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The Exposure of
Port Cities to Flooding:A Comparative Global Analysis
Robert J. NichollsSchool of Civil Engineering and the Environment
and Tyndall Centre for Climate Change
University of Southampton UK
Email: [email protected]
PLAN
• Goal
• Methods
• Results/Discussion
• Conclusions
Goal
• Port cities are the nexus between growing population and trade, and a focus for impacts and adaptation needs under changing climate.
• A global assessment1 of present (2005) and future (2070s) exposure to coastal floods2 in large port cities3 due to the full range of drivers:– demographic trends;
– economic growth and development;
– human-induced subsidence (a local component of sea level);
– climate-induced sea-level rise (a global component of sea level);
– changing storms (influencing extreme sea levels).
1. Funded by the OECD, Paris
2. To the 1 in 100 year event
3. Over 1 million population in 2005
Scenarios (for the 2070s)Considers high-end scenarios
• Population and economic growth– Single scenario from the OECD ENV-Linkages model
– Assets linked to population and GDP/capita by a constant multiplier (5)
• Global sea-level rise– From Rahmstorf (2007) assumed 0.5 m rise – bigger than IPCC
(2007)
• More intense storms and higher storm surges– Increased intensity of 100-year storms consistent with IPCC
(2007)
• Potential human-induced subsidence– Assumed average subsidence of 0.5 m across the 100 year
flood plain in all susceptible cities (during 20th Century subsidence was locally up to 5 m in Tokyo!)
Methodology(elevation from the SRTM global data)
UN City database
Port databases
Port city locations>1 million population in 2005
136 locations
Key global results for the flood plain
• 40 million people
• 0.6% of global population
• (10% of port city population)
• US $3000 billion of assets
• 5% of global GDP
Exposure by Continentin 2005
0
5,000
10,000
15,000
20,000
25,000
30,000
AFR
ICA
ASIA
AUSTR
ALA
SIA
EURO
PE
N. A
MERIC
A
S. A
MERIC
A
Exp
osed
po
pu
lati
on
(000s)
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
1,400,000
1,600,000
AFR
ICA
ASIA
AUSTR
ALA
SIA
EURO
PE
N. A
MERIC
A
S. A
MERIC
A
Exp
osed
assests
(U
S$m
n)
(a) Population
(b) Assets
Global Population Exposureinfluence of different change factors from 2005 to 2070s
0
20,000
40,000
60,000
80,000
100,000
120,000
140,000
160,000
Current Situation/Baseline with storm enhancement
factor only
with sea-level rise only with human induced
subsidence only
All Factors
Factors
Ex
po
se
d p
op
ula
tio
n (
00
0)
Current population
Projected population
0
5,000,000
10,000,000
15,000,000
20,000,000
25,000,000
30,000,000
35,000,000
40,000,000
Current Situation/Baseline with storm enhancement
factor only
with sea-level rise only with human induced
subsidence only
All Factors
Exp
osed
assets
(U
S$ m
il)
Current GDP (PPP)
Projected GDP (PPP)
Global Asset Exposureinfluence of different change factors from 2005 to 2070s
-
5,000
10,000
15,000
20,000
25,000
30,000
35,000
CHIN
A
INDIA
BAN
GLA
DES
H
VIE
TNAM
UNIT
ED S
TATE
S
JAPA
N
THAIL
AND
MYA
NMAR
EGYP
T
NIG
ERIA
INDONES
IA
CÔTE
D'IVOIR
E
NET
HER
LANDS
BRAZ
IL
ECUADOR
Po
pu
lati
on
exp
osed
(0
00
)
Climate change & subsidence
Socio-economic change
Today
Population exposedTop 15 countries in the 2070s
Exposed population (2005)
Top 20
Exposed population (2070s)
Top 20
Exposed assets (2005)
Top 20
Exposed assets (2070s)
Top 20
What about protection?
North Sea Flood Defences
(post-1953)
Inferred protection standard versus
GDP classes
Countries and cities with low incomein 2005
Country Agglomeration
Per capita GDP (PPP)
GDP Class
Exposed Population (000s) (Scenario C)
INDIA Chennai 3,316 LOW 1
Kochi 3,316 LOW 255
Kolkata 3,316 LOW 844
Mumbai 3,316 LOW 441
Surat 3,316 LOW 11
Visakhapatnam 3,316 LOW 519
ANGOLA Luanda 2,829 LOW 22
VIETNAM Hai Phòng 2,782 LOW 14
Ho Chi Minh City 2,782 LOW 41
GHANA Accra 2,601 LOW 1
PAKISTAN Karachi 2,549 LOW 159
CAMEROON Douala 2,284 LOW 94
BANGLADESH Chittagong 1,998 LOW 1,929
Dhaka 1,998 LOW 2,787
Khulna 1,998 LOW 418
GUINEA Conakry 1,986 LOW 25
SENEGAL Dakar 1,914 LOW 61
DEM Republic of Korea N'ampo 1,800 LOW 510
HAITI Port-au-Prince 1,688 LOW 357
TOGO Lomé 1,600 LOW 49
CÔTE D'IVOIRE Abidjan 1,493 LOW 18
MYANMAR Rangoon 1,417 LOW 9
MOZAMBIQUE Maputo 1,335 LOW 119
NIGERIA Lagos 1,188 LOW 36
UNITED REPUBLIC OF TANZANIA Dar-es-Salaam 720 LOW
794
SOMALIA Muqdisho_(Mogadishu) 600 LOW 1,931
Relative population increase
Top 20 2005 to 2070sCities were selected from the Top 50 cities with the highest exposure in 2005
0% 200% 400% 600% 800% 1000% 1200%
Dhaka
Chittagong
Ningbo
Rangoon
Lagos
Khulna
Kolkata (Calcutta)
Lomé
Abidjan
Hai Phòng
Krung_Thep_(Bangkok)
Surat
Ho Chi Minh City
Chennai (Madras)
Palembang
Jakarta
Mumbai (Bombay)
Fuzhou_Fujian
Tianjin
Xiamen
Conclusions
• Flood risk and management is a dynamic problem requiring proactive assessment
• Flooding in port cities is more than a single city problem
• While all port cities are threatened, risks are concentrated in a few cities
• Promoting shared city experience on moving to proactive responses to changing flood risk would be useful
• Further global assessments are in progress:– Looking at a wider range of scenarios/timescales
– Considering adaptation responses.
• Case studies are also in progress (e.g., Mumbai)
Acknowledgements
• Authors: Nicholls, R.J.1, Hanson, S. 1, Herweijer, C.2, Patmore, N. 2, Hallegatte, S.3, Corfee-Morlot, J.4, Chateau, J.4, and Muir-Wood, R. 2
– 1. School of Civil Engineering and the Environment and Tyndall Centre for Climate Change Research, University of Southampton, Southampton SO17 1BJ UK
– 2. Risk Management Solutions Limited, London, EC3R 8NB UK
– 3. Centre International de Recherche sur l’Environnement et le Développement et Ecole Nationale de la Météorologie, Météo-France, Paris, France
– 4. Organisation for Economic Co-operation and Development, Paris, France
• Funded by OECD (Project Officer: Jan Corfee-Morlot)
The Exposure of
Port Cities to Flooding:A Comparative Global Analysis
Robert J. NichollsSchool of Civil Engineering and the Environment
and Tyndall Centre for Climate Change
University of Southampton UK
Email: [email protected]
