caa a22 4500 46790359X CHVBK 20180406152826.0 cr unu---uuuuu 170328e20060801xx s 000 0 eng 10.1007/s10661-005-9044-1 doi (NATIONALLICENCE)springer-10.1007/s10661-005-9044-1 Chou Charissa Pacific Northwest National Laboratory, MSIN:K6-75, P.O. Box 999, Richland, Washington, U.S.A. aut Assessing Spatial, Temporal, and Analytical Variation of Groundwater Chemistry in a Large Nuclear Complex, USA [Elektronische Daten] [Charissa Chou] Statistical analyses were applied at the Hanford Site, USA, to assess groundwater contamination problems that included (1) determining local backgrounds to ascertain whether a facility is affecting the groundwater quality and (2) determining a ‘pre-Hanford' groundwater background to allow formulation of background-based cleanup standards. The primary purpose of this paper is to extend the random effects models for (1) assessing the spatial, temporal, and analytical variability of groundwater background measurements; (2) demonstrating that the usual variance estimate s 2, which ignores the variance components, is a biased estimator; (3) providing formulas for calculating the amount of bias; and (4) recommending monitoring strategies to reduce the uncertainty in estimating the average background concentrations. A case study is provided. Results indicate that (1) without considering spatial and temporal variability, there is a high probability of false positives, resulting in unnecessary remediation and/or monitoring expenses; (2) the most effective way to reduce the uncertainty in estimating the average background, and enhance the power of the statistical tests in general, is to increase the number of background wells; and (3) background for a specific constituent should be considered as a statistical distribution, not as a single value or threshold. The methods and the related analysis of variance tables discussed in this paper can be used as diagnostic tools in documenting the extent of inherent spatial and/or temporal variation and to help select an appropriate statistical method for testing purposes. Springer Science + Business Media, Inc., 2006 ANOVA nationallicence bias nationallicence mixed nationallicence nested nationallicence random effects model nationallicence two-way crossed nationallicence unbiased estimate nationallicence variance components nationallicence Environmental Monitoring and Assessment Kluwer Academic Publishers 119/1-3(2006-08-01), 571-598 0167-6369 119:1-3<571 2006 119 10661 https://doi.org/10.1007/s10661-005-9044-1 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10661-005-9044-1 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Chou Charissa Pacific Northwest National Laboratory, MSIN:K6-75, P.O. Box 999, Richland, Washington, U.S.A aut NATIONALLICENCE 773 0- Environmental Monitoring and Assessment Kluwer Academic Publishers 119/1-3(2006-08-01), 571-598 0167-6369 119:1-3<571 2006 119 10661 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer