Throughout this research, geophysical data is utilised to constrain numerical groundwater flow models at two applied study areas: a sandstone aquifer in Northern Ireland and a basement rock aquifer in Benin, west Africa. In Northern Ireland, airborne passive magnetics data are used to determine regional heterogeneity occurrence combined with methods of upscaling / equivalence and a density function. Furthermore, a stochastic component is undertaken in the form of multiple point statistics. This analysis performs a probability simulation and pattern matching to determine a statistical occurrence of heterogeneity distribution. In Benin, point magnetic resonance sounding data and electrical resistivity tomography surveys are utilised to determine relationships to hydrogeological properties to aid many conceptualisations of the. region. All studies employed finite element groundwater flow modelling, alongside comparative statistics and model ranking to determine the success and applicability of such analysis. In Northern Ireland, the deterministic analysis indicates that an intermediate level of upscaling (between field scale and one regional anisotropy value) provides statistically significant results at regional scale. The stochastic analysis effectively 'cleans' the magnetics data to provide a new distribution of regional heterogeneity. Modelling results are relatively comparable to the deterministic analysis and demonstrate the successful application of continuous geophysical data into model parameterisation. In Benin, all models provide significant results despite variations in model geometry and parameter conceptualisation. Point geophysical data permits effective model creation and parameter distribution through positive correlation to hydro-structural controls. For all models, minimal boundary conditions are applied and no post-processing is performed. As a result, the benefit of adapting geophysics for model parameterisation is clearly evident and suggests new hydrogeological paradigms for the study areas. Further work is required with regard to predicted anthropogenic and climate change scenarios.