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Natural Flood Management and
the Catchment Based Approach
Ian PattisonSchool of Civil and Building
Engineering, Loughborough University
Outline
• Background to the Catchment Scale flood
risk problem
• Sub-catchment interactions
• NFM and working with natural processes
- case study of soil compaction
• Therefore, this heterogeneity (Soil characteristics / land cover)
within catchments needs to be accounted for.
Context
• Impact of rural land management on flood risk is spatially and
temporally dependent
Pattison I, Lane SN. (2012). The link between land use management and flood
risk: a chaotic conception?, Progress in Physical Geography.
Impact of Land Use on Flows
Spatial Scale = Plot/Field (10m²) Vs Catchment (2000m²)
- Individual practices
- Diffuse (combine)
- Different practices (amplify/balance out)
Bloschl et al., 2007
Doing Flood Risk Management
Research Differently
Field / Reach Sub-sub- Sub-catchment Catchment
catchment
• Upscaling to Downscaling
• Carlisle
Spatial Downscaling of Flood Risk
Petteril
Upper
EdenEamont
Caldew
?Carlisle
Irthing
Statistical Approach
• Uses widely available gauged
data
• Sub-catchment Peak flow
magnitude and Timing
• Multivariate Statistics – PCA and
Stepwise Regression
• iSIS model calibration
• Sensitivity of downstream
hydrograph to sub-catchment
flow magnitudes and timing.
• Scenario testing approach
(Single and Multiple)
Hydraulic Modelling Approach
Explaining Flood Risk in Carlisle
• Eamont = 19.3%
Upper Eden = 18.7%
• Magnitude
= U. Eden
Timing (delay)
= Caldew
Carlisle peak flow magnitude = 67.4 PC1 - 45.2 PC2 + 497.3
• 84% downstream peak discharge predicted
• 50% Magnitude
34% Timing (21% Positive = increase lag = delay)
Hydraulic Modelling Results
Timing
• Delaying U.Eden
and Eamont
reduce peak stage
by 0.32 m and
0.27 m respectively
• Speeding up
Caldew and Irthing
reduces peak stage
by 0.33m and
0.26m respectively
• Petteril has no
effect
• Maximum reduction peak stage (0.331 m) caused by a 25%
reduction in the Upper Eden.
• Eamont = 0.22m, Irthing = 0.25m
• Caldew has little effect (especially <10%), Petteril = no effect
Magnitude
Earlier Delayed
Compaction
(adapted from O’Connell et al.,
2004)
Compaction degrades soil structure
- Decreased porosity
- Decreasing hydraulic conductivity
- Alters partitioning of precipitation
into overland and sub-surface
flow
Problem of Process Complexity
CompactionCompaction levels vary spatially and are caused by different
mechanisms
Gate
Feeding Trough
Tree
Shelter
Open
Field
Inter-
Field
Intra-
Field
Experimental Design
• Stratified Random sampling around
features of interest
• Combined Field and Laboratory
measurements
Hydrology
- Soil Moisture
- Saturated
Hydraulic
Conductivity
- Double Ring
Infiltrometer
Soil Properties
- Porosity
- Organic
Content
- Particle Size
- Cores
Compaction
- Dynamic
Cone
Penetrometer
penetrometer
(surface)
Dynamic Cone Penetrometer
Deeper =
less
compaction
Intra-Field
• Cattle Open Field = most variability (frequency of tread) and
statistically different to Gate (0.0001) and Tree (0.01)
• Sheep/Horse Tree Shelter = statistically different to all other
within-field sites
Inter-Field
• Open areas – Sheep statistically different to cattle/horses
• Trends between fields not as significant as intra-field variations.
Compaction Soil Properties Hydrolo
gy
Soil Porosity
• All sites statistically different to one another
• Largest difference is between Open field and Gate
Cattle
Compaction Soil Properties Hydrology
Soil Moisture
Intra-Field
• All sites statistically significantly different to one another for
Cattle and Horses fields
• Tree shelter site different to other parts of Sheep field
Inter-Field
• The Open and Gate areas are statistically different to one
another in each of the fields.
• No difference between feeding areas in fields with different
animals.
Compaction Soil Properties Hydrology
Saturated Hydraulic Conductivity
Cattle
• No statistically significant results at 0.05 level
• Largest difference between Open field and Feeding and
Shelter areas.
Compaction Soil Properties Hydrology
Conclusions
• Inter-Field Variation
= Significant differences between fields with different types of
animals in.
• Intra-Field Variation
= Significant differences between different areas of the same
field (Open and Features)
Implications of small scale variability
(sub-field/grid scale) for Catchment
Scale Flood Risk
Landscape Management Scenarios
Hydrological Model – CRUM 3
ID Process Representation2D Catchment Scale
Compaction
Winter 04-05
Light = 36.9 m3s-1
Moderate = 58.7 m3s-1
Heavy = 60.9 m3s-1
• Flashy response
Compaction – Effect on Hydrological
Processes
• Runoff decreases
from 77% to 65%
with compaction
• Proportion as
throughflow
decreases from 56%
to 1%
• Storage increases
from 3.2% to 16%
Soil Moisture Contents = 2 layer model
Main Soil
• Heavy compaction never below 0.95 (saturated)
• Moderate compaction reaches saturation in flood events
• Light compaction never reaches saturation
• M to H 3.7% increase in peak flows
• Soil Moisture drives flood generation
Dynamic Layer
• Heavy compaction at saturation for 60% of time
• Moderate compaction at saturation for 6.5% time (floods)
• Light compaction – maximum level of 0.84
• Continuum
• 2nd flood peak
- Light
compaction
produces
highest flow
= throughflow
= ppt intensity
/ total.
January 2005 Flood
Main Soil Dynamic Layer
• Fully saturated main soil for the whole period
• Dynamic layer has storage capacity (2%) during this
secondary flood event
Upscaling Effects to the Catchment
Scale
Spatially nested modelling approach
Upscaling effectsCompaction
• Compare L and H scenarios
• 24 m3s-1 (65%) Dacre
• 36 m3s-1 (16.4%) Udford (0.17m)(0.18%)
• 49.9 m3s-1 (3.5%) Eden (-14cm)
Conclusions• Landscape scale changes reduce flood risk at the sub-
catchment and catchment scale (whole sub-catchment
managed)
• Importance of WHERE management is implemented on its
impact.
• Questions of “where to focus on?” and “what to do there?”
need to answered simultaneously
= “Where to focus and what to do there?”
• Impact of land management scales up to the catchment scale
even for extreme floods