High-resolution geophysical data can bridge the gap in terms of resolution
and coverage between traditional hydrological methods, such as core
analyses and tracer/pumping tests. Although there is ample evidence
of links between geophysical and hydrological parameters, such relationships
are often weak, ambiguous and site-specific. Therefore, alternative
approaches must be developed to combine geophysical and hydrological
data measured at different scales. The quantitative integration of
such a diverse database represents one of the major challenges in
the field of hydrogeophysics. In this study, we explore the usefulness
of conditional geostatistical simulations for this purpose. Using
a realistic porosity model of a heterogeneous alluvial aquifer, we
simulate corresponding neutron porosity logs and crosshole georadar
tomographic surveys. The reason for the choice of these geophysical
methods is that they provide the most direct estimates of the porosity
structure. We then use a conditional simulation approach based on
simulated annealing to integrate this database. The effectiveness
of this approach is assessed by comparing the results for a variety
of modeled porosity fields that differ fundamentally in terms of
their conditioning data. Our results indicate that this approach
allows for a realistic characterization in the sub-meter range of
the porosity distribution in heterogeneous alluvial aquifers.