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Left-censoring of data sets complicates subsequent statistical analyses. Generally, substitution or deletion methods provide poor estimates of the mean and variance of censored samples. These substitution and deletion methods include the use of values above the detection limit (DL) only, or substitution of 0, DLI2 or the DL for the below DL values during the calculation of mean and variance. A variety of statistical methods provides better estimators for different types of distributions and censoring. Maximum likelihood and order statistics methods compare favorably to the substitution or deletion methods. Selected statistical methods applicable to left-censoring of environmental data sets are reviewed with the purpose of demonstrating the use of these statistical methods for coping with Type I (and Type fl) left-censoring of normally and log-normally distributed environmental data sets. A PC program (TJNCENSOR) is presented that implements these statistical methods. Problems associated with data sets with multiple DLs are discussed relative to censoring methods for life and fatigue tests as recently applied to water quality data sets.

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Milling activities at a former uranium mill site near Riverton, Wyoming, USA, contaminated the shallow groundwater beneath and downgradient of the site. Although the mill operated for \6 years (1958)(1959)(1960)(1961)(1962)(1963), its impact remains an environmental liability. Groundwater modeling predicted that natural flushing would achieve compliance with applicable groundwater protection standards by the year 2098. A decade of groundwater monitoring indicated that contaminant concentrations were declining steadily, which confirmed the conceptual site model (CSM). However, local flooding in 2010 mobilized contaminants that migrated downgradient from the Riverton site and resulted in a dramatic increase in groundwater contaminant concentrations. This observation indicated that the original CSM was inadequate to explain site conditions and needed to be refined. In response to the new observations after the flood, a collaborative investigation to better understand site conditions and processes commenced. This investigation included installing 103 boreholes to collect soil and groundwater samples, sampling and analysis of evaporite minerals along the bank of the Little Wind River, an analysis of evapotranspiration in the shallow aquifer, and sampling naturally organic-rich sediments near groundwater discharge areas. The enhanced characterization revealed that the existing CSM did not account for high uranium concentrations in groundwater remaining on the former mill site and groundwater plume stagnation near the Little Wind River. Observations from the flood and subsequent investigations indicate that additional characterization is still needed to continue refining the CSM and determine the viability of the natural flushing compliance strategy. Additional sampling, analysis, and testing of soil and groundwater are necessary to investigate secondary contaminant sources, mobilization of contaminants during floods, geochemical processes, contaminant plume stagnation, distribution of evaporite minerals and organic-rich sediments, and mechanisms and rates of contaminant transfer from soil to groundwater. Future data collection will be used to continually revise the CSM and evaluate the compliance strategy at the site.