The document describes a flood event model that uses open data to help emergency responders better predict and respond to flooding. The model analyzes data on flood extents, geology, surface water, and road/river interactions to identify areas at high risk of flooding. The model was visualized on a large 3D screen and can be used with real-time weather forecasts. Future plans include expanding the model to predict rail infrastructure flooding, access historic flood data, and scale the model to other regions.

1. Flood Event Model
Winner of the STFC/ODI Open Data Prize 2014
chris.Cooper@kn-i.com

2. How did we get here?

3. The Project - WUDoWUD
Weather U Do or Whether U don’t

4. Different Fire Service Events are
concentrated in different areas

5. Open Data Providers

6. 6

7. What is a flood event?

8. Areas of focus
Where can I place my emergency resources to better effect during extreme weather?
• Paramedics
• Signage
• Sandbags
• Fire and Rescue
• Respite Centres

9. Flood Events by Time of Day

10. Geology of Hampshire
The red crosses indicate
boreholes with available
data

11. Surface Water

12. Spot Heights

13. Flood Extents

14. Road/Rail Interactions

15. Road/River Interactions

16. First Pass at a Predictive Model
White represents areas with a
high probability of flooding
Green represents areas with a
low probability of flooding
Red crosses indicate known flood
callout locations (positive
targets)
Blue crosses indicate non-flooded
locations (negative targets)

17. 17

18. 18
Visualisation
The model has been deployed on the
STFC’s 40 foot 3d screen which enables
you to zoom into the areas of interest.
An application is currently in
development which will allow people to
visualise the data using real-time
forecasts from the Met Office and from

19. 19
What next?
• Resilience Direct have agreed to help KnowNow identify a path for inclusion into this domain
• Ongoing support from Hampshire County Council to develop the new proactive process’ as a result of
new Flood Event Model triggers.
• Collaborating with Network Rail to better understand if we can predict flood events associated with the
rail infrastructure.
• Working with a large multi-national taking FEM outside the UK - investigating a Brushfires use case.
• Adoption of ‘Time Machine’ to access historic events
• Scale up - providing more predictions by using more data sets
•river silting
•new-build sites
•river abstraction
• Scale out - by adopting model for other UK regions

20. Flood Event Model
Winner of the STFC/ODI Open Data Prize 2014
@FloodEventModel