Authors: Weaver, TR; Kovacsy, D; Windle, DE; Gemson, W; Hausmann, N; Shibata, M; Staggs, D; Iles, M

Open access courtesy of:


Cite As:
Weaver, TR, Kovacsy, D, Windle, DE, Gemson, W, Hausmann, N, Shibata, M, Staggs, D & Iles, M 2022, 'Deriving background concentrations of contaminants of potential concern in groundwater: an example from the Ranger uranium mine, Australia', in AB Fourie, M Tibbett & G Boggs (eds), Mine Closure 2022: 15th International Conference on Mine Closure, Australian Centre for Geomechanics, Perth, pp. 691-704,

Download citation as:   ris   bibtex   endnote   text   Zotero

In the absence of pre-mining groundwater quality data, ERM interrogated nearly 220,000 data points in the Ranger uranium mine groundwater database to establish a background dataset for analytes for each hydrolithologic unit (HLU) at the site. These datasets were used to identify if analytes in groundwater were operations related, and therefore contaminants of potential concern (COPCs), and to develop background threshold values (BTVs) to inform groundwater monitoring programs and mine closure activities. The assessment assumes COPC concentrations from monitored areas comprise both operations-derived and background concentrations. The approach applied allows a site-specific background dataset to be extracted from a dataset obtained from impacted areas at a site; it relies on a weight-of-evidence approach consistent with that described in guidance from the US Navy, Interstate Technology and Regulatory Council and the US Environmental Protection Agency. In this assessment, if analyte concentrations were not related to mining activities (i.e. derived only from background conditions), the analyte was not considered to be a COPC. BTVs were then developed for the background datasets to support decision-making during closure at the site. Ranger data was compiled and reviewed so as to meet data quality standards. Iterative population partitioning was used to identify breakpoints in each HLU analyte–specific dataset using quantile-quantile (QQ) plots, independent of site-qualifying information. The breakpoint was refined using multiple lines of evidence, including temporal concentration trends, covariance with known site sources, expected source composition, and spatial patterns of impacts. For each analyte within a given HLU, 95/95 upper tolerance limits were used as BTVs for each background dataset. This approach allows background concentrations to be developed for sites where insufficient up-hydraulic gradient background or pre-development data are available, thus capitalising on a site’s operational database. This is particularly relevant in mineralised areas where background (naturally occurring) concentrations of metals or other inorganic constituents may be higher than guideline or default trigger values and concentrations.

Keywords: background threshold values, contaminants of potential concern, quantile-quantile plots, groundwater monitoring programs, mine closure

Allaire, J, Xie, Y, McPherson, J, Luraschi, J, Ushey, K, Atkins, … Iannone, R 2020, Rmarkdown: Dynamic Documents for R, R package version 2.1,
Chang, W, Cheng, J, Allaire, J, Xie, Y & McPerson, J 2018, Shiny: Web Application Framework for R, R package version 1.1,
Department of Toxic Substances Control 1997, Selecting Inorganic Constituents as Chemicals of Potential Concern at Risk Assessments at Hazardous Waste Sites and Permitted Facilities. California Environmental Protection Agency, Sacramento.
Energy Resources Australia Ltd 2018, Ranger Water Management Plan, Brisbane.
National Environment Protection Council 1999, National Environment Protection (Assessment of Site Contamination) Amendment Measure 2013 (No. 1), amended 2013, Government of Australia, Canberra.
R Core Team 2019, R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna,
South Australia Environmental Protection Authority 2008, Site contamination – Determination of background concentrations, South Australia Environmental Protection Authority, Adelaide.
US Environmental Protection Agency 1991, Guidance for Data Useability in Risk Assessment (Part A), Washington,
US Environmental Protection Agency 2002, Guidance for Comparing Background and Chemical Concentrations in Soil for CERCLA Sites, EPA/540/R/01/003, Office of Emergency and Remedial Response, Washington.
US Environmental Protection Agency 2006, Data Quality Assessment: Statistical Methods for Practitioners, EPA/240/B-06/003, Office of Environmental Information, Washington.
US Environmental Protection Agency 2009, Statistical Analysis of Groundwater Monitoring Data at RCRA Facilities, Unified Guidance. EPA/530/R/09/007, Office of Resource Conservation and Recovery, Washington.
US Environmental Protection Agency 2014, Extracting a Site -Specific Background Dataset for a Constituent from a Broader Dataset Consisting of Onsite Constituent Concentrations & Estimating Background Level Constituent Concentrations, Region 3 and Region 4, Washington.
US Environmental Protection Agency 2015, ProUCL Version 5.1 Technical Guide. Statistical Software for Environmental Applications for Data Sets with and without Nondetect Observations, EPA/600/R-07/041, Office of Research and Development, Washington.
US Navy 2004, Guidance for Environmental Background Analysis. Volume III: Groundwater, UG-2059-ENV, Naval Facilities Engineering Command (NAVFAC), Washington.

© Copyright 2022, Australian Centre for Geomechanics (ACG), The University of Western Australia. All rights reserved.
Please direct any queries or error reports to