Comparison of Approaches for Predicting Solute Transport: Sandbox Experiments

The main purpose of this paper was to compare three approaches for predicting solute transport. The approaches include: (1) an effective parameter/macrodispersion approach (Gelhar and Axness 1983); (2) a heterogeneous approach using ordinary kriging based on core samples; and (3) a heterogeneous approach based on hydraulic tomography. We conducted our comparison in a heterogeneous sandbox aquifer. The aquifer was first characterized by taking 48 core samples to obtain local-scale hydraulic conductivity (K). The spatial statistics of these K values were then used to calculate the effective parameters. These K values and their statistics were also used for kriging to obtain a heterogeneous K field. In parallel, we performed a hydraulic tomography survey using hydraulic tests conducted in a dipole fashion with the drawdown data analyzed using the sequential successive linear estimator code (Yeh and Liu 2000) to obtain a K distribution (or K tomogram). The effective parameters and the heterogeneous K fields from kriging and hydraulic tomography were used in forward simulations of a dipole conservative tracer test. The simulated and observed breakthrough curves and their temporal moments were compared. Results show an improvement in predictions of drawdown behavior and tracer transport when the K tomogram from hydraulic tomography was used. This suggests that the high-resolution prediction of solute transport is possible without collecting a large number of small-scale samples to estimate flow and transport properties that are costly to obtain at the field scale.

[1]  Cheng-Haw Lee,et al.  Time to Change the Way We Collect and Analyze Data for Aquifer Characterization , 2007, Ground water.

[2]  Hiromitsu Saegusa,et al.  Hydraulic tomography in fractured granite: Mizunami Underground Research site, Japan , 2009 .

[3]  P. K. Kitanidis,et al.  Large‐scale inverse modeling with an application in hydraulic tomography , 2011 .

[4]  E. Eric Adams,et al.  Field study of dispersion in a heterogeneous aquifer: 1. Overview and site description , 1992 .

[5]  D. Freyberg,et al.  A natural gradient experiment on solute transport in a sand aquifer: 1. Approach and overview of plume movement , 1986 .

[6]  Shuyun Liu,et al.  Effectiveness of hydraulic tomography: Sandbox experiments , 2001 .

[7]  L. Konikow.  The Secret to Successful Solute‐Transport Modeling , 2011, Ground water.

[8]  Allan L. Gutjahr,et al.  An Iterative Cokriging‐Like Technique for Ground‐Water Flow Modeling , 1995 .

[9]  E. Eric Adams,et al.  Field study of dispersion in a heterogeneous aquifer , 1992 .

[10]  Walter A. Illman,et al.  Hydraulic tomography using temporal moments of drawdown recovery data: A laboratory sandbox study , 2007 .

[11]  T.-C. Jim Yeh,et al.  A Geostatistical Inverse Method for Variably Saturated Flow in the Vadose Zone , 1995 .

[12]  A. Bellin,et al.  A Bayesian approach for inversion of hydraulic tomographic data , 2009 .

[13]  Peter K. Kitanidis,et al.  An interactive Bayesian geostatistical inverse protocol for hydraulic tomography , 2006 .

[14]  E. Sudicky.  A natural gradient experiment on solute transport in a sand aquifer: Spatial variability of hydraulic conductivity and its role in the dispersion process , 1986 .

[15]  T.-C. Jim Yeh,et al.  Observation and three-dimensional simulation of chloride plumes in a sandy aquifer under forced-gradient conditions , 1995 .

[16]  James J. Butler,et al.  Steady shape analysis of tomographic pumping tests for characterization of aquifer heterogeneities , 2002 .

[17]  Harihar Rajaram,et al.  Assessment of the predictive capabilities of stochastic theories in a three‐dimensional laboratory test aquifer: Effective hydraulic conductivity and temporal moments of breakthrough curves , 2005 .

[18]  T. Yeh,et al.  Cokriging estimation of the conductivity field under variably saturated flow conditions , 1999 .

[19]  Junfeng Zhu,et al.  Laboratory sandbox validation of transient hydraulic tomography , 2007 .

[20]  Walter A Illman,et al.  Hydraulic/partitioning tracer tomography for DNAPL source zone characterization: small-scale sandbox experiments. , 2010, Environmental science & technology.

[21]  Jet-Chau Wen,et al.  A simultaneous successive linear estimator and a guide for hydraulic tomography analysis , 2009 .

[22]  W. Nowak,et al.  Geostatistical inverse modeling of transient pumping tests using temporal moments of drawdown , 2005 .

[23]  Geoffrey C. Bohling,et al.  A field assessment of the value of steady shape hydraulic tomography for characterization of aquifer heterogeneities , 2007 .

[24]  Junfeng Zhu,et al.  Sequential aquifer tests at a well field, Montalto Uffugo Scalo, Italy , 2007 .

[25]  T. Harter,et al.  A Numerical Model for Water Flow and Chemical Transport in Variably Saturated Porous Media , 1993 .

[26]  T. Yeh,et al.  Hydraulic tomography: Development of a new aquifer test method , 2000 .

[27]  Walter A. Illman,et al.  Capturing aquifer heterogeneity: Comparison of approaches through controlled sandbox experiments , 2011 .

[28]  W. W. Wood,et al.  Large-Scale Natural Gradient Tracer Test in Sand and Gravel, , 1991 .

[29]  W. Li,et al.  Two‐dimensional characterization of hydraulic heterogeneity by multiple pumping tests , 2007 .

[30]  Walter A. Illman,et al.  Heterogeneity in hydraulic conductivity and its role on the macroscale transport of a solute plume: From measurements to a practical application of stochastic flow and transport theory , 2010 .

[31]  T. Yeh,et al.  Cost-effective hydraulic tomography surveys for predicting flow and transport in heterogeneous aquifers. , 2009, Environmental science & technology.

[32]  J. McCarthy,et al.  Field Tracer Tests on the Mobility of Natural Organic Matter in a Sandy Aquifer , 1996 .

[33]  C. Axness,et al.  Three‐dimensional stochastic analysis of macrodispersion in aquifers , 1983 .

[34]  Junfeng Zhu,et al.  Comparison of aquifer characterization approaches through steady state groundwater model validation: A controlled laboratory sandbox study , 2010 .

[35]  Minghui Jin,et al.  AN ITERATIVE STOCHASTIC INVERSE METHOD: CONDITIONAL EFFECTIVE TRANSMISSIVITY AND HYDRAULIC HEAD FIELDS , 1995 .

[36]  Peter Dietrich,et al.  A travel time based hydraulic tomographic approach , 2003 .

[37]  Peter Dietrich,et al.  Identification of the permeability distribution in soil by hydraulic tomography , 1995 .

[38]  Walter A Illman,et al.  Practical Issues in Imaging Hydraulic Conductivity through Hydraulic Tomography , 2008, Ground water.

[39]  Tian-Chyi J. Yeh,et al.  Characterization of aquifer heterogeneity using transient hydraulic tomography , 2004 .

[40]  Tian-Chyi J. Yeh,et al.  Hydraulic/partitioning tracer tomography for characterization of dense nonaqueous phase liquid source zones , 2007 .

[41]  A Revil,et al.  A Potential‐Based Inversion of Unconfined Steady‐State Hydraulic Tomography , 2009, Ground water.

[42]  Walter A Illman,et al.  Field Study of Hydrogeologic Characterization Methods in a Heterogeneous Aquifer , 2011, Ground water.

[43]  L. Gelhar.  Stochastic Subsurface Hydrology , 1992 .

[44]  T. Yeh,et al.  Analysis of hydraulic tomography using temporal moments of drawdown recovery data , 2006 .

[45]  T.-C. Jim Yeh,et al.  Stochastic modelling of groundwater flow and solute transport in aquifers , 1992 .

[46]  Walter A. Illman,et al.  Steady-state hydraulic tomography in a laboratory aquifer with deterministic heterogeneity: Multi-method and multiscale validation of hydraulic conductivity tomograms , 2007 .