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Crops' exposure, sensitivity and adaptive capacity to drought occurrence

机译:农作物的暴露,敏感性和自适应能力发生

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摘要

In the context of sustainable agricultural management, drought monitoring plays a crucial role in assessing the vulnerability of agriculture to drought occurrence. Drought events are very frequent in the Iberian Peninsula (and in Portugal in particular), and an increase in frequency of these extreme events are expected in a very near future. Therefore, the quantitative assessment of the natural-ecosystem vulnerability to drought is still very challenging, mainly due to the difficulties of having a common definition of vulnerability. Consequently, several methods have been proposed to assess agricultural vulnerability. In this work, a principal component analysis (PCA) was performed based on the components which characterize the exposure, sensitivity and adaptive capacity of the agricultural system to drought events with the aim of generating maps of vulnerability of agriculture to drought in Portugal. Several datasets were used to describe these components, namely drought indicators, vegetation indices and soil characterization variables. A comparison between the PCA-based method and a variance method using the same indicators was performed. Results show that both methods identify Minho and Alentejo as regions of low and extreme vulnerability, respectively. The results are very similar between the two methods, with small differences in certain vulnerability classes. However, the PCA method has some advantages over the variance method, namely the ability to identify the sign of the indicators, not having to use the indicator-component subjective relationship, and not needing to calculate weights. Furthermore, the PCA method is fully statistical and presents results according to prior knowledge of the region and the data used.
机译:在可持续农业管理的背景下,干旱监测在评估农业对干旱发生的脆弱性方面发挥着至关重要的作用。干旱事件在伊比利亚半岛(特别是葡萄牙)非常频繁,并且在近期将在近期预期这些极端事件的频率增加。因此,对干旱的自然生态系统脆弱性的定量评估仍然非常具有挑战性,主要是由于具有脆弱性定义的困难。因此,已经提出了几种方法来评估农业脆弱性。在这项工作中,基于将农业系统的暴露,敏感性和自适应能力的组成部分进行了主成分分析(PCA),其目的是在葡萄牙中的干旱地区产生脆弱性的目的。几个数据集用于描述这些组件,即干旱指标,植被指数和土壤表征变量。进行了基于PCA的方法与使用相同指标的方差方法的比较。结果表明,两种方法都分别识别Minho和Alentejo作为低和极端漏洞的区域。两种方法之间的结果非常相似,在某些漏洞类别中具有较小的差异。但是,PCA方法对方差方法具有一些优点,即识别指标符号的能力,不必使用指示器组件主观关系,而不需要计算权重。此外,PCA方法是完全统计的,并且根据该区域的先前知识和使用的数据提出结果。

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