Flood risk assessment for delta mega-cities: a case study of Jakarta

Budiyono, Yus; Aerts, Jeroen C. J. H.; Brinkman, J. J.; Marfai, Muh Aris; Ward, Philip J.

doi:10.1007/s11069-014-1327-9

Cited by 122 publications

(99 citation statements)

References 39 publications

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“…In this study, we use Damagescanner-Jakarta, a flood risk model for Jakarta developed by Budiyono et al (2015) in the Python programming language. Damagescanner-Jakarta estimates flood risk as a function of hazard, exposure, and vulnerability.…”

Section: Methodsmentioning

confidence: 99%

“…Damagescanner-Jakarta estimates flood risk as a function of hazard, exposure, and vulnerability. The model is explained in detail in Budiyono et al (2015). In brief, the model has a horizontal resolution of 50 m × 50 m, and works by combining maps of hazard and exposure with a depth-damage function to represent vulnerability.…”

Section: Methodsmentioning

confidence: 99%

“…Extensive overviews of the drivers of increasing flood risk can be found elsewhere (e.g. Budiyono et al, 2015;Caljouw et al, 2005;Steinberg, 2007;Ward et al, 2011b).…”

Section: Introductionmentioning

confidence: 99%

“…The first city-scale quantitative flood risk assessment in Jakarta was that of Budiyono et al (2015), who developed a river flood risk assessment model (Damagescanner-Jakarta) to assess current river flood risk. However, when planning adaptation measures and strategies, it is also vital to know how risk will develop in the future.…”

Section: Introductionmentioning

confidence: 99%

“…The aim of this paper, therefore, is to further apply and develop the Damagescanner-Jakarta risk model from Budiyono et al (2015) to project possible future changes in river flood risk in Jakarta as a result of climate change, land subsidence, and land use change. Using these simulations, we can examine the individual influence of these risk drivers to overall changes in flood risk.…”

Section: Introductionmentioning

confidence: 99%

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River flood risk in Jakarta under scenarios of future change

Budiyono

Aerts

Tollenaar

et al. 2016

Nat. Hazards Earth Syst. Sci.

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106

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Abstract. Given the increasing impacts of flooding in Jakarta, methods for assessing current and future flood risk are required. In this paper, we use the DamagescannerJakarta risk model to project changes in future river flood risk under scenarios of climate change, land subsidence, and land use change. Damagescanner-Jakarta is a simple flood risk model that estimates flood risk in terms of annual expected damage, based on input maps of flood hazard, exposure, and vulnerability. We estimate baseline flood risk at USD 186 million p.a. Combining all future scenarios, we simulate a median increase in risk of +180 % by 2030. The single driver with the largest contribution to that increase is land subsidence (+126 %). We simulated the impacts of climate change by combining two scenarios of sea level rise with simulations of changes in 1-day extreme precipitation totals from five global climate models (GCMs) forced by the four Representative Concentration Pathways (RCPs). The results are highly uncertain; the median change in risk due to climate change alone by 2030 is a decrease by −46 %, but we simulate an increase in risk under 12 of the 40 GCM-RCPsea level rise combinations. Hence, we developed probabilistic risk scenarios to account for this uncertainty. If land use change by 2030 takes places according to the official Jakarta Spatial Plan 2030, risk could be reduced by 12 %. However, if land use change in the future continues at the same rate as the last 30 years, large increases in flood risk will take place. Finally, we discuss the relevance of the results for flood risk management in Jakarta.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…Extensive overviews of the drivers of increasing flood risk can be found elsewhere (e.g. Budiyono et al, 2015;Caljouw et al, 2005;Steinberg, 2007;Ward et al, 2011b).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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