Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data

S. Muis, B. Güneralp, B. Jongman, J.C.J.H. Aerts, P.J. Ward

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

An accurate understanding of flood risk and its drivers is crucial for effective risk management. Detailed risk projections, including uncertainties, are however rarely available, particularly in developing countries. This paper presents a method that integrates recent advances in global-scale modeling of flood hazard and land change, which enables the probabilistic analysis of future trends in national-scale flood risk. We demonstrate its application to Indonesia. We develop 1000 spatially-explicit projections of urban expansion from 2000 to 2030 that account for uncertainty associated with population and economic growth projections, as well as uncertainty in where urban land change may occur. The projections show that the urban extent increases by 215%–357% (5th and 95th percentiles). Urban expansion is particularly rapid on Java, which accounts for 79% of the national increase. From 2000 to 2030, increases in exposure will elevate flood risk by, on average, 76% and 120% for river and coastal floods. While sea level rise will further increase the exposure-induced trend by 19%–37%, the response of river floods to climate change is highly uncertain. However, as urban expansion is the main driver of future risk, the implementation of adaptation measures is increasingly urgent, regardless of the wide uncertainty in climate projections. Using probabilistic urban projections, we show that spatial planning can be a very effective adaptation strategy. Our study emphasizes that global data can be used successfully for probabilistic risk assessment in data-scarce countries.
Original languageEnglish
Pages (from-to)445-457
JournalScience of the Total Environment
Volume538
Early online date28 Aug 2015
DOIs
Publication statusPublished - 2015

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Climate change
climate change
Rivers
Sea level
spatial planning
Risk management
Developing countries
river
Risk assessment
analysis
economic growth
population growth
Hazards
risk assessment
developing world
hazard
Planning
Economics
Uncertainty
climate

Cite this

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title = "Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data",
abstract = "An accurate understanding of flood risk and its drivers is crucial for effective risk management. Detailed risk projections, including uncertainties, are however rarely available, particularly in developing countries. This paper presents a method that integrates recent advances in global-scale modeling of flood hazard and land change, which enables the probabilistic analysis of future trends in national-scale flood risk. We demonstrate its application to Indonesia. We develop 1000 spatially-explicit projections of urban expansion from 2000 to 2030 that account for uncertainty associated with population and economic growth projections, as well as uncertainty in where urban land change may occur. The projections show that the urban extent increases by 215{\%}–357{\%} (5th and 95th percentiles). Urban expansion is particularly rapid on Java, which accounts for 79{\%} of the national increase. From 2000 to 2030, increases in exposure will elevate flood risk by, on average, 76{\%} and 120{\%} for river and coastal floods. While sea level rise will further increase the exposure-induced trend by 19{\%}–37{\%}, the response of river floods to climate change is highly uncertain. However, as urban expansion is the main driver of future risk, the implementation of adaptation measures is increasingly urgent, regardless of the wide uncertainty in climate projections. Using probabilistic urban projections, we show that spatial planning can be a very effective adaptation strategy. Our study emphasizes that global data can be used successfully for probabilistic risk assessment in data-scarce countries.",
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Flood risk and adaptation strategies under climate change and urban expansion: A probabilistic analysis using global data. / Muis, S.; Güneralp, B.; Jongman, B.; Aerts, J.C.J.H.; Ward, P.J.

In: Science of the Total Environment, Vol. 538, 2015, p. 445-457.

Research output: Contribution to JournalArticleAcademicpeer-review

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