Estimating contaminant attenuation half-lives in alluvial groundwater systems.

One aspect of describing contamination in an alluvial aquifer is estimating changes in concentrations over time. A variety of statistical methods are available for assessing trends in contaminant concentrations. We present a method that extends trend analysis to include estimating the coefficients for the exponential decay equation and calculating contaminant attenuation half-lives. The conceptual model for this approach assumes that the rate of decline is proportional to the contaminant concentration in an aquifer. Consequently, the amount of time to remove a unit quantity of the contaminant inventory from an aquifer lengthens as the concentration decreases. Support for this conceptual model is demonstrated empirically with log-transformed time series of contaminant data. Equations are provided for calculating system attenuation half-lives for non-radioactive contaminants. For radioactive contaminants, the system attenuation half-life is partitioned into the intrinsic radioactive decay and the concentration reduction caused by aquifer processes. Examples are presented that provide the details of this approach. In addition to gaining an understanding of aquifer characteristics and changes in constituent concentrations, this method can be used to assess compliance with regulatory standards and to estimate the time to compliance when natural attenuation is being considered as a remediation strategy. A special application of this method is also provided that estimates the half-life of the residence time for groundwater in the aquifer by estimating the half life for a conservative contaminant that is no longer being released into the aquifer. Finally, the ratio of the half-life for groundwater residence time to the attenuation half-life for a contaminant is discussed as a system-scale retardation factor which can be used in analytical and numerical modeling.

Investigations of contaminated fluvial sediment deposits: merging of statistical and geomorphic approaches.

Concentrations of contaminants in sediment deposits can have large spatial variability resulting from geomorphic processes acting over long time periods. Thus, systematic (e.g., regularly spaced sample locations) or random sampling approaches might be inefficient and/or lead to highly biased results. We demonstrate the bias associated with systematic sampling and compare these results to those achieved by methods that merge a geomorphic approach to evaluating the physical system and stratified random sampling concepts. By combining these approaches, we achieve a more efficient and less biased characterization of sediment contamination in fluvial systems. These methods are applied using a phased sampling approach to characterize radiological contamination in sediment deposits in two semiarid canyons that have received historical releases from the Los Alamos National Laboratory. Uncertainty in contaminant inventory was used as a metric to evaluate the adequacy of sampling during these phased investigations. Simple, one-dimensional Monte Carlo simulations were used to estimate uncertainty in contaminant inventory. We also show how one can use stratified random sampling theory to help estimate uncertainty in mean contaminant concentrations.