Www.floodrisk.org.uk EPSRC Grant: EP/FP202511/1 Visualising Uncertain Flood Inundation Maps David Leedal 1, Jeff Neal 2, Keith Beven 1,3 and Paul Bates.

www.floodrisk.org.uk EPSRC Grant: EP/FP202511/1

Visualising Uncertain Flood Inundation Maps

David Leedal1, Jeff Neal2, Keith Beven1,3 and Paul Bates2.

(1) Lancaster Environment Centre, Lancaster University, Lancaster, UK;(2) School of Geographical Sciences, University of Bristol, Bristol, UK;

(3) Geocentrum, Uppsala University, Uppsala, Sweden



Outline

1. Demonstrate the Google uncertain flood inundation map tool

2. Talk about why information visualisation is important in this context

3. Discuss the potential impact of ‘smart operations’ such as the visualisation tool within flood risk management



Visualisation tool components

1. JSON mechanism for loading data to JavaScript arrays

2. Python scripts for batch processing GIS data to JSON format and PNG images

3. Jquery sliders4. Depth Exceedence selector5. Point depth exceedence selector using

Google charts



Visualisation tool components

1. JSON mechanism for loading data to JavaScript arrays

2. Python scripts for batch processing GIS data to JSON format and PNG images

3. Jquery sliders4. Depth Exceedence selector5. Point depth exceedence selector using

Google charts

Drag and drop marker with interactive depth exceedence graph

Main control panel with intuitive user interface widgets

The ‘show all’ probabilities option using a colour map to represent probability of exceediong the chosen depth.



Why is information visualisation important?

Some useful definitions:

• The human/floodplain system

• ‘Objects’ or ‘blocks’

• Operations

• Data > information > understanding

• Semiotic mechanism



Examples of ObjectsHuman systems:

• Governance

• National

• Regional

• local

• Developer

• Environmental NGO (EA)

• Consultant

• Resident of floodplain



Examples of ObjectsPhysical systems:

• A risk zone

• A residential property

• A factory

Documents:

• Planning proposal

• Flood risk Assessment

• Risk map



Examples of ObjectsEach object:

• encapsulates its own data (which could be other objects)

• can perform operations on its data

• Can interact with other objects



Examples of ObjectsObjects represented by UML/SySML:



Examples of ObjectsWhen an actor in the human/floodplain

system instigates a use-case:

A series of interactions between objects is instigated.

See for example the UK PPS25 document.



Data > understanding

• Data is not information

• Information is not understanding

• Information implies data in flow

• Understanding comes about through the decoding of information by a suitable semiotic system



Operations are high level

Example: a ‘resident’ object may contain the operation:

‘Show me the estimated risk that my property will flood sometime in the next 100 years’

The operation must be designed to create understanding (combination of data and semiotic processes)



Complicated to Complex systems

Well designed operations should aim to:

• Increase the degree of understanding that actors can extract from available information

• Increase the ease with which actors can access and exchange information

• Increase the capacity to archive information




medieval

1800

1890




Present (OS crown (c))




Present (OS crown (c))



Desirable properties of a complex human/floodplain system

To redistribute and allocate land use types to achieve:

• Self adapting behaviour

• Robustness

• Decentralisation

• Optimal seeking



Summary• The human/floodplain system is complicated but not Complex. If we can move

towards a Complex system we may achieve robustness, self adaptation and efficient allocation of land use types

• Transition to self adaptation may be hastened by the design of effective operations

• Understanding

• Access

• Exchange

• Archive

• Probabilistic inundation mapping is key

• The google maps visualisation tool is an attempt to design such an operation



David Leedal1, Jeff Neal2, Keith Beven1,3 and Paul Bates2.

Fig(d). Drag and drop marker with interactive depth exceedence graph

Fig(a) Main control panel with intuitive user interface widgets

Fig(b). The ‘show all’ probabilities option using a colour map to represent probability of exceediong the chosen depth.

Fig(c). The web-tool for visualising uncertain flood inundation data. The figure shows the main components of the tool including a georeferenced overlay selectable by the user via slider controls, a point-specific marker showing depth against probability of exceedence, and text areas providing word-based summaries of the chosen overlay and key technical terms.

Www.floodrisk.org.uk EPSRC Grant: EP/FP202511/1 Visualising Uncertain Flood Inundation Maps David Leedal 1, Jeff Neal 2, Keith Beven 1,3 and Paul Bates.

Documents

epsrc grant

flood risk management

sweden slide

loading data

semiotic mechanism slide

humanfloodplain system

batch processing gis

json mechanism