Vulnerability proxy selection and risk calculation formula for global flood risk assessment: a preliminary study

Abstract

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

Possibilities and challenges in the development of a global flood disaster risk indicator from the post-2015 UN processes perspective: a preliminary study

“…R i number of flood fatalities for the ith country (persons per 1,000 km 2 ) a E i number of affected people for the ith country (persons per 1,000 km 2 ) a v ij value of the jth proxy for the ith country b Ṽ ij standardized value of the jth proxy for the ith country over all countries (standardized values with a minimum of 1) c and C Coefficients for factors not to be considered a parameter for affected people b j parameter for the jth vulnerability proxy i 1 for Bangladesh, 2 for Cambodia, 3 for India, 4 for Indonesia, 5 for Japan, 6 for Kazakhstan, 7 for Korea, 8 for Laos, 9 for Nepal, 10 for Pakistan, 11 for Philippines, 12 for Tajikistan, 13 for Thailand, and 14 for Vietnam j 1 for the age-related dependency ratio, 2 for the undernourishment prevalence, 3 for the urban population growth, 4 for the corruption perception index, and 5 for the HFA early warning score result, this study found the following five proxies, which are considered to be contextually and statistically meaningful for flood fatalities (see Lee et al (2014) for more on vulnerability proxies):…”

“…A vulnerability assessment is conducted by using proxies to identify anthropogenic factors, which are important to possibly describe the whole shape of risk. To select proxies which are contextually meaningful for flood fatalities, vulnerability is considered to consist of four categories of proxies suggested by Lee et al (2014): (i) 'marginalized group', mainly associated with people and relevant to demographics, disability and other socio-economic weaknesses; (ii) 'urbanization', mainly associated with living circumstances and relevant to deforestation, illegal settlement, urban sprawl and other environmental deteriorations; (iii) 'weak governance', mainly associated with government and relevant to accountability, effectiveness and regulatory quality; and (iv) 'coping capacity', relevant to various efforts which are made at all administrative levels in order to overcome flood disasters, including early warning systems and information and communication technologies, disaster education and community-based programs. Based on the above categories, a vulnerability assessment first investigates what proxies are available over the study sites and then tests which proxies show a high correlation with flood fatalities.…”

“…(The equation structure is relatively free of assumptions, encouraging parameters to be specified analytically; hence, it has often appeared in previous studies (BCPR, 2004;Raschky, 2008;Peduzzi et al, 2009;Lee et al, 2014). However, the authors admit that statistical implications inherent in the structure need to be rigorously discussed.…”

“…Despite many attempts, it is still a major challenge to develop GFDRIs which are fully acceptable (e.g. Barredo et al, 2007;IHP, 2012;Lee et al, 2014). Few studies have yet discussed much about what GFDRIs propose in terms of reliability, accuracy and meaningfulness for day-to-day decision making.…”

Development of a Method for Assessing Country-Based Flood Risk at the Global Scale

“…Initially applied to river basins in Japan (Connor and Hiroki 2005), and later, to 114 major river basins across the world (Hara et al 2009), the index is used only at the riverbasin scale and cannot be used for country-based assessment because of limited data availability. Lee et al (2015) developed a country-based flood risk method incorporating eight vulnerability proxies and viewed flood risk as expected death tolls due to flood disasters. However, the study covered only 15 Asian countries selected on the basis of data availability.…”