Exploring the link between drought indicators and impacts
Exploring the link between drought indicators and impacts
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DOI：
10.5194/nhess-15-1381-2015
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发表时间：
2015-01-01
影响因子：
4.6
通讯作者：
Stahl, K.
中科院分区：
文献类型：
--
作者：
Bachmair, S.;Kohn, I.;Stahl, K.
目前的干旱监测和预警系统使用不同的指标来监测干旱状况，并采用不同的指标阈值和规则来分配干旱强度等级或发出警告或警报。然而，人们对地面影响发生的不同水文气象指标的含义知之甚少。迄今为止，由于关于干旱影响的数据稀少且不完整，很少有人试图系统地描述指标-影响关系。新建立的欧洲干旱影响报告清单(EDII)提供了调查这种联系的可能性。这项研究的目的是探讨德国案例研究区水文气象指标与干旱影响之间的联系，从而测试定性影响数据在评估干旱指标绩效方面的潜力。作为干旱指标，选择了两个气候干旱指数--标准化降水指数(SPI)和标准化降水蒸散指数(SPI)--以及径流量和地下水位百分位数。通过数据可视化、与影响开始同时进行的指标值提取以及联邦州一级指标和影响数据的月度时间序列之间的相关性分析，以及选定干旱事件的空间模式之间的相关分析，评估了联系。分析清楚地表明，一些州和干旱事件之间存在着显着的、中等到强烈的相关性，从而可以相互比较不同干旱指标的表现。重要的发现是SPI和SPI的中间累积期的相关性最强，SPI的表现略好于SPI，在许多情况下，流向百分位数的表现与SPI相似。除了这些共性，分析还揭示了联邦州和干旱事件之间的差异，表明这种联系在一定程度上是时变的和地区特有的。关于干旱影响开始的“阈值”，即与过去的影响开始同时发生的指标值，我们发现不能确定单一的“最佳”阈值，但影响发生在一个指标值的范围内。然而，阈值分布的中位数在北部/东北部与南部/西南部联邦州之间以及干旱事件之间存在差异。虽然研究结果在很大程度上依赖于数据，未来可能会随着EDII条目的增加而改变，但这项研究清楚地证明了使用基于文本的影响报告来评估水文气象变量的可行性，并强调了影响报告作为监测干旱情况的工具的价值。
Current drought monitoring and early warning systems use different indicators for monitoring drought conditions and apply different indicator thresholds and rules for assigning drought intensity classes or issue warnings or alerts. Nevertheless, there is little knowledge on the meaning of different hydro-meteorologic indicators for impact occurrence on the ground. To date, there have been very few attempts to systematically characterize the indicator-impact relationship owing to sparse and patchy data on drought impacts. The newly established European Drought Impact report Inventory (EDII) offers the possibility to investigate this linkage. The aim of this study was to explore the link between hydro-meteorologic indicators and drought impacts for the case study area Germany and thus to test the potential of qualitative impact data for evaluating the performance of drought indicators. As drought indicators two climatological drought indices - the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) - as well as streamflow and groundwater level percentiles were selected. Linkage was assessed though data visualization, extraction of indicator values concurrent with impact onset, and correlation analysis between monthly time series of indicator and impact data at the federal state level, and between spatial patterns for selected drought events. The analysis clearly revealed a significant moderate to strong correlation for some states and drought events allowing for an intercomparison of the performance of different drought indicators. Important findings were strongest correlation for intermediate accumulation periods of SPI and SPEI, a slightly better performance of SPEI versus SPI, and a similar performance of streamflow percentiles to SPI in many cases. Apart from these commonalities, the analysis also exposed differences among federal states and drought events, suggesting that the linkage is time variant and region specific to some degree. Concerning ''thresholds'' for drought impact onset, i.e. indicator values concurrent with past impact onsets, we found that no single ''best'' threshold value can be identified but impacts occur within a range of indicator values. Nevertheless, the median of the threshold distributions showed differences between northern/northeastern versus southern/southwestern federal states, and among drought events. While the findings strongly depend on data and may change with a growing number of EDII entries in the future, this study clearly demonstrates the feasibility of evaluating hydro-meteorologic variables with text-based impact reports and highlights the value of impact reporting as a tool for monitoring drought conditions.