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

Abstract

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.

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

“…WaterGAP 2.2d model output data used in this study are available at https://doi.org/10.1594/PANGAEA.918447 (Müller Schmied et al, 2020). The outputs from this study are available at https://doi.org/10.6084/m9.figshare.14213852 (Popat and Döll, 2021).…”