Soil moisture and streamflow deficit anomaly index: An approach to quantify drought hazards by combining deficit and anomaly

Drought is understood as both a lack of water (i.e., a deficit as compared to demand) and a temporal anomaly in 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 (Cammalleri et al., 2016), 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 and nature 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 adapting 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.

干旱可被定义为兼具两类属性：一是水资源短缺（即相对于用水需求的水量亏缺），二是水文循环一个或多个组分出现的时间尺度异常。然而，现有多数干旱指数仅聚焦于异常维度，即评估当前水文状态的异常程度。本研究提出两种可同时反映水量亏缺与状态异常的干旱灾害指数。土壤水分亏缺异常指数（Soil Moisture Deficit Anomaly Index，SMDAI）以干旱严重度指数（Drought Severity Index，DSI，Cammalleri等，2016）为基础，但其计算方式更为简便，无需定义映射函数。本研究同时提出一种适用于河道供水的新型干旱灾害评估指标——径流亏缺异常指数（Streamflow Deficit Anomaly Index，QDAI），该指标兼顾人类地表水需求与淡水生物群落的用水需求。本研究以全球水资源模型WaterGAP2.2d生成的逐月变量时间序列为数据源，在全球尺度上对两种指数开展了1981-2010年的计算与分析，空间分辨率约为50千米。研究结果显示，SMDAI与QDAI的计算结果与纯异常型干旱指数的数值大体相近。但亏缺异常型干旱指数能够呈现出更具区分度的时空分布特征，有助于厘清植被健康或河道供水所面临的实际干旱灾害的程度与本质。通过调整维持河道生态系统健康所需留存水量的计算方法，QDAI可适配对生态保护重要性持有不同认知的利益相关方需求。两类亏缺异常型干旱指数均适用于纳入区域或全球尺度的干旱风险研究当中。