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Dike failure due to piping – concentrated flow of seepage water underneath the dike during periods of high flood water levels – has been recognized as a major component of flood risk. Simulation models to predict piping in risk assessments require detailed information on subsurface characteristics such as sediment grain size and thickness of overburden layers. Quantitative local determination of these characteristics poses a major challenge in natural environments with a heterogeneous substrate. Geological knowledge on the natural genesis and resulting structure of the subsurface may provide useful information on the spatial variability of substrate characteristics. When correctly implemented, available subsurface geological information can provide for a-priori identification of dike sections of which the subsurface is susceptible to piping (strategic to new data collection), and a-posteriori screening of new collected field data (identifying unexpected values). In these two ways it has potential to reduce the uncertainty in parameter estimates for calculations that determine the potential occurrence of piping at a specific site. Here we describe a framework for using geological subsurface information for these assessments. Based on existing digital geological mapping products and knowledge of the geological development of the Rhine-Meuse delta, we first compiled a map that distinguishes primary hydrologically relevant units: upper main aquifer sands (pre-deltaic subunits), topped by the deltaic wedge aquitard that is dissected by channel belt sand bodies (deltaic subunits). We then used these spatial divisions in an analysis of digital borehole data (>130.000 locations, UU-LLG dataset), to provide quantitative information on grain sizes of the very top of sand bodies and non-sand overburden thicknesses, split per subunit and summarized for sub regions (lower delta, central delta, upper delta, delta rim sectors). This framework enables us to demonstrate to what extent the median grain size of the top of sand deposits varies within the delta. We quantitatively determined (1) a delta-scale longitudinal downstream fining trend due to drops in specific stream power through changes in gradient and substrate erodibility, (2) pulsed variations associated with local uptake and reworking of pre-deltaic sediments within channel belts. Although tailored for the Rhine-Meuse delta, utilizing geological knowledge as a substantiation for grouping of subsurface data underneath local dike sections can be transposed for such applications in delta regions elsewhere. This regionalization of the delta plain can greatly help streamline data acquisition, anticipating growing availability of medium to high density subsurface datasets in increasingly urbanized deltas with managed rivers around the world.