Abstract. Drought is understood as both a lack of water (i.e., a deficit as compared to some requirement) and an anomaly in the condition of one or more components of the hydrological cycle. Most drought indices, however, only consider the anomaly aspect, i.e., how unusual the condition is. In this paper, we present two drought hazard indices that reflect both the deficit and anomaly aspects. The soil moisture deficit anomaly index, SMDAI, is based on the drought severity index, DSI, but is computed in a more straightforward way that does not require the definition of a mapping function. We propose a new indicator of drought hazard for water supply from rivers, the streamflow deficit anomaly index, QDAI, which takes into account the surface water demand of humans and freshwater biota. Both indices are computed and analyzed at the global scale, with a spatial resolution of roughly 50 km, for the period 1981–2010, using monthly time series of variables computed by the global water resources and the model WaterGAP2.2d. We found that the SMDAI and QDAI values are broadly similar to values of purely anomaly-based indices. However, the deficit anomaly indices provide more differentiated, spatial and temporal patterns that help to distinguish the degree of the actual drought hazard to vegetation health or the water supply. QDAI can be made relevant for stakeholders with different perceptions about the importance of ecosystem protection, by adopting the approach for computing the amount of water that is required to remain in the river for the well-being of the river ecosystem. Both deficit anomaly indices are well suited for inclusion in local or global drought risk studies.

中文翻译：

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土壤水分和流量赤字异常指数：一种结合赤字和异常来量化干旱危害的方法

摘要。干旱被理解为缺水（即与某些需求相比缺乏）和在水文循环的一个或多个组成部分情况下的异常。但是，大多数干旱指数仅考虑异常方面，即该状况有多异常。在本文中，我们提出了两个干旱风险指数，它们同时反映了赤字和异常方面。土壤水分亏缺异常指数SMDAI基于干旱严重度指数DSI，但以更直接的方式计算，不需要定义映射函数。我们提出了一种新的干旱指标，用于河流供水的流量赤字异常指数QDAI，该指标考虑了人类和淡水生物区系的地表水需求。这两个指数都是在全球范围内计算和分析的，使用全球水资源和模型WaterGAP2.2d计算的月度时间序列变量，在1981-2010年期间的空间分辨率约为50 km。我们发现SMDAI和QDAI值与纯粹基于异常的索引的值大致相似。但是，赤字异常指数提供了更多差异化的时空模式，有助于区分实际干旱对植被健康或供水的危害程度。通过采用计算河流中生态系统福祉所需的水量的方法，可以使QDAI与对生态系统保护的重要性有不同认识的利益相关者相关。两种赤字异常指数都非常适合纳入本地或全球干旱风险研究。