期刊
ATMOSFERA
卷 30, 期 2, 页码 101-120出版社
CENTRO CIENCIAS ATMOSFERA UNAM
DOI: 10.20937/ATM.2017.30.02.03
关键词
Climate change adaptation; cost-benefit analysis; flood risk; natural hazards; risk and uncertainty
资金
- Zurich Flood Resilience Program
- Netherlands Organisation for Scientific Research (VIDI) [016.161.324]
Economic losses as a result of natural hazards have been rising over the past few decades due to socio-economic development and perhaps climate change. This upwards trend is projected to continue, highlighting the need for adequate adaptation strategies. This raises the question of how to determine which adaptation strategies are preferred to cope with uncertain climate change impacts. This study shows how a multi-disciplinary cascade of hazard modelling, risk modelling, and a cost-benefit analysis can be applied to provide a first indicator of economically efficient adaptation strategies. We apply this approach to an analysis of flood risk and the desirability of flood protection in the state of Tabasco in Mexico, which faces severe flooding on an almost yearly basis. The results show that expected annual damage caused by coastal flooding is expected to increase from 0.53 billion USD today up to 4.12 billion USD in 2080 due to socio-economic development and climate change. For river floods, expected annual damages are estimated to increase from 1.79 billion USD up to 10.6 billion USD in 2080 if no adaptation measures are taken. Based on the estimated risk and cost-benefit analysis of installing flood protection infrastructure, we determined the economically optimal protection standards for both river and coastal floods as at least 100 years, if we take into account climate change. Our main conclusions are robust to key uncertainties about climate change impacts on flood risks, indirect damage caused by floods, the width of the protected floodplains, and the adopted social discount rate. We discuss how our multi-disciplinary approach can assist policy-makers in decisions about flood risk management, and how future research can extend our method to more refined local analyses which are needed to guide local adaptation planning.
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