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

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.