Analyzing the informative value of alternative hazard indicators for monitoring drought hazard for human water supply and river ecosystems at the global scale

Abstract. Streamflow drought hazard indicators (SDHIs) are mostly lacking in large-scale drought early warning systems (DEWSs). This paper presents a new systematic approach for selecting and computing SDHIs for monitoring drought for human water supply from surface water and for river ecosystems. We recommend considering the habituation of the system at risk (e.g., a drinking water supplier or small-scale farmers in a specific region) to the streamflow regime when selecting indicators; i.e., users of the DEWSs should determine which type of deviation from normal (e.g., a certain interannual variability or a certain relative reduction of streamflow) the risk system of interest has become used to and adapted to. Distinguishing four indicator types, we classify indicators of drought magnitude (water anomaly during a predefined period) and severity (cumulated magnitude since the onset of the drought event) and specify the many relevant decisions that need to be made when computing SDHIs. Using the global hydrological model WaterGAP 2.2d, we quantify eight existing and three new SDHIs globally. For large-scale DEWSs based on the output of hydrological models, we recommend specific SDHIs that are suitable for assessing the drought hazard for (1) river ecosystems, (2) water users without access to large reservoirs, and (3) water users with access to large reservoirs, as well as being suitable for informing reservoir managers. These SDHIs include both drought magnitude and severity indicators that differ by the temporal averaging period and the habituation of the risk system to reduced water availability. Depending on the habituation of the risk system, drought magnitude is best quantified either by the relative deviation from the mean or by the return period of the streamflow value that is based on the frequency of non-exceedance. To compute the return period, we favor empirical percentiles over the standardized streamflow indicator as the former do not entail uncertainties due to the fitting of a probability distribution and can be computed for all streamflow time series. Drought severity should be assessed with indicators that imply habituation to a certain degree of interannual variability, to a certain reduction from mean streamflow, and to the ability to fulfill human water demand and environmental flows. Reservoir managers are best informed by the SDHIs of the grid cell that represents inflow into the reservoir. The DEWSs must provide comprehensive and clear explanations about the suitability of the provided indicators for specific risk systems.