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Assessment of agricultural drought vulnerability to climate change at a municipal level in South Korea

机译:评估农业干旱脆弱性对韩国市级的气候变化

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摘要

This study aimed to analyze the future vulnerability to agricultural drought of the Korean administrative units of cities (Si) and counties (Gun) following the climate change phenomenon. To assess the vulnerability in a quantitative manner and also to deal with different physical and socioeconomic data on the occurrence of agricultural drought, principal component analysis (PCA), a multivariate statistical analysis method, was adopted, and a vulnerability index, regional vulnerability index to agricultural drought (RVIAD), was suggested. RVIAD having a range from 0.0 to 1.0 was calculated by rescaling the weighted summation of principal component scores. The analysis was performed with all 21 standardized variables in each administrative unit of Si and Gun: 3 sensitivity variables, 8 exposure variables, and 10 adaptation variables. It resulted in four principal components explaining about 85.7% of the total variance, and the third principal component, comprised of only climate variables, was used for applying future climate data from the RCP 8.5 scenario. The districts of Chungchongnam-Do (M1), Jeollabuk-Do (L1), and Jeollanam-Do (L2) were evaluated as having the highest vulnerability to agricultural drought based on the climate change scenario, not only in the present but also in future. Despite the limitation inherent in the PCA, the approach in this study could reflect different factors other than climate factors on minimizing subjective interruption, and such is expected to contribute to improving the decision-making for diagnosing the drought adaptation capacity in a region and developing measures to mitigate the drought damage.
机译:本研究旨在分析在气候变化现象之后,分析韩国行政单位和县(Si)和县(枪)的农业干旱的脆弱性。为了以定量方式评估漏洞,并还处理农业干旱发生的不同身体和社会经济数据,采用了主要成分分析(PCA),多变量统计分析方法,以及漏洞指数,区域漏洞指数建议农业干旱(RVIAD)。通过重新加入主成分分数的加权总和来计算具有0.0至1.0的RVIAD。通过SI和GUA的每个管理单元中的所有21个标准化变量进行分析:3个灵敏度变量,8个曝光变量和10个适应变量。它导致四个主要成分解释了总方差的约85.7%,并且仅由气候变量组成的第三个主成分用于从RCP 8.5场景应用未来的气候数据。 Chungchongnam-Do(M1),Jeollabuk-Do(L1)和Jeollanam-Do(L2)的地区被评估为基于气候变化情景的农业干旱脆弱性最高,不仅在目前而且还在将来。尽管PCA固有的限制,但本研究中的方法可能反映除了最大限度地减少主观中断的气氛因素之外的不同因素,这有望有助于改善诊断区域和发展措施的干旱适应能力的决策减轻干旱伤害。

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