By using the data from 15 countries in Asia, this study aims to improve the current global flood risk assessment methods in the aspects of vulnerability proxy selection and a risk calculation formula. In estimating global flood risk, the current methods treat vulnerability in a very simplistic manner. Based on recent literature and empirical findings, this study classifies vulnerability into susceptibility (in terms of marginalized groups, unplanned urbanization, and weak governance), and coping capacity. Each of the four components is, in light of global data availability, expressed by eight proxies, namely, age-related dependency ratio, undernourishment prevalence, urbanization growth rate, deforestation, corruption perceptions index, and three core scores from the Hyogo Framework for Action. Regarding the risk calculation formula, this study tries to break through the limitations of the multiple regression, which is commonly used for estimating coefficients and parameters, by applying the partial least squares regression (PLSR) method. The PLSR method makes it possible to include many proxies in the formula without lowering the explanatory power, even when the proxies are highly correlated.
AcronymsAQUASTAT FAO's global information system on water and agriculture CPI Corruption perceptions index CRED Centre for Research on the Epidemiology of Disasters DRR Disaster risk reduction EM-DAT Emergency disasters database FAO Food and Agriculture
Owing to climate change, torrential rains and typhoons have become more frequent. However, to cope with this threat, conventional flood management suffers from limitations and difficulties because of the practice of uniform flood prevention measures being applied to all stream sections according to river grade classification. A wide array of measures should be considered to differentiate flood protection targets: adaptive flood management strategy is one such effort. One obstacle, however, to introducing such a measure is lack of clarity over how to divide quantitatively the degree of risk from flooding. In this study, we undertook quantitative risk assessment to determine the risk level in a riparian zone. We compared our results with statistically derived societal risk limits to determine whether the risk level was acceptable within the framework of the tolerance risk limit. We found that the flood risk could be reduced through adaptive flood management.
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