Drought propagation through the terrestrial hydrological cycle is associated with a change in drought characteristics (duration and deficit), moving from precipitation via soil moisture to discharge. Here we investigate climate controls on drought propagation with a modeling experiment in 1271 virtual catchments that differ only in climate type. For these virtual catchments we studied the bivariate distribution of drought duration and standardized deficit for the variables precipitation, soil moisture, and discharge. We found that for meteorological drought (below‐normal precipitation), the bivariate distributions of drought characteristics have a linear shape in all climates and are thus not affected by seasonality in climate. Despite the linear shape of meteorological drought, soil moisture drought (below‐normal storage in the unsaturated zone) and hydrological drought (below‐normal water availability in aquifers, lakes, and/or streams) show strongly nonlinear shapes in drought characteristics in climates with a pronounced seasonal cycle in precipitation and/or temperature. These seasonality effects on drought propagation are found in monsoonal, savannah, and Mediterranean climate zones. In these regions, both soil moisture and discharge show deviating shapes in drought characteristics. The effect of seasonality on drought propagation is even stronger in cold seasonal climates (i.e., at high latitudes and altitudes), where snow accumulation during winter prevents recovery from summer hydrological drought, and deficit increases strongly with duration. This has important implications for water resources management in seasonal climates, which cannot solely rely on meteorology‐based indices as proxies for hydrological drought duration and deficit and need to include seasonal variation in both precipitation and temperature in hydrological drought forecasting.

Abstract. Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata ("Factors Affecting Runoff") of the UK National River Flow Archive (NRFA). A screening approach was applied on the streamflow records to identify human-influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in (1) the relationship between streamflow drought duration and the base flow index, BFI (specifically, BFIHOST, the BFI predicted from the hydrological properties of soils), (2) the correlation between streamflow and precipitation and (3) the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e. an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of their records was found for some of the catchments affected by groundwater abstractions and a decrease in streamflow drought occurrence for some of the catchments with either reservoirs or groundwater abstractions. In conclusion, the proposed screening approaches were sometimes successful in identifying streamflow records with deviating drought characteristics that are likely related to different human influences. However, a quantitative attribution of the impact of human influences on streamflow drought characteristics requires more detailed case-by-case information about the type and degree of all different human influences. Given that, in many countries, such information is often not readily accessible, the approaches adopted here could provide useful in targeting future efforts. In England and Wales specifically, the catchments with deviating streamflow drought characteristics identified in this study could serve as the starting point of detailed case study research.

Precipitation‐based drought indices are most commonly used in drought monitoring and early warning systems whereas impacts of drought are often related to other domains of the hydrological cycle such as streamflow. Precipitation droughts do not always coincide with streamflow droughts, as the propagation from precipitation to streamflow is affected by climate, catchment properties, and human influences. For monitoring in ungauged catchments it is the question to what extent drought indices solely based on precipitation or other (more recently developed) meteorological drought indices that include evaporation or snowmelt, have a stronger correlation with streamflow, and whether this correlation is weaker in catchments where streamflow is altered by human influences. Results of a correlation exercise between various meteorological drought indices and streamflow showed that the strongest correlation was often found for meteorological drought indices that include evaporation (especially in drier climates) or snow processes (especially in colder climates). Most catchments with an indicated presence of human influences showed a maximum correlation between meteorological drought indices and streamflow that was comparable in strength to the same correlation for catchments with near‐natural flow. However, up to 15% of catchments with an indicated presence of human influences show weaker correlations. Drought indices derived from these influenced records with a weaker correlation do not necessarily correspond to reported drought impacts. In conclusion, knowing which meteorological drought index has the strongest correlation with streamflow in different climate zones has the potential of improving large‐scale drought monitoring and early warning systems in ungauged areas or regions that lack real‐time streamflow availability.

Abstract. Oceanic-atmospheric climate modes, such as El Niño-Southern Oscillation (ENSO), are known to affect the local streamflow regime in many rivers around the world. A new method is proposed to incorporate climate mode information into the well-known ensemble streamflow prediction (ESP) method for seasonal forecasting. The ESP is conditioned on an ENSO index in two steps. First, a number of original historical ESP traces are selected based on similarity between the index value in the historical year and the index value at the time of forecast. In the second step, additional ensemble traces are generated by a stochastic ENSOconditioned weather resampler. These resampled traces compensate for the reduction of ensemble size in the first step and prevent degradation of skill at forecasting stations that are less affected by ENSO. The skill of the ENSO-conditioned ESP is evaluated over 50 years of seasonal hindcasts of streamflows at three test stations in the Columbia River basin in the US Pacific Northwest. An improvement in forecast skill of 5 to 10 % is found for two test stations. The streamflows at the third station are less affected by ENSO and no change in forecast skill is found here.

Abstract. Numerous indices exist for the description of hydrological drought. The EURO FRIEND-Water Low flow and Drought Group has repeatedly discussed changing paradigms in the perception and use of existing and emerging new indices for hydrological drought identification and characterization. Group members have also tested the communication of different indices to stakeholders in several national and international transdisciplinary research projects. This contribution presents the experience gained with regard to the purpose and applicability of different classes of drought indices. A recent paradigm shift is the use of anomalies, traditionally from climatology, in hydrology. For instance, anomaly-based indices, such as the Standardized Streamflow Index (SSI) and the variable threshold level method to define streamflow deficiencies, are used increasingly for real-time monitoring. How these indices relate to low flows and their impacts may have become less clear as a result. Assessments of the severity of a particular drought may also differ depending on whether return periods based on traditional low flow or drought frequency analyses or whether SSI time series index values are used. These experiences call for a systematic comparison, classification and evaluation of different low flow and drought indices and their usages.

The streamflow drought hazard can be characterized in a variety of ways, including using different indices. Traditionally, percentile-based indices, such as Q95 (the flow exceeded 95% of time), have been used by the hydrological community. Recently, the use of anomaly indices such as the Standardized Streamflow Index (SSI), a probability index-based approach adopted from the climatological community, has increased in popularity. The SSI can be calculated based on various (non)parametric methods. Up to now, there is no consensus which method to use. This study aims to raise awareness how the inherent sensitivity of the SSI to the used method influences derived drought characteristics. We compared SSI time series computed with seven different probability distributions and two fitting methods as well as with different nonparametric methods for 369 rivers across Europe. Results showed that SSI time series and associated drought characteristics are indeed sensitive to the method of choice. A resampling experiment demonstrated the sensitivity of the parametric SSI to properties of both the low and high end of the sample. Such sensitivities might hinder a fair comparison of drought in space and time and highlight the need for a clear recommendation which method to use. We could recommend overall suitable methods, for example, from the parametric approaches, the Tweedie distribution has several advantageous properties such as a low rejection rate (2%) and a lower bound at zero. However, the most suitable method depends on the used evaluation criteria. Rather, we stress that shown approach-specific sensitivities and uncertainties should be carefully considered.

Abstract. Human influences can affect streamflow drought characteristics and propagation. The question is where, when and why? To answer these questions, the impact of different human influences on streamflow droughts were assessed in England and Wales, across a broad range of climate and catchments conditions. We used a dataset consisting of catchments with near-natural flow as well as catchments for which different human influences have been indicated in the metadata ("Factors Affecting Runoff") of the UK National River Flow Archive (NRFA). A screening approach was applied on the streamflow records to identify human influenced records with drought characteristics that deviated from those found for catchments with near-natural flow. Three different deviations were considered, specifically deviations in: 1) the relationship between streamflow drought duration and the Base Flow Index; 2) the correlation between streamflow and precipitation and 3) the temporal occurrence of streamflow droughts compared to precipitation droughts, i.e., an increase or decrease in streamflow drought months relative to precipitation drought months over the period of record. The identified deviations were then related to the indicated human influences. Results showed that the majority of catchments for which human influences were indicated did not show streamflow drought characteristics that deviated from those expected under near-natural conditions. For the catchments that did show deviating streamflow drought characteristics, prolonged streamflow drought durations were found in some of the catchments affected by groundwater abstractions. Weaker correlations between streamflow and precipitation were found for some of the catchments with reservoirs, water transfers or groundwater augmentation schemes. An increase in streamflow drought occurrence towards the end of record was found for some of the catchments affected by groundwater abstractions and a decrease in streamflow drought occurrence for some of the catchments with either reservoirs or groundwater abstractions. In conclusion, the proposed screening approaches were successful in identifying streamflow records with deviating drought characteristics that are likely related to different human influences. However, a quantitative attribution of the impact of human influences on streamflow drought characteristics requires more detailed case by case information about the type and degree of all different human influences. Given that, in many countries, such information is often not readily accessible, the approach adopted here could provide useful in targeting future efforts. In England and Wales specifically, the catchments with deviating streamflow drought characteristics identified in this study could serve as the starting point of detailed case study research.

Abstract. Droughts are multidimensional hazards that can lead to substantial environmental and societal impacts. To understand causes and impacts, multiple perspectives need to be considered. Many studies have identified past drought events and investigated drought propagation from meteorological droughts via soil moisture to hydrological droughts, and some studies have included the impacts of these different types of drought. However, it is not certain whether the increased frequency and severity of drought events in the past decade is unprecedented in recent history. Therefore, we analyze different droughts and their impacts in a regional context using a multidisciplinary approach. We compile a comprehensive and long-term dataset to investigate possible temporal patterns in drought occurrence and place recent drought events into a historical context. We assembled a dataset of drought indices and recorded impacts over the last 218 years in southwestern Germany. Meteorological and river-flow indices were used to assess the natural drought dynamics. In addition, tree-ring data and recorded impacts were utilized to investigate drought events from an ecological and social perspective. Since 1801, 20 extreme droughts have been identified as common extreme events when applying the different indices. All events were associated with societal impacts. Our multi-dataset approach provides insights into similarities but also the unique aspects of different drought indices.