Permeability classification for UK Natural Superficial Deposits - a Hydro-JULES dataset

This report describes the outputs of a work package which forms part of the NERC-funded Hydro-JULES project. One of the core outputs for the Hydro-JULES project is a km-scale national hydrogeological model that couples the ground surface to the bedrock. Part of this geological column, which occurs between the ground surface and the bedrock surface (rockhead), is the natural superficial geology or the geology that formed during the current geological period – the Quaternary (0 to 2.6 Ma). Characterising the natural superficial geology for the purposes of the national hydrogeological model is challenging. This is due in-part to the spatial complexity of this part of the geological record, but also the quality of published geological map data (superficial) which is variable reflecting the historical legacy (150 years) of Quaternary understanding, data capture and mapping approaches. To overcome these issues and produce a national-scale dataset that is relevant to the hydrogeological model, a holistic approach was undertaken to characterise the natural superficial geology. This approach utilised published geological map data (superficial), together with other surface (aerial photography, digital terrane models) and sub-surface (borehole records, superficial thickness model) information, combined with tacit knowledge of geological processes and events that have occurred in the UK during recent Earth History. This semipredictive approach therefore combines observations and tacit knowledge to inform the characterisation. The characterisation of the natural superficial deposits is shown as a relative measure of permeability based upon the interpreted vertical stack of different geological units and lithologies between the ground and bedrock surface. The primary outputs are a series of gridded GIS data layers which can be enhanced with numerical hydrogeological attributes to underpin future numerical modelling. Within this report, a brief overview of the aims of the study and methodology are presented together with a brief description of the results. Key assumptions in the interpretation and areas of uncertainty within the final dataset are also discussed. For further information on the scope of the study and methodology – including testing of the approach in six case study areas, readers are directed to a companion report (Lee, 2021).