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Related Experiment Videos

Modelling faecal indicator concentrations in large rural catchments using land use and topographic data.

J Crowther1, M D Wyer, M Bradford

  • 1Centre for Research into Environment and Health, University of Wales, Lampeter, Ceredigion, UK. crowther@lamp.ac.uk

Journal of Applied Microbiology
|May 20, 2003
PubMed
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Land use, particularly improved pasture, significantly influences faecal indicator organism concentrations in rural catchments. These indicator levels can be successfully modeled using land use and topographic data.

Area of Science:

  • Environmental microbiology
  • Water quality assessment
  • Hydrology

Background:

  • Faecal indicator organisms (FIOs) are crucial for assessing water quality, especially in rural catchments during bathing seasons.
  • Understanding spatial variations in FIOs is essential for managing coastal water quality.

Purpose of the Study:

  • To characterize and model spatial variations in faecal-indicator organism concentrations in watercourses draining a large rural catchment.
  • To investigate the relationship between FIOs and land use/topographic variables.

Main Methods:

  • Monitoring of presumptive coliform (PC), presumptive Escherichia coli (PE), and presumptive enterococci (PEnt) at 24 points in the Rheidol/Ystwyth catchment.
  • Analysis of FIO concentrations under base- and high-flow conditions.

Related Experiment Videos

  • Correlation of FIO data with land use and topographic variables within subcatchments using distributed modeling.

    • Main Results:

    • FIO concentrations increased over 10-fold during high-flow conditions.
    • The proportion of improved pasture explained over 80% of the variance in high-flow FIO concentrations (PC, PE, PEnt).
    • Organism loss due to die-off/sedimentation occurred at base flow but not high flow; reservoir impoundments also reduced concentrations.

    Conclusions:

    • Large rural catchments are significant contributors to coastal faecal indicator loadings.
    • Land use and topographic data provide a successful modeling approach for FIO concentrations.
    • The developed model offers insights into FIO sources, transport, and survival within catchments.