The Exposure of Port Cities to Flooding: A Comparative Global Analysis

The Exposure of Port Cities to Flooding: A Comparative Global Analysis Robert J. Nicholls School of Civil Engineering and the Environment and Tyndall Centre for Climate Change University of Southampton UK Email: r.j.nicholls@soton.ac.uk

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 assessment 1 of present (2005) and future (2070s) exposure to coastal floods 2 in large port cities 3 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 20 th Century subsidence was locally up to 5 m in Tokyo!)

UN City database Port databases Methodology (elevation from the SRTM global data)

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

Exposed assests (US$mn) Exposed population (000s) Exposure by Continent in 2005 30,000 25,000 20,000 15,000 (b) Assets 10,000 5,000 0 AFRICA ASIA AUSTRALASIA EUROPE N. AMERICA S. AMERICA 1,600,000 1,400,000 1,200,000 (a) Population 1,000,000 800,000 600,000 400,000 200,000 0 AFRICA ASIA AUSTRALASIA EUROPE N. AMERICA S. AMERICA

Exposed population (000) Global Population Exposure influence of different change factors from 2005 to 2070s 160,000 140,000 Current population Projected population 120,000 100,000 80,000 60,000 40,000 20,000 0 Current Situation/Baseline with storm enhancement factor only with sea-level rise only with human induced subsidence only All Factors Factors

Exposed assets (US$ mil) Global Asset Exposure influence of different change factors from 2005 to 2070s 40,000,000 35,000,000 Current GDP (PPP) Projected GDP (PPP) 30,000,000 25,000,000 20,000,000 15,000,000 10,000,000 5,000,000 0 Current Situation/Baseline with storm enhancement factor only with sea-level rise only with human induced subsidence only All Factors

Population exposed (000) Population exposed Top 15 countries in the 2070s 35,000 30,000 Climate change & subsidence Socio-economic change Today 25,000 20,000 15,000 10,000 5,000 - CHINA INDIA BANGLADESH VIETNAM UNITED STATES JAPAN THAILAND MYANMAR EGYPT NIGERIA INDONESIA CÔTE D'IVOIRE NETHERLANDS BRAZIL ECUADOR

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 income in 2005 Per capita Country Agglomeration GDP (PPP) GDP Class INDIA Chennai 3,316 LOW Kochi 3,316 LOW Kolkata 3,316 LOW Mumbai 3,316 LOW Surat 3,316 LOW Visakhapatnam 3,316 LOW ANGOLA Luanda 2,829 LOW VIETNAM Hai Phòng 2,782 LOW Ho Chi Minh City 2,782 LOW GHANA Accra 2,601 LOW PAKISTAN Karachi 2,549 LOW CAMEROON Douala 2,284 LOW BANGLADESH Chittagong 1,998 LOW Dhaka 1,998 LOW Khulna 1,998 LOW GUINEA Conakry 1,986 LOW SENEGAL Dakar 1,914 LOW DEM Republic of Korea N'ampo 1,800 LOW HAITI Port-au-Prince 1,688 LOW TOGO Lomé 1,600 LOW CÔTE D'IVOIRE Abidjan 1,493 LOW MYANMAR Rangoon 1,417 LOW MOZAMBIQUE Maputo 1,335 LOW NIGERIA Lagos 1,188 LOW UNITED REPUBLIC OF TANZANIA Dar-es-Salaam 720 LOW SOMALIA Muqdisho_(Mogadishu) 600 LOW Exposed Population (000s) (Scenario C) 1 255 844 441 11 519 22 14 41 1 159 94 1,929 2,787 418 25 61 510 357 49 18 9 119 36 794 1,931

Relative population increase Top 20 2005 to 2070s Cities were selected from the Top 50 cities with the highest exposure in 2005 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 0% 200% 400% 600% 800% 1000% 1200%

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)