Griffin, A.; Kay, A.; Bell, V.; Stewart, E.J.; Sayer, P.; Carr, S.

Peak flow and probability of exceedance data for Grid-to-Grid modelled widespread flooding events across mainland GB from 1980-2010 and 2050-2080

https://doi.org/10.5285/26ce15dd-f994-40e0-8a09-5f257cc1f2ab Cite this dataset

This dataset is a set of 24 gridded netcdf files, each including data describing a total of 14,400 widespread flooding events across mainland GB, with event selection based on a peaks-over-threshold approach. The data describes peak river flow in m3/s and the associated annual probability of exceedance for each 1km grid-square on the GB river network. The data is extracted from daily time series data from the Grid-to-Grid model, using UKCP18 12km regional projections from 12 members of a perturbed parameter ensemble, over the periods Dec 1980 – Nov 2010 and Dec 2050 – Nov 2080 (based on 360-day years). Multi-day events were summarised by taking cell-wise flow maxima.

This data was generated for use in analysis of risk through catastrophe modelling using the Future Flows Explorer. It was generated and interpreted by UKCEH, working with Sayers & Partners Consultancy, as part of the AquaCAT project, part of the UK Climate Resilience Programme.

Publication date: 2022-06-27

Formats

Comma-separated values (CSV)
Shapefile

Spatial information

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

Temporal information

Temporal extent: 1980-12-01 to 2080-11-30

Provenance & quality

Hydrological flow records were generated using Grid-to-Grid and UKCP18 12km regional projections. Widespread events were selected for which daily flow exceeded a 99.5% percentile simultaneously over at least 20km^2. Multi-day events (consecutive days for which the above conditions were met) are summarised by pointwise maxima of flow.

Probabilities of exceedance are computed pointwise using a mixed distribution, with an empirical distribution used for non-extreme values (below the 99.5% percentile) and a Generalised Pareto distribution used above, both fitted to the full time series of daily flow.

Citations

Griffin, A., Kay, A., Stewart, E., & Sayers, P. (2022). Spatially coherent statistical simulation of widespread flooding events under climate change. Hydrology Research, 53(11), 1428-1440 https://doi.org/10.2166/nh.2022.069