Determination of groundwater threshold values: A methodological approach


Bulut O. F. , Duru B., Cakmak O., Gunhan O., Dilek F. B. , Yetiş Ü.

JOURNAL OF CLEANER PRODUCTION, vol.253, 2020 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 253
  • Publication Date: 2020
  • Doi Number: 10.1016/j.jclepro.2020.120001
  • Journal Name: JOURNAL OF CLEANER PRODUCTION
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, PASCAL, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Chimica, Communication Abstracts, Compendex, INSPEC, Metadex, Pollution Abstracts, Public Affairs Index, Veterinary Science Database, Civil Engineering Abstracts
  • Keywords: Groundwater, Pre-selection, Outliers, Threshold value, Natural background level, NATURAL BACKGROUND LEVELS, WATER-QUALITY, RIVER-BASIN, BODIES, CONTAMINATION, DERIVATION, IMPACT, VALLEY, PLOT

Abstract

This article is concerned with the establishment of natural background levels and threshold values for naturally-occurring parameters in groundwaters in the absence of relevant and accurate long-term spatial data. A new approach was developed and exemplified, adopting the groundwaters of the Gediz River Basin, Turkey, as a case study. The available groundwater monitoring data was from a one-year seasonal water quality monitoring campaign. The approach used combines pre-selection, selection and statistical evaluation of the selected data to eliminate outliers to determine natural background levels. The application of three different statistical tools, namely, probability plot, 2-sigma iteration, and distribution function methods, resulted in different natural background level estimates. The 2-sigma iteration method provided the most conservative values for almost all the parameters. The use of this three-step approach, which adopts different statistical methods, appeared to solve the limited data availability challenges specific to groundwater contamination and improve natural background level assessment and threshold value setting. Lessons learned from this study can help policymakers to promote similar initiatives in other countries where groundwater quality data is limited. (C) 2020 Elsevier Ltd. All rights reserved.