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Flood Risks, Climate Change Impacts and Adaptation Benefits in Mumbai: An Initial Assessment of Socio-Economic Consequences of Present and Climate Change Induced Flood Risks and of Possible Adaptation Options

Author

Listed:
  • Stéphane Hallegatte

    (Centre International de Recherche sur l'Environnement et le Développement)

  • Nicola Ranger

    (Grantham Research Institute for Climate Change)

  • Sumana Bhattacharya

    (NATCOM PMC, MoEF)

  • Murthy Bachu

    (RMS)

  • Satya Priya

    (RMS)

  • K. Dhore

    (RMS)

  • Farhat Rafique

    (RMS)

  • P. Mathur

    (RMS)

  • Nicolas Naville

    (Centre International de Recherche sur l'Environnement et le Développement)

  • Fanny Henriet

    (Centre International de Recherche sur l'Environnement et le Développement)

  • Anand Patwardhan

    (Indian Institute of Technology)

  • K. Narayanan

    (Indian Institute of Technology)

  • Subimal Ghosh

    (Indian Institute of Technology)

  • Subhankar Karmakar

    (Indian Institute of Technology)

  • Unmesh Patnaik

    (Indian Institute of Technology)

  • Abhijat Abhayankar

    (Indian Institute of Technology)

  • Sanjib Pohit

    (National Council of Applied Economic Research)

  • Jan Corfee-Morlot

    (OECD)

  • Celine Herweijer

    (Risk Managment Solutions Limited)

Abstract

Managing risks from extreme events will be a crucial component of climate change adaptation. In this study, we demonstrate an approach to assess future risks and quantify the benefits of adaptation options at a city-scale, with application to flood risk in Mumbai. In 2005, Mumbai experienced unprecedented flooding, causing direct economic damages estimated at almost two billion USD and 500 fatalities. Our findings suggest that by the 2080s, in a SRES A2 scenario, an ‘upper bound’ climate scenario could see the likelihood of a 2005-like event more than double. We estimate that total losses (direct plus indirect) associated with a 1-in-100 year event could triple compared with current situation (to $690 – $1890 million USD), due to climate change alone. Continued rapid urbanisation could further increase the risk level. Moreover, a survey on the consequences of the 2005 floods on the marginalized population reveals the special vulnerability of the poorest, which is not apparent when looking only through a window of quantitative analysis and aggregate figures. For instance, the survey suggests that total losses to the marginalized population from the 2005 floods could lie around $250 million, which represents a limited share of total losses but a large shock for poor households. The analysis also demonstrates that adaptation could significantly reduce future losses; for example, estimates suggest that by improving the drainage system in Mumbai, losses associated with a 1-in-100 year flood event today could be reduced by as much as 70%. We show that assessing the indirect costs of extreme events is an important component of an adaptation assessment, both in ensuring the analysis captures the full economic benefits of adaptation and also identifying options that can help to manage indirect risks of disasters. For example, we show that by extending insurance to 100% penetration, the indirect effects of flooding could be almost halved. As shown by the survey, the marginalized population has little access to financial support in disaster aftermaths, and targeting this population could make the benefits of such measures even larger. While this study explores only the upper-bound climate scenario and is insufficient to design an adaptation strategy, it does demonstrate the value of risk-assessment as an important quantitative tool in developing city-scale adaptation strategies. We conclude with a discussion of sources of uncertainty, and of risk-based tools that could be linked with decision-making approaches to inform adaptation plans that are robust to climate change. hangement climatique. Dans cette étude, nous décrivons une méthode permettant d’évaluer les risques futurs et de quantifier les avantages de solutions d’adaptation à l’échelle urbaine, puis nous l’appliquons à l’estimation des risques d’inondation à Mumbai (Bombay). En 2005, une inondation sans précédent frappait la ville de Mumbai, faisant 500 victimes et occasionnant des dommages économiques directs estimés à près de deux milliards de dollars. Nos résultats suggèrent que, d’ici les années 2080, en appliquant le scénario SRES A2 et en sélectionnant un scénario climatique dans le haut de la fourchette, la probabilité d’un événement tel que celui de 2005 pourrait plus que doubler. Selon nos estimations, les pertes totales (directes et indirectes) causées par une catastrophe centennale pourraient tripler par rapport à leur niveau actuel (pour atteindre 690 à 1890 millions de dollars), du seul fait du changement climatique. L’urbanisation rapide et continue pourrait accroître d’autant plus le niveau de risque. D’autre part, l’étude que nous avons faite des conséquences des inondations de 2005 sur les populations marginalisées met en lumière la vulnérabilité particulière des plus démunis, qui n’est pas apparente lorsqu’on se limite aux analyses quantitatives et aux chiffres globaux. Par exemple, selon notre étude, le total des pertes subies lors des inondations de 2005 par les personnes marginalisées avoisinerait 250 millions de dollars, une faible part du total des dommages, mais un désastre considérable pour les foyers pauvres. Notre analyse montre également que l’adaptation pourrait substantiellement réduire les dommages futurs : nous estimons ainsi que les dommages causés par une inondation centennale pourraient être réduits de 70 % si l’on améliore le réseau d’assainissement de Mumbai. Quand on procède à une évaluation de l’adaptation, il importe d’estimer les coûts indirects des événements extrêmes car on peut ainsi à la fois intégrer à l’analyse l’ensemble des avantages économiques de l’adaptation et identifier des options de gestion des risques indirects liés aux catastrophes. Par exemple, nous montrons que si 100 % des habitants étaient en mesure de souscrire une assurance, les effets indirects des inondations pourraient être réduits de près de la moitié. Comme l’indique notre étude, la population marginalisée a peu accès aux aides financières après les catastrophes : les avantages de telles mesures pourraient donc être encore plus élevés si cette population était ciblée en priorité. Notre étude se limite à un scénario climatique dans le haut de la fourchette et ne suffit pas à élaborer une stratégie d’adaptation à part entière. Néanmoins, elle démontre la valeur des évaluations des risques, outils de mesure importants quand il s’agit de concevoir des stratégies d’adaptation à l’échelle urbaine. Nous concluons par un examen des sources d’incertitude ainsi que des outils fondés sur les risques qui, associés à des processus décisionnels, permettraient de formuler des plans d’adaptation durable au changement climatique.

Suggested Citation

  • Stéphane Hallegatte & Nicola Ranger & Sumana Bhattacharya & Murthy Bachu & Satya Priya & K. Dhore & Farhat Rafique & P. Mathur & Nicolas Naville & Fanny Henriet & Anand Patwardhan & K. Narayanan & Sub, 2010. "Flood Risks, Climate Change Impacts and Adaptation Benefits in Mumbai: An Initial Assessment of Socio-Economic Consequences of Present and Climate Change Induced Flood Risks and of Possible Adaptation," OECD Environment Working Papers 27, OECD Publishing.
  • Handle: RePEc:oec:envaaa:27-en
    DOI: 10.1787/5km4hv6wb434-en
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    Cited by:

    1. Matthew Ranson & Lisa Tarquinio & Audrey Lew, 2016. "Modeling the Impact of Climate Change on Extreme Weather Losses," NCEE Working Paper Series 201602, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised May 2016.
    2. De Silva, M.M.G.T. & Kawasaki, Akiyuki, 2018. "Socioeconomic Vulnerability to Disaster Risk: A Case Study of Flood and Drought Impact in a Rural Sri Lankan Community," Ecological Economics, Elsevier, vol. 152(C), pages 131-140.
    3. Lalitha Kamath & Anushri Tiwari, 2022. "Ambivalent Governance And Slow Violence In Mumbai'S Mithi River," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 46(4), pages 674-686, July.
    4. Samuel Fankhauser & Thomas K.J. McDermott, 2013. "Understanding the adaptation deficit: why are poor countries more vulnerable to climate events than rich countries?," GRI Working Papers 134, Grantham Research Institute on Climate Change and the Environment.
    5. Hirte, Georg & Nitzsche, Eric & Tscharaktschiew, Stefan, 2018. "Optimal adaptation in cities," Land Use Policy, Elsevier, vol. 73(C), pages 147-169.
    6. Darshan Anil Sansare & Sumedh Yamaji Mhaske, 2020. "Natural hazard assessment and mapping using remote sensing and QGIS tools for Mumbai city, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 100(3), pages 1117-1136, February.
    7. Vittal Hari & Suman Dharmasthala & Akash Koppa & Subhankar Karmakar & Rohini Kumar, 2021. "Climate hazards are threatening vulnerable migrants in Indian megacities," Nature Climate Change, Nature, vol. 11(8), pages 636-638, August.
    8. Rose, Julia & Wilke, Christina Benita, 2015. "Climate change vulnerability in cities: The case of Hamburg," HWWI Research Papers 167, Hamburg Institute of International Economics (HWWI).
    9. Hallegatte,Stephane & Bangalore,Mook & Jouanjean,Marie Agnes, 2016. "Higher losses and slower development in the absence of disaster risk management investments," Policy Research Working Paper Series 7632, The World Bank.
    10. Castells-Quintana, David & Lopez-Uribe, Maria del Pilar & McDermott, Thomas K.J., 2018. "Adaptation to climate change: A review through a development economics lens," World Development, Elsevier, vol. 104(C), pages 183-196.
    11. Yi He & Desmond Manful & Rachel Warren & Nicole Forstenhäusler & Timothy J. Osborn & Jeff Price & Rhosanna Jenkins & Craig Wallace & Dai Yamazaki, 2022. "Quantification of impacts between 1.5 and 4 °C of global warming on flooding risks in six countries," Climatic Change, Springer, vol. 170(1), pages 1-21, January.
    12. Vito Frontuto & Silvana Dalmazzone & Francesco Salcuni & Alessandro Pezzoli, 2020. "Risk Aversion, Inequality and Economic Evaluation of Flood Damages: A Case Study in Ecuador," Sustainability, MDPI, vol. 12(23), pages 1-17, December.
    13. Azreen Karim & Ilan Noy, 2016. "Poverty And Natural Disasters — A Qualitative Survey Of The Empirical Literature," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 61(01), pages 1-36, March.
    14. McDermott,Thomas K.J., 2016. "Investing in disaster risk management in an uncertain climate," Policy Research Working Paper Series 7631, The World Bank.
    15. Hallegatte, Stephane, 2014. "Economic resilience: definition and measurement," Policy Research Working Paper Series 6852, The World Bank.
    16. Vahid Mojtahed & Carlo Giupponi & Claudio Biscaro & Animesh K. Gain & Stefano Balbi, 2013. "Integrated Assessment of Natural Hazards and Climate-Change Adaptation: II. The SERRA Methodology," Working Papers 2013:07, Department of Economics, University of Venice "Ca' Foscari".

    More about this item

    Keywords

    action publique; adaptation; adaptation; aménagement urbain; assurance; catastrophes naturelles; changement climatique; climate change; développement durable; flood management; gestion des inondations; global warming; government policy; insurance; natural disasters; réchauffement climatique; sustainable development; urban planning;
    All these keywords.

    JEL classification:

    • E20 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - General (includes Measurement and Data)
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
    • Q01 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Sustainable Development
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming
    • R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
    • R52 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Regional Government Analysis - - - Land Use and Other Regulations

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