Three-dimensional geological modelling of anthropogenic deposits at small urban sites: a case study from Sheepcote...

Improvements in computing speed and capacity and the increasing collection and digitisation of geological data now allow geoscientists to produce meaningful 3D spatial models of the shallow subsurface in many large urban areas, to predict ground conditions and reduce risk and uncertainty in urban planning. It is not yet clear how useful this 3D modelling approach is at smaller urban scales, where poorly characterised anthropogenic deposits (artificial/made ground and fill) form the dominant subsurface material and where the availability of borehole and other geological data is less comprehensive. This is important as it is these smaller urban sites, with complex site history, which frequently form the focus of urban regeneration and redevelopment schemes. This paper examines the extent to which the 3D modelling approach previously utilised at large urban scales can be extended to smaller less well-characterised urban sites, using a historic landfill site in Sheepcote Valley, Brighton, UK as a case study. Two 3D models were generated and compared using GSI3D™ software, one using borehole data only, one combining borehole data with local geological maps and results from a desk study (involving collation of available site data, including ground contour plans). These models clearly delimit the overall subsurface geology at the site, and allow visualisation and modelling of the anthropogenic deposits present. Shallow geophysical data collected from the site partially validate the 3D modelled data, and can improve GSI3D™ outputs where boundaries of anthropogenic deposits may not be clearly defined by surface, contour or borehole data. Attribution of geotechnical and geochemical properties to the 3D model is problematic without intrusive investigations and sampling. However, combining available borehole data, shallow geophysical methods and site histories may allow attribution of generic fill properties, and consequent reduction of urban development risk and uncertainty.