Audio Recorded Live at the AGI Showcase Event in York. For details of more AGI Events, visit our website: www.agi.org.uk

1. Interactive Maps for
Managing Asset Flood
Risk Across Manchester
Anneka Lowis BSc, MSc - JBA Consulting
Dr Barry Hankin BSc, FCIWEM, C.WEM - JBA Consulting
Dr Tariq M Ziad, BSc, MSc, PhD, CEng, MICE – MCC
Esther Goodship BSc, MRes, C.WEM, CSci, CEnv, MCIWEM - MCC

2. Background
• Section 21 of the Flood and Water
Management Act 2010
• Lead Local Flood Authority (LLFA) duty to
establish and maintain
– A register of structures that are likely to have a
significant effect on flood risk
– A record of information about each of those structures
or features, including information about ownership
and state of repair

3. Aims
• Create a Flood Risk Asset Register
– Location and type of asset and watercourse
– Details on asset condition to be populated by LLFA
• Enable the LLFA to prioritise maintenance
– Quantify properties and infrastructure at risk
– Spatially differentiate and visualise flood risk
– Provide an understanding of the relative risks from
asset blockage across the city

4. Methodology
Asset
Register
Flood Hazard
Grids
Impact
Analysis
Interactive
Maps

5. Creation of Asset Register
Existing Records
•Spreadsheet
•Paper records
•GIS layers
Records Combined
•Duplicates consolidated
•Location and Type recorded
•Unique ID
Intersecting GIS Layers
Asset Register
•960 assets
•463 assessed
for flood risk
•Roads
•Railways, Metro
•Watercourse

6. Flood Modelling
Hydrology
16
Q5
14
Q30
Flow m 3/s
12
Q100
10
Q200
8
Q1000
6
4
2
0
0
2
4
6
•463 assets
•58 return periods
10
12
•Depth
•Hazard
•Velocity
Time (hrs)
JFLOW+
•Rapid 2D overland flood model
•100% blocked scenario
•Unblocked or partial blockage
scenarios in future work
Flood Grids
•6945 (463 * 5 * 3)
•GIS format

7. Impact Analysis
Receptors
•National Receptor Dataset (NRD)
•Residential
•Non Residential
Ground Floor
•Key Infrastructure
•Roads, Railways, Metrolink
Frism
•JBA’s ArcGIS based impact
analysis software
•Batch consequence analysis
•Flood metrics calculated for each
asset and return period modelled
Metrics
•Detailed Count
•Damages
•Lengths
Damages
•NRD property type
•Depth within property footprint
•MCM depth damage curve
•Floor area

8. Impact Analysis
Geodatabase
•Feature Class per scenario
•Feature per asset
•Attribute per Metric
Excel spreadsheet
•Asset details
•Hydrology
•Metric information
•Ranked
Impact Analysis
•Results for 463 assets
•Hazard data
•Receptor data

9. Interactive Maps
Solution
Challenge
• Clearly present asset
blockage data
•
– 463 independent assets
– Flood Hazard grids
– Impact analysis
• Viewable to non technical
users without GIS software •
Suite of interactive PDFs
– Individual asset report
containing flood maps and
impact analysis tables
– Overview maps summarising
information at the ward level
– Interlinked PDFs
Viewable to non technical
users without GIS software

10. Asset Map Package
Data
•Asset information
•Flood grids
•Receptors
•Impact analysis
Automated Mapping
•Data driven pages
(ArcGIS)
•Python scripting
•One map package per
asset modelled(463)
Map Package
•Multipage PDF
•Depth, Hazard, Velocity
•5 return periods

11. Asset Map Package
Data
•Asset information
•Asset information
•Flood grids
•Flood grids
•Receptors
•Receptors
•Impact analysis
•Impact analysis

12. Interactive Overview Maps
Ward Map
Overview Map
Linked to
Ward Map
•Coloured by
number of assets
•Spatial relationship
•Coloured by impact
•Appreciation of risk
for each asset
Interactive Maps
•Easy to navigate
•Drill down detail

13. Map Animation
13

15. Further Work
• Benefit calculations
– Unblocked or partial blockage modelling
– Annual Average damages
– Benefit of culvert maintenance
• Increase interactivity of individual PDFs
– Dropdowns to allow users to switch between depth, hazard and
velocity grids
• Advantages: Reduce file sizes
• Disadvantages: Increasing complexity

16. Map Animation
16

17. Conclusions and Outcomes
• GIS techniques have been used to visualise local
flood risk from bridge and culvert assets
– GIS automation and python scripting has streamlined the process of
generating interactive risk maps from large quantities of data
– Repeatable operation
• Maps viewable by those without GIS software
– Easy to disseminate and print
– Provides an understanding of the relative flood risk from asset
blockage around the City
– Allows asset maintenance to be prioritised

18. Conclusions and Outcomes
• Creation of Manchester City Council’s Flood Risk
Asset Register
• Satisfies their requirements under the Flood and
Water Management Act 2010
– Asset location
– Understanding of asset risk
– Visualisation of local flood risk
– Prioritisation for flood risk management and maintenance
– Accessible outputs