Changes In Hydrological Extremes Research Articles

Drivers, changes, and impacts of hydrological extremes in India: A review

AbstractThe frequency of hydrological extremes (droughts and floods) has increased in recent years in India. A dense population, intensive agriculture, and rapidly developing physical infrastructure put India under the risk of hydrological extremes. However, a comprehensive overview of the drivers, changes, and impacts associated with hydrological extremes in India has been lacking. We examine the key processes and the role of climate and human interventions on hydrological extremes in India. We discuss the observed and projected changes in hydrological extremes along with their impacts. While the Indian summer monsoon is the primary driver of the hydrological extremes in India, human interventions (irrigation, reservoir storage, and groundwater pumping) play a crucial role in the changes and variability of hydrological extremes. The relative role of climate change and direct human interventions on changing the intensity and impacts of hydrological extremes need to be considered for future adaptation planning under climate change. The observed increase in the frequency and intensity of hydrological extremes will continue in the future with compound and cascading impacts due to the warming climate. We need to strengthen the observational network, improve hydrological modeling, reduce climate uncertainty, and develop robust early warning systems to adapt and mitigate hydrological extremes in India.This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water Extremes Science of Water > Water and Environmental Change

How Have Hydrological Extremes Changed over the Past 20 Years?

Abstract Severe floods and droughts, including their back-to-back occurrences (weather whiplash), have been increasing in frequency and severity around the world. Improved understanding of systematic changes in hydrological extremes is essential for preparation and adaptation. In this study, we identified and quantified extreme wet and dry events globally by applying a clustering algorithm to terrestrial water storage (TWS) data from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (FO). The most intense events, ranked using an intensity metric, often reflect impacts of large-scale oceanic oscillations such as El Niño–Southern Oscillation and consequences of climate change. The severity of both wet and dry events, represented by standardized TWS anomalies, increased significantly in most cases, likely associated with intensification of wet and dry weather regimes in a warmer world, and consequently, exhibited strongest correlation with global temperature. In the Dry climate, the number of wet events decreased while the number of dry events increased significantly, suggesting a drying trend that may be attributed to climate variability and possible increases in irrigation and reliance on groundwater. In the Continental climate where temperature has risen faster than global average, dry events increased significantly. Characteristics of extreme events often showed strong correlations with global temperature, especially when averaged over all climates. These results suggest changes in hydrological extremes and underscore the importance of quantifying total water storage changes when studying hydrological extremes. Extending the GRACE/FO record, which spans 2002 to the present, is essential to continuously tracking changes in TWS and hydrological extremes.

Simulating Changes in Hydrological Extremes—Future Scenarios for Morocco

This paper presents a comprehensive river discharge analysis to estimate past and future hydrological extremes across Morocco. Hydrological simulations with historical forcing and climate change scenario inputs have been performed to better understand the change in magnitude and frequency of extreme discharge events that cause flooding. Simulations are applied to all major rivers of Morocco, including a total of 16 basins that cover the majority of the country. An ensemble of temperature and precipitation input parameter sets was generated to analyze input uncertainty, an approach that can be extended to other regions of the world, including data-sparse regions. Parameter uncertainty was also included in the analyses. Historical simulations comprise the period 1979–2021, while future simulations (2015–2100) were performed under the Shared Socioeconomic Pathway (SSP) 2–4.5 and SSP5–8.5. Clear patterns of changing flood extremes are projected; these changes are significant when considered as a proportion of the land area of the country. Two types of basins have been identified, based on their different behavior in climate change scenarios. In the Northern/Mediterranean basins we observe a decrease in the frequency and intensity of events by 2050 under both SSPs, whereas for the remaining catchments higher and more frequent high-flow events in the form of flash floods are detected. Our analysis revealed that this is a consequence of the reduction in rainfall accumulation and intensity in both SSPs for the first type of basins, while the opposite applies to the other type. More generally, we propose a methodology that does not rely on observed time series of discharge, so especially for regions where those do not exist or are not available, and that can be applied to undertake future flood projections in the most data-scarce regions. This method allows future hydrological hazards to be estimated for essentially any region of the world.

Climate feedbacks associated with land-use and land-cover change on hydrological extremes over the Yangtze River Delta Region, China

Quantifying how land-use and land-cover change (LULCC) drives extreme events is a priority to inform adaptation planning in a changing environment. Previous studies mainly focus on the effects of local LULCC on runoff generation processes; however, few on the effects of the climate feedbacks of LULCC. Here we couple the Variable Infiltration Capacity model with climate forcing from the Land Use Model Intercomparison Project, part of the new state-of-the-art Coupled Model Intercomparison Project phase 6, to synthetically detect global LULCC-induced impacts on hydrological extremes in one of the fastest developing areas in China and the world, i.e., the Yangtze River Delta (YRD). Results suggest that global LULCC increased extreme rainfall by 1.41 ∼ 3.90 % with spatial heterogeneity over YRD, especially during the rapid urbanization period. Regions with increasing extreme rainfall during the rapid urbanization stage match well with the city belt distribution, indicating the precipitation enhancement effects of the urban land surface. The combined impacts (with both LULCC and its climate feedbacks) lead to a 3.01–7.18 % increase in extreme runoff, much higher than the effects of LULCC only (0.05–0.14 %). The consistent signs of changes in extreme rainfall and runoff indicate the dominant role of LULCC-induced climate feedback in the changes in extreme runoff over the YRD region. In addition, flash droughts increased when considering the climate feedbacks of global LULCC, particularly during the rapid urbanization stage. LULCC tends to increase average flows, high flows, and low flows, particularly in an urban-dominated basin. When considering the climate feedback effects from global LULCC, the LULCC would lead to a larger increase in high flows and average flows, thus floods. We highlight a need to consider land–atmosphere interactions in addition to land-surface processes in projecting changes in hydrological extremes.

Changing flood dynamics in Norway since the last millennium and to the end of the 21st century

• All GCMs except MIROC-ESM simulate a higher mean temperature in Medieval Climate Anomaly (MCA) period than Little Ice Age (LIA) period, while simulated annual precipitation varies a lot in different GCMs and catchments. • No significant change of flood characteristics during the last millennium from ensemble-mean results. • In future, we will have an extraordinary shift in flood seasonality and generating processes, and flood frequency increase in most of the study catchments in Norway. • Climate projections represent the largest contribution to overall uncertainty in the projected changes in hydrological extremes for most of the catchments. With the recent warming trend over Europe and the Arctic, the Nordic regions have experienced more frequent and damaging extreme hydrological events which are anticipated to increase towards the end of the 21st century. Despite explicit trends, large variations have been observed across basins and regions when it comes to precipitation and floods hinting at a strong natural hydroclimatic variability that further complicates any assessment of potential future changes. In this study, we aim to better understand how climate variability links with the current extremes and future projections of floods in Norway in the context of the last millennium and the future. Specifically, we simulate over 1000 years (850–2099) daily discharge and floods at 34 catchments over five regions of Norway from the last millennium (including a warm period and a cold period; 850–1849) to the end of the 21st century by an ensemble model-chain method including four global climate models (GCMs), two bias-correction methods and two hydrological models. The modelling results show (i) all GCMs except MIROC-ESM simulate a higher mean temperature in Medieval Climate Anomaly (MCA) period than Little Ice Age (LIA) period, while simulated annual precipitation varies a lot in different GCMs and catchments, (ii) no significant change of flood characteristics during the last millennium from ensemble-mean results, (iii) in future, we will have an extraordinary shift in flood seasonality and generating processes, and flood frequency increase in most of the study catchments in Norway, and (iv) climate projections represent the largest contribution to overall uncertainty in the projected changes in hydrological extremes for most of the catchments.

Intra‐Annual Variation of High and Low‐Flow Extremes Associated With Land Use and Climate Change in the Upper Tekeze of the Nile River Basin

AbstractIn northern Ethiopian highlands, climate variability and land use/land cover (LULC) change has been observed during the past decades. However, it remains unclear that to which extent and how these key drivers contributed to changes in hydrological extremes. As a case study, the respective impacts of LULC change and climate variability on hydrological extremes with respect to magnitude, duration, and frequency metrics were assessed in the Upper Tekeze basin, Ethiopia. A scenario‐based approach using LULC and hydro‐climatological data was developed and five simulation experiments were conducted using Soil and Water Assessment Tool model. Results showed that, during 1986–2015, low‐flow duration has decreased by 5.0 days/yr, and the magnitude and occurrence of high flow has increased by 5.23 m3/s/yr and 5.11 days/yr, respectively. Meanwhile, about 47.42% of the landscape has changed its category while no significant change was detected in annual rainfall during the past 31 yr. Particularly, rocky area increased by 82% which was mostly contributed by losses of bare, sand, and low biomass areas. Significant positive and negative contributions to the changes in high and low‐flow extremes, respectively, were detected from LULC change, while no significant contribution was detected from climate change. The increased rock area tends to be one of the major contributors to the increased high flow while climate change seemed to play a minor role. The potential mechanism is the expansion in rock area increased runoff and high flow, which may lead to significant land deterioration and loss of water storage capacity in the mountainous basin.

Climate Change Impact on the Magnitude and Timing of Hydrological Extremes Across Great Britain

Climate change could intensify hydrological extremes, changing not just the magnitude but also the timing of flood and drought events. Understanding these potential future changes to hydrological extremes at the national level is critical to guide policy decisions and ensure adequate adaptation measures are put in place. Here, climate change impact on the magnitude and timing of extreme flows is modelled across Great Britain (GB), using an ensemble of climate data from the latest UK Climate Projections product (UKCP18) and a national grid-based hydrological model. All ensemble members show large reductions in low flows, of around −90 to −25% for 10-year return period low flows by 2050–2080. The direction of change for high flows is uncertain, but increases in 10-year return period high flows of over 9% are possible across most of the country. Simultaneous worsening of both extremes (i.e., a reduction in low flows combined with an increase in high flows) are projected in the west. Changes to flow timing are also projected; with mostly earlier annual maximum flows across Scotland, later annual maximum flows across England and Wales, and later low flows across GB. However, these changes are generally not statistically significant due to the high interannual variability of annual maximum/minimum flow timing. These results highlight the need for adaptation strategies that can cope with a wide range of future changes in hydrological extremes, and consider changes in the timing as well as magnitude.

Review: Can temperature be used to inform changes to flood extremes with global warming?

As climate change alters flood risk, there is a need to project changes in flooding for water resource management, infrastructure design and planning. The use of observed temperature relationships for informing changes in hydrologic extremes takes many forms, from simple proportional change approaches to conditioning stochastic rainfall generation on observed temperatures. Although generally focused on understanding changes to precipitation, there is an implied transfer of information gained from precipitation-temperature sensitivities to flooding as extreme precipitation is often responsible for flooding. While reviews of precipitation-temperature sensitivities and the non-stationarity of flooding exist, little attention has been given to the intersection of these two topics. Models which use temperature as a covariate to assess the non-stationarity of extreme precipitation outperform both stationary models and those using a temporal trend as a covariate. But care must be taken when projecting changes in flooding on the basis on precipitation-temperature sensitivities, as antecedent conditions modify the runoff response. Although good agreement is found between peak flow-temperature sensitivities and historical trends across Australia, there remains little evaluation of flood projections using temperature sensitivities globally. Significant work needs to be done before the use of temperature as a covariate for flood projection can be adopted with confidence. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

Ultra-high resolution regional climate projections for assessing changes in hydrological extremes and underlying uncertainties

The frequency and intensity of extreme hydrological events (droughts and floods) have been increasing over the past few decades, which has been posing a threat to water security and agriculture production. Thus, projecting the future evolution of hydrological extremes plays a crucial role in sustainable water management and agriculture development in a changing climate. In this study, we develop the high-resolution projections of multidimensional drought characteristics and flood risks using the convection-permitting Weather Research and Forecasting (WRF) model with the horizontal grid spacing of 4 km for the Blanco and Mission River basins over South Texas. Uncertainties in model parameters are addressed explicitly, thereby leading to probabilistic assessments of hydrological extremes. Our findings reveal that the probabilistic multivariate assessments of drought and flood risks can reduce the underestimation and the biased conclusions generated from the univariate assessment. Furthermore, our findings disclose that future droughts are expected to become more severe over South Texas even though the frequency of the occurrence of droughts is projected to decrease, especially for the long-term drought episodes. In addition, South Texas region is expected to experience more floods with an increasing river discharge. Moreover, the Blanco and Mission river basins will suffer from higher flood risks as flood return periods are expected to become longer under climate change.

Defining Robustness, Vulnerabilities, and Consequential Scenarios for Diverse Stakeholder Interests in Institutionally Complex River Basins

AbstractThe Upper Basin of the Colorado River in the southwestern United States supports municipal, industrial, agricultural, and recreational activities worth an estimated $300 billion/year within the state of Colorado alone. The allocation of water to these activities is fundamentally shaped by water rights that in turn distribute risks among a diverse suite of sectors and stakeholders. In this study, we assess the vulnerabilities faced by the hierarchy of hundreds of water users in the portion of the Upper Basin within the state of Colorado, as a result of changes in hydrologic extremes, demand growth, and institutional and physical infrastructure in the basin. We also determine how robust the different users are to these potential changes, examining how their sensitivity to these factors depends on the magnitude and frequency of shortage they are unwilling to exceed. This advances previous robustness evaluation methods by formalizing an a posteriori exploration of alternative definitions of robustness tailored to each user's unique context. Our analysis reveals that robustness varies significantly not only across users but also across different definitions of acceptable performance for each user. We further show the importance of using scenario discovery to evaluate how the factors that drive consequential scenarios differ depending on the definition of robustness. Our results highlight the need for robustness and vulnerability frameworks to avoid broad categorical aggregations of stakeholder groups, to carefully capture complex institutional dependencies (e.g., water rights), and to facilitate a more transparent illustration of the implications of alternative definitions of robustness for specific stakeholders.

Statistical Analysis and Stochastic Modelling of Hydrological Extremes

Analysis of hydrological extremes is challenging due to their rarity and small sample size and the interconnections between different types of extremes and gets further complicated by an untrustworthy representation of meso-scale processes involved in extreme events by coarse spatial and temporal scale models as well as biased or missing observations due to technical difficulties during extreme conditions. The special issue “Statistical Analysis and Stochastic Modelling of Hydrological Extremes”—motivated by the need to apply and develop innovative stochastic and statistical approaches to analyze hydrological extremes under current and future climate conditions —encompass 13 research papers. Case studies presented in the papers exploit a wide range of innovative techniques for hydrological extremes analyses. The papers focus on six topics: Historical changes in hydrological extremes, projected changes in hydrological extremes, downscaling of hydrological extremes, early warning and forecasting systems for drought and flood, interconnections of hydrological extremes and applicability of satellite data for hydrological studies. This Editorial provides an overview of the covered topics and reviews the case studies relevant for each topic.

Added Value of Large Ensemble Simulations for Assessing Extreme River Discharge in a 2 °C Warmer World

AbstractThe assessment of return periods of extreme hydrological events often relies on statistical analysis using generalized extreme value (GEV) distributions. Here we compare the traditional GEV approach with a novel large ensemble approach to determine the added value of a direct, empirical distribution‐based estimate of extreme hydrological events. Using the global climate and hydrological models EC‐Earth and PCR‐GLOBWB, we simulate 2,000 years of global hydrology for a present‐day and 2 °C warmer climate. We show that the GEV method has inherent limitations in estimating changes in hydrological extremes, especially for compound hydrological events. The large ensemble method does not suffer from these limitations and quantifies the impacts of climate change with greater precision. The explicit simulation of extreme events enables better hydrological process understanding. We conclude that future studies focusing on the impact of climatic changes on hydrological extremes should use large ensemble techniques to properly account for these rare hydrological events.

Projected Changes in Hydrological Extremes in the Yangtze River Basin with an Ensemble of Regional Climate Simulations

This paper estimates the likely impacts of future climate change on streamflow, especially the hydrological extremes over the Yangtze River basin. The future climate was projected by the Coordinated Regional Climate Downscaling Experiment in East Asia (CORDEX-EA) initiative for the periods 2020–2049 under two representative concentration pathways (RCP) 4.5 and 8.5 emission scenarios. The bias corrected outputs from five regional climate models (RCMs) were used in conjunction with the variable infiltration capacity (VIC) macroscale hydrological model to produce hydrological projections. For the future climate of the Yangtze River basin, outputs from an ensemble of RCMs indicate that the annual mean temperature will increase for 2020–2049 by 1.81 °C for RCP4.5 and by 2.26 °C for RCP8.5. The annual mean precipitation is projected to increase by 3.62% under RCP4.5 and 7.65% under RCP8.5. Overall, increases in precipitation are amplified in streamflow, and the change in streamflow also shows significant temporal and spatial variations and large divergence between regional climate models. At the same time, the maximum streamflow in different durations are also projected to increase at three mainstream gauging stations based on flood frequency analysis. In particular, larger increases in maximum 1-day streamflow (+14.24% on average) compared to 5-day and 15-day water volumes (+12.79% and +10.24%) indicate that this projected extreme streamflow increase would be primarily due to intense short-period rainfall events. It is necessary to consider the impacts of climate change in future water resource management.

Effects of 21st century climate change on seasonal flow regimes and hydrologic extremes over the Midwest and Great Lakes region of the US

Analyzing future changes in hydrologic extremes such as floods, low flows, and soil moisture extremes is important because many impacts on ecosystems and human systems occur during extreme events. To quantify changes in hydrologic extremes, this study conducts hydrologic modeling experiments over 20 Midwestern watersheds using the Variable Infiltration Capacity (VIC) model forced by historical observed datasets and future projections from statistically downscaled Global Climate Model (GCMs) simulations. Our results show that peak daily streamflow at the 100-yr reoccurrence interval will increase (+10–30%) in most watersheds by 2080s due to significant increases in precipitation (P) and increasing P as rainfall during winter and spring seasons. The simulations also show strong shifts towards earlier peak flow timing (up to a month), especially in strongly snowmelt-dominated watersheds. These effects are linked to strong decreasing trends in maximum Snow Water Equivalent (SWE) with warming, which are simulated over essentially the entire domain. Projected changes in 7-day extreme low flows are smaller in magnitude (−10–+10%) with somewhat larger decreases simulated at the end of century; however, the timing of extreme low flows is projected to shift from winter/spring to summer and fall in strongly snowmelt-dominated watersheds in the northernmost parts of the domain. Extreme low soil moisture increases over most of the domain in the future projections up to the 2050s, but by the 2080s there are more widespread decreases in extreme low soil moisture, especially in the northernmost parts of the domain.

Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices

When selecting a subset of climate change scenarios (GCM models), the priority is to ensure that the subset reflects the comprehensive range of possible model results for all variables concerned. Though many studies have attempted to improve the scenario selection, there is a lack of studies that discuss methods to ensure that the results from a subset of climate models contain the same range of uncertainty in hydrologic variables as when all models are considered. We applied the Katsavounidis–Kuo–Zhang (KKZ) algorithm to select a subset of climate change scenarios and demonstrated its ability to reduce the number of GCM models in an ensemble, while the ranges of multiple climate extremes indices were preserved. First, we analyzed the role of 27 ETCCDI climate extremes indices for scenario selection and selected the representative climate extreme indices. Before the selection of a subset, we excluded a few deficient GCM models that could not represent the observed climate regime. Subsequently, we discovered that a subset of GCM models selected by the KKZ algorithm with the representative climate extreme indices could not capture the full potential range of changes in hydrologic extremes (e.g., 3-day peak flow and 7-day low flow) in some regional case studies. However, the application of the KKZ algorithm with a different set of climate indices, which are correlated to the hydrologic extremes, enabled the overcoming of this limitation. Key climate indices, dependent on the hydrologic extremes to be projected, must therefore be determined prior to the selection of a subset of GCM models.

Observed changes in hydrological extremes and flood disaster in Yangtze River Basin: spatial–temporal variability and climate change impacts

The variation and tendency of hydrological extremes in the context of climate change have received extensive concern. However, there is still no clear understanding toward the evolution of hydrological extremes, and the impacts of climate change on flood disaster and risk have been explored very poorly. This study investigated the trends in flood-related variables of extreme precipitation, extreme river flow (1955–2012), and flood damages (1990–2014) in Yangtze River Basin. To further explore the impacts of climate change, the relations of changes in extreme river flow and precipitation were evaluated using wavelet transform analysis, and the trends in normalized flood damages were re-examined with the elimination of changes in exposure. The results showed that flood damages decreased significantly in the middle and lower reaches, while extreme precipitation and river flow still had increasing trends, indicating the potential of increasing flood risk. For upper basin, extreme precipitation increased significantly in the west and northeast part, while significant decreasing trends can also be found in the central part. The wavelet analysis revealed significant covarying relations for extreme discharge and precipitation, demonstrating the substantial influence of climate variability on extreme river flow. Meanwhile, the normalized flood damages showed increasing trend in Sichuan province, indicating significant climate change impacts on flood disaster. This study suggests the need for more effective measures to mitigate flood risk and better adaptation for climate change in Yangtze River Basin, especially in the middle and lower basin and northeast of the upper basin.

Shifts in historical streamflow extremes in the Colorado River Basin

The global phenomenon of climate change-induced shifts in precipitation leading to “wet regions getting wetter” and “dry regions getting drier” has been widely studied. However, the propagation of these changes in atmospheric moisture within stream channels is not a direct relationship due to differences in the timing of how changing precipitation patterns interact with various land surfaces. Streamflow is of particular interest in the Colorado River Basin (CRB) due to the region’s rapidly growing population, projected temperature increases that are expected to be higher than elsewhere in the contiguous United States, and subsequent climate-driven disturbances including drought, vegetation mortality, and wildfire, which makes the region more vulnerable to changes in hydrologic extremes. Here, we determine how streamflow extremes have shifted in the CRB using two statistical methods—the Mann-Kendall trend detection analysis and Generalized Extreme Value (GEV) theorem. We evaluate these changes in the context of key flow metrics that include high and low flow percentiles, maximum and minimum 7-day flows, and the center timing of streamflow using historical gage records representative of natural flows. Monthly results indicate declines of up to 41% for high and low flows during the June to July peak runoff season, while increases of up to 24% were observed earlier from March to April. Our results highlight a key threshold elevation and latitude of 2300m and 39° North, respectively, where there is a distinct shift in the trend. The spatiotemporal patterns observed are indicative of changing snowmelt patterns as a primary cause of the shifts. Identification of how this change varies spatially has consequences for improved land management strategies, as specific regions most vulnerable to threats can be prioritized for mitigation or adaptation as the climate warms.

Trend and Variability in Observed Hydrological Extremes in the United States

AbstractIdentification of changes in hydrological extremes plays an important role in water resources management. This study investigates various properties in hydrological extremes including annual maximum daily flow (high flow) and annual minimum 7-day flow (low flow) in 252 unimpaired streamflow gauges in the continental United States. Three statistical methodologies are performed: the nonparametric Mann-Kendall test is used to evaluate temporal trends; the non-parametric change point Pettitt test, to identify abrupt shifts; and the quantile perturbation method, to assess temporal variability. In the results of trend analysis, low flow exhibited some spatial patterns compared to high flow. In addition, low flow has increased over 64 years (1950–2013) in many stations. The Pettitt test indicates that low flows have experienced more significant abrupt changes compared to high flow. The results of the quantile perturbation method confirm that many significant increasing trends obtained during the 64 years...

Grand Challenges Related to the Assessment of Climate Change Impacts on Freshwater Resources

AbstractThe present contribution reviews a suite of grand challenges related to assessment of climate change impacts on freshwater resources. Among them are challenges related to the detection and attribution of changes in observed records, projections for the future, changes in hydrologic extremes (floods and droughts), assessing and reducing uncertainty, and adaptation to change under uncertainty. The global water system is very complex, so that it is difficult to disentangle individual contributions of various factors to changes in freshwater variables at any scale. As for detection and attribution of changes in global river discharge in twentieth century, variations in precipitation were the main force. Other major factors were temperature effects on evapotranspiration, direct effects of rising atmospheric CO2 concentration on the physiology and abundance of vegetation, and anthropogenic changes in land cover and land use. A general finding regarding possible future trends in the water cycle is that w...

Projections of climate change impacts on floods and droughts in Germany using an ensemble of climate change scenarios

Under a warming climate, changes in hydrological extremes may be more significant than changes in hydrological mean conditions. Due to the high risk of damage and the increasing trends of floods and droughts in Germany, the potential changes in hydrological extreme events are of high importance. However, projections of extreme events particularly for floods are associated with large uncertainties and depend on climate scenarios. If only a few scenarios are applied, there is a danger that the impact assessment is biased. This study aims to evaluate the performance of a set of climate scenarios from the ENSEMBLES project for flood and drought projections and to detect the robust changes using the eco-hydrological model SWIM in five large river basins covering 90 % of the German territory. The study shows that there is a moderate certainty that most German rivers will experience more extreme 50-year floods and more frequent occurrences of 50-year droughts. Projected changes with a high certainty include an increasing trend of floods in the Elbe basin and more frequent extreme droughts in the Rhine basin in 2061–2100. Wetter conditions, i.e., more extreme floods and less frequent droughts, are projected for the alpine rivers in 2021–2060. Using only those RCMs for impact assessments that perform best in the reference period does not guarantee more consistent and certain future projections. Hence, the use of the whole ensemble of available scenarios is necessary to quantify the “full” range of uncertainties corresponding to the current state of knowledge and assuring the robustness of projected change patterns.