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Integrated Land-Water Risk Analysis for Sensitive Catchments

Learn about SCIMAP approach for diffuse pollution protection in catchments. Real world applications, training, and uncertainty analysis covered.

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Integrated Land-Water Risk Analysis for Sensitive Catchments

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  1. Integrated land-water risk analysis for the protection of sensitive catchments from diffuse pollution Reaney S M (1&2), Lane S N (1), Heathwaite A L (2) and Dugdale L (1&3) Department of Geography, Durham University, UK Centre for Sustainable Water Management, Lancaster Environment Centre, Lancaster, UK Eden Rivers Trust, UK

  2. ? ? ? ? ? What to do where?

  3. The nature of diffuse pollution • Diffuse pollution has some special characteristics: • spatially-distributed • spatially-structured • time-varying • above ground and below ground • The source of a in-stream problem may be • Extensive • Hidden from view

  4. The SCIMAP approach • Based on the approach • Risk + Connection = Problem • Focus on the connectivity • Integrates long term behaviour • Based on a probabilistic framework • Considers surface runoff and near surface flows • Integrated consideration of uncertainty

  5. Surface Flow Connectivity

  6. Real World Example of Connected and Disconnected Areas

  7. Example Application of SCIMAP – Fine Sediment The River Eden Catchment, UK

  8. Calculation of a Fine Sediment Risk Map

  9. Field scale problem identification

  10. Testing of the approach • River Eden catchment • Electrofishing • Annual sampling by Environment Agency and the Eden Rivers Trust • Across 2,309 km2 • 280 sites per year • Salmon parr and fry • Trout parr and fry • Spatial water quality sampling • 211 samples collected within 3 hours • Across 614 km2 • Analysed for Nitrogen, Phosphorus and Potassium • Potassium results presented today

  11. Electro Fishing Results Acknowledgement: Eden Rivers Trust

  12. Fry and Risk

  13. Potassium and Risk Using only the surface flow index No land use weighting

  14. Assessment of land cover riskuncertainty • Sensitivity of the approach to land cover risk parameterisation • GLUE type framework • 30,000 parameter sets investigated • Uniform distribution • No assumed relationships between parameters • Assessed against the • electro-fishing data for 2002 • Spatial water quality sampling for NO3

  15. Uncertanity results presentation • Determine an objective function (OF) • Find the best OF values (minimum 10) and work out mean and standard deviation of parameter values that give best results • Add in next best OF • Plot the weightings against the objective function

  16. Training land use weightings on salmonid fry

  17. Training land use weightings on water quality (nitrate)

  18. Expression of uncertainty in the risk maps • The fittest 0.1% parameter sets used for the uncertainty analysis • Mean and coefficient of variation calculated • Colour of the in stream points determined by the mean • Size of the points related to the variation in the sample results

  19. Thin green lines = low risk but low certainty Wide red lines = high risk and high certainty

  20. Conclusions • SCIMAP offers a risk mapping framework • Explicit handling of spatial risk connectivity • Based on available data • Simple to apply to new locations • Low cost • Integrated assessment of parameter uncertainty • Currently being tested • With physical and ecological data • Uncertainty analysis of model structural options • Flow routing, slope determination, rescaling of risk, etc • Will be expanded to consider • Nitrogen • Phosphorus

  21. For More Information • Email: • info@scimap.org.uk • Web: • www.scimap.org.uk

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