Revealing the Mechanism of Solute Anomalous Transport Within Discrete Fracture Networks: Insight From Differences in Flow Pathways

Abstract

Understanding anomalous solute transport is crucial for effective groundwater contamination prediction and control, and efficient utilization of subsurface oil reservoirs. Variations in fracture pathways within fractured rock masses play a pivotal role in these anomalous behaviors. Traditional models face challenges in capturing complex phenomena, such as early breakthrough, heavy tailing, and multimodality, caused by these variations, highlighting the need for a quantitative, pathway‐resolved understanding of fracture‐network transport responses. In this study, a three‐dimensional discrete fracture network model was constructed from measured fracture data and subsequently converted into an equivalent pipe network for efficient simulation of both flow and solute transport. By identifying complete inlet‐to‐outlet flow pathways and tracing particle trajectories to these pathways, the study quantified the contributions of different pathways to solute transport behaviors. The results show that early arrivals are concentrated in a small number of connected pathways, whereas late arrivals are associated with longer, lower‐velocity connected pathways that contribute to power‐law tailing; parallel pathway groups with substantially different travel times contribute to multimodal behavior. Furthermore, the early breakthrough index ( I _EA ) and tailing index ( β _BTC ) show systematic correspondence with flow‐conditioned pathway travel‐time characteristics across 200 network realizations. Including variable apertures correlated with trace length further enhances flow focusing, early breakthrough, and tailing. These findings demonstrate that pathway decomposition provides a quantitative means of attributing breakthrough‐curve features to identifiable transport pathways, offering a path‐resolved interpretation of anomalous transport arising from differential advection and hydrodynamic dispersion in complex fracture networks.