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)
(1)
Department of Geography, Durham University, UK
(2) Centre for Sustainable Water Management,
Lancaster Environment Centre, Lancaster, UK
(3) Eden Rivers Trust, UK
What to do where?
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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
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Extensive
Hidden from view
The SCIMAP approach
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Based on the approach
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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
Surface Flow Connectivity
Real World Example of Connected
and Disconnected Areas
Example Application of
SCIMAP – Fine Sediment
The River Eden Catchment, UK
Calculation of a Fine Sediment Risk Map
Rainfall
Pattern
DEM
Land Cover
Slope
Upslope Area
Channels
Stream Power
Erodability
Classical Wetness
Index
Surface Flow
Index
(Connection Risk)
Point Scale
Risk
Route risk through
catchment (concn
and dilute)
Risk Map
Field scale problem
identification
Testing of the approach
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River Eden catchment
Electrofishing
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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
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211 samples collected within 3 hours
Across 614 km2
Analysed for Nitrogen, Phosphorus and Potassium
 Potassium results presented today
Electro Fishing Results
Acknowledgement: Eden Rivers Trust
Fry and Risk
20.00
18.00
Salmonid fry counts
16.00
14.00
12.00
Connectivity plus fine
sediment risk
Connectivity only
10.00
8.00
6.00
4.00
2.00
0.00
0-20%
20-40% 40-60% 60-80% 80-100%
Connectivity band
Potassium and Risk
Using only the surface flow index
No land use weighting
Scatterplot of ln (K) vs Risk_1
3
ln (K)
2
1
0
-1
0.0070
0.0075
0.0080
Risk_1
0.0085
0.0090
Assessment of land cover risk
uncertainty
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Sensitivity of the approach to land cover risk
parameterisation
GLUE type framework
30,000 parameter sets investigated
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Uniform distribution
No assumed relationships between parameters
Assessed against the
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electro-fishing data for 2002
Spatial water quality sampling for NO3
Uncertanity results
presentation
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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
Training land use weightings on
salmonid fry
Extensive grazing
0.8
0.8
0.8
0.6
0.4
0
Weighting
1
0.2
0.6
0.4
0.2
0.06
0.07
0.08
OF
Peat
0.09
0
0.1
0.6
0.4
0.2
0.06
0.07
0.08
OF
Arable
0.09
0
0.1
1
1
0.8
0.8
0.8
0.6
0.4
0.2
0
Weighting
1
Weighting
Weighting
Moorland
1
Weighting
Weighting
Improved pasture
1
0.6
0.4
0.2
0.06
0.07
0.08
OF
0.09
0.1
0
0.06
0.07
0.06
0.07
0.08
OF
Woodland
0.09
0.1
0.09
0.1
0.6
0.4
0.2
0.06
0.07
0.08
OF
0.09
0.1
0
0.08
OF
Training land use weightings on
water quality (nitrate)
Extensive grazing
0.8
0.8
0.8
0.6
0.4
0
Weighting
1
0.2
0.6
0.4
0.2
0
0.05
0.1
0.15
OF
Peat
0.2
0.25
0
0.3
0.6
0.4
0.2
0
0.05
0.1
0.15
0.2
OF
Arable
0.25
0
0.3
1
1
0.8
0.8
0.8
0.6
0.4
0.2
0
Weighting
1
Weighting
Weighting
Moorland
1
Weighting
Weighting
Improved pasture
1
0.6
0.4
0.2
0
0.05
0.1
0.15
OF
0.2
0.25
0.3
0
0
0.05
0.1
0
0.05
0.1
0.15
0.2
OF
Woodland
0.25
0.3
0.25
0.3
0.6
0.4
0.2
0
0.05
0.1
0.15
OF
0.2
0.25
0.3
0
0.15
OF
0.2
Expression of uncertainty in
the risk maps
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The fittest 0.1% parameter sets used for the
uncertainty analysis
Mean and coefficient of variation calculated
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Colour of the in stream points determined by the
mean
Size of the points related to the variation in the
sample results
Thin green lines = low
risk but low certainty
Wide red lines = high
risk and high certainty
Conclusions
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SCIMAP offers a risk mapping framework
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Currently being tested
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Explicit handling of spatial risk connectivity
Based on available data
Simple to apply to new locations
Low cost
Integrated assessment of parameter uncertainty
With physical and ecological data
Uncertainty analysis of model structural options
 Flow routing, slope determination, rescaling of risk, etc
Will be expanded to consider
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Nitrogen
Phosphorus
For More Information
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Email:
[email protected]
Web:
www.scimap.org.uk