On the relationship between indicators of geostatistical, flow and transport connectivity

Connectivity of high conductivity (K) paths is important because it can lead to channeling, i.e. flow along preferential paths, which can reduce travel times very significantly. Nevertheless, limited effort has been devoted to defining the concept quantitatively. We propose and evaluate nine indicators of connectivity. Three account for the presence of flow connectivity, that is, the flow rate increase caused by preferential flow paths. Two account for the presence of transport connectivity, that is, the existence of fast paths allowing early solute arrival. The remaining four are statistical indicators based on two- and multiple-point statistics. We test these indicators on heterogeneous conductivity fields with different visual connectivity. The indicators of flow connectivity and one of the transport connectivity indicators succeed in identifying the increased presence of connected high-K features. The two-point statistical indicators fail to do so. The directional multi-point statistical indicator performs better. None of the statistical indicators correlate with the flow and transport indicators. We find only weak dependence between the flow and transport indicators. Our results suggest that transport connectivity is much less sensitive to barriers, which control flow connectivity. Instead, transport connectivity appears to be controlled by the existence of narrow, possibly discontinuous high-K paths. Therefore, we conclude that connectivity is a process-dependent concept.