Vulnerability Resilience in the Major Watersheds of the Korean Peninsula

Abstract

Water resources management requires policy enforcement in a changing environment. Climate change must be considered in major watershed river restorations in Korea. The aim of river restorations is to provide better water resource control -now and in the future. To aid in policy making in the government sector, "vulnerability-resilience indexes" (VRIs) with a Delphi survey method have been adopted to provide a possible reference. The Delphi survey offers prioritized vulnerability proxy variables based on expert opinions regarding the changing environment in terms of climate change and river restorations. The VRIs of watersheds were improved after river restorations, with the exception of some locations. However, when climate change was taken into consideration in the analysis of conditions after the restorations were completed, the results showed that governments need to provide better mitigation strategies to increase vulnerability resilience in the face of climate change.

Comparative Analysis of Flood Vulnerability Indicators by Aggregation Frameworks for the IPCC’s Assessment Components to Climate Change

“…As the vulnerability is also defined in terms of adaptability to cope with potential impacts of other global changes as well as climate change [1,36,37], potential impact PI is undertaken as a function of exposure and sensitivity [18]. Hence, the second flood vulnerability indicator FVI 2 can be expressed in Equation (2) by the potential impact PI linearly aggregated from the exposure E and sensitivity S [19,[38][39][40] along with a lack of adaptability A, following the framework in previous studies [20,21,[41][42][43]:…”

“…Thus, two proxy variables, which are deemed relevant to human and properties are identified based on the IPCC's widely referred assessment components. A comprehensive review was carried out for previously published flood vulnerability assessment articles [13][14][15][16][17][19][20][21]23,[30][31][32]34,35] to select each proxy variable for the study site, as presented in Table 1. To represent the duration and extent to which the study site is influenced by flood events, the proxy variables for the exposure component comprised of days of heavy rainfall greater than 80 mm per day [52] and ratio of flooded area to each administrative district area.…”

“…A normalization method was necessary to transform proxy variables generally measured at different scales and units into a common domain. This study adopts the min-max normalization method as used in previous studies [19,22,25,27,30,31,35,38,40], and all proxy variables ranged from 1 to 100 by Equations (5) and (6). Note that 1.0 was taken for the normalized minimum score to avoid the zero composite outcomes by multiplicative aggregation forms in Equations (1)-(4).…”

“…where u i is the normalized value of the original value x i for the proxy variable i, max(x i ) and min(x i ) are the maximum and the minimum values, respectively of the proxy variable i, and s max and s min are the maximum of 100 and the minimum of 1, respectively of the normalized value u i . Following previous studies [19,[22][23][24][25][26][27][29][30][31][32][33][34][35]38,39], the normalized proxy variables are then linearly aggregated into each component indicator such as exposure E, sensitivity S, lack of adaptability A, potential impact PI, livelihood vulnerability LV, or internal factor IF, respectively with the weighting factor w i for the total number k of proxy variables for each component indicator:…”

Spatial Assessment of Damage Vulnerability to Storms Based on the Analysis of Historical Damage Cost Data in the Korean Peninsula

“…First, after Adger [8] proposed that vulnerability to climate change can be quantified by a general function for aggregating the IPCC's three assessment components, the composite indicators have been compiled individually from exposure, sensitivity, and adaptive capacity components to measure the vulnerability to natural disasters, as conducted in the selected previous studies for the flood vulnerability in coastal areas [9,10], in national industrial parks [11], and in urban areas [12]. Second, following another assessment framework using the potential impact component as a function of exposure and sensitivity components by Metzger et al [13], vulnerability to climate-related disasters has been evaluated, as presented in some selected previous studies for the flood vulnerability in watersheds [14], in urban areas by land-use changes [15,16], and in coastal metropolitan areas [17]. Third, as Hahn et al [18] proposed the livelihood vulnerability index based on the IPCC's three components, the sensitivity component is combined with the difference between exposure and adaptive capacity components to assess vulnerability to natural disasters, as shown in the selected previous studies for the livelihood vulnerability in wetland communities [19], in farming communities, [20], horticultural districts [21], and riverine communities [22].…”