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Dispersivity Estimates from a Tracer Experiment in a Sandy Aquifer
Author(s) -
Mallants Dirk,
Espino Armando,
Hoorick Marijke,
Feyen Jan,
Vandenberghe Noel,
Loy Walter
Publication year - 2000
Publication title -
groundwater
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 94
eISSN - 1745-6584
pISSN - 0017-467X
DOI - 10.1111/j.1745-6584.2000.tb00341.x
Subject(s) - tracer , aquifer , hydraulic conductivity , plume , soil science , dispersion (optics) , geology , aquifer properties , hydrology (agriculture) , groundwater , environmental science , mechanics , geotechnical engineering , physics , meteorology , optics , groundwater recharge , nuclear physics , soil water
The success or failure of transport models in predicting the migration of a contaminant plume in ground water depends to a large extent on the quality of flow and transport parameters used. In this study, we investigate the spatial variability in the tracer velocity and dispersivity in a shallow sandy aquifer in northern Belgium. Based on hydraulic conductivity measurements on cores sampled along a vertical profile, the aquifer was found to be mildly heterogeneous, i.e., with the variance of the log‐transformed conductivity K, ω 2 InK, equal to 0.22. By means of a natural gradient tracer experiment, transport of a chloride tracer was investigated in a three‐dimensional network of multilevel point samplers (MLS). Least squares fitting of a two‐dimensional transport model to the individual breakthrough curves resulted in an average longitudinal dispersivity that was 10 times larger than the transverse dispersivity. The results further showed the existence of a dispersion‐scale effect whereby the depth‐averaged longitudinal dispersivity increases with increasing travel distance. The average longitudinal dispersivity corresponding to a travel distance of 10 m was equal to 0.2 m. We finally show that theoretical expressions for the macroscopic dispersivity tensor, which require input on hydraulic conductivity heterogeneity, could be used here to approximate the observed dispersive behavior. These conceptually simple models are useful to estimate macroscopic dispersivities when no tracer data are available.