70f798-442a-4775-963c-b6600023830f Cite this dataset

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This dataset contains high-resolution (5-minute) raw, atmospheric corrected and mean sea level adjusted water level data for 9 flood storage areas (FSAs) in the Littlestock Brook catchment (a tributary of the River Evenlode, Thames Basin) from 2018 to 2022. The dataset also includes the estimated 9 x FSA stored volume time-series, estimated using a depth-stored volume lookup table for each FSA, produced from a digital elevation model of each feature and a depth-area-volume toolset. The annual barometric pressure time-series used to correct water level is also provided.

This dataset was collected by UKCEH as part of a hydrological monitoring programme for the Littlestock Brook Natural Flood Management scheme. This work was supported by the SPITFIRE NERC DTP (NE/L002531/1) and the SCENARIO NERC DTP (NE/L002566/1).

Publication date: 2022-09-06

Format

Comma-separated values (CSV)

Spatial information

Study area
Spatial representation type: Tabular (text)
Spatial reference system: OSGB 1936 / British National Grid

Temporal information

Temporal extent: 2018-01-01 to 2022-12-31

Provenance & quality

Data were generated using pressure sensors supplied with a factory calibration. A barometric correction was applied to sensor pressure time-series. Barometric corrected pressure data were then calibrated to stage using a linear regression developed between these data and observed stage board readings. After this correction data were quality controlled to flag any spurious readings, which were removed and interpolated if appropriate. Flood Storage Area (FSA) volume for each feature was estimated using a Digital Elevation Model (DEM) produced with LiDAR data. If LiDAR data were not available, as-built manual survey data were interpolated using the Natural Neighbour method. The DEMs were imported into ArcGIS to create a raster and apply a depth-area-volume toolset for each FSA. The continuous corrected water level time-series in each FSA was then used to produce a time-series of stored volume for each FSA, by matching the water level time-series to the depth-stored volume lookup table produced from ArcGIS.