A GIS-Based Flood Risk Assessment Tool for Emergency Planning

A GIS-based Flood Risk Assessment Tool:
Supporting Flood Incident Management at
the local scale
Meghan Alexander, Christophe Viavattene, Hazel Faulkner and Sally Priest
Flood Hazard Research Centre, Middlesex University
July 2011
FRMRC Research Report SWP3.2
Project Website: www.floodrisk.org.uk

Supporting Flood Incident Management at the local scale
i
Document Details
Document History
Version Date Lead
Authors
Institution Joint Authors Comments
001 25th July
2011
Meghan
Alexander
FHRC Christophe Viavattene,
Hazel Faulkner and
Sally Priest
Draft - complete
002 26
th
July,
2011
Meghan
Alexander
FHRC Christophe Viavattene,
Hazel Faulkner and
Sally Priest
Submitted to
FRMRC for review
and comment
Statement of Use
This report is intended to be used by researchers working on decision support tools in flood risk
management. It describes the construction of a GIS-based flood risk assessment tool, trialled with
emergency professionals in the UK. A more detailed methodology is presented in a companion
document (Alexander et al. 2011). This document presents the feedback from emergency
professionals and some practical recommendations for future tool development.
Acknowledgements
This research was performed as part of a multi-disciplinary programme undertaken by the Flood Risk
Management Research Consortium. The Consortium is funded by the UK Engineering and Physical
Sciences Research Council under grant GR/S76304/01, with co-funders including the Environment
Agency, Rivers Agency Northern Ireland and Office of Public Works, Ireland.
Disclaimer
This document reflects only the authors’ views and not those of the FRMRC Funders. The information
in this document is provided ‘as is’ and no guarantee or warranty is given that the information is fit for
any particular purpose. The user thereof uses the information at its sole risk and neither the FRMRC
Funders nor any FRMRC Partners is liable for any use that may be made of the information.
© Copyright 2009
The content of this report remains the copyright of the FRMRC Partners, unless specifically
acknowledged in the text below or as ceded to the Funders under the FRMRC contract by the
Partners.

ii
Summary
AIM The original objective of this research was to develop an exploratory tool that addressed the
potential for incorporating vulnerability assessments into risk mapping; ‘bolting’ this information onto
local, urban scale flood modelling developed within Phase 1 of the Consortium and mapping these
data at a relevant scale to emergency professionals (Wilson, 2008). Preliminary discussions with
professional stakeholders (i.e. Category One Responders, as identified under the Civil Contingencies
Act, 2004) supported Wilson’s (ibid) statement that the household scale of vulnerability and risk
mapping was desirable; however, responders acknowledged not only the impracticality of this goal,
but also the dangers of relying on household information given the highly variable and dynamic
nature of vulnerability, (unless derived from up-to-date databases, such as the health service and
utility companies). Furthermore, the Data Protection Act (1998) constrains the storing, sharing and
mapping of personal information. The vulnerability component in this tool is therefore reliant upon
census-derived data. Rather than allowing this to become a restriction, this research sought to
explore the ways in which potential indicators of vulnerability and a composite vulnerability index
(the Social Flood Vulnerability Index, SFVI after Tapsell et al., 2002), could be adjusted and
manipulated to suit the varied tasks carried out by professional end-users, in the context of Flood
Incident Management (FIM). A key research question regarded the utility of social vulnerability
assessment and whether more interactive engagement with vulnerability data could facilitate its
usage within FIM decision making.
METHODS This study sought to engage with emergency professionals throughout the research
process i.e. both pre and post tool completion. Preliminary interviews with professional stakeholders
(i.e. Category One Responders) were conducted to elicit; i) Professional views on vulnerability, its
application in decision making and how it should be assessed; ii) As the target end-user of the tool,
responders were asked to rate a number of design ideas and make further suggestions on how a tool
of this nature might be packaged together. From these discussions, the tool was designed and
constructed and then demonstrated to a sample of responders originally interviewed. Professional
feedback from this has been used to steer a number of more practical recommendations for future
tool-developers.
“THE TOOL” was approached almost as an ‘eggs all in one basket’ to see how different end-user react
and rate different design features, to inform some practical recommendations for how such a tool
might be more specifically tailored in real-life applications. Datasets are stored within a Personal
Geodatabase constructed in ArcCatalogue and the tool itself, has been designed within, and launches
from, the ESRI product ArcMap. Rather than simply allowing layers to be added and removed, this
tool enables users to manipulate these layers to suit their needs and perform calculations on the data
to produce vulnerability and risk profiles from a number of flood scenarios. This interactive nature
seeks to engage the end-user to become actively involved in the assessment process and map
production. The tool provides a means for integrating the informed subjectivities of the end-user,
with the objectivity of the ‘scientific expert’ that is inherently built within the tool. The tool has been
developed for two case studies: Cowes, Isle of Wight and Keighley, West Yorkshire. The tool is
designed with three key interfaces isolating hazard and vulnerability and allowing the user to bring
these together in the calculation of risk.
The Hazard Interface: Utilises the model outputs from 1D-2D modelling developed for Cowes, Isle of
Wight (Allitt et al., 2009) and Keighley, West Yorkshire (Chen et al. 2009) and provides a range of
scenarios for pluvial flooding. Users can adjust hazard thresholds, ‘clean’ the map to view flooding to
road network and property; where the latter offers two hazard models based on risk to life or depth-
damage thresholds. The user can also launch an interactive flood animation.
The Vulnerability Interface: Utilises existing census data (2001) and adapts the original SFVI
methodology, allowing users to adjust the spatial scale at which relative vulnerability is calculated.
Users can view indicators in isolation, alongside rationales, and construct their own vulnerability index
where selection and weighting of indicators is user-defined.

iii
The Risk Interface: Brings together the hazard and vulnerability models at the property scale. User
can define the weighting between hazard and vulnerability and view an automated property and
people count to summarise risk categories.
FINDINGS Options to animate and interact with flood inundation modelling rated highly on the end-
users ‘wish list’ and professionals commented on the application-potential of this feature for
exercising/training, planning and responding to flood events. The indicator/indices approach to
measuring and monitoring social vulnerability is widely acknowledged as limited for informing
emergency response, which requires accurate and timely information at the household scale: Only
during broad-scale flood events requiring strategic decision making (such as 2007 floods), could this
form of assessment be helpful for prioritising stretched resources. For the purpose of planning and
targeting future mitigation strategies vulnerability indicators are deemed valuable, providing there is
a clear expert-declared rationale underlining each potential indicator. Professionals interviewed
highly rated the option to view vulnerability indicators in isolation, rather than as a product score (e.g.
the SFVI, after Tapsell et al., 2002), with the additional option to adjust the spatial scale at which
relative vulnerability is calculated. The ability to ‘build their own’ vulnerability index, incorporating the
user’s informed subjectivities concerning the relative importance of each indicator, was highly
regarded for the right context (i.e. not during their ‘response’ phase of professional activities).
Furthermore, the interactive nature of the Risk interface of the tool allowed the user to explore the
variability in the risk picture, by varying the weighting assigned to hazard and vulnerability for
assessing local risk; this feature was deemed particularly useful for professional training.
RECOMMENDATIONS
Design flood scenarios (including different flood drivers and return periods) are useful for
planning and training and exercising; however, the worst case scenario is essential.
Visualising flood scenarios is a useful tool for prompting proactive thinking (rather than
merely reactive), and providing a visual example of the possible spatial patterning of the
flood. Tools supporting emergency response should enable an interactive feature for the
user to manipulate river/rainfall levels to mirror incoming real-time information.
Interactive animation is in invaluable means of depicting the spatial-temporal patterning of
the flood (as it accumulates, recedes and ponds): Where and when are key questions in
planning for and responding to flood incidents. Providing the animation is a slick operation
i.e. can be sped-up/slowed-down/paused etc. Summary tables should be used to support the
visualisation and give a rapid summary of what is being displayed on screen (e.g. flood start,
end, peak).
Future vulnerability assessment needs to be malleable and flexible to the broad base of FIM
practitioners, with varied demands, responsibilities and professional constraints. Interactive
assessments and map-making is a powerful tool for not only communicating science at the
professional interface, but integrating professional knowledge and supporting the increasing
demands on FIM in the UK.
Pragmatic flood research requires the stakeholder to become an active participant in the
research process; thereby acknowledging the importance of a two-way knowledge exchange
in facilitating the uptake of new ideas and tools in practice, as well as prompting new
thinking. This constitutes a broader effort to enhance the translation of science at the
practitioner interface.
The requisite for simplistic tools is tied to a contentious debate concerning the dualistic
meaning of simplicity: Do practitioners require simplistic-user-friendly tools or simplistic-
information tools. It is apparent from the professional interviews reported on in this report,
that simplistic-user-friendly tools are essential. This is due mainly to the varied demands
placed on professionals which mean flood-related matters are but one, small component of
the day-job; and inexperience, and a lack of confidence and self-efficacy in using new

iv
software. There is mixed support for the interpretation that the desire for simplicity reflects
a desire for simplistic-information. For instance, most responders acknowledged the
difficulties of defining and mapping vulnerability and appreciated the nuances in this
concept; on the other hand, while acknowledging uncertainties in flood modelling, some
responders seemed reluctant to engage with it – this may be because they found it difficult
to visualise how uncertainty might be integrated in mapping, or because uncertainty is
common place in the day-job and therefore not regarded as an issue. There is a need for
further research on this matter which implies a greater tension involving the translation of
science to practitioners and the professional context.
REFLECTIONS Although this research illustrates that there are possibilities for extending and utilising
vulnerability indicators within pragmatic decision support tools, the response from professional
stakeholders demonstrate that there are some fundamental limitations of this approach. In particular
there is a mismatch between the scales available for assessing flood hazard and social vulnerability,
which inherently constrain local risk assessments. On one hand, flooding can be modelled and
depicted through space and time and thus easily transformed into useable visualisations (e.g.
animation), capturing the dynamism of the hazard; conversely, vulnerability assessment remains
constrained by a static-snapshot-layering approach. Professionals interviewed in this study heavily
discussed these limitations (e.g. the decadal timescale of the census and issues of accuracy), which
means that this form of vulnerability assessment is considered useful only as a ‘broad brush’ approach
to painting an areas social make-up. The two approaches in hazard and vulnerability appraisal are
divorced in terms of scale (spatial and temporal) and must be equally resolved in order to inform a
meaningful risk assessment.
It has been argued that more meaningful assessments of vulnerability could derive for instance, from
the use of existing social data regarding people’s attitudes and responses to flood risk (Twigger-Ross,
2010). One might question who has the authority to impart this information and define what is
meaningful; is it the professional stakeholder, the academic researcher or the role of the community
under scrutiny? This report highlights potential methods for adapting existing vulnerability
approaches (using the SFVI as an example) and the potential for integrating this flexibility and end-
user control within a decision support tool. Limitations in the area-wide approach, resulting from the
dependency upon existing census data, could be resolved with the inclusion of locally-informed
information; whether this arises from exiting social surveys regarding flood experience and responses
specifically or from more generic discussions with the public in at-risk locations. Social science could
facilitate this process of seeking more meaningful assessments of social vulnerability.

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Table of Contents
1 Introduction ............................................................................................................................................. 6
2 The professional context: Flood Incident Management in the UK .................................... 6
2.1 A framework for Integrated Emergency Management (IEM)…………………………7
2.2 Extending the “toolkit” for FIM.............................................................................................. 8
2.3 A note on visualisation............................................................................................................10
3 Research design....................................................................................................................................11
3.1 Study sites.....................................................................................................................................13
3.2 Preminary interviews: The end-user “wish list”...........................................................17
4 A flood risk assessment tool............................................................................................................23
4.1 The Hazard Interface................................................................................................................25
4.2 The Vulnerability Interface....................................................................................................31
4.3 The Risk Interface......................................................................................................................35
5 Evaluating the tool: Professional feedback ...............................................................................37
6 Recommendations for future tools in practice........................................................................49
7 Reflections………………………………………………………………………………………………………..52
8 Conclusions.............................................................................................................................................54

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1 Introduction
Flood risk is defined in the UK by the probability of flood occurrence and its potential consequences
(Flood and Water Management Act, 2010). The risk management approach adopted in the UK is seen
as a holistic and sustainable strategy (EA, 2009); as such, alleviating risk is both a matter of addressing
the likelihood of flooding (e.g. flood defences and development planning) and the potential impacts
(e.g. forecasting and warning, and emergency management). Risk is thus a function of the hazard (i.e.
frequency and magnitude of the flood) and the vulnerability (susceptibility) of the receptor exposed to
the hazard. Mapping has become the keystone for flood risk management and communication in
representing the spatial relationship between hazard and vulnerability and resulting risk. In light of
growing climate change concerns and the predicted escalation of flooding, the EU Floods Directive
(2007) means member states are now required to develop and utilize flood hazard and risk mapping to
inform flood risk management plans by 2015. The purpose of these plans is to steer strategies towards
prevention, protection and preparedness, in attempts to alleviate future costs from flooding. This
research seeks to build upon this cornerstone of mapping and develop an interactive, GIS-based tool
for local-scale flood risk assessment.
This report establishes the context of Flood Incident Management (FIM) within the UK and describes
some of the current tools which are employed in practice to support decision making. The research
process is reviewed in section 3. Two study sites have been selected based on i) the availability of
existing flood modelling developed within FRMRC Phase 1 and ii) the socially-contrasting nature of
these locations in Keighley, West Yorkshire and Cowes, Isle of Wight Hampshire. Feedback from
preliminary interviews with professional stakeholders (namely Category One Responders: section 3.2)
was used to inform the construction of the GIS-based flood risk assessment tool. The completed tool is
illustrated and explained in section 4 and followed with a discussion of the secondary-feedback from
emergency professionals to whom the tool was demonstrated. A number of practical
recommendations are outlined in section 6 and it is suggested that further tailoring is required to
launch such a tool in practice. Limitations in the vulnerability approach adopted in this study are
acknowledged and it is recognised that this exists partly because the spatial and temporal scales of
vulnerability and hazard assessment are mismatched, making the assessment of local risk problematic.
2 The professional context: Flood Incident Management
(FIM) in the UK
A central objective to this research was to tailor and trial a flood risk assessment tool with potential
professional end-users; namely Category One Responders concerned with flood incident management.
This section reviews this professional context, which is situated within a framework of Integrated
Emergency Management (IEM). There has been a growth of decision support tools, for data storing,
mining, sharing and visualisation and a sample of these are presented in section 2.2. Although the tool
developed here is not intended for real-life application at this stage, an understanding of what is currently
‘on the market’ was deemed useful for steering the design of the tool (alongside stakeholder
recommendations) and highlighting current gaps – in this instance, the lack of interactive assessment for
social vulnerability for flood risk assessment. This section concludes with a note on visualisation, drawing
heavily from Cartography literature to highlight the scope for continuing tool development which utilises
visualisation and interactivity; to facilitate the communication and knowledge transfer across the
scientific-practitioner divide, ownership and prompt new modes of thinking.

7
2.1 A framework of Integrated Emergency Management (IEM)
Risk is acknowledged as changing in dynamic ways during the course of an emergency
1
event; ‘New risks
emerge, previously recognised risks recede and the balance between risks change continuously’ (HM
Government, 2004). Balancing risks is a crucial part of planning, training and exercising emergency
situations. While the UK is faced with a number of climatologically-related hazards (snow storms, heat
waves, drought) flooding has arguably been at the forefront of discussions and subject to recent policy
amendments. Emergency management in the UK is organised through the statutory framework of the
Civil Contingencies Act (HM Government, 2004), set within the wider context of integrated emergency
management (IEM). The aspiration of IEM is to facilitate joined-up, multi-agency response from the local,
regional and national scale. Local Resilience Forums (LRF) provide the setting for multi-agency discussion,
planning and exercising for the array of threats posed to civil protection in the UK. LRF membership
consists of representatives from Category One and Two Responder groups (Table 1). Regional Resilience
Forums (RRF) similarly aim to enhance multi-agency coordination for regional-wide emergency
preparedness and mediate new initiatives and policy amendments effected in Central Government, with
the region, and from the region to local responders.
Table 1: Category One and Category Two Responders
Category One Responders Category Two Responders
Local Authority
A county council, district
council; including emergency
planning
Utilities
Electricity; Gas; Water and
sewerage; Public
communication providers
Emergency Services
A chief officer of Police: A chief
constable of British Transport
Police force: A Fire and Rescue
authority: Maritime and
Coastguard agency: Ambulance
service
Transport Operators
Network Rail: Train operating
companies: London
underground and Transport
for London: Airport
operators: Harbour
authorities: Highways Agency
Health authority
A NHS Truest: A Primary Care
Trust (PCT): Health Protection
Agency (HPA): Foundation
trusts: Acute trusts
Health and Safety
Executive
Environment Agency
Strategic Health
Authority
Category One responders are central to emergency response and are subject to the full set of civil
protection duties: These include putting into place a number of plans (contingency, emergency, business
continuity); establishing arrangements for sharing information (with other responders, as well as the
public); meeting the responsibilities within the existing remits of the agency, as well as ensuring the
‘joined-up’ working across agencies. Category Two responders function as ‘cooperating bodies’ to the
Category One response and are principally tasked with sharing information and advice with all necessary
responders involved (for full details of civil protection duties consult the CCA, 2004). Integrated
emergency response is coordinated through a tiered command structure; from broad scale events
requiring a strategic response, through to the tactical and operational command required on the ground.
Within the remits of the individual agencies involved these tiers of command and control are referred to
as gold, silver and bronze, respectively.
1
Where emergency is defined as an event of situation which threatens serious damage to human welfare / or the
environment of a place in the UK (Civil Contingencies Act: HM Government, 2004)

8
In the context of flooding, Multi-Agency Flood Plans (MAFP) necessitate this joined-up working to
coordinate flood response; indeed this process of working together is considered equally as important as
the final product (HM Government et al., 2008). Vulnerable groups are identified and accounted for
within MAFP via the mapping of key facilities; such as schools, elderly care homes, hospitals etc. The
impracticalities of creating inclusive repositories of household-scale vulnerabilities (i.e. keeping it up to
date and issues surrounding data protection), means that emergency planners and responders are
required to build inclusive lists, not of vulnerable groups
2
per se, but detailing the appropriate agencies
(and databases) responsible for these groups and pathways for accessing these lists as and when required
(HM Government, 2008); of which the Local Authority and constituent departments of Adult and Social
Care, lead. This central list of partners and contact details are used to infer the potential scale and nature
of the response required in the event of an emergency. The guidance document for identifying vulnerable
people further emphasises the importance of employing this methods as a means of ‘pushing’ warning
messages and ‘pulling’ potentially vulnerable individuals towards the authorities in advance of an
emergency. Vulnerability mapping and the use of Geographic Information Systems (GIS) is highlighted as
an invaluable tool for appreciating both the scale of the response required (e.g. location of rest centres)
and potential impact (i.e. nature of aftercare). This guidance document in particular emphasises the
importance of complementing the mapping of vulnerable groups, with estimated people counts and
appropriate response mechanisms required (HM Government, 2008).
While national flood risk management (and coastal erosion) remains within the remits of the Environment
Agency, the Flood and Water Management Act (2010) assigns Local Authorities (LA) as the lead agency in
response to local flood risk management; including flooding from surface water, small watercourse,
canals, reservoirs and groundwater. Under the Flood Risk Regulations (20093
) LAs are required to
complete flood risk assessments by June 2011: Social vulnerability mapping is inexplicitly incorporated
within these maps through the mapping of ‘human health’ (risk indicator) and is based on a property
count, estimated people count (i.e. 2.5 people per property) and the mapping of critical services (e.g.
hospitals: Environment Agency, 2010). It is not a requirement to consider the social make-up of these
properties.
These recent policies, the Flood Risk Regulations (2009), the Flood and Water Management Act (2010)
and earlier suggestions from the Pitt Review (2007), place a mounting pressure on Local Authorities to
identify and map localised flood risk, and coordinate appropriate responses to meet the goals of
sustainable flood risk management. Furthermore, this ‘devolution’ of FRM, places responsibility into the
hands of professional stakeholders with less and less formal training in flood science (Faulkner et al., in
press). There is a need to develop new tools with the ability to not only support the shifting roles of local-
based practitioners and decision making, but also in translating flood science to professional end-users of
this knowledge. It is argued that this translation process could not only facilitate the up-take on new
ideas, knowledge and tools in practice, but also augment practitioner engagement in flood science. In the
long-term this form of translation and focus on pragmatic flood research which seeks to adjoin science
and practitioners, could meet the goals for capacity building and improve local flood risk management
(Defra, 2010).
2.2 Extending the ‘toolkit’ for FIM
Information mining is a critical task in FIM. The nature of multi-agency working means professionals
must strive toward a commonly recognised information picture (CRIP) before coming to a collective
decision. Web-based portals have been effectively used to centralise incoming, up-to-date information,
as well as acting as a store house for relevant documents. Hazard Manager is one such example and uses
mapping and real-time weather (e.g. links into the Flood Forecasting Centre for extreme weather alerts)
and incident related information, to facilitate CRIP and joint decision making activities between
2
Where vulnerable people are defined as those that are less able to help themselves in the circumstances of an
emergency. This may include the elderly, young children, mobility impaired, minority language speakers etc. (for a full
list please consultant HM Government, 2008)
3
The Flood Risk Regulations 2009 represent the UKs response to the EC Floods Directive 2007.

9
professional partners (http://www.metoffice.gov.uk/publicsector/hazardmanager). This system was
developed by the Met Office and is considered to be a “one-stop information source”.
The National Resilience Extranet (NRE) has similarly sought to establish itself as an information portal to
facilitate multiagency working through shared knowledge, emergency planning and managing real-time
incidents (Cabinet Office, 2010). The main function of the NRE is to serve data sharing (current, archived
and classified documents), but the system also provides an inclusive contact list of all key responders,
updates on good practice, expertise sharing and an open-shared calendar for organising meetings.
Although this system is currently being used by 350 organisations (mainly local authorities: Cabinet
Office, 2010), it has been greeted with mixed responses. During the course of semi-structured interviews
with emergency professionals in this research, it seems the main failing of the NRE was its attempts to
be a ‘one stop’ tool. Rather than offering limitless capabilities, end users felt that the system would have
been effective if it can kept to its original brief as a storehouse of key documents and contacts only. The
implication of this for the flood risk assessment tool developed in this research, is that it must have a
clear focus; indeed supporting a small number of tasks, but supporting the well, is better than trying to
everything to everyone and hence nothing to no one.
Computer technology is a crucial tool for simulating emergency events and facilitating joined-up
working. A number of tools exist for training and exercising purposes. The HYDRA-MINERVA system used
by Fire and Rescue provide a number of scenarios within fire rescue, to chemical incidents and heavy
snowfall events. Each scenario runs in real-time, feeding-in information from multiple sources, allowing
for fast and slow decision making and tactical and strategic levels of command. Decisions are logged and
audited for the purpose of debriefing – flooding is not currently included in the portfolio of emergency
events simulated in this tool (http://www.hydrafire.org/).
Simulating real-life events is an important part of building-up professional skills and expertise, and
trialling new tools to support decision making. FloodViewer© for instance, was trailed in the UK EA-lead,
national Exercise Watermark 2011. This tool enables end users to view flood information in a dynamic
way, employing functions of zoom, pan and animation, whilst visualising the spatial patterning of
flooding onto vulnerable hot spots (e.g. key roads, hospitals etc.). Users of this tool can select a specific
return period for flooding or view a given water level using a slider control bar, and visualise the corresponding
flood extent. Crucially this tool is designed outside off expensively-licensed products (such as ArcGIS) and
is viewed universally (e.g. online) by multiple decision making partners (Halcrow, 2011).
There has been a growth in the development of commercial products designed to support decision
making in flood risk management. UK consultancies such as Gaist Ltd have sought specialism in
emergency management with products such as Inca (Incident command administrator) and a multi-
agency collaborative tool, ‘Gaist emergency’ (Gaist, 2010). This latter system is specifically designed to
facilitate multi-agency working with universal display, an interactive and user-friendly interface and
provides access to a virtual earth server to access Bing maps. This system is compatible with INCA
(Incident command administrator) tailored to meet the demands of the Fire and Rescue Service and
enables on-the-ground risk assessments (‘tough books’) to be electronically sent and logged into the
INCA interface and used to inform the incident commander and control room.
Socio-demographic data has been exploited for commercial products such as MOSAIC, developed by
Experian Ltd. Details regarding the demographics, lifestyles and behaviour of all individuals and
households in the UK are centralised into this one tool and derived from the census, media and market
research. The tool is essentially based on a classification criterion which identifies 146 person types
and groups these into 69 categories based on lifestyle types; these categories are further reduced into
15 main socio-economic groups (according to MOSAIC Public Sector; Experian 2009). This 3-tier
classification system means that the MOSAIC tool can be deployed at the individual, household or
postcode scale to suit the decision maker’s needs. While this tool was originally designed to support
commercial decision making, it has application potential for emergency management. For instance,
MOSAIC is employed by the Fire and Rescue Service for targeting risk communication and fire safety
campaigns. Other products from this line such as MOSAIC Daytime have application potential for
emergencies. This particular tool records the shift in population patterns from day to evening and is

10
currently deployed for targeting home selling; in an emergency situation this information could prove
highly useful for prioritising response into certain areas.
The tool developed within this research aimed to explore how end-users interacted with an interactive
feature of vulnerability assessment; indeed, when given the choice, do professionals value a
vulnerability ‘product’ (e.g. the social flood vulnerability index), over the option to select and weight
indicators and essentially build their own vulnerability index, adjusted to their professional needs.
Given the partnership with the hazard in governing overall risk, this tool also sought to gauge how
professionals rate different approaches to hazard assessment and the calculation of risk at the local
scale. For example, how might end-users negotiate the balance between hazard and vulnerability
when given an option to weight them within the risk equation? The findings from semi-structured
interviews and questionnaires with professional stakeholders were used to inform some practical
recommendations for real-life application (see section 6).
2.3 A note on visualisation
There is an ever-expanding reservoir of accessible, georeferenced data, which has arguably
corresponded with changing scientific and societal demands and applications of these data
(Maceachren, 1998). Visualisation techniques have received considerable attention over the past
twenty years with developments in technology opening new windows into previously inconceivable
approaches. The development of Geographic Information Systems (GIS) for instance, has made
possible the handling (from storing, visualising and analysing) of spatially-referenced data in interactive
ways.
Mapping has become the keystone for flood risk assessment and communication. Presentation is a
crucial element to successful map-based communication (i.e. does the user infer the map information
in the way it was intended?). Visualisation decisions have been shown to exert a profound influence on
the effectiveness of information transfer and the receptiveness of the end-user to this information
(Alphen et al., 2009). Alphen et al. (2009) note the use of colour and the role of social conditioning in
map interpretation; for instance, blue is widely recognised as a sign for water and a scale of red,
orange, green as a scaling for danger. While computer technology has increasingly enabled the
rendering of ‘realistic 3D worlds’ (Kot et al., 2005), it has been stressed that the power of visualisation
rests with its ability to abstract reality (Muehrcke, 1990; cited in DiBiase et al., 1992); for instance
maps can be adjusted to varying scales, employ numerous symbols etc. This enables the viewer to
more readily identify patterns in the data; ‘distinguishing pattern from noise’ (Maceachren and Ganter,
1990).
While traditional, top-down approaches to map making have developed map products for end-user
delivery, there is now a shifting agenda towards tailoring the final product to the end-user themselves.
Visualisation is defined within the Cartography literature under two paradigms; a communication
model and a visualisation model. The first perspective for communication has dominated the field of
Cartography (and other disciplines utilising cartographic principals) and emphasises the value of maps
as communicating ‘what we know’ (Maceachren and Ganter, 1990). Conversely the visualisation
perspective on map function emphasises ‘what is yet unknown’; that is to say, the map is a stimulant
or facilitator for new ways of thinking and in this light has profound implications for exciting scientific
creativity (ibid). The work of Maceachren and colleagues in particular has emphasised the importance
of the visualisation perspective and the associated potential for visualisation techniques in prompting
new ideas and modes of thinking. Visualisation should therefore be viewed as a facilitator, rather than
the end product in itself.
Viewpoints from Cartography have been offered and have proposed a shift from seeking ‘optimal
design’ and visual communication to facilitating visual thinking (DiBiase et al., 1992). Flood science has
thus far focussed on the enhancement of communication i.e. to transfer ‘what we know’, but how
might visualisations prompt new thinking in users? Will this new generation of visualisations and
decision support instruments change the data requirements of end-users in the long-term? McCarthy
et al., (2007) show that user-interaction with new visualisation tools and with tools designers can alter

11
initial assumptions and facilitate the want for new techniques; and most importantly the self-efficacy
of the end-user to utilise new techniques. The expressed desire for ‘simplicity’ voiced by end-users
arguably stems from an uneasiness with new and seemingly complicated tools. For new tools to be
fully integrated and not viewed as ‘the shiny new toy’ (only to be neglected soon after) it is crucial that
any new visualisation tool presented is user-friendly and self-explanatory. Engaging with target end-
users in the design process is a necessary step towards end-user satisfaction. Morss et al. (2005) argue
that the traditional, scientific view of the ‘end-user’ as the passive receiver of knowledge should be
replaced by the inclusion of the ‘end user’, enabling them to become active members of the research
process. This strategy is deemed beneficiary to both science and professional stakeholder groups and
can facilitate co-knowledge production, a sense of shared ownership and encourage the uptake of new
ideas and tools in practice. Visualisation tools in their own right offer the potential for user
engagement with the data and can be considered as useful aids to the decision-making process.
3 Research design
This research is centred on the development of a GIS-based flood risk assessment tool (“the tool”). The
methodological stages of this research are illustrated in Figure 1. Although the tool was not designed for
real-life application, Figure 1 recognises the need for multiple iterations between tool developer and end-
users to tailor the tool to professional cultures and requirements. This report reflects on the first stage of
iteration only and discusses the tool’s construction and evaluation with a select sample of emergency
professionals.
STAGE 1 sought to draw upon existing scientific knowledge to infer what should be included, whilst
equally framing the possibilities for what ‘could’ be included in such a tool. In this research, the scientific
input derived from the interdisciplinary contributions from physical and social sciences to represent the
hazard and vulnerability dimensions of the risk equation respectively. Available to this study were
relatively small-scale flood inundation visualisations, produced as outputs from previous 1D-2D
inundation modelling developed under the auspices of the Flood Risk Management Consortium’s research
(FRMRC Phase1). These model outputs were developed for two UK locations; in Keighley, near Bradford in
West Yorkshire (Djordjević et al., 2005) and Cowes on the Isle of Wight (IOW), in Hampshire (Allitt et al.,
2009). The original objective of this research was to utilise these existing 1D-2D model outputs for pluvial
flooding and address the extent to which vulnerability data can be successfully ‘bolted-on’ to give a
calculation of risk at the local scale. A key research question regards the utility of social vulnerability
assessment and whether more interactive engagement with vulnerability data could facilitate its usage
within FIM decision making. In this first stage, expert consultations and literature review helped inform
the scope for the vulnerability interface of the tool (Wilson, 2008).
STAGE 2 involved the preliminary engagement with emergency professionals. Semi-structured interviews
with the Category One Responders chosen for the study were administered to elicit professional
viewpoints on flood risk assessment, how it is currently assessed and how a decision support tool might
aid current practice. These interviews also helped contextualise the roles and responsibilities of
emergency professionals. A total of 18 professionals participated in preliminary interviews, representing
the Police, Fire and Rescue, Ambulance service, Environment Agency, Emergency Planning (county and
district council), Health Protection Agency and a utility company. Interviews were complemented by
structured questionnaires, which asked respondents to rate the design suggestions proposed by the
scientists (concerning tool functionality and presentation).
STAGE 3 concerned the tool’s construction, which was designed to be exploratory in this first stage (i.e.
not a final product). The tool was written in Visual Basic for ESRI and constructed as an interface to the
commercial GIS application, ESRI’s ArcMap (9.3). Datasets are launched from a personal geodatabase and
automatically situated within the tool’s interfaces for hazard, vulnerability and risk assessment. This ‘GIS-
interface’ approach, aimed to facilitate user-friendliness, whilst maintaining the GIS interactive
capabilities (e.g. zoom, pan). As the user’s interacts with this interface, both the global map in ArcMap
and a corresponding ‘summary window’ on the interface itself are updated.

12
STAGE 4 is essentially the ‘tailoring stage’. Firstly, the completed tool was demonstrated to a sample of
Category One Responders (n=8) and each interface and feature was explained. Responders were also
given the opportunity to interact with certain features. Throughout this process, responders were invited
to give their views on what worked well and whether there was application potential for supporting FIM
decision making; this was essentially an open-interview approach. Finally, following this extensive
interaction and discussion phase, professionals completed a short questionnaire to rate each feature in
turn. All interviews were transcribed and analysed in the qualitative data software NVivo using thematic
analysis (via open and selective coding: e.g. Fereday and Muir-Cochrane, 2006), to locate key themes and
identify different and convergent opinions expressed across stakeholder groups. Professional feedback
from this has been used to steer a number of more practical recommendations for future tool-developers
(section 6).
Figure 1: Summary of research stages

13
3.1 Study sites
This research focuses on two contrasting UK locations in Keighley, near Bradford in West Yorkshire and
Cowes on the Isle of Wight (IOW), in Hampshire. Both locations are exposed to pluvial flooding, resulting
from the interaction between heavy rainfall and failings in managed drainage networks. Pluvial flood
event matrices have been modelled for both areas within the research of the Flood Risk Management
Research Consortium (FRMRC), thus providing the ‘hazard’ details required for a flood risk assessment
tool. This section describes the geographical setting of these case studies, the flood histories and
respective modelling work simulating these.
Moreover, there are some interesting socio-economic differences which make Keighley and Cowes an
interesting comparison. This section addresses these differences drawn from the Index and Multiple
Deprivation (IMD) and less clearly from the Social Flood Vulnerability Index (SFVI). These differences could
prove important to understanding how vulnerability is conceptualised by professionals responsible for
these areas.
3.1.1 Keighley, West Yorkshire
The Stockbridge area of Keighley is situated at a confluence between the River Aire and the River Worth
(Figure 1). Significant fluvial flooding in October 2000 caused damage to 370 residential properties
(Wilkinson, 2007) and represented the worst scale of flooding witnessed in the area for fifty years. While
those registered at the time to receive the EA flood warning had one hour to respond, the event occurred
at 5am local time and was therefore a ‘surprise event’. It took 6-12 months for people to be able to return
to their properties. Post event reviews revealed insurance to be a significant issue, with nearly half of the
affected population lacking either contents of buildings insurance (Wilkinson, 2007). Furthermore,
localised storm events over Keighley have since caused localised flooding in July and August 2003
(CBMDC, 2005).
These events sparked an independent enquiry into water management within the Bradford district which
highlighted the importance of joined-up working, information sharing and need for community
engagement to engender an awareness of ownership of responsibilities for dealing with risk and
mitigations. The Flooding Local Action Plan (FLAP) emerged from this enquiry, which sought to promote
community involvement in flood issues (Cashman, 2009); funding cuts has since meant that the ten FLAPs
set up now cease to exist. However, Bradford city council remains committed to gauging its population’s
awareness of flood risk and suggestions for flood risk management (e.g. current Bradford District online
questionnaire as part of the EU project FloodResilienCities www.bradofrd.gov.uk). Over three thousand
properties are at flood risk within Bradford, with an estimated value of £247m; this figure accounts for
fluvial flood risk only and does not include surface water flooding.
Flood defences have been installed in response to the significant 2000 flood in Stockbridge, including a
levee and reinforcements to the river channel; these flood defences are designed to protect Stockbridge
against the 100 year event (CBMDC, 2005). However, the area remains susceptible to surface water
flooding which has been identified as an increasing problem (EA, 2008). As part of the government’s
Making Space for Water (Defra, 2005a), the River Aire in Bradford and Leeds was one of 15 projects
informing the Integrated Urban Drainage Programme (CBMDC et al., 2008). Hydraulic modelling
conducted in this research suggested a potential rise in surface water flooding by 200% by 2085, resulting
from patterns of climate change and urbanisation.

14
Figure 1: Flood hazard map of Keighley, West Yorkshire (Environment Agency Flood Map)
Flood modelling is integrated in this research and utilised to equate the ‘Hazard’ component of the flood
risk assessment tool. 1D-2D modelling in Stockbridge simulates the interaction between urban sewer
systems and overland flow, based on the SIPSON-UIM model (Chen et al., 2009: Djordjević et al.,2005).
Whereas SIPSON is a 1D hydraulic model which records the flow routing in the sewer systems and rainfall-
runoff hydrographs, the 2D UIM model stimulates ground surface inundation. These models are coupled
via discharge through manholes to reflect drainage and surcharge flows. The spatial distribution of
flooding has been modelled for various combinations of rainfall-runoff intensity and duration (pluvial and
fluvial flood matrices), modelled with and without the presence of flood defences and for scenarios of
levee breach and overbanking (for more details on SIPSON-UIM the reader is referred to Chen et al.,
2009).
Several scenarios were considered suitable for inclusion in the tool. Firstly, a range of scenarios with
depth and depth-velocity details were integrated. These simulate pluvial flood events and are modelled
for a series of return period (2 yr, 5 yr, 10 yr, 20 yr, 50 yr and 100 yr) and storm duration (15 min, 30 min
and 60 min). Ultimately each scenario is modelled for 12 hours and therefore illustrates the progression of
flood water, its flow pathways, ponding and ultimate recession. Secondly, a scenario for a fluvial flood
event was used and simulates a breach and overbanking scenario on the levee system. The breached
scenario was calculated by removing the levee system from the model; water overflows when it surpasses
the grid elevation of the surrounding cells. In the overbanking scenario, water overflows when the flood
stage in the channel exceeds the crest elevation of the levee (100 yr flood + 10 cm). This model runs for 10
hours. Thirdly, a scenario for fluvial-pluvial combined flooding is included, based on the 100 year event,
for a 60 minute storm duration (and again, is run for 10 hours). This model also includes scenarios for
breach and overbanking.
There are a number of underlying assumptions which underwrite the uncertainty of this flood model.
Firstly, the rainfall input is assumed to be spatially and temporally uniform. This is a common assumption
made in pluvial flood modelling which is naturally highly variable in space and time and very difficult to
predict. Secondly, the propagation of flooding (flow routing, pooling) is dominated by the underlying
elevation model and is a potential source of error. In this instance, the elevation surface is based on OS
Mastermap and high resolution LiDAR and thus minimises this source of uncertainty. Finally, the
governing equations of any modelling tool can amplify uncertainty. The SIPSON-UIM model has been
benchmarked with the Environment Agency’s 2D model and trialled in eight different types of case
studies; one can be confident at least that the model is producing similar results. Communicating

15
uncertainty in flood science is a contentious issue and current debates surround the responsibility and
ownership of these data (Faulkner et al., 2007). The tool presents these sources of uncertainties as a
series of bullet points in a pop-up window. Arguably there is a need to consider graphical and cartographic
means of visualising this and a case for avoiding the ‘prescription note’ or ‘health warning’ of uncertainty
(Faulkner, pers coms). The cascade of uncertainty in flood modelling means that there are even
uncertainties in uncertainty communication and while professionals were asked whether the uncertainty
information was something they used, it was not a pivotal research question addressed in the tool.
3.1.2 Cowes, Isle of Wight, Hampshire
Cowes is situated at the mouth of the Medina River as it drains into the sea off the Isle of Wight (IOW). In
theory the Island is an extended arm of Hampshire on the mainland, but in practise its isolated nature
means that in terms of emergency management it often relies upon its own resources. Flooding is a
recurring issue Island-wide. In Cowes, the main source of flooding is tidal and the tourist centre of the
town, the High street (Figure 2), is periodically inundated with more significant flood events occurring in
October 2004 and July, 2006.
Figure 2: Flood hazard map of Keighley, West Yorkshire (Environment Agency website)
As with Keighley, the complex nature of pluvial flooding has been modelled for the West Cowes
catchment. Allit et al (2009) have used Infoworks CS 2D model, in conjunction with a 1D sewer model. The
assimilation of 1D-2D modelling aims to capture the dynamics of minor and major systems respectively,
between the underground sewer network and overland flow pathways. For Cowes, the following model
outputs have been supplied to this research through the Flood Risk Management Research Consortium
(FRMRC phase 1). Firstly, the tool integrates a number of design storms for the 2, 5, 10, 20 and 50 year
return periods, modelled at 30, 60 and 90 minutes. These files include the maximum depth and hazard
values obtained in each model run; where the hazard has been calculated according to the recent Defra
guidelines including debris factors (HR Wallingford et al., 2006). Secondly, a 100 year storm event was
used to constitute the animation feature of the tool, based on model outputs at one minute time-steps
and simulating an event over 120 minutes. These results were based on the SIPSON-UIM model (run for
Keighley, by Exeter University); these two models are compared in Allitt et al (2009).

16
The resulting simulations correlate strongly with known sites of flooding and flood records from actual
rainfall events (Allitt et al., 2009). Field observations have also been integrated into the model to capture
the dynamics between surface features (e.g. walled entrances to properties, alleyways) that can divert or
constrain flow pathways. This model also captures the pluvial runoff within the catchment, based off the
surface topography; assuming no infiltration, initial losses or depression storage (Allitt et al., 2009). The
results presented illustrate the model-run with the inclusion of sewers and buildings.
3.1.3 Contrasting Keighley and Cowes
Both towns have a common flood driver in the form of pluvial flooding, which is used within the
respective tools for these locations. It was decided to utilise earlier research developed within FRMRC
Phase 1 and to use these two socially-contrasting locations to explore whether this exerts any effect upon
professionals’ perspectives of vulnerability, or indeed upon the residents in these respective areas.
Social vulnerability is currently recorded within Catchment Flood Management Plans (CFMP) according to
the Index of Multiple Deprivation (CLG, 2008). The IMD calculates a rank of England-wide Lower Super
Output Areas (LSOA), an aggregation of ca. 1000 properties. A rank of 1 indicates the highest deprivation
and 32,482 indicates the lowest; these are based on the aggregation of seven domain indices, including
income, employment, health and disability, education skills and training, barriers to housing and services,
living environment and crime. Keighley displays a wide range in IMD ranks, from a minimum rank of 199
(high deprivation) to a relatively high rank 29,061 (low deprivation), with an average rank of 9296. Cowes
by comparison has an average rank of 17,917 and is a considerably less deprived area than Keighley
(Graph 1).
Graph 1: The Index of Multiple Deprivation for Keighley and Cowes; Descriptive statistics (based IMD,
2007: CLG, 2008)
The predecessor to the IMD was the Social Flood Vulnerability Index (SFVI, Tapsell et al., 2002). In terms of
recorded social vulnerability, both locations have an average SFVI score of 3 i.e. a national average
category. There are noticeably variations between the two locations and the range of SFVI categories
(Table 2), as Keighley displays a wider range of SFVI categories (from low to very high vulnerability),
compared to Cowes which consistently records an SFVI category of 3 or 4 (from average to high
vulnerability). It was originally hypothesised that Cowes and Keighley would provide to socially-
contrasting areas for comparison: For instance, Keighley is regarded as a diverse, multi-ethnic setting,
with 10% of the population of Asian ethnicity (predominantly Pakistani, based on 2001 census). In terms
of the Social Flood Vulnerability Index (SFVI) however, these differences are masked within this
composite, additive model. Each indicator is treated with equal importance in terms of its influence upon
vulnerability (explained further in section 3.3.2). Graph 2 illustrates the break-down of the SFVI and
presents the average percentage of each indicator within Keighley and Cowes. Lone parent households

17
and non-car ownership dominate vulnerability within Keighley; whereas Cowes is dominated by non-car
ownership, non-home ownership and illness indicators.
Table 2: Observations from the SFVI categories in Stockbridge, Keighley and Cowes, IOW (when SFVI is a relative
measure of vulnerability for England and Wales, based on the original dataset from Tapsell et al., 2002)
SFVI statistics Stockbridge, Keighley Cowes, IOW
Mean 3.17 3.55
Minimum 2 3
Maximum 5 4
Graph 2: The break-down of the SFVI indicators within Keighley and Cowes, based on average percentages recorded
in the 2001 census
The SFVI methodology represents a ‘classical’ approach to vulnerability assessment, based on
assumptions of demographic indicators, all equally as important in governing vulnerability. This research is
interested in adapting this approach and investigating the ways in which it might be adjusted and made
malleable to suit the varied needs of Category One Responders (as identified under the Civil Contingencies
Act 2004). Aside from the tool, fieldwork was conducted in Keighley, using questionnaire surveys to
appreciate the perception of vulnerability amongst those ‘objectively’ labelled as being vulnerable; i.e. is
there a resonance between the SFVI classification system and householder declared vulnerability?
3.2 Preliminary interviews: The end users “wish list”
In both case study locations, a sample of Category One and Two responders were interviewed at the
preliminary stage of enquiry to ascertain current views on vulnerability and its application in decision
making. Furthermore respondents were asked to rate a number of initial design suggestions for the tool
and disclose their opinions on the value of integrating hazard and vulnerability data at the local scale.

18
Although all Category One Responders have a statutory requirement to communicate and integrate their
response, the emphasis on responding agencies shifts throughout the course of the emergency
management cycle; from preparation, response and recovery (Figure 3). It is important to remain mindful
of this when interpreting their responses from the semi-structured interviews. Each interview has been
transcribed and analysed in the qualitative data analysis software, NVivo.
Figure 3: Locating the principal roles of Category One Responders within the emergency management cycle
3.2.1 Findings
There was a wide agreement across responders as to what constitutes vulnerability and a high level of
awareness regarding its complexities. For those particularly concerned with the ground-response (e.g. Fire
and Rescue, Police and Ambulance), risk to life is at the forefront of decision making.
Vulnerability was considered by some to be an all-encompassing term; from people’s socio-demographic
characteristics, people’s attitudes and awareness towards flooding, human behaviour, to an area’s
infrastructure etc. From the professional’s interviews, this was regarded as a potential limitation; “ It’s
such an umbrella terms….It’s so broad so as to be meaningless” (Fire and Rescue, West Yorkshire).
However, whilst acknowledging the highly variable nature of vulnerability, given their professional focus,
vulnerability is defined as any characteristic which will limit a person’s ability to save themselves; most
notably, people suffering with a limiting long-term illness or disability. The elderly population is also a
recurring indicator, based on the assumption that it correlates highly with illness and disability
perspective

19
While respondent’s cited a number of indicators and discussed the value of the common indicators cited
in the literature, many emphasised the grey nature of these and observed how an indicator can both
indicate both, high or low vulnerability.
“Yeah I was looking at the home ownership one and it’s kind of a mix because a lot of the council tenants
get a lot of support from the local council when their properties flood because it’s the council’s duty to
maintained council-owned properties. And then you’ve got the other side of people who own their own
homes and are slightly richer and can afford insurance. But then you’ve got in the middle of that people
who own their own homes but can’t necessarily afford insurance and they go uninsured and they shouldn’t
really in a flood risk band or wherever they live and their kind of in that middle ground, they’re not rich
enough to help themselves but they’re not in a council owned property so the council can do very little to
support them.” (Environment Agency, West Yorkshire)
Furthermore some responders challenged the assumptions of vulnerability indicators. While indicators
such as elderly suggest a level of social dependence that is not to say that all elderly people will require
assistance. Prioritising certain social groups when responding to an event, could be at the detriment to
others; “There the people who fall through the gaps and you’ve got this list here, yeah we could target
those but actually it’s the single male in the late 40’s who’s on the disability allowance who spends the day
drinking whisky in the middle of the day. So vulnerability is both about lifestyles, about attitude and our
response I think in the main is to take a very equality and diversity sort of attitude to response (West
Yorkshire Fire and Rescue). This comment from Fire and Rescue is very informative. The literature
suggests that vulnerability assessments are potentially useful for prioritising actions. In the context of
flood response in the UK, this comment from Fire and Rescue implies that this goal may conflict with the
need to offer an equitable service. Targeting certain social groups is instead considered a matter of
prevention; “we probably carry out most of our prevention work with people who you would {276} identify
as being vulnerable in one way or another” (ibid).This perspective suggests that vulnerability may be more
useful from a planning perspective as opposed to informing the operational phase of FIM where it is
informed by incoming 999 calls. Similarly, the IOW council reported that; “The compromise that we came
to was vulnerable is anyone who describes themselves as being vulnerable in response to a situation (680)
because they, the people who are affected by flooding in this case, will be able to know more than any
external label that we put on them.(IOW emergency planning).
From these discussions it can be concluded that the role of vulnerability assessment during the immediate
response phase is limited. Immediate response necessitates accessible and accurate information. While
responders indicated that an overview of an area’s social make-up can do no harm and agreed that it
could play a part in wide-scale flood events, ultimately it is the nature of the hazard which influences
priority setting. Where will it flood first? How bad will the flood be? Second to this, who are the
vulnerable people within these areas? Vulnerability is understood as the location of elderly care homes
and critical patients. Information is passed between organisations such as social services, NHS and PCTs,
and utility companies to locate these people and is not stored centrally by any one organisation due to
data protection (DPA, 2004). While some responders commented on the frustration associated with this
(e.g. Emergency Planning Hampshire), it was widely acknowledge that any database that sought to
centralise critical vulnerabilities (i.e. at the household scale), although a ‘dream tool’, could never function
in reality; indeed given the variable nature of vulnerability how could such a database ever be kept up to
date? Including vulnerability within operational response is a matter of pooling information from a
number of agencies (social services, PCT, utility companies). This is of course supplemented with the 999
calls where households have identified themselves as vulnerable and in need of assistance. During the
other phases of FIM the household scale is considered to be too refined to inform decision making, rather
it is the overview of an area that is required. For instance, demographic profiling is a crucial part of
targeting and tailoring community engagement and flood awareness campaigns, currently being trailed
within the EA’s internal project, FloodWise (EA, Hampshire); for which the proportion of elderly, low-
income families and families with young children are the leading indicators.
Responders were asked to rate a number of design suggestions for the tool, relating to the information
and presentation of the hazard, vulnerability and risk (Graph 3; Table 3).

20
0
2
4
6
8
10
12
1 2 3 4 5 6 7
Numberofresponderswhoratedthe
feature1to5
Question number (see corresponding Table 3)
Graph 3: Category One Responders feedback on design suggestions for the tool, based on a 1 to 5 rating scale of
usefulness in informing decision making (5 being very useful). This graph presents a count of responders rating each
feature 1 to 5.
Question Table 3: Professionals were asked to rate initial design suggestions (1 to 7)
1 Ability to select a number of flood scenarios (2yr, 10yr, 20yr, 30yr, 50yr and 100yr return period
flood events)
2 Ability to either run the full duration of the event (up to 720 minutes) (i.e. animation), or to
select a given time (snapshot)
3 Ability to zoom in or out of a given area of interest
4 Ability to obtain summary flood statistics at a point location (e.g. depth and velocity details at a
specific manhole, for a specific event and the range across all events)
5 The option to use an enquiry function, whereby the user can ask a specific question (e.g.
identify all areas flooded to depths greater than … within a …specified time… or specified
event/across all events).
6 The ability to view results within a 3D environment (based on terrestrial LiDAR scanning of the
area)
7 Ability to obtain summary statistics for social vulnerability i.e. at the street level
Any information on the hazard, from the extent of different scenarios, depth and velocity details and
ability to view these at given points in time, rate highly on a scale of usefulness; and could support
decisions regarding the allocation of resources (time, equipment), safety and continuity planning. The
hazard posed to the road network was also cited by the blue light services as crucial for flagging-up issues
of access and planning alternative routes. Visualisation is considered to be a powerful communication
tool; however 3D visualisation (question 6) was considered to be less important for decision making but a
potential tool for communicating with the public. What is also clear from these results is that users value
the ability to switch between spatial scales, from the broad overview down to the local picture to mirror
Rating 5: Highly useful
Rating 4
Rating 3: Neither useful nor not
useful
Rating 2
Rating 1: Not useful

21
the nature of a flood event which might occur very locally only, or may become a region-wide problem.
Responders also highly rated the ability to query vast quantities of data very quickly, supporting the rapid
pace of immediate response.
Question 7 asked responders whether it would be useful to view vulnerability at the local scale. Graph 3
illustrates the mixed response to this. Presenting data obtained at the household scale would be highly
impractical, not only in terms of the labour intensive nature of data collection but also in actually using
these data which could change very rapidly. Furthermore, there are issues surrounding data protection as
previously discussed. The semi-structured interviews queried responders about the use of indices, such as
the Social Flood Vulnerability Index (SFVI, Tapsell et al., 2002) and the value of plotting relative
vulnerability across a district, town etc. Responders commented that they would want to know how the
score had been constructed and be able to deconstruct it to view the individual indicators and their
contribution towards vulnerability.
“…this sort of information would be hugely useful but not in the response plan to the flood, but more in an
evacuation plan and a rest centre plan; in the fact that, as is best practice with the CCA and how we’re
meant to plan and respond rather than just chucking ourselves into it, fire fighting and responding…It
would allow us to target our efforts. At the moment we could target efforts if we had the resource to do
so, in the areas that we know are at flood risk, but within that there are areas that perhaps have more
vulnerabilities which would feed into that prioritisation about where you’re going to do first. {talking about
targeting parishes to write their own flood plans: IOW Emergency Planning)
The phase-relevance of vulnerability indicators was also noted. During response the primary concern is
risk to life, therefore indicators such as the elderly, illness and disability are paramount. Vulnerability is
also manifest after a flood event, effecting single parent households for example (EA, West Yorkshire).
This observation suggests that it is inappropriate to apply a universal vulnerability index, stretching across
the phases of a flood event; rather what is required is a flexible system of selecting and weighting
vulnerability indicators according to the context in which they will be applied.
Vulnerability indicators are already held within council databases, such as social services, housing register
etc. These indicators are not specifically flood related. Instead, there is a common view that vulnerability
is generic in nature across hazard events. For example, “our flood management is just part of our overall
crisis management. We do the same things for snow as we do for floods…”(Fire and Rescue, West
Yorkshire). The same indicators that are used to identify social vulnerability for heat waves, snow storms,
swine flu etc., are equally applied to the context of flooding.
The professionals reported that for them vulnerability assessment is a tool for planning response and
longer term mitigation strategies (e.g. tailoring awareness raising campaigns), as opposed to informing
the immediate response phase of FIM. In addition, there is a role for vulnerability assessment in planning
the recovery strategy of an area, in highlighting the nature of support that might be required from local
authorities (IOW Emergency Planning).
The perceived value of integrating vulnerability during response, varied across groups. For the ground
response teams, vulnerability data appeared secondary to the hazard; i.e. responders indicated a
preference towards where not who; with the exception of the ambulance service where this statement is
reversed. Conversely the emergency planning departments of the council display a keen interest in
vulnerability information.
“All we want to know is, where is it going to be wet? That’s all we want to know because that’s all we base
our response on…we can see you know that’s a residential street and we’ll assume there is 2.4 people in
every house and that gives us a rough estimate of we’re going to have to evacuate that many number of
people” (West Yorkshire Police)
“I think we would be very much focused on responding to water, on rescue and water management. The
actual people issues I don’t think would, I think we would work on the advice of other agencies, I don’t
think it is something that we would (716) in first instance be thinking off, we would be reliant upon other

22
agencies and they would be there anyway so why would we need additional information” (West Yorkshire
F&R)
“Obviously knowing information about vulnerability helps us a lot in terms of gearing-up what response
we need. So if we know that there’s an area affected that’s got a lot of people in care homes, that means
that we can save ourselves a whole lot of grief by before someone getting there and realising there’s a
problem, we can say well actually there’s a likelihood that a lot of people will need medical support in our
residential homes, we can make the call before we get there to make sure that we’ve got a building set up
with adequate facilities, people with professional knowledge, whether that’s from NHS, to make sure they
can go in there and care for them”. (IOW, emergency planning)
3.2.2 Some conclusions
There are some conclusions that may be made from this initial survey of the target professional group in
relation to their understanding and need for vulnerability assessment. It would seem we can summarise
the view that “there is a time and a place for vulnerability assessment”. It emerged as a consensus that
vulnerability can be more meaningfully used for prevention, planning, recovery and training but has a
limited role during the immediate response phase of a flood incident. Vulnerability is considered to be a
subjective and disputed concept, and ultimately from a response perspective, responders must prioritise
their efforts to where the hazard is and key vulnerable people. This latter information is provided through
data sharing (health services, utility companies and social scare databases) in accordance with the Data
Protection Act 2004. This information is supplemented by those who disclose themselves to be vulnerable
and actively seek assistance (i.e. 999 calls). The rapid pace of response decision making and the need for
accurate information (exact location, up-to-date details on vulnerability) means that the composite, area-
wide index approach for measuring vulnerability would not be used during a response situation. Instead,
responders felt that this type of information could perhaps be more usefully applied to support broad
scale assessments and for painting the social ‘make-up’ of the area. In this light, this form of social
vulnerability assessment could help inform the planning of response.
This tool was designed to facilitate a host of research questions, rather than as an application that could
roll-out in practise; although it is recognised that the feedback from professionals could help inform some
practical recommendations for the future assessment and presentation of hazard, vulnerability and risk
within FIM. ArcGIS was selected as the platform for designing and demonstrating the tool. It is
acknowledged that this software has a number of limitations which would prevent this tool functioning in
real-life situations. Aside from expensive licensing, the desktop application is not suitable for creating and
sharing a ‘common picture’ of the situation as required for multi-agency working and discussed with this
sample of professional stakeholders. The software is also unfamiliar to practitioners and would require
training. The platform for launching a tool of this nature would need to be something that is user-friendly,
not reliant of licensing and open to all potential users. An open source GIS via a secure website would
probably be the closest to meeting these requirements. This would appease the recurring comment that
any successful decision support tool should K.I.S.S.; Keep It Stupid Simple. This In vivo statement (i.e. in
the respondent’s own words) reflects the nature of the professional context, as responders discussed,
flooding is but one part of the day-job and therefore any supporting tool needs to be simple and self-
explanatory to use after potentially long time-gaps. Furthermore it needs to be user friendly and easily
‘fixable’ should it go wrong, without relying upon the tool’s developer.
The requirement for simplicity raises an interesting debate. Is simplicity a requisite of the tool itself, i.e.
synonymous to user-friendly? Or is the desire for simplicity reflective of a desire to disengage with the
complexities of flood science? This might be framed within two simplicity models: (1) simplistic-user-
friendly and (2) simplistic-information tool. The latter is arguably indicative of a greater tension involving
the translation of science to practitioners and the professional context. On the basis of these preliminary
interviews it seems that there is a cross-over between this dualistic meaning of simplicity: It is very
apparent amongst all responders that a simplistic-user-friendly tool is essential, whereas simplistic-
information received mixed views. This is discussed further in section 6 and 7.

23
Multi-agency working means that any system designed to calculate flood risk needs to be flexible to
multiple users, with different data requirements and different emphases on hazard and vulnerability. The
tool’s potential and limitations also need to be apparent. For instance, the IOW council commented that a
tool which seems to portray the ‘answer’ from a series of tick boxes is arguably less informative than a
tool which prompts new thinking.
“… I was concerned that if it would be something that is a bit more scripted, tick a box if (663) we did that,
tick a box of we did this, it would then funnel the mind into being a bit more closed and blinkered, rather
than opening up to the fullest extent of what one’s day job role is, to think outside of the box, because if
they’re thinking that they’ve got a handy tool that does all this for them and seems to be looking right and
giving them the right answers, it’s just too good to be true and they don’t need to think so therefore they
won’t. (IOW emergency planning)
The importance of being able to view the bigger picture was stressed in these interviews. Examples such
as 2007 flooding were used by some responders to demonstrate the complicated nature of decision
making when resources become stretched and priorities need to be set. Therefore, while this tool focuses
on the very local scale of the case study areas it is considered to be an example of a tool that could be
extended to include a number of local ‘hot spot’ flood locations, framed within the district. The
development of the tool, which is described in the following section, is heavily influenced by these views
expressed in the preliminary interviews.
4 A flood risk assessment tool
This section describes the features of the flood risk assessment tool that were developed in response to
the preliminary interviews discussed in the previous section. The tool was approached almost as an ‘eggs
all in one basket’ to see how different end-user react and rate different design features, to inform some
practical recommendations for how such a tool might be more specifically tailored in real-life applications.
The tool itself loads the datasets from a Personal Geodatabase constructed in ArcCatalogue. Rather than
simply allowing layers to be added and removed, this tool enables users to manipulate these layers to suit
their needs and perform calculations on the data to produce vulnerability and risk profiles from a number
of flood scenarios. This interactive nature seeks to engage the end-user to become actively involved in the
assessment process and map production. This moves away from the traditional paradigm of
communicating “what we know” and targeting an ‘information deficit’ model (Lane et al., 2010); to one
that recognises the end-user as an expert in their right and providing the means in which they can
integrate their informed subjectivities from the day-job, with the objectivity of the ‘scientific expert’ that
is inherently built within the tool.
The tool is written in Visual Basic for ESRI and designed with the ESRI application ArcMap where the tool is
launched. This is a commercial product for Geographic Information Systems (GIS). In the preliminary
interviews with professional stakeholders, many reported unfamiliarity with this system or felt that they
‘knew the basics’ but did not feel comfortable using ArcGIS. If this tool was to be used in practise, the
platform from which it is launched would need to be reconsidered. For the purpose of this research it was
considered appropriate but it was consciously decided to minimise the user’s
4
interaction with ArcMap as
far as possible. Therefore the tool uses a display window to illustrate what is going on the main screen; if
the user wishes to view the main screen as opposed to this ‘summary window’ then they need only drag
and slide the interface of the tool aside. Further options to zoom in and out on the main screen are
provided on the interface of the tool (Figure 4).
4
Category One Responders are the target user of this tool and the tool has been designed according to the feedback
from preliminary interviews; as such, the terms end-user (or user) and responder are used interchangeably in this
discussion.

24
Figure 4: Screenshot of the upload-page of the tool, with contents page and summary window on the right.
The tool is designed with three key interfaces (i.e. separate pages), isolating hazard and vulnerability and
allowing the user to bring these together in the calculation of risk. Each interface seeks to address a
number of minor research questions. This is summarised in Figure 5.
Ability to zoom in and out on the main screen Ability to clear all layers from the map
Summary window:
Updates as new layers
are added to ArcMap

25
Figure 5: The architecture of the tool
4.1 The Hazard Interface
The hazard interface centralises all the details pertaining to the flood hazard and aims to answer a
number of research questions. Firstly, do responders value a range of flood scenarios or will they always
plan to the worst case event? Secondly, rather than simply viewing the extent and relying on different
shades of blue to indicate various depths, of the flooding, as is standard practise, do responders value the
option to re-colour the flooding according to the hazard posed to life? Taking this another step forward, is
the option to essentially ‘clean’ the map image to the flooding created on the road network or to
properties only, useful? Fourthly, given the option to select from two hazard models (risk to life versus
depth-damages) which model would responders use (and for what purpose) if they were to view the
flooding at the property level? And finally, how informative is an animation and user-control in viewing
the flood inundation in a dynamic form? Figure 6 provides a screenshot of the hazard interface: Each
feature is numbered to facilitate the discussion hereon.

26
Figure 6: The Hazard Interface to the GIS-based flood risk assessment tool
[1] In the first instance, the user can select from a flood scenario and view the spatial extent of the flood
(based on the maximum flood value). Scenarios range from high frequency, low impact events to low
frequency, high impact events (i.e. 2 year to 50 year rainfall events respectively). Cowes offers pluvial
flood scenarios only, whereas Keighley has additional scenarios for fluvial flooding (100 year event),
including scenarios for overbanking or breaching the levee system; furthermore, Keighley stimulates
pluvial-fluvial interaction. Preliminary interviews with professionals indicated that the ability to upload
and view a range of flood scenarios was deemed useful and highly useful.
[2] The tool provides the user with the option to reload the flood scenario of their choice, but this time
viewing the model outputs for depth-velocity interaction (rather than merely depth offered in the
previous option). Expert-declared thresholds are provided adjacent to this, from which the user can either
select go and view the flooding when it is re-coloured according to risk to life thresholds; or the user can
decide whether to manipulate these thresholds and adjust the hazard classification according to their
choice. The expert-declared thresholds are automatically entered into the tool and are set to those based
on Risk to Life research (HR Wallingford et al., 2006).The Flood Risk to People methodology calculates
flood hazard ratings on the principles of equation 1.
Flood Hazard Rating = ((v + 0.5) * D) + DF Equation 1 (HR Wallingford et al., 2006)
Where: v = velocity (m/s), D = depth (m), DF = debris factor (0.5)
1
2
4
3

27
In the Cowes case study, this calculation has already been developed in the (h) scenario files and uses a
debris factor of 0.5; this is consistent across all scenarios and is not adjusted for depths surpassing 0.25 m
as the original Risk to People methodology suggests. The hazard matrix presented in this paper is
illustrated in the background page of this tool and describes the varying levels of danger at crucial hazard
thresholds (Table 4).
Table 4: Risk to life thresholds based on a combination of depth-velocity (Priest et al., 2008)
Depth X Velocity (m
2
/sec) Hazard Description
< 0.75
LOW
Caution
Shallow flood water or deep standing water
0.75 < 1.5
MODERATE
Dangerous to vulnerable groups
Deep or fast flowing water.
Fatalities concentrated in vulnerable groups or
the result of human behaviour.
1.5 < 2.5
HIGH
Dangerous to most people
Deep or fast flowing water.
Fatalities due mainly to exposure to the hazard.
2.5 > 7.0
EXTREME
Dangerous for all
Extreme danger from deep, fast flowing water.
Fatalities due to hazard exposure.
> 7.0
EXTREME
Dangerous for all
Extreme danger from deep, fast flowing water
and risk of building collapse.
[3] This third option enables the end-user to essentially ‘clean’ the map image and view the hazard posed
to the road network only. This is based on the significant depth-velocity thresholds outlined in Table 4.
The Safe access and exit section for the Flood Risk Assessment Guidance document for New
Developments (Defra, 2005) identifies a number of situations in which a vehicle should not be used. These
include i) when the presence of water results in engine malfunctioning; ii) point at which vehicle begins to
float; iii) point at which the vehicle becomes difficult to control. For a standard car floating may occur at
depths of 0.5 m (compared to up to 1 m for heavy duty emergency vehicles) in standing water. These
depth values decrease as velocity of water increases. A more detailed hazard matrix from which the risk to
life thresholds are based, is presented in Table 5. According to the Risk to People methodology, safe
access routes should be based on the interaction between depth and velocity in the white boxes only. The
increase in either depth or velocity results in an escalation of risk, the road hazard presented in this tool is
thus based on the depth-velocity matrix presented here.

28
Table 5: Depth-velocity matrix based on danger posed to people. Safe access routes identified d-v interaction within
the white boxes (Priest et al., 2008)
This model is essentially a risk-based model, as it considers both the hazard parameters and the
population characteristics (whether demographic or behaviour-related) which might heighten
susceptibility towards harm in its classification of risk. Nonetheless it is included within the hazard section
of the tool. The reason for this is that the vulnerability component of this model is generic and not based
on data from the area; the vulnerability pages introduce these data and encourage the end-user to
explore a number of indicators to explain the make-up of the population first, before uniting hazard and
vulnerability together in the risk page.
[4] The final feature of this page provides the user with the option to view whether a potential hazard
exists at the property level. Again, this option provides another means of cleansing the map, but it also
provides the user with the option to view two different hazard models. Firstly, the user can view the risk
to life model (HM1) as previously discussed. On the basis of the hazard rating calculated (equation 1) this
option will re-colour the properties according to whether there is a potential danger to life. Hazard model
2 (HM2) classifies the hazard according to depth information only. The thresholds in this instance are
based on depth-damage thresholds (Table 6 and Table 7). Each threshold is assigned a score on a 1 to 5,
according to the degree of hazard posed; this scoring system corresponds to the one used for vulnerability
assessment and was required for the final risk calculation.

29
Hazard Model 1: Risk to Life
thresholds, based on a hazard
factor (m3
s-1
)
Hazard
category
< = 0.01 1
0.02 <= 0.75 2
0.76< 1.5 3
1.5 < 2.5 4
< 2.5 5
The depth-based hazard model uses critical thresholds identified in the Multi-coloured Manual (MCM)
developed at the Flood Hazard Research Centre, Middlesex University (FHRC, 2010), for depth-damages
arising for the average residential property, based on 2010 prices and flood duration of less than 12 hours.
According to the MCM there are 15 categories of depth-damages; these were simply divided by 5 to
obtain hazard thresholds (Table 7). Although more detailed information is provided for types and classes
of property, this is not considered in this tool; however If this tool were to become a real life application it
is suggested that the EA’s property database could be used to inform a more detailed classification. The
rationale for applying a depth-damage based model relates to the nature of vulnerability, which is not
only exhibited during the actual event but manifests during the post-event, recovery phase also. Users
engaged in this phase of emergency management may wish to identify properties that are particularly
susceptible towards damage, may need to evacuate or seek support during the aftermath of a flood
event.
In addition to this option to select from two types of hazard model, the user can further decide whether
to base this hazard classification according to the minimum, maximum or average flood statistics
calculated in the flood model. A 20 m buffer from the central point of each property was used to ascertain
flood statistics (Figure 7). As such, the user can select whether they wish to view the minimum, maximum
or average hazard value or depth value; these values have all been pre-classified according to the hazard
threshold and assigned a score of 1 to 5, representing very low hazard to very high hazard respectively.
Hazard Model
2: Depth
thresholds (m)
Damage estimates; based on
total damages calculated for
the average residential
property (max damage per
threshold, £)
Hazard
category
<= 0.05 £8529.98 1
0.06 <= 0.3 £ 11,952.27 2
0.31 <= 1.2 £33,225.92 3
1.21 <= 2.1 £41,882.69 4
> 2.1 £51,438.33 5
Table 7: Hazard categories based on depth-damage estimates
for the average residential property (FHRC, 2010)
Table 6: Hazard categories based on Risk to Life
thresholds (Priest et al., 2008)

30
Figure 7: Applying a 20m buffer around each property to assign flood statistics (min, max and mean) to the property
[5] The final page for the hazard section (Figure 8) enables the user to select and view a flood scenario
from beginning-to-end; in the case of Cowes this runs from 1 to 120 minutes (with 1 minute time steps)
and for Keighley scenarios run from 1 to 720 minutes (at 6 minute time steps). The user can load a time
step individually (a), can view the full animation (b) or can use a time scrollbar to control the view (c).
Simultaneously, the user can overlay this animation onto key GIS base layers (e.g. location of property,
vulnerability, fluvial flood zones etc.).
Figure 8: Launching animation in the GIS-based flood risk assessment tool. The user can (a) load individual time-steps
in the scenario, (b) play the animation or (c) use a scroll bar to view a snapshot of the flood at a time of their
choosing.
A
A
5
(a)
(b)
(c)

31
4.2 The Vulnerability Interface
Vulnerability is similarly navigated through a series of pages, the main purpose of which is to explore the
end-users views on scale, dynamic indicator selection and the context in which such information might be
applicable. This section of the tool explores a series of questions. Firstly, to what extent do responders
desire only the ‘answer’ i.e. a vulnerability product such as the SFVI (Tapsell et al. 2002) or the Index of
Multiple Deprivation (IMD, 2007)? To what extent can isolated indicators help support decision making?
How do responders regard the usefulness of being able to select, weight and construct their own index of
vulnerability? And finally, at what scale should vulnerability be assessed, and indeed, what activities
within FIM do responders feel vulnerability could support.
The Social Flood Vulnerability Index is employed in the tool to represent a ‘vulnerability product’; that is
to say it has been packaged together by expert academics. The disadvantage of such a product is that it is
based on assumptions that may not be apparent to end users. Perhaps the strongest critique for the SFVI
is the treatment of vulnerability indicators as equal partners in governing risk. The SFVI represents an
aggregated index for social vulnerability, based on an additive model of four variables (Table 8). The
Townsend Index is handled separately in this approach, with its individual components summed
separately and then multiplied by 0.25 before inclusion into the overall SFVI. All variables are firstly
equated as percentages and then transformed (Table 9): Results are then standardised as z-values before
summation. Final scores are classified into five bands; with 1 to 5 representing low to high social
vulnerability respectively. This method was utilised by the UK Environment Agency as a means of
highlighting socially vulnerable areas more sensitive to the adverse impacts generated from flood events,
but has since been replaced by the Index of Multiple Deprivation (discussed below).
Table 8: The Social Flood Vulnerability Index (after Tapsell et al., 2002); with data sources for this research
Variable Measure
Townsend Index for
Deprivation
Including;
Unemployment
Overcrowding
Non-car ownership
Non-home ownership
Unemployed residents 16yrs and over, as a percentage of all economically
active residents
Households with more than one person per room, as a percentage of all
households.
Households with no car as a percentage of all households.
Households not owning their own home as a percentage of all households
75 years + Residents aged 75years and over as a percentage of all residents
Lone parent households Lone parents as a percentage of all residents
Long-term illness
Residents suffering from a limiting long-term illness, as a percentage of all
residents

32
Table 9: Transformation methods selected to reduce skewness and kurtosis in the distribution (Tapsell et al., 2002)
Indicator Transformation method
Lone parents Log natural (x + 1)
Aged 75 + Log natural (x + 1)
Long-term sick Square root
Non-homeowners Square root
Unemployed Log natural (x + 1)
Non-car owners Square root
Overcrowding Square root
Figure 9 presents a snap-shot of the vulnerability interface developed within this research.
Figure 9: The Vulnerability Interface to the GIS-based flood risk assessment tool
[6] The first feature of the vulnerability interface enables users to view the SFVI for the Bradford district or
Island-wide, or focus the SFVI to the census Output Areas (OA) or properties of Stockbridge or Cowes only.
It is noteworthy that although the SFVI can be illustrated at the property level, the score remains based on
the OA (i.e. properties are merely assigned the score of the OA in which they are located); the scaling
challenge for vulnerability assessments is discussed further in section 7. By enabling the user to switch
between the local to district-wide view, this feature targets the preliminary feedback from professionals.
Furthermore, the SFVI scoring system can be adjusted by the end-user to reflect the relative vulnerability
according to different geographical scales. This adjusts the standardisation technique within the original
6

A GIS-Based Flood Risk Assessment Tool for Emergency Planning

A GIS-Based Flood Risk Assessment Tool for Emergency Planning

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