Assessing current and future impacts of climate-related extreme events. The case of Bangladesh

Hochrainer-Stigler, S., Mechler, R. ORCID: https://orcid.org/0000-0003-2239-1578, & Pflug, G. ORCID: https://orcid.org/0000-0001-8215-3550 (2010). Assessing current and future impacts of climate-related extreme events. The case of Bangladesh. IIASA Interim Report. IIASA, Laxenburg, Austria: IR-09-030

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Abstract

Extreme events and options for managing these risks are receiving increasing attention in research and policy. In order to cost these extremes, a standard approach is to use Integrated Assessment Models with global or regional resolution and represent risk using add-on damage functions that are based on observed impacts and contingent on gradual temperature increase. Such assessments generally find that economic development and population growth are likely to be the major drivers of natural disaster risk in the future; yet, little is said about changes in vulnerability, generally considered a key component of risk. As well, risk is represented by an estimate of average observed impacts using the statistical expectation. Explicitly accounting for vulnerability and using a fuller risk-analytical framework embedded in a simpler economic model, we study the case of Bangladesh, the most flood prone country in the world, in order to critically examine the contribution of all drivers to risk. Specifically, we assess projected changes in riverine flood risk in Bangladesh up to the year 2050 and attempt to quantitatively assess the relative importance of climate change versus socio-economic change in current and future disaster risk. We find that, while flood frequency and intensity, based on regional climate downscaling, are expected to increase, vulnerability, based on observed behaviour in real events over the last 30 years, can be expected to decrease. Also, changes in vulnerability and hazard are roughly of similar magnitudes, while uncertainties are large. Overall, we interpret our findings to corroborate the need for taking a more risk-based approach when assessing extreme events impacts and adaptation - cognizant of the large associated uncertainties and methodological challenges -.

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