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Watershed Planning within a Quantitative Scenario Analysis Framework

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Microbial water pollution: a screening tool for initial catchment-scale assessment and source apportionment.

D Kay¹, S Anthony, J Crowther

¹Catchment and Coastal Research Centre, River Basin Dynamics and Hydrology Research Group, IGES, University of Wales, Aberystwyth, Ceredigion SY23 3DB, UK. dvk@aber.ac.uk

The Science of the Total Environment

|September 1, 2009

Summary

High-flow conditions significantly increase faecal indicator organism (FIO) flux, with agricultural sources like livestock dominating. Urban sources are key under base-flow. These findings aid water quality management, especially with climate change.

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Area of Science:

Environmental Science
Water Quality Management
Ecology

Background:

The EU Water Framework Directive mandates River Basin District Management Plans.
Rapid assessment tools are needed for faecal indicator organisms (FIOs) concentrations, fluxes, and sources (agriculture vs. sewage).
Understanding FIO dynamics is crucial for effective water quality management and public health protection.

Purpose of the Study:

To develop and apply generic models for assessing FIO concentrations, fluxes, and source apportionment in UK catchments.
To calibrate national land use data for improved model accuracy.
To provide provisional FIO assessments for England and Wales, particularly for the summer bathing season.

Main Methods:

Utilized water quality and land cover data from previous UK catchment studies.
Developed preliminary generic screening models for FIO assessment.
Calibrated national land use data against existing model data.
Assessed FIO concentrations and source apportionment under base- and high-flow conditions.

Main Results:

High-flow conditions are critical for FIO flux, with improved grassland and associated livestock identified as the primary source.
FIO loadings from grasslands can be as high as from urbanized catchments.
In rural areas, agricultural sources contributed ≥40% of FIOs, especially in livestock farming regions.
Under base-flow, urban (sewerage-related) sources dominated FIOs, even in rural catchments.

Conclusions:

The developed models show the significant impact of high-flow events on FIO transport.
Agricultural land use, particularly improved grassland, is a major contributor to FIO pollution during high flows.
Urban sources are dominant under base-flow conditions.
This modeling approach is valuable for policy development and investment prioritization, especially considering climate change impacts like increased high-flow events.