Modelling Spatiotemporal Dynamics of Floods ...

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Modelling Spatiotemporal Dynamics of Floods, Population Movement and Road Travel ... having a large effect on the level of disruption. ... Somerset Levels, UK.
Modelling Spatiotemporal Dynamics of Floods, Population Movement and Road Travel for Enhanced Risk Assessment Kate Rawlings Email: [email protected] Twitter: @geogkate 1. Project Background

2. Research Objectives

Risk is often described as a function of hazard, exposure and vulnerability. In reality, risk varies over space (S) and time (T) and this affects the severity of impacts on surrounding populations.

For example, although most studies use census data when assessing exposure to hazards, this does not capture daily and seasonal population movement, which substantially changes the number of people exposed to a hazard at any given time.

Event 2

Event 3

Event 4

1 in 100-year flood extent

1 in 100-year flood extent 1 in 100-year flood extent

x

x

x

Night-time population, Road network

Road access

x

Summer Daytime x population, Road network Winter Daytime x population, Road network

Night-time population e.g children, elderly,

(Research Objective 3)

Evaluation of Case Study Results (Research Objective 3)

Hours

Road access Summer population 1500 people = e.g. tourists, 300 Vulnerable Road access 600 people Winter population, = 100 Vulnerable Road access

Daily Travel

Infrastructure Updates

Daily Activity (Children and workers)

Months

Years

Decades

6. Case Study Locations

c) Vulnerability c) Vulnerability

Seasonal Tourists

Hours

10km 10m

(immobile population) Minutes

Days

Months

Emergency service callout

Years

Decades

Temporal Change

Critical Road Network

Demographic changes (e.g. increase in elderly population)

Children’s travel

100m

Topography

Demographic Shifts and Migration

1km

(Covered in average daily travel)

Daily Activity

Days

Examine how the case study findings apply to other local authorities and flood risk areas

Macro-economic Policy

Spatial Change

10km

Spatial Change

Expansion of Urban Area

Road Network

1km

Large Flood Protection Schemes

Temporal Change

500 people = 70 Vulnerable

100km

100km

100km 10km 1km

Minutes

Expansion of Urban Area

Flood Defences

Secondary Hazards

(Research Objective 3)

Travel Model and Transport Analysis

Macro-economic Policy

100m

Daytime population e.g children, elderly, x = 750 people students, 100 Vulnerable

100m

Risk

b) Exposure b) Exposure

Climate Change

Flood Event Characteristics (depth, velocity, extent)

Flood Modelling

(Research Objective 4)

10m

x

Daytime population, Road network

=

10m

Event 1

1 in 100-year flood extent

Vulnerability

(Research Objective 2)

4.To assess the implications of scenario findings for all local authorities who have to respond to flood events.

a) Hazard

Spatial Change

Table 1: Examples of changing risk for a 1 in 100 year flood. Risk here refers to the number of people at risk from the flood event, if it happened at that point in time. x

(Research Objective 1)

5. Defining the Spatial and Temporal Scales of the Project

Table 1 illustrates how the time of flood onset interacts with daily and seasonal changes in the population to produce different risk outcomes, as described in the project background.

Exposure

Road Network Vulnerability Analyses

3. To evaluate how the consequences of a flood event differ between groups of people and at different times of day/year.

Therefore the aim of this project is to analyse the interactions between the time of flood onset and daily/seasonal population movements, to see how the impact on road travel and service accessibility varies, particularly for vulnerable groups.

x

Spatiotemporal Population Modelling

2. To explore how critical road links can be defined through network vulnerability and accessibility methods.

A major issue during UK floods is road network disruption. Whilst the spatial dimension is well studied, the temporal aspects of risk have not been applied as frequently to flood risk assessments for roads, despite the time of flood onset having a large effect on the level of disruption.

4. Hypothetical Example

3. Proposed Methodology

1. To model how the location of the general population, and those who are most vulnerable in flood events, changes at a daily and seasonal scale.

Risk = f(HazardST,ExposureST,VulnerabilityST)

Hazard

Supervisors: Dr Jim Wright, Dr Alan Smith, Dr Sally Brown

Seasonal Tourists

Somerset Levels, UK. Susceptible to long duration floods which cause wide-ranging travel issues, a good case study of rural isolation. Photo: Langport, Somerset (2014). Harvey Hook/Hotspot Media/Daily Mail)

Perception of Risk

Immobile Population Minutes

Hours

Days

Months

Years

Decades

Temporal Change

Figure 1: Plots showing the spatial and temporal characteristics of a) Hazard, b) Exposure and C) Vulnerability in this research project. The dotted box demonstrate the factors considered within the temporal and spatial scales of this project. Connected circles indicate a link between factors. Blue: Environmental Factors and Processes Green: Man Made Structures Yellow/Orange: People Pink: Policy

York, UK. Frequent flooding disrupts the transport network. It is a good case study of a disrupted urban network and reduction in access to services. Photo: York (2015) AFP/Getty Images/Daily Mail)