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Assessing the capability of multi-scale drought datasets to quantify drought severity and to identify drought impacts: An example in the Ebro Basin

机译:评估多尺度干旱数据集量化干旱严重程度并确定干旱影响的能力:埃布罗盆地的一个例子

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摘要

Assessing the risk, the severity and the likely evolution of droughts are key tasks for improving preparedness of regions prone to drought conditions, and mitigation of drought consequences. The access to real-time and high-quality climatic information is essential for this purpose. Different climatic databases are being developed and made available on real time by climatic research institutions, but their capability for quantifying droughts characteristics including severity, or spatio-temporal variability, is uncertain given their low spatial resolution. In this study, we assessed the capability of three databases with contrasted spatial resolution for measuring spatial and temporal variability of drought occurrence. The standardized precipitation index, calculated for each database, showed that the low resolution datasets allow an acceptable measurement of the magnitude, intensity and duration of droughts, while failing mostly in detecting the spatial patterns of the specific drought episodes. Moreover, the capability of the datasets for assessing the impacts of droughts on surface hydrology and tree growth was examined. Results confirmed the usefulness of the drought index for assessing drought impacts on water resources and forest ecosystems even when low resolution databases are used.
机译:评估干旱的风险,严重程度和可能的演变是提高易受干旱条件影响的地区的备灾和减轻干旱后果的关键任务。为此目的,获取实时和高质量的气候信息至关重要。气候研究机构正在开发并实时提供不同的气候数据库,但是鉴于其空间分辨率较低,其定量干旱特征(包括严重程度或时空变异性)的能力尚不确定。在这项研究中,我们评估了具有对比的空间分辨率的三个数据库测量干旱发生时空变化的能力。为每个数据库计算的标准化降水指数表明,低分辨率数据集可以对干旱的强度,强度和持续时间进行可接受的测量,而主要无法检测出特定干旱事件的空间格局。此外,还检查了数据集评估干旱对地表水文学和树木生长影响的能力。结果证实,即使使用低分辨率数据库,干旱指数也可用于评估干旱对水资源和森林生态系统的影响。

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