Climate and change: simulating flooding impacts on

Centre for Earth Systems Engineering Research


Climate and change: simulating flooding impacts on urban transport network MARIA PREGNOLATO Richard Dawson, Alistair Ford European Geosciences Union EGU General Assembly 2015 Wien | Austria| 12-17 April 2015 [email protected]

School of Civil Engineering and Geosciences, Newcastle University, UK


Bring-here question How addressing and assessing the flooding impact for urban transport network?

INTRODUCTION 2/18

source: theguardian.com

Background Centre for Earth Systems Engineering Research

CITIES UNDER PRESSURE PERCENTAGE URBAN

• Socio-economic change

1950

2007

2030

– Population increase (new demand)

• Urbanisation – Complexity increase (technology, interdependencies, interconnections)

World

Africa

Asia

Europe

Latin America

North America

Projection of urbanized population by 2030. source: United Nations, World Urbanization Prospects: The 2005 Revision (2006)

• Environmental issues – Climate changes (unusual weather patterns, increase frequency and intensity of hazards, extreme events)

• Infrastructure networks INTRODUCTION 4/18

– Persistence of the performance

Change in precipitation by end of 21st century. source: NOAA Geophysical Fluid Dynamics Laboratory

Research aim Centre for Earth Systems Engineering Research

IMPROVING URBAN RESILIENCE

• Climate impacts and urban environment interaction analysis • Risks of flooding assessment

• Urban spatial configuration and resilience relationship

A “non-resilient” solution. source: https://agenda.weforum.org

• Decision support tool for adaptation of urban areas AIM 4/18

Barcelona designed as a “smart city”. source: http://blog.panasonic.es

Methodology Centre for Earth Systems Engineering Research

RISK ASSESSMENT FRAMEWORK CONTEXT Climate change

HAZARD

UKCP09 Projections Flooding (intensity, frequency) Downscaling (Weather Generator)

Urban complexity

Uncertainties

JTW Observation Speed and capacity People flows

Literature Experimental data Expert judgment

Network travel model

Flood safety function

O-D matrix (ArcGIS)

Flood water vs safety speed

EXPOSURE MAP

VULNERABILITY

EXPOSURE MAP Transport Flood modelnetwork (CityCat)

VULNERABILITY HAZARD MAPS Vulnerability curve

Risk as combination of hazard, vulnerability and exposure. source: IPCC (2012), SREX Report

RISK ASSESSMENT METHOD 5/18

disruptions assessment (in to terms ofClimate commuting route delays) IPCC (2012). Impact “Managingand the Risks of Extreme Events and Disasters Advance Change Adaptation”. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge, United Kingdom Economic damage [£] and New York, NY, USA.

Hazard Centre for Earth Systems Engineering Research

FLOODWATER DEPTH [m]

Urban Weather Generator (UWG) • hourly time series of rainfall variables • 5 km grid • consistent with UKCP09 projections

Variation of rainfall Intensity, duration and return period for rainfall.

City Catchment Analysis Tool (CityCAT)

source: Morita (2014).

• time series of hazard maps • floodwater depth and velocity • realistic simulation

METHOD 6/18

Morita, M. (2014). “Flood Risk Impact Factor for Comparatively Evaluating the Main Causes that Contribute to Flood Risk in Urban Drainage Areas“. Water 2014, 6(2), 253-270

Example of output from CityCAT flood model.

Hazard Centre for Earth Systems Engineering Research

FLOODWATER DEPTH [m]

Different scenarios, for return period and intensity • SCENARIO A: T = 10 ys, r = 60’

• SCENARIO B: T = 200 ys, r = 60’

METHOD 7/18

T = Return Period R = Rainfall Duration

Exposure Centre for Earth Systems Engineering Research

MODEL OF NETWORK TRIPS

2001 UK CENSUS DATA • Journey-To-Work (JTW) observation (commuting)

ROAD INFORMATION • Ordnance Survey ITN MasterMap

• Free flow speed, road type, capacity

Commuter journey from origins to the central destination ward..

NETWORK TRAVEL MODEL (ArcGIS) • O-D matrix • Shortest time between origin-destination wards METHOD 8/18

The network system adopted in the whole area.

Vulnerability Centre for Earth Systems Engineering Research

VULNERABILITY CURVE

FLOOD SAFETY FUNCTION Flood water depth vs safety speed Data source • Safety Literature • Experimental report and data

• Expert Judgement Uncertainties • Driving characteristic • Driving behaviour • Type of road and car METHOD 9/18

The function that relates floodwater depth and driving speed.

Impact Centre for Earth Systems Engineering Research

FLOODING IMPACT ON NETWORK ASSESSMENT

Hazard footprints and network spatially overlapped

1. Free flood speed adjustment (according to the curve) 2. Flow redistribution, routes recalculation

Newcastle flooding in 2012. source: www.thejournal.co.uk

3. Comparison between pre-event and post-event travel time

4. Journey delays (minutes)

METHOD 11/18

5. Economic cost by assigning a monetary value to the delay

Another photo of 2012 Newcastle flooding. source: http://www.pqube.co.uk

Example BASELINE


O

Origin

D

Destination

Baseline

BASELINE Km = 9

O

D

Example SCENARIO A (T = 10 ys, r = 60’)


O

Origin

D

Destination

Baseline Route A Impacted network

BASELINE Km = 9

Route A Km = 11.5 Delay = 17’

O

D

METHOD 12/18

Example SCENARIO B (T = 200 ys, r = 60’)


O

Origin

D

Destination

Baseline Route A Route B Impacted network

BASELINE Km = 9

Route A Km = 11.5 Delay = 17’

O

D

METHOD 13/18

Route B Km = 13 Delay = 27’

Results NEWCASTLE CASE STUDY


• Flooding impact on traffic flows and network performance • Need of urban adaptation measures • Different scenarios need different solutions

25 min.

25 min.

25 min.

RESULTS 14/18

Further research ADAPTATION COST-BENEFITS


Next steps • Complete range of scenario simulations • Testing a portfolio of adaptation options – soft measures (e.g.: SUDs) – hard measures (e.g.: node strengthening)

• Cost-benefit analysis of adaptation options The “Big U” project for a more resilient New York.

Possible developments

source: www.thisbigcity.net

• Other infrastructure type • Other type of hazard

• Interdependencies and interconnections • Second case study (London) A future imaginary flooded London. FUTURE WORK 15/18

source: www.wired.co.uk

Further research ADAPTATION COST-BENEFITS


CONTEXT Climate change UKCP09 Projections (intensity, frequency) Downscaling (Weather Generator)

GREEN ADAPTATION Flood model e.g.: SUDs (CityCat)

BASELINE COST HAZARD MAPS ADAPTATION COST FUTURE WORK 16/18

Urban complexity

Uncertainties

JTW Observation Speed and capacity People flows

Literature Experimental data Expert judgment

GREY ADAPTATION Network travel model

SOFT Flood safety function

e.g.: critical nodes O-D matrix hardening (ArcGIS)

ADAPTATION Flood water vs safety e.g.: work from home speed

Damage cost of hazard impact WITHOUT ADAPTATION

EXPOSURE MAP

Damage cost WITH ADAPTATION

Adaptation intervention cost

VULNERABILITY Co-benefits from adaptation

+ RISK ASSESSMENT Impact and disruptions assessment (in terms of commuting route delays) BASELINE COST COST-BENEFIT - [£] ADAPTATION COST Economic damage

Take-home notes Centre for Earth Systems Engineering Research

• FRAMEWORK | Impacts of extreme weather events on urban transport infrastructure • METHODOLOGY | Combining climate simulations with spatial representations of networks

• AIM | Measuring flooding disruptions to commuting journeys on road transport networks • NEXT STEPS| Analysis of wide-ranging adaptation strategies and scenarios • POTENTIAL DEVELOPMENT| Multi-hazard and multiinfrastructure model for future scenarios analysis FUTURE WORK 17/18



Questions/suggestions?

Thank you [email protected] Maria Pregnolato MariaPregnolat1

https://www.students.ncl.ac.uk/m.pregnolato/index.html http://www.ncl.ac.uk/ceser/ The research is supported by