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Developing spatial agricultural drought risk index with controllable geo-spatial indicators: A case study for South Korea and Kazakhstan

Authors
Kim, S.J.Park, S.Lee, S.J.Shaimerdenova, A.Kim, J.Park, E.Lee, W.Kim, G.S.Kim, N.Kim, T.H.Lim, C.-H.Choi, Y.Lee, W.-K.
Issue Date
15-2월-2021
Publisher
Elsevier Ltd
Keywords
Adaptive capacity; Agricultural drought risk index; Disaster; Risk; Sensitivity; Vulnerability
Citation
International Journal of Disaster Risk Reduction, v.54
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Disaster Risk Reduction
Volume
54
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/129204
DOI
10.1016/j.ijdrr.2021.102056
ISSN
2212-4209
Abstract
Constant environmental degradation and increased frequency and severity of natural disasters have been evident over the past few decades worldwide. As such, scientific tools to predict and assess risks keep being developed. Assessing disaster risk is an important task in supporting the transition to a sustainable society. However, as disasters and systems become more complex, disaster models combining diverse aspects including climatic, social, economic, and environmental factors are necessary. For this study, we set a model using the concept of risk by identifying hazards, exposure, and vulnerability. Here, the vulnerability was classified into two domains, sensitivity and adaptive capacity, and two spheres, natural/built environment and human environment. Also, we stressed that controllable geo-spatial indicators should be included in risk assessments to effectively reduce risk and implement adequate spatio-temporal actions. The approach of this study was applied to Kazakhstan and South Korea as a pilot study to develop Agricultural Drought Risk Index (ADRI) and maps. As a result, the agricultural drought risk could be analyzed for South Korea and Kazakhstan. In addition, we performed additional spatial analyses at a reasonable scale for practical use. It was concluded that prioritizing risk areas at administrative and site level could contribute in decision and policy-making for risk reduction. Furthermore, spatial data availability and quality were found to be significant in assessing disaster risk. © 2021 The Authors
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