Evaluation of mass recovery impacts on transport parameters using least-squares optimization and moment analysis

Accurate assessment of the fate of contaminants in soil relies on precise estimation of solute transport parameters under field conditions. Traditionally, transport parameters are estimated from measured solute transport data using the least-squares optimization (LSO) technique or the method of moments (MOM). Considerable mismatch between the parameters estimated by these two methods has been reported in the solute transport literature. In this study, the MOM and LSO approaches were examined for estimating pore water velocity (v) and dispersion coefficient (D) from 85 laboratory- and field-measured breakthrough curves (BTCs). The two methods yielded similar estimates of v and D for BTCs with 100% mass recovery. They yielded similar estimates of v for BTCs with incomplete mass recovery. However, estimates of D obtained by the MOM departed significantly from those estimated using LSO for BTCs with incomplete mass recovery. Analyses of truncated BTCs showed that 91% mass recovery resulted in errors of 138 and 57% in D values estimated by the MOM for repacked and undisturbed soil columns, respectively. Corresponding errors in estimated D values were below 5% for the LSO approach. Although it may be possible to normalize or extrapolate the BTC using its zeroth experimental moment to ensure 100% mass recovery, the use of either LSO or MOM would yield a different set of parameters representing a new set of experimental conditions and, therefore, would lead to further complications in obtaining a unique set of transport parameters. This suggests that where the MOM is indispensable, 100% experimental mass balance should be ensured.