s u m m a r y Impacts of a drought are generally dependent on the severity of the hydrological drought event, which can be expressed by streamflow drought duration or deficit volume. For prediction and the selection of drought sensitive regions, it is crucial to know how streamflow drought severity relates to climate and catchment characteristics. In this study we investigated controls on drought severity based on a comprehensive Austrian dataset consisting of 44 catchments with long time series of hydrometeorological data (on average around 50 year) and information on a large number of physiographic catchment characteristics. Drought analysis was performed with the variable threshold level method and various statistical tools were applied, i.e. bivariate correlation analysis, heatmaps, linear models based on multiple regression, varying slope models, and automatic stepwise regression. Results indicate that streamflow drought duration is primarily controlled by storage, quantified by the Base Flow Index or by a combination of catchment characteristics related to catchment storage and release, e.g. geology and land use. Additionally, the duration of dry spells in precipitation is important for streamflow drought duration. Hydrological drought deficit, however, is governed by average catchment wetness (represented by mean annual precipitation) and elevation (reflecting seasonal storage in the snow pack and glaciers). Our conclusion is that both drought duration and deficit are governed by a combination of climate and catchment control, but not in a similar way. Besides meteorological forcing, storage is important; storage in soils, aquifers, lakes, etc. influences drought duration and seasonal storage in snow and glaciers influences drought deficit. Consequently, the spatial variation of hydrological drought severity is highly dependent on terrestrial hydrological processes.

Abstract. The summer drought of 2015 affected a large portion of continental Europe and was one of the most severe droughts in the region since summer 2003. The summer of 2015 was characterized by exceptionally high temperatures in many parts of central and eastern Europe, with daily maximum temperatures 2 °C higher than the seasonal mean (1971–2000) over most of western Europe, and more than 3 °C higher in the east. It was the hottest and climatologically driest summer over the 1950–2015 study period for an area stretching from the eastern Czech Republic to Ukraine. For Europe, as a whole, it is among the six hottest and driest summers since 1950. High evapotranspiration rates combined with a lack of precipitation affected soil moisture and vegetation and led to record low river flows in several major rivers, even beyond the drought-hit region. The 2015 drought developed rather rapidly over the Iberian Peninsula, France, southern Benelux and central Germany in May and reached peak intensity and spatial extent by August, affecting especially the eastern part of Europe. Over the summer period, there were four heat wave episodes, all associated with persistent blocking events. Upper-level atmospheric circulation over Europe was characterized by positive 500 hPa geopotential height anomalies flanked by a large negative anomaly to the north and west (i.e., over the central North Atlantic Ocean extending to northern Fennoscandia) and another center of positive geopotential height anomalies over Greenland and northern Canada. Simultaneously, the summer sea surface temperatures (SSTs) were characterized by large negative anomalies in the central North Atlantic Ocean and large positive anomalies in the Mediterranean basin. Composite analysis shows that the western Mediterranean SST is strongly related to the occurrence of dry and hot summers over the last 66 years (especially over the eastern part of Europe). The lagged relationship between the Mediterranean SST and summer drought conditions established in this study can provide valuable skill for the prediction of drought conditions over Europe on interannual to decadal timescales.

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Abstract. In 2015 large parts of Europe were affected by drought. In this paper, we analyze the hydrological footprint (dynamic development over space and time) of the drought of 2015 in terms of both severity (magnitude) and spatial extent and compare it to the extreme drought of 2003. Analyses are based on a range of low flow and hydrological drought indices derived for about 800 streamflow records across Europe, collected in a community effort based on a common protocol. We compare the hydrological footprints of both events with the meteorological footprints, in order to learn from similarities and differences of both perspectives and to draw conclusions for drought management. The region affected by hydrological drought in 2015 differed somewhat from the drought of 2003, with its center located more towards eastern Europe. In terms of low flow magnitude, a region surrounding the Czech Republic was the most affected, with summer low flows that exhibited return intervals of 100 years and more. In terms of deficit volumes, the geographical center of the event was in southern Germany, where the drought lasted a particularly long time. A detailed spatial and temporal assessment of the 2015 event showed that the particular behavior in these regions was partly a result of diverging wetness preconditions in the studied catchments. Extreme droughts emerged where preconditions were particularly dry. In regions with wet preconditions, low flow events developed later and tended to be less severe. For both the 2003 and 2015 events, the onset of the hydrological drought was well correlated with the lowest flow recorded during the event (low flow magnitude), pointing towards a potential for early warning of the severity of streamflow drought. Time series of monthly drought indices (both streamflow- and climate-based indices) showed that meteorological and hydrological events developed differently in space and time, both in terms of extent and severity (magnitude). These results emphasize that drought is a hazard which leaves different footprints on the various components of the water cycle at different spatial and temporal scales. The difference in the dynamic development of meteorological and hydrological drought also implies that impacts on various water-use sectors and river ecology cannot be informed by climate indices alone. Thus, an assessment of drought impacts on water resources requires hydrological data in addition to drought indices based solely on climate data. The transboundary scale of the event also suggests that additional efforts need to be undertaken to make timely pan-European hydrological assessments more operational in the future.

Abstract:In this study we examine three seasonality indices for their potential in regionalizing low flows. The indices are seasonality histograms (SHs) that represent the monthly distribution of low flows, a cyclic seasonality index (SI) that represents the average timing of low flows within a year, and the seasonality ratio (SR), which is the ratio of summer and winter low flows. The rationale of examining these indices is the recognition that summer and winter low flows are subject to important differences in the underlying hydrological processes. We analyse specific low flow discharges q 95 , i.e. the specific discharge that is exceeded on 95% of all days at a particular site. Data from 325 subcatchments in Austria, ranging in catchment area from 7 to 963 km 2 , are used in the analysis. In a first step, three seasonality indices are compared. Their spatial patterns can be interpreted well on hydrological grounds. In a second step, the indices are used to classify the catchments into two, three, and eight regions based on different combinations of the indices. In a third step, the value of the seasonality indices for low flow regionalization is examined by comparing the crossvalidation performance of multiple regressions between low flows and catchment characteristics. The regressions make use of the three seasonality-based classifications. The results indicate that grouping the study area into two regions and three regions and separate regressions in each region gives the best performance. A global regression model yields the lowest performance and a global regression model that uses different calibration coefficients in each of the eight regions only performs slightly better. This suggests that separate regression models in each of the regions are to be preferred over a global model in order to represent differences in the way catchment characteristics are related to low flows.