Efficient identification of preferential flow path in heterogeneous media based on stream function

Abstract

Existence of preferential flow paths (PFP) in heterogeneous aquifers may dramatically change the behavior of aquifers, making it critical to recognize PFP in solute transport simulation and environmental risk analysis. Conventional particle tracking method can recognize PFP but is computationally demanding and hardly applicable in real high-dimensional problems. Minimum resistance method based on graph theory, though efficient, is unable to consider flow conditions and may lead to implausible path results. In this paper we propose an easy-to-implement method based on stream function to analyze and recognize PFP in heterogeneity of multiple levels. Illustrative examples and robustness tests are reported to demonstrate the effectiveness of the stream function-based method compared with particle tracking and minimum resistance methods. It is found that the proposed method is able to avoid high computational demand and potential conflicts with hydrodynamic conditions thus is both efficient and reliable.