Occurrence of microbial indicators, pathogenic bacteria and viruses in tropical surface waters subject to contrasting land use

Shin Giek Goh, Nazanin Saeidi, Xiaoqiong Gu, Genevieve Gabrielle Rose Vergara, Liang Liang, Haoming Fang, Masaaki Kitajima, Ariel Kushmaro, Karina Yew Hoong Gin

Research output: Contribution to journalArticlepeer-review

30 Scopus citations


Fecal indicator bacteria, such as Escherichia coli (E.coli) and Enterococcus, have been widely used to indicate the presence of pathogens. However, the suitability of fecal indicator bacteria to represent health risks is still being challenged, particularly in tropical aquatic environments. The objective of this study is to understand the occurrence and prevalence of indicators and pathogens in areas with contrasting land use, as well as to identify the major correlations between indicators, pathogens and environmental parameters. The spatial and temporal variation of indicators and pathogens was studied to examine the distribution patterns for areas with different land use, and the impact of seasonal changes on microbial populations. A total of 234 water samples were sampled for two years from reservoirs and their tributaries, and tested for fecal indicator bacteria, coliphages, human specific markers, pathogenic bacteria and viruses. The prevalence of indicators and pathogens in reservoirs were generally low, while relatively high concentrations were observed in tributaries to varying degrees. Of the enteric viruses, norovirus GII was among the most prevalent and had the highest concentration. Although strong correlations were found between indicators, only relatively weak correlations were found between indicators and pathogens. The results in this study showed that none of the bacteria/phage indicators were universal predictors for pathogens. Inclusion of the alternative indicators, Methanobrevibacter smithii, Bacteroides and human polyomaviruses (HPyVs) to monitoring programs could help to determine whether the fecal source was human. The microbial distribution patterns allow the classification of sampling sites to different clusters and thus, help to identify sites which have poor water quality. This approach will be useful for water quality management to pinpoint factors that influence water quality and help to prioritize sites for restoration of water quality.

Original languageEnglish
Pages (from-to)200-215
Number of pages16
JournalWater Research
StatePublished - 1 Mar 2019
Externally publishedYes


  • Bacteria indicators
  • Coliphages
  • Correlations
  • Enteric viruses
  • Occurrence
  • Pathogens

ASJC Scopus subject areas

  • Environmental Engineering
  • Civil and Structural Engineering
  • Ecological Modeling
  • Water Science and Technology
  • Waste Management and Disposal
  • Pollution


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