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A Flow-through Exposure System for Evaluating Suspended Sediments Effects on Aquatic Life
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Developing environment-specific water quality guidelines for suspended particulate matter.

G S Bilotta1, N G Burnside, L Cheek

  • 1School of Environment and Technology, University of Brighton, Cockcroft Building, Lewes Road, Brighton, East Sussex BN2 4GJ, UK. G.S.Bilotta@brighton.ac.uk

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|March 6, 2012
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Existing water quality guidelines for suspended particulate matter (SPM) are inadequate. This study proposes a new model for environment-specific SPM guidelines to better protect aquatic ecosystems.

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Area of Science:

  • Environmental Science
  • Ecology
  • Water Quality Management

Background:

  • Suspended particulate matter (SPM) significantly degrades aquatic ecosystems.
  • Current water quality guidelines for SPM are often inappropriate for diverse environments.
  • There's a need for tailored SPM management targets to support ecological health.

Purpose of the Study:

  • To analyze long-term SPM data from UK reference-condition temperate environments.
  • To evaluate the suitability of current European Union (EU) SPM water quality guidelines.
  • To develop a predictive model for environment-specific SPM guidelines.

Main Methods:

  • Analysis of SPM data from 638 stream/river sites across 42 ecosystem types.
  • One-way analysis of variance to identify significant differences in background SPM.
  • Stepwise Multiple Discriminant Analysis (MDA) to predict SPM ranges based on environmental variables.

Main Results:

  • Significant differences in background SPM concentrations exist between contrasting reference ecosystems.
  • One ecosystem type exceeded the EU guideline (25 mg L(-1)) even in reference condition.
  • A predictive model using 10 environmental factors accurately assigned sites to SPM ranges (90% success rate).

Conclusions:

  • The current blanket EU SPM guideline is unsuitable for all ecosystems.
  • Some ecosystems require significantly lower SPM limits for effective protection.
  • The developed model offers a probabilistic approach to setting environment-specific SPM guidelines.