재해위험식별은 이상기후 대응 재해위험관리의 첫 번째 단계이다. 재해위험식별을 통한 정확한 정보의 제공은 이상기후에 대한 이해당사자들의 인식을 향상시킬 뿐만 아니라 이상기후에 영향에 보다 강건하며 지속가능한 정책 수립 혹은 의사결정에 필수적인 요소이다. 현재 농업부문의 경우 재해위험식별에 관한 정책과 관련 연구가 매우 제한적이다. 따라서 본 보고서는 국내 농업부문의 이상기후에 대응한 재해위험관리 정책과 관련 연구의 한계를 극복하기 위한 출발점으로 재해위험식별에 초점을 맞추었다.
우선 본 보고서에서는 이상기후 대응 재해위험식별에 필수적인 이상기후의 발생 현황과 시공간적 분포변화에 관한 자료를 구축하였다. 또한, 구축된 이상기후 관련 자료와 가용가능한 농축산업 관련 자료를 통합하여 이상기후가 농업부문에 미치는 직접적·간접적 영향 분석은 물론 이상기후에 대한 시군별 취약성을 분석하였다. 이러한 이상기후의 경제적 영향 분석과 이상기후에 대한 취약성 분석은 재해위험식별의 가장 기초적인 구성요소로서 향후 이상기후 관련 의사결정지원도구 구축 시 중요한 참고자료로 활용될 수 있을 것이다.
두 번째로 본 보고서에서는 생산자와 소비자에 대한 설문조사와 국내외 이상기후 대응 현황에 대해 분석함으로써 우리나라 농업부문의 효과적인 이상기후 대응 재해위험관리를 위한 정책적 시사점을 도출하였다. 비록 본 보고서에서 제시한 효과적 재해위험관리를 위한 정책적 시사점은 아직 정책으로 구체화되기에는 많이 부족하지만 국내외의 농업부문 이상기후 대응 재해위험관리 정책과 소비자 및 생산자의 이상기후 인식과 대응에 대해 분석한 결과는 현재 농업부문 재해위험관리의 현황을 제대로 파악하고 이상기후 대응 재해위험관리 정책의 방향설정에 충분히 활용될 수 있을 것이다.
The 2018 Extreme Weather Report (published by involved ministries in 2019) describes that the frequency and intensity of extreme weather events continued to increase for the last 100 years, and it is likely that climate change will further exacerbate the tendency. Agriculture is an industry susceptible to weather conditions. Therefore, it is inevitable that extreme weather events can have a direct or indirect impact on agriculture, requiring political response to it. Moreover, active efforts have been made recently to reduce the negative impact of extreme weather events resulting from climate change and seek sustainable growth by integrating disaster risk management with adaptation to climate change.
However, Korean governmental policies for risk management related to extreme weather events only focus on disaster management and risk transfer rather than the climatic disaster risk identification. Previous literature in Korea also mainly focuses on the causal relationship between extreme weather events and agricultural productivity. Also, studies regarding changes in frequency and intensity of extreme weather events for establishing policies, its direct and indirect impact on the economy, and measurement of vulnerability are lacking.
This study focuses mainly on the disaster risk identification which is essential for improving the synergistic relationship between disaster risk management and climate change adaptation. Specifically, the purpose of this study is as follows: 1) to create primary data about extreme weather events required to identify disaster risks, 2) to analyze the economic impact of major extreme weather events based on the ideal analytical method therefor, 3) to establish implications for effective risk management of weather disasters.
The process used for this study is described below:
First, based on previous literature and expert advices, we select estimation methods for measuring the economic impact of extreme weather events, and construct an analytical framework and indexes for assessing vulnerability to extreme weather events. Furthermore, we study the methodology for disaster risk assessment and disaster risk management of international organizations (IPCC, UNISDR), foreign countries (Australia, the US), and Korea.
We analyze spatial distribution of extreme weather events and its changes based on the past weather data and climate change scenario data. The information from the ASOS (Automated Surface Observing System) of the KMA (Korea Meteorological Administration) and the Thiessen network analysis are incorporated to analyze the temporal and spatial distribution of hourly temperatures and precipitation in the past. Lastly, the climate change scenarios provided by the KMA are applied to forecast future changes of the temporal and spatial distribution of extreme weather events resulting from climate change.
How to measure direct economic costs of disasters and disaster risk depend on the availability of empirical data. First, for rice of which the productivity data for each region are available, we estimate causal effects of extreme weather events on rice yield and its distribution by applying a regression analysis. For apples and pears of which the data about agricultural insurance for each region and crop are available, a regression analysis is also incorporated to identify the causal relationship between the loss cost ratio and extreme weather events for each region and crop. For pigs and chickens of which the damage data for each region and livestock due to heatwaves are available, we measure changes of disaster risks before and after climate change. Moreover, EDM (Equilibrium Displacement Model) is used to analyze indirect disaster costs of extreme weather events due to heatwaves. The hazards-of-place model (Cutter et al. 1996) is adopted to build a framework for analyzing vulnerability to extreme weather events, and apply the nonparametric frontier approach to normalize and integrate indexes related to vulnerability (Zhou et al. 2017). Lastly, we survey with questionnaires to analyze producer and consumer response to extreme weather events in this study.
Chapter 2 analyzes spatial distribution and changes in its extreme weather events related to precipitation or temperatures. The analysis forecasts a severe water scarcity between 2021 and 2040 and between 2071 and 2100, showing more water scarcity in the central region, including Gyeonggi-do than in the southern region of Korea. A continued increase in extreme weather events (average +2σ) related to high temperature is also forecasted because of climate change, mainly in the central region and the coastal areas. It is also shown that extreme weather events (average-2σ) related to low temperature continue to decrease after a sharp increase mainly in the inland areas between 2021 and 2040. The analysis shows that heatwaves (the highest temperature above 35℃) continue to increase, mainly in the central region, coastal and inland areas of Gyeongsang-do. This result implies that the occurrence of extreme weather events and changes in frequency and intensity of them due to climate change varies with regions and periods. Moreover, it is necessary to pay attention to geographical features for the effective climatic disaster risk management.
(The rest is omitted. See the attached file for details.)
Researchers: Sung Jaehoon, Jeong Hakkyun, Lee Hyunjung
Research period: 2019. 1. ~ 2019. 10.
E-mail address: email@example.com
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