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Human influences threaten environmental flows directly or indirectly through groundwater abstraction. In alluvial geological settings, these may affect the contributions from groundwater-sustaining streamflow during dry summer months. The Dreisam River valley in southwest Germany represents a typical case where recurrent hydrological drought events between 2015 and 2022 have led to interruptions of longitudinal connectivity in the stream network. When and where vertical connectivity changes and where the streambed dries out have therefore become important questions. To help answer them, zero water level (ZWL) occurrences were previously measured at 20 locations in the river network during the drought of 2020, but they revealed high variability. This study therefore aimed to develop a methodology that allows the connectivity to be assessed along the entire stream network, i.e. by employing a numerical groundwater model to obtain the spatial distribution of the exchange flow between groundwater and surface water along the river. A reference model simulation for the period 2010–2022 assumed near-natural conditions. Stress test scenario model runs then imposed either an altered recharge regime or a set of introduced groundwater abstraction wells or both. To gain confidence in the model, ZWL patterns are compared to observations of dry riverbed locations in 2020, and the model generally reproduces the observed relative drying. Modelled exchange flows of the stress tests were then compared against the reference simulation. A set of specific metrics combining longitudinal and vertical connectivity is introduced for this task. The results of the stress test model runs show stronger changes of vertical connectivity in response to groundwater (GW) abstraction than to the imposed recharge stress. Reaches are identified where the effects of the stresses are particularly strong. Nevertheless, these results have to be interpreted within the limits of model realism and uncertainty. For more model realism, a number of improvements will be needed such as a higher-resolution parametrization of the riverbed's hydraulic conductivities and better coupling to contributions from hillslopes; for a quantification of the uncertainties, a systematic sensitivity analysis would be required. The study introduces a framework for modelling stress tests and metrics for surface water–groundwater interaction that can be transferred to other cases. It also suggests that even if not all influences can be modelled, the approach may help inform a resilient management of water resources under multiple stresses.

Drought estimates in terms of physically measurable variables such as precipitation deficit or streamflow deficit are key knowledge for an effective water management. How these deficits vary with the drought event severity indicated by commonly used standardized indices is often unclear. Drought severity calculated from the drought index does not necessarily correspond to the same amount of deficit in precipitation or streamflow at different regions, and it is different for each month in the same region. We investigate drought to remove this disadvantage of the index-based drought intensity–duration–frequency (IDF) curves and develop IDF curves in terms of the associated deficit. In order to study the variation of deficits, we use the link between precipitation and streamflow and the associated indices, the Standardized Precipitation Index (SPI) and the Standardized Streamflow Index (SSI). More specifically, the analysis relies on frequency analysis combined with the total probability theorem applied to the critical drought severity. The critical drought has varying durations, and it is extracted from dry periods. IDF curves in terms of precipitation and streamflow deficits for the most severe drought of each drought duration in each year are then subject to comparison of statistical characteristics of droughts for different return periods. Precipitation and streamflow data from two catchments, the Seyhan River (Türkiye) and the Kocher River (Germany), provide examples for two climatically and hydrologically different cases. A comparison of the two cases allows a similar method to be tested in different hydrological conditions. We found that precipitation and streamflow deficits vary systematically, reflecting seasonality and the magnitude of precipitation and streamflow characteristics of the catchments. Deficits change from one month to another at a given station. Higher precipitation deficits were observed in winter months compared to summer months. Additionally, we assessed observed past major droughts experienced in both catchments on the IDF curves, which show that the major droughts have return periods at the order of 100 years at short durations. This coincides with the observation in the catchments and shows the applicability of the IDF curves. The IDF curves can be considered a tool for using in a range of specific activities of agriculture, ecology, industry, energy and water supply, etc. This is particularly important to end users and decision-makers to act against the drought quickly and precisely in a more physically understandable manner.

As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed review-style reports about the events and key processes between the two events of a pair; (2) the key data table containing variables that assess the indicators which characterize management shortcomings, hazard, exposure, vulnerability, and impacts of all events; and (3) a table of the indicators of change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators of change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses, e.g. focused on causal links between risk management; changes in hazard, exposure and vulnerability; and flood or drought impacts. The data can also be used for the development, calibration, and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al., 2023, https://doi.org/10.5880/GFZ.4.4.2023.001).

Droughts are natural hazards that lead to severe impacts in the agricultural sector. Mountain regions are thought to have abundant water, but have experienced unprecedented drought conditions as climate change is affecting their environments more rapidly than other places. The effect radiates by reducing water availability well beyond the mountains' geographical locations. This study aims to improve the understanding of agriculture's vulnerability to drought in Europe's pre-Alpine region, considering two case studies that have been severely impacted in the past. We applied a mixed-method approach combining the knowledge of regional experts with quantitative data analyses in order to define the region-specific vulnerability based on experts' identified factors. We implemented two aggregation methods by combining the vulnerability factors that could be supported with subregional data. Whereas the equal weighting method combines all factors with the same weight, the expert weighting method combines the factors with varying weight based on the expert's opinion. These two methods resulted in vulnerability maps with the expert weighting showing a higher vulnerability, and partly relocating the medium and lower vulnerabilities to other subregions within the case study regions. In general, the experts confirmed the resulting subregions with higher vulnerability. They also acknowledged the value of mapping vulnerability by adopting different aggregation methods confirming that this can serve as a sensitivity analysis. The identified factors contributing most to the regions' vulnerability point to the potential of adaptation strategies decreasing the agriculture's vulnerability to drought that could enable better preparedness. Apart from region-specific differences, in both study regions the presence of irrigation infrastructure and soil texture are among the most important conditions that could be managed to some extent in order to decrease the regions' vulnerability. Throughout the analyses, the study benefited from the exchange with the experts by getting an in-depth understanding of the regional context with feedback relations between the factors contributing to vulnerability. Qualitative narratives provided during the semi-structured interviews supported a better characterization of local vulnerability conditions and helped to better identify quantitative indicators as proxies to describe the selected vulnerability factors. Thus, we recommend applying this mixed-method approach to close the gap between science and practitioners.

Droughts often have a severe impact on the environment, society, and the economy. The variables and scales that are relevant to understand the impact of drought motivated this study, which compared hazard and propagation characteristics, as well as impacts, of major droughts between 1990 and 2019 in southwestern Germany. We bring together high-resolution datasets of air temperature, precipitation, soil moisture simulations, and streamflow and groundwater level observations, as well as text-based information on drought impacts. Various drought characteristics were derived from the hydrometeorological and drought impact time series and compared across variables and spatial scales. Results revealed different drought types sharing similar hazard and impact characteristics. The most severe drought type identified is an intense multi-seasonal drought type peaking in summer, i.e., the events in 2003, 2015, and 2018. This drought type appeared in all domains of the hydrological cycle and coincided with high air temperatures, causing a high number of and variability in drought impacts. The regional average drought signals of this drought type exhibit typical drought propagation characteristics such as a time lag between meteorological and hydrological drought, whereas propagation characteristics of local drought signals are variable in space. This spatial variability in drought hazard increased when droughts propagated through the hydrological cycle, causing distinct differences among variables, as well as regional average and local drought information. Accordingly, single variable or regional average drought information is not sufficient to fully explain the variety of drought impacts that occurred, supporting the conclusion that in regions as diverse as the case study presented here, large-scale drought monitoring needs to be complemented by local drought information to assess the multifaceted impact of drought.

Drought affects the European Alpine mountain region, despite a humid climate. Droughts' damaging character in the past and increasing probability in future projections call for an understanding of drought impacts in the mountain regions. The European Drought Impact report Inventory (EDII) collects text reports on negative drought impacts. This study presents a considerably updated EDII focusing on the Alpine region. This first version release of an Alpine Drought Impact report Inventory (EDIIALPS) classifies impact reports into categories covering various affected sectors and enables comparisons of the drought impact characteristics. We analysed the distribution of reported impacts on the spatial, temporal and seasonal scale and by drought type for soil moisture drought and hydrological drought. For the spatial analysis, we compared the impact data located in the Alpine region to the whole of Europe. Furthermore, we compared impact data between different climatic and altitudinal domains (the northern region vs. the southern region and the pre-Alpine region vs. the high-altitude region) and between the Alpine countries. Compared to the whole of Europe, in the Alpine region agriculture and livestock farming impacts are even more frequently reported, especially in the southern region. Public water supply is the second most relevant sector but overall less prominent compared to Europe, especially in spring when snowmelt mitigates water shortages. Impacts occur mostly in summer and early autumn, with a delay between those impacts initiated by soil moisture and those initiated by hydrological drought. The high-altitude region shows this delay the strongest. From 1975 to 2020, the number of archived reports increases, with substantially more impacts noted during the drought events of 1976, 2003, 2015 and 2018. Moreover, reported impacts diversify from agricultural dominance to multi-faceted impact types covering forestry, water quality, industry and so forth. Though EDIIALPS is biased by reporting behaviour, the region-specific results of negative drought impacts across the water-rich European mountain region demonstrate the need to move from emergency response to prevention and preparedness actions. These may be guided by EDIIALPS' insights to regional patterns, seasons and drought types.

Warm and dry summer days can lead to low streamflow due to a lack of rainfall and increased evaporation. In glacierized catchments, however, such periods can lead to a very different hydrological response as glaciers can supply an increased amount of meltwater, thereby compensating for the rainfall deficits. Here, we analyzed glacier-fed streamflow responses to warm and dry (WD) periods in long-term streamflow observations (>50 years). WD events during summer (June–September) were analyzed for catchments with varying glacier cover in western Canada, southwestern Norway, and the European Alps. WD events were defined by days with temperatures above a daily varying threshold, based on the 80th percentile of the respective long-term temperature data for that day in the year, and daily precipitation sums below a fixed threshold ( mm d−1) for a minimum duration of 7 d. Streamflow responses to these WD events were expressed as level of compensation (C) and were calculated as the event streamflow relative to the long-term streamflow regime. C≥100 % indicates that increased melt and other catchment storages could compensate, or even overcompensate, the rainfall deficit and increased evaporation. Results showed a wide range of compensation levels, both between catchments and between different WD events in a particular catchment. C was, in general, higher than 100 % for catchments with a relative glacier cover higher than 5 %–15 %, depending on region and month. June was the month with highest compensation levels, but this was likely more influenced by snowmelt than by glacier melt. For WD events in September, C was still higher than 100 % in many catchments, which likely indicates the importance of glacier melt as a streamflow contributor in late summer. There was a considerable range in C of different WD events for groups of catchments with similar glacier cover. This could be partly explained by antecedent conditions, such as the amount of snow fallen in the previous winter and the streamflow conditions 30 d before the WD event. Some decreasing trends in C were evident, especially for catchments in western Canada and the European Alps. Overall, our results suggest that glaciers do not compensate straightforwardly, and the range in compensation levels is large. The different streamflow components – glacier, snow and rain – and their variations are important for the buffering capacity and the compensating effect of glaciers in these high mountain water systems.

Wet-running multi-plate clutches fulfill a major safety-relevant role in drive trains and, as a result, damage to and failure of the clutch system must be strictly avoided, especially spontaneous damage. This paper deals with spontaneous damage to wet-running multi-plate clutches with paper friction lining with respect to spontaneous damage behavior. The paper presents a comparison method, by means of which the load-carrying capacity of various multi-plate clutches can be compared with regard to spontaneous damage based on experimental data and recommendations can be formulated. The experiments were performed on six different clutch variants, and the results were examined for significant differences. Various statistical tools were used to detect statistically significant variations. The experiments showed that higher load levels have a greater dispersion of the measured values, thus making comparisons more difficult. In the clutch variants investigated, significant changes in spontaneous damage behavior could only be detected when the cooling plate thickness or the carbon content was changed.

Groundwater is the main source of freshwater and maintains streamflow during drought. Potential future groundwater and baseflow drought hazards depend on the systems' sensitivity to altered recharge conditions. We performed groundwater model experiments using three different generic stress tests to estimate the groundwater and baseflow drought sensitivity to changes in recharge. The stress tests stem from a stakeholder co-design process that specifically followed the idea of altering known drought events from the past, i.e. asking whether altered recharge could have made a particular event worse. Across Germany, groundwater responses to the stress tests are highly heterogeneous, with groundwater heads in the north more sensitive to long-term recharge and in the Central German Uplands to short-term recharge variations. Baseflow droughts are generally more sensitive to intra-annual dynamics, and baseflow responses to the stress tests are smaller compared to the groundwater heads. The groundwater drought recovery time is mainly driven by the hydrogeological conditions, with slow (fast) recovery in the porous (fractured rock) aquifers. In general, a seasonal shift of recharge (i.e. less summer recharge and more winter recharge) will have lesser effects on groundwater and baseflow drought severity. A lengthening of dry spells might cause much stronger responses, especially in regions with slow groundwater response to precipitation. Water management may need to consider the spatially different sensitivities of the groundwater system and the potential for more severe groundwater droughts in the large porous aquifers following prolonged meteorological droughts, particularly in the context of climate change projections indicating stronger seasonality and more severe drought events.

The stable isotopes of oxygen and hydrogen, 18O and 2H, provide information on water flow pathways and hydrologic catchment functioning. Here a data set of time series data on precipitation and streamflow isotope composition in medium-sized Swiss catchments, CH-IRP, is presented that is unique in terms of its long-term multi-catchment coverage along an alpine to pre-alpine gradient. The data set comprises fortnightly time series of both δ2H and δ18O as well as deuterium excess from streamflow for 23 sites in Switzerland, together with summary statistics of the sampling at each station. Furthermore, time series of δ18O and δ2H in precipitation are provided for each catchment derived from interpolated data sets from the ISOT, GNIP and ANIP networks. For each station we compiled relevant metadata describing both the sampling conditions and catchment characteristics and climate information. Lab standards and errors are provided, and potentially problematic measurements are indicated to help the user decide on the applicability for individual study purposes. For the future, the measurements are planned to be continued at 14 stations as a long-term isotopic measurement network, and the CH-IRP data set will, thus, continuously be extended. The data set can be downloaded from data repository Zenodo at https://doi.org/10.5281/zenodo.4057967 (Staudinger et al., 2020).

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.

Precipitation deficits and temperature anomalies are often the main cause for low flows and summer streamflow droughts. However, where groundwater is the main contribution to sustain water availability and ecological integrity during dry spells, the role of recharge and catchment storage is crucial to understand streamflow drought sensitivity. Here we introduce recharge stress tests as complement to climate scenarios to characterize and quantify the streamflow drought sensitivities of catchments. The stress tests are presented by applying them to six headwater catchments in Switzerland with various catchment and streamflow characteristics. The stress tests drive the bucket-type hydrological model HBV in a framework, in which pre-drought recharge conditions can be decreased to test how catchments respond to and recover from drought. We identified an upper limit of stress test durations around 12 months as indicator of maximum recharge- and storage-memory for the study catchments. Varying response on stress testing across the catchments suggests different storage properties and thus different recovery times from drought. From the stress test simulations, we found up to 200 d longer summer streamflow droughts with additional streamflow deficits which account for up to 40 d of median flow. Using a worst-case pre-drought recharge in stress test simulation leads to minimum flow reductions of 50 %–80 % compared with the reference simulation. Based on the results we conclude with recommendations for further stress test research in drought hydrology.

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.

Understanding components of the total streamflow is important to assess the ecological functioning of rivers. Binary or two-component separation of streamflow into a quick and a slow (often referred to as baseflow) component are often based on arbitrary choices of separation parameters and also merge different delayed components into one baseflow component and one baseflow index (BFI). As streamflow generation during dry weather often results from drainage of multiple sources, we propose to extend the BFI by a delayed-flow index (DFI) considering the dynamics of multiple delayed contributions to streamflow. The DFI is based on characteristic delay curves (CDCs) where the identification of breakpoint (BP) estimates helps to avoid rather subjective separation parameters and allows for distinguishing four types of delayed streamflow contributions. The methodology is demonstrated using streamflow records from a set of 60 mesoscale catchments in Germany and Switzerland covering a pronounced elevation gradient of roughly 3000 m. We found that the quickflow signal often diminishes earlier than assumed by two-component BFI analyses and distinguished a variety of additional flow contributions with delays shorter than 60 d. For streamflow contributions with delays longer than 60 d, we show that the method can be used to assess catchments' water sustainability during dry spells. Colwell's predictability (PT), a measure of streamflow periodicity and sustainability, was applied to attribute the identified delay patterns to dynamic catchment storage. The smallest dynamic storages were consistently found for catchments between approx. 800 and 1800 m a.s.l. Above an elevation of 1800 m the DFI suggests that seasonal snowpack provides the primary contribution, whereas below 800 m groundwater resources are most likely the major streamflow contributions. Our analysis also indicates that dynamic storage in high alpine catchments might be large and is overall not smaller than in lowland catchments. We conclude that the DFI can be used to assess the range of sources forming catchments' storages and to judge the long-term sustainability of streamflow.

Alpine catchments show a high sensitivity to climate variation as they include the elevation range of the snow line. Therefore, the correct representation of climate variables and their interdependence is crucial when describing or predicting hydrological processes. When using climate model simulations in hydrological impact studies, forcing meteorological data are usually downscaled and bias corrected, most often by univariate approaches such as quantile mapping of individual variables, neglecting the relationships that exist between climate variables. In this study we test the hypothesis that the explicit consideration of the relation between air temperature and precipitation will affect hydrological impact modelling in a snow-dominated mountain environment. Glacio-hydrological simulations were performed for two partly glacierized alpine catchments using a recently developed multivariate bias correction method to post-process EURO-CORDEX regional climate model outputs between 1976 and 2099. These simulations were compared to those obtained by using the common univariate quantile mapping for bias correction. As both methods correct each climate variable's distribution in the same way, the marginal distributions of the individual variables show no differences. Yet, regarding the interdependence of precipitation and air temperature, clear differences are notable in the studied catchments. Simultaneous correction based on the multivariate approach led to more precipitation below air temperatures of 0 ∘C and therefore more simulated snowfall than with the data of the univariate approach. This difference translated to considerable consequences for the hydrological responses of the catchments. The multivariate bias-correction-forced simulations showed distinctly different results for projected snow cover characteristics, snowmelt-driven streamflow components, and expected glacier disappearance dates. In all aspects – the fraction of precipitation above and below 0 ∘C, the simulated snow water equivalents, glacier volumes, and the streamflow regime – simulations resulting from the multivariate-corrected data corresponded better with reference data than the results of univariate bias correction. Differences in simulated total streamflow due to the different bias correction approaches may be considered negligible given the generally large spread of the projections, but systematic differences in the seasonally delayed streamflow components from snowmelt in particular will matter from a planning perspective. While this study does not allow conclusive evidence that multivariate bias correction approaches are generally preferable, it clearly demonstrates that incorporating or ignoring inter-variable relationships between air temperature and precipitation data can impact the conclusions drawn in hydrological climate change impact studies in snow-dominated environments.

Drought is an important natural hazard with large impacts on society. Changes in drought characteristics have been studied for different parts of the hydrological cycle, but insights into changes of groundwater resources are obscured due to the lack of long-term observations and large heterogeneity of hydrogeological conditions. Moreover, predicted future changes in precipitation are uncertain and have a lagged effect on streamflow and groundwater. We investigated past changes and potential future changes in catchment baseflow as a reflection of groundwater drought for 338 headwater catchments across Germany based on catchments' characteristic response times. First, baseflow dynamics as a proxy of groundwater storage and outflow on a catchment scale were derived from streamflow records and related to precipitation input. Second, past trends in baseflow minima were calculated and attributed to climate and catchment controls. Last, response times and the timing of yearly baseflow minima were combined into estimates of the sensitivity to future precipitation changes. Baseflow response times of the studied headwaters are heterogenous across Germany, ranging from a few months to several years, and depend significantly on hydrogeological conditions. Few significant trends were found in past baseflow minima, and trends are highly dependent on the period of analysis. Based on the assumption of a typical regional scenario of increasing winter precipitation and decreasing summer precipitation, increases in hydrological drought hazard or no changes are projected for most parts of Germany. Catchments with longer response times can buffer interannual precipitation shifts, whereas catchments with fractured rocks are sensitive to summer precipitation decreases. These results urge for a surface water and groundwater management based on local groundwater response to precipitation and help to assess impacts of climate change on overall water supply.

Glaciers play an important role in high-mountain hydrology. While changing glacier areas are considered of highest importance for the understanding of future changes in runoff, glaciers are often only poorly represented in hydrological models. Most importantly, the direct coupling between the simulated glacier mass balances and changing glacier areas needs feasible solutions. The use of a complex glacier model is often not possible due to data and computational limitations. The Δh parameterization is a simple approach to consider the spatial variation of glacier thickness and area changes. Here, we describe a conceptual implementation of the Δh parameterization in the semi-distributed hydrological model HBV-light, which also allows for the representation of glacier advance phases and for comparison between the different versions of the implementation. The coupled glacio-hydrological simulation approach, which could also be implemented in many other semi-distributed hydrological models, is illustrated based on an example application.

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.

Glaciers are essential hydrological reservoirs, storing and releasing water at various timescales. Short-term variability in glacier melt is one of the causes of streamflow droughts, here defined as deficiencies from the flow regime. Streamflow droughts in glacierised catchments have a wide range of interlinked causing factors related to precipitation and temperature on short and long timescales. Climate change affects glacier storage capacity, with resulting consequences for discharge regimes and streamflow drought. Future projections of streamflow drought in glacierised basins can, however, strongly depend on the modelling strategies and analysis approaches applied. Here, we examine the effect of different approaches, concerning the glacier modelling and the drought threshold, on the characterisation of streamflow droughts in glacierised catchments. Streamflow is simulated with the Hydrologiska Byråns Vattenbalansavdelning (HBV-light) model for two case study catchments, the Nigardsbreen catchment in Norway and the Wolverine catchment in Alaska, and two future climate change scenarios (RCP4.5 and RCP8.5). Two types of glacier modelling are applied, a constant and dynamic glacier area conceptualisation. Streamflow droughts are identified with the variable threshold level method and their characteristics are compared between two periods, a historical (1975–2004) and future (2071–2100) period. Two existing threshold approaches to define future droughts are employed: (1) the threshold from the historical period; (2) a transient threshold approach, whereby the threshold adapts every year in the future to the changing regimes. Results show that drought characteristics differ among the combinations of glacier area modelling and thresholds. The historical threshold combined with a dynamic glacier area projects extreme increases in drought severity in the future, caused by the regime shift due to a reduction in glacier area. The historical threshold combined with a constant glacier area results in a drastic decrease of the number of droughts. The drought characteristics between future and historical periods are more similar when the transient threshold is used, for both glacier area conceptualisations. With the transient threshold, factors causing future droughts can be analysed. This study revealed the different effects of methodological choices on future streamflow drought projections and it highlights how the options can be used to analyse different aspects of future droughts: the transient threshold for analysing future drought processes, the historical threshold to assess changes between periods, the constant glacier area to analyse the effect of short-term climate variability on droughts and the dynamic glacier area to model more realistic future discharges under climate change.

Drought management frameworks are dependent on methods for monitoring and prediction, but quantifying the hazard alone is arguably not sufficient; the negative consequences that may arise from a lack of precipitation must also be predicted if droughts are to be better managed. However, the link between drought intensity, expressed by some hydrometeorological indicator, and the occurrence of drought impacts has only recently begun to be addressed. One challenge is the paucity of information on ecological and socioeconomic consequences of drought. This study tests the potential for developing empirical drought impact functions based on drought indicators (Standardized Precipitation and Standardized Precipitation Evaporation Index) as predictors and text-based reports on drought impacts as a surrogate variable for drought damage. While there have been studies exploiting textual evidence of drought impacts, a systematic assessment of the effect of impact quantification method and different functional relationships for modeling drought impacts is missing. Using Southeast England as a case study we tested the potential of three different data-driven models for predicting drought impacts quantified from text-based reports: logistic regression, zero-altered negative binomial regression (hurdle model), and an ensemble regression tree approach (random forest). The logistic regression model can only be applied to a binary impact/no impact time series, whereas the other two models can additionally predict the full counts of impact occurrence at each time point. While modeling binary data results in the lowest prediction uncertainty, modeling the full counts has the advantage of also providing a measure of impact severity, and the counts were found to be reasonably predictable. However, there were noticeable differences in skill between modeling methodologies. For binary data the logistic regression and the random forest model performed similarly well based on leave-one-out cross validation. For count data the random forest outperformed the hurdle model. The between-model differences occurred for total drought impacts and for two subsets of impact categories (water supply and freshwater ecosystem impacts). In addition, different ways of defining the impact counts were investigated and were found to have little influence on the prediction skill. For all models we found a positive effect of including impact information of the preceding month as a predictor in addition to the hydrometeorological indicators. We conclude that, although having some limitations, text-based reports on drought impacts can provide useful information for drought risk management, and our study showcases different methodological approaches to developing drought impact functions based on text-based data.

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.

Climate classification systems, such as Köppen–Geiger and the aridity index, are used in large-scale drought studies to stratify regions with similar hydro-climatic drought properties. What is currently lacking is a large-scale evaluation of the relation between climate and observed streamflow drought characteristics. In this study we explored how suitable common climate classifications are for differentiating catchments according to their characteristic hydrologic drought duration and whether drought durations within the same climate classes are comparable between different regions. This study uses a dataset of 808 near-natural streamflow records from Europe and the USA to answer these questions. First, we grouped drought duration distributions of each record over different classes of four climate classification systems and five individual climate and catchment controls. Then, we compared these drought duration distributions of all classes within each climate classification system or classification based on individual controls. Results showed that climate classification systems that include absolute precipitation in their classification scheme (e.g., the aridity index) are most suitable for differentiating catchments according to drought duration. However, differences in duration distributions were found for the same climate classes in Europe and the USA. These differences are likely caused by differences in precipitation, in catchment controls as expressed by the base flow index and in differences in climate beyond the total water balance (e.g., seasonality in precipitation), which have been shown to exert a control on drought duration as well. Climate classification systems that include an absolute precipitation control can be tailored to drought monitoring and early warning systems for Europe and the USA to define regions with different sensitivities to hydrologic droughts, which, for example, have been found to be higher in catchments with a low aridity index. However, stratification of catchments according to these climate classification systems is likely to be complemented with information of other climate classification systems (Köppen–Geiger) and individual climate and catchment controls (precipitation and the base flow index), especially in a comparative study between Europe and the USA.

In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows, outflows, and storage changes. Our current inability to adequately analyse and manage drought in many places points to gaps in our understanding and to inadequate data and tools. The Anthropocene requires a new framework for drought definitions and research. Drought definitions need to be revisited to explicitly include human processes driving and modifying soil moisture drought and hydrological drought development. We give recommendations for robust drought definitions to clarify timescales of drought and prevent confusion with related terms such as water scarcity and overexploitation. Additionally, our understanding and analysis of drought need to move from single driver to multiple drivers and from uni-directional to multi-directional. We identify research gaps and propose analysis approaches on (1) drivers, (2) modifiers, (3) impacts, (4) feedbacks, and (5) changing the baseline of drought in the Anthropocene. The most pressing research questions are related to the attribution of drought to its causes, to linking drought impacts to drought characteristics, and to societal adaptation and responses to drought. Example questions include (i) What are the dominant drivers of drought in different parts of the world? (ii) How do human modifications of drought enhance or alleviate drought severity? (iii) How do impacts of drought depend on the physical characteristics of drought vs. the vulnerability of people or the environment? (iv) To what extent are physical and human drought processes coupled, and can feedback loops be identified and altered to lessen or mitigate drought? (v) How should we adapt our drought analysis to accommodate changes in the normal situation (i.e. what are considered normal or reference conditions) over time? Answering these questions requires exploration of qualitative and quantitative data as well as mixed modelling approaches. The challenges related to drought research and management in the Anthropocene are not unique to drought, but do require urgent attention. We give recommendations drawn from the fields of flood research, ecology, water management, and water resources studies. The framework presented here provides a holistic view on drought in the Anthropocene, which will help improve management strategies for mitigating the severity and reducing the impacts of droughts in future.

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, appropriateness of drought indices selection for specific applications, and drought risk assessment.

Drought monitoring and early warning is an important measure to enhance resilience towards drought. While there are numerous operational systems using different drought indicators, there is no consensus on which indicator best represents drought impact occurrence for any given sector. Furthermore, thresholds are widely applied in these indicators but, to date, little empirical evidence exists as to which indicator thresholds trigger impacts on society, the economy, and ecosystems. The main obstacle for evaluating commonly used drought indicators is a lack of information on drought impacts. Our aim was therefore to exploit text-based data from the European Drought Impact report Inventory (EDII) to identify indicators that are meaningful for region-, sector-, and season-specific impact occurrence, and to empirically determine indicator thresholds. In addition, we tested the predictability of impact occurrence based on the best-performing indicators. To achieve these aims we applied a correlation analysis and an ensemble regression tree approach, using Germany and the UK (the most data-rich countries in the EDII) as test beds. As candidate indicators we chose two meteorological indicators (Standardized Precipitation Index, SPI, and Standardized Precipitation Evaporation Index, SPEI) and two hydrological indicators (streamflow and groundwater level percentiles). The analysis revealed that accumulation periods of SPI and SPEI best linked to impact occurrence are longer for the UK compared with Germany, but there is variability within each country, among impact categories and, to some degree, seasons. The median of regression tree splitting values, which we regard as estimates of thresholds of impact occurrence, was around −1 for SPI and SPEI in the UK; distinct differences between northern/northeastern vs. southern/central regions were found for Germany. Predictions with the ensemble regression tree approach yielded reasonable results for regions with good impact data coverage. The predictions also provided insights into the EDII, in particular highlighting drought events where missing impact reports may reflect a lack of recording rather than true absence of impacts. Overall, the presented quantitative framework proved to be a useful tool for evaluating drought indicators, and to model impact occurrence. In summary, this study demonstrates the information gain for drought monitoring and early warning through impact data collection and analysis. It highlights the important role that quantitative analysis with impact data can have in providing "ground truth" for drought indicators, alongside more traditional stakeholder-led approaches.

Drought is a natural hazard that can cause a wide range of impacts affecting the environment, society, and the economy. Providing an impact assessment and reducing vulnerability to these impacts for regions beyond the local scale, spanning political and sectoral boundaries, requires systematic and detailed data regarding impacts. This study presents an assessment of the diversity of drought impacts across Europe based on the European Drought Impact report Inventory (EDII), a unique research database that has collected close to 5000 impact reports from 33 European countries. The reported drought impacts were classified into major impact categories, each of which had a number of subtypes. The distribution of these categories and types was then analyzed over time, by country, across Europe and for particular drought events. The results show that impacts on agriculture and public water supply dominate the collection of drought impact reports for most countries and for all major drought events since the 1970s, while the number and relative fractions of reported impacts in other sectors can vary regionally and from event to event. The analysis also shows that reported impacts have increased over time as more media and website information has become available and environmental awareness has increased. Even though the distribution of impact categories is relatively consistent across Europe, the details of the reports show some differences. They confirm severe impacts in southern regions (particularly on agriculture and public water supply) and sector-specific impacts in central and northern regions (e.g., on forestry or energy production). The protocol developed thus enabled a new and more comprehensive view on drought impacts across Europe. Related studies have already developed statistical techniques to evaluate the link between drought indices and the categorized impacts using EDII data. The EDII is a living database and is a promising source for further research on drought impacts, vulnerabilities, and risks across Europe. A key result is the extensive variety of impacts found across Europe and its documentation. This insight can therefore inform drought policy planning at national to international levels.

Surface climate in Europe is changing and patterns in trends have been found to vary at sub-seasonal scales. This study aims to contribute to a better understanding of these changes across space and time by analysing to what degree observed climatic trends can be attributed to changes in synoptic atmospheric circulation. The relative importance of synoptic circulation changes (i.e. trends in synoptic type frequencies) as opposed to trends in the hydrothermal properties of synoptic types (within-type trends) on precipitation and temperature trends in Europe is assessed on a monthly basis. The study is based on mapping spatial and temporal trend patterns and their variability at a relatively high resolution (0.5° × 0.5°; monthly) across Europe. Gridded precipitation and temperature data (1963–2001) originate from the Watch Forcing Data set and synoptic types are defined by the objective SynopVis Grosswetterlagen (SVG). During the study period, relatively high influence of synoptic circulation changes are found from January to March, contributing to wetting trends in northern Europe and drying in the south. Simultaneously, particularly dry synoptic types get warmer first in south-western Europe in November and/or December and affect most of Europe in March and/or April. Strong influence of synoptic circulation changes is again found in June and August. In general, changes in synoptic circulation has a stronger effect on climate trends in north-western Europe than in the south-east. The exact locations of the strongest influence of synoptic circulation changes vary with the time of year and to some degree between precipitation and temperature. Throughout the year and across the whole of Europe, precipitation and temperature trends are caused by a combination of synoptic circulation changes and within-type changes with their relative influence varying between regions, months and climate variables.

Current drought monitoring and early warning systems use different indicators for monitoring drought conditions and apply different indicator thresholds and rules for assigning drought intensity classes or issue warnings or alerts. Nevertheless, there is little knowledge on the meaning of different hydro-meteorologic indicators for impact occurrence on the ground. To date, there have been very few attempts to systematically characterize the indicator–impact relationship owing to sparse and patchy data on drought impacts. The newly established European Drought Impact report Inventory (EDII) offers the possibility to investigate this linkage. The aim of this study was to explore the link between hydro-meteorologic indicators and drought impacts for the case study area Germany and thus to test the potential of qualitative impact data for evaluating the performance of drought indicators. As drought indicators two climatological drought indices – the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) – as well as streamflow and groundwater level percentiles were selected. Linkage was assessed though data visualization, extraction of indicator values concurrent with impact onset, and correlation analysis between monthly time series of indicator and impact data at the federal state level, and between spatial patterns for selected drought events. The analysis clearly revealed a significant moderate to strong correlation for some states and drought events allowing for an intercomparison of the performance of different drought indicators. Important findings were strongest correlation for intermediate accumulation periods of SPI and SPEI, a slightly better performance of SPEI versus SPI, and a similar performance of streamflow percentiles to SPI in many cases. Apart from these commonalities, the analysis also exposed differences among federal states and drought events, suggesting that the linkage is time variant and region specific to some degree. Concerning "thresholds" for drought impact onset, i.e. indicator values concurrent with past impact onsets, we found that no single "best" threshold value can be identified but impacts occur within a range of indicator values. Nevertheless, the median of the threshold distributions showed differences between northern/northeastern versus southern/southwestern federal states, and among drought events. While the findings strongly depend on data and may change with a growing number of EDII entries in the future, this study clearly demonstrates the feasibility of evaluating hydro-meteorologic variables with text-based impact reports and highlights the value of impact reporting as a tool for monitoring drought conditions.

In recent years Switzerland has experienced some unprecedented drought situations. At a political level solutions have been requested for early recognition of hydrological droughts. A prototype information platform has been developed to guide water resources management during situations where water resources drop below critical levels. The development was steered by stakeholders from national administrations and different economic sectors. Since June 2013 the platform has presented daily updated real-time information on several drought indicators including precipitation, streamflow, lake levels, groundwater levels, soil moisture deficit, snow resources, dryness in forests and stream temperatures. For three basins, ensemble forecasts of runoff, soil moisture, snowpack and groundwater storage have been provided. Furthermore, a nationwide operational hydrological simulation at 600 × 600 m resolution gives indications on local water resources deficits. Information for each variable has been used to create automatic "awareness maps" for nine large regions. Three levels of information with increasing detail and complexity can be accessed by over 180 registered users. The operators of the platform give interpreted comments on the content of the platform each week-day. The test phase of the platform will last until the end of 2014.

In January 2011 a rain-on-snow (RoS) event caused floods in the major river basins in central Europe, i.e. the Rhine, Danube, Weser, Elbe, Oder, and Ems. This event prompted the questions of how to define a RoS event and whether those events have become more frequent. Based on the flood of January 2011 and on other known events of the past, threshold values for potentially flood-generating RoS events were determined. Consequently events with rainfall of at least 3 mm on a snowpack of at least 10 mm snow water equivalent (SWE) and for which the sum of rainfall and snowmelt contains a minimum of 20% snowmelt were analysed. RoS events were estimated for the time period 1950–2011 and for the entire study area based on a temperature index snow model driven with a European-scale gridded data set of daily climate (E-OBS data). Frequencies and magnitudes of the modelled events differ depending on the elevation range. When distinguishing alpine, upland, and lowland basins, we found that upland basins are most influenced by RoS events. Overall, the frequency of rainfall increased during winter, while the frequency of snowfall decreased during spring. A decrease in the frequency of RoS events from April to May has been observed in all upland basins since 1990. In contrast, the results suggest an increasing trend in the magnitude and frequency of RoS days in January and February for most of the lowland and upland basins. These results suggest that the flood hazard from RoS events in the early winter season has increased in the medium-elevation mountain ranges of central Europe, especially in the Rhine, Weser, and Elbe river basins.

This study seeks to provide a long-term context for the growing number of trend analyses which have been applied to river flows in Europe. Most studies apply trend tests to fixed periods, in relatively short (generally 1960s–present) records. This study adopts an alternative "multi-temporal" approach, whereby trends are fitted to every possible combination of start and end years in a record. The method is applied to 132 catchments with long (1932–2004) hydrometric records from northern and central Europe, which were chosen as they are minimally anthropogenically influenced and have good quality data. The catchments are first clustered into five regions, which are broadly homogenous in terms of interdecadal variability of annual mean flow. The multi-temporal trend approach was then applied to regional time series of different hydrological indicators (annual, monthly and high and low flows). The results reveal that the magnitude and even direction of short-term trends are heavily influenced by interdecadal variability. Some short-term trends revealed in previous studies are shown to be unrepresentative of long-term change. For example, previous studies have identified post-1960 river flow decreases in southern and eastern Europe: in parts of eastern Europe, these trends are resilient to study period, extending back to the 1930s; in southern France, longer records show evidence of positive trends which reverse from the 1960s. Recent (post-1960) positive trends in northern Europe are also not present in longer records, due to decadal variations influenced by the North Atlantic Oscillation. The results provide a long-term reference for comparison with published and future studies. The multi-temporal approach advocated here is recommended for use in future trend assessments, to help contextualise short-term trends. Future work should also attempt to explain the decadal-scale variations that drive short-term trends, and thus develop more sophisticated methods for trend detection that take account of interdecadal variability and its drivers.

Streamflow recession has been investigated by a variety of methods, often involving the fit of a model to empirical recession plots to parameterize a non-linear storage–outflow relationship based on the dQ/dt−Q method. Such recession analysis methods (RAMs) are used to estimate hydraulic conductivity, storage capacity, or aquifer thickness and to model streamflow recession curves for regionalization and prediction at the catchment scale. Numerous RAMs have been published, but little is known about how comparably the resulting recession models distinguish characteristic catchment behavior. In this study we combined three established recession extraction methods with three different parameter-fitting methods to the power-law storage–outflow model to compare the range of recession characteristics that result from the application of these different RAMs. Resulting recession characteristics including recession time and corresponding storage depletion were evaluated for 20 meso-scale catchments in Germany. We found plausible ranges for model parameterization; however, calculated recession characteristics varied over two orders of magnitude. While recession characteristics of the 20 catchments derived with the different methods correlate strongly, particularly for the RAMs that use the same extraction method, not all rank the catchments consistently, and the differences among some of the methods are larger than among the catchments. To elucidate this variability we discuss the ambiguous roles of recession extraction procedures and the parameterization of the storage–outflow model and the limitations of the presented recession plots. The results suggest strong limitations to the comparability of recession characteristics derived with different methods, not only in the model parameters but also in the relative characterization of different catchments. A multiple-methods approach to investigating streamflow recession characteristics should be considered for applications whenever possible.

An overall appraisal of runoff changes at the European scale has been hindered by "white space" on maps of observed trends due to a paucity of readily-available streamflow data. This study tested whether this white space can be filled using estimates of trends derived from model simulations of European runoff. The simulations stem from an ensemble of eight global hydrological models that were forced with the same climate input for the period 1963–2000. The derived trends were validated for 293 grid cells across the European domain with observation-based trend estimates. The ensemble mean overall provided the best representation of trends in the observations. Maps of trends in annual runoff based on the ensemble mean demonstrated a pronounced continental dipole pattern of positive trends in western and northern Europe and negative trends in southern and parts of eastern Europe, which has not previously been demonstrated and discussed in comparable detail. Overall, positive trends in annual streamflow appear to reflect the marked wetting trends of the winter months, whereas negative annual trends result primarily from a widespread decrease in streamflow in spring and summer months, consistent with a decrease in summer low flow in large parts of Europe. High flow appears to have increased in rain-dominated hydrological regimes, whereas an inconsistent or decreasing signal was found in snow-dominated regimes. The different models agreed on the predominant continental-scale pattern of trends, but in some areas disagreed on the magnitude and even the direction of trends, particularly in transition zones between regions with increasing and decreasing runoff trends, in complex terrain with a high spatial variability, and in snow-dominated regimes. Model estimates appeared most reliable in reproducing observed trends in annual runoff, winter runoff, and 7-day high flow. Modelled trends in runoff during the summer months, spring (for snow influenced regions) and autumn, and trends in summer low flow were more variable – both among models and in the spatial patterns of agreement between models and the observations. The use of models to display changes in these hydrological characteristics should therefore be viewed with caution due to higher uncertainty.

Low flows are often poorly reproduced by commonly used hydrological models, which are traditionally designed to meet peak flow situations. Hence, there is a need to improve hydrological models for low flow prediction. This study assessed the impact of model structure on low flow simulations and recession behaviour using the Framework for Understanding Structural Errors (FUSE). FUSE identifies the set of subjective decisions made when building a hydrological model and provides multiple options for each modeling decision. Altogether 79 models were created and applied to simulate stream flows in the snow dominated headwater catchment Narsjø in Norway (119 km2). All models were calibrated using an automatic optimisation method. The results showed that simulations of summer low flows were poorer than simulations of winter low flows, reflecting the importance of different hydrological processes. The model structure influencing winter low flow simulations is the lower layer architecture, whereas various model structures were identified to influence model performance during summer.

The hydrology of ecosystem succession gives rise to new challenges for the analysis and modelling of water balance components. Recent large-scale alterations of forest cover across the globe suggest that a significant portion of new biophysical environments will influence the long-term dynamics and limits of water fluxes compared to pre-succession conditions. This study assesses the estimation of summer evapotranspiration along three FLUXNET sites at Campbell River, British Columbia, Canada using a data-driven soil water balance model validated by Eddy Covariance measurements. It explores the sensitivity of the model to different forest succession states, a wide range of computational time steps, rooting depths, and canopy interception capacity values. Uncertainty in the measured EC fluxes resulting in an energy imbalance was consistent with previous studies and does not affect the validation of the model. The agreement between observations and model estimates proves that the usefulness of the method to predict summer AET over mid- and long-term periods is independent of stand age. However, an optimal combination of the parameters rooting depth, time step and interception capacity threshold is needed to avoid an underestimation of AET as seen in past studies. The study suggests that summer AET could be estimated and monitored in many more places than those equipped with Eddy Covariance or sap-flow measurements to advance the understanding of water balance changes in different successional ecosystems.

This study investigates the low-frequency components of observed monthly river flow from a large number of small catchments in Europe. The low-frequency components, defined as fluctuations on time scales longer than one year, were analysed both with respect to their dominant space-time patterns as well as their contribution to the variance of monthly runoff. The analysis of observed streamflow and corresponding time series of precipitation and temperature, showed that the fraction of low-frequency variance of runoff is on average larger than, and not correlated to, the fraction of low-frequency variance of precipitation and temperature. However, it is correlated with mean climatic conditions and is on average lowest in catchments with significant influence of snow. Furthermore, it increases (decreases) under drier (wetter) conditions – indicating that the average degree of catchment wetness may be a primary control of low-frequency runoff dynamics. The fraction of low-frequency variance of runoff is consistently lower in responsive catchments, with a high variability of daily runoff. The dominant space-time patterns of low-frequency runoff in Europe, identified using nonlinear dimension reduction, revealed that low-frequency runoff can be described with three modes, explaining together 80.6% of the variance. The dominant mode has opposing centres of simultaneous variations in northern and southern Europe. The secondary mode features a west-east pattern and the third mode has its centre of influence in central Europe. All modes are closely related to the space-time patterns extracted from time series of precipitation and temperature. In summary, it is shown that the dynamics of low-frequency runoff follows well known continental-scale atmospheric features, whereas the proportion of variance attributed to low-frequency fluctuations is controlled by catchment processes and varies with mean climatic conditions. The results may have implications for interpreting the impact of changes in temperature and precipitation on river-flow dynamics.

Streamflow observations from near-natural catchments are of paramount importance for detection and attribution studies, evaluation of large-scale model simulations, and assessment of water management, adaptation and policy options. This study investigates streamflow trends in a newly-assembled, consolidated dataset of near-natural streamflow records from 441 small catchments in 15 countries across Europe. The period 1962–2004 provided the best spatial coverage, but analyses were also carried out for longer time periods (with fewer stations), starting in 1932, 1942 and 1952. Trends were calculated by the slopes of the Kendall-Theil robust line for standardized annual and monthly streamflow, as well as for summer low flow magnitude and timing. A regionally coherent picture of annual streamflow trends emerged, with negative trends in southern and eastern regions, and generally positive trends elsewhere. Trends in monthly streamflow for 1962–2004 elucidated potential causes for these changes, as well as for changes in hydrological regimes across Europe. Positive trends were found in the winter months in most catchments. A marked shift towards negative trends was observed in April, gradually spreading across Europe to reach a maximum extent in August. Low flows have decreased in most regions where the lowest mean monthly flow occurs in summer, but vary for catchments which have flow minima in winter and secondary low flows in summer. The study largely confirms findings from national and regional scale trend analyses, but clearly adds to these by confirming that these tendencies are part of coherent patterns of change, which cover a much larger region. The broad, continental-scale patterns of change are mostly congruent with the hydrological responses expected from future climatic changes, as projected by climate models. The patterns observed could hence provide a valuable benchmark for a number of different studies and model simulations.