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‘Water circles’ are presented as flexible water cycle diagrams aggregating the flows through a system for a specific region and time period, categorized by flow type and organized by magnitude. Water circles for an entire system and separate storage components can be interpreted as water cycle speedometers and can help compare and communicate different climate and human impacts on different regions, time periods, and storage components. Water circles can facilitate comparisons between hydrological models and other methods for deriving water balances.

Mountain areas play a vital role in global water resources as they often generate disproportionally high runoff and seasonally delay runoff due to storage as snow and ice. Water originating from mountains is used to satisfy human water demand further downstream in the lowlands of the corresponding river basins. Although the relevance of mountains for water supply is widely acknowledged, our current quantitative knowledge of their relevance for human water use on a global scale remains limited to decadal averages. As both water demand and mountain water supply have a strong seasonality, it is crucial to assess the global relevance of mountain areas beyond the annual time scale. To this end, we examined the share of lowland surface water abstraction (LSWA) stemming from mountain runoff in all river basins larger than 10 000 km ^2 globally from 1990 to 2019, focusing on the intra-annual variability. We distinguished between essential runoff contributions from low and high mountains and potential mountain runoff contributions to LSWA. Essential mountain contributions are defined as the share of water abstractions in the lowlands that can solely be satisfied by mountain runoff, whereas potential mountain contributions are the share that can originate from the mountains but does not necessarily have to. Our results confirm a strong spatial heterogeneity in the contribution of mountain runoff to LSWA. Globally, 15% of annual LSWA can solely be satisfied by mountain runoff, with monthly variations between 9% and 23%, highlighting the strong seasonality in the reliance on mountain runoff for lowland water use. The share of potential mountain contributions is much higher (51% annually). Slightly less than half of the essential mountain contributions to LSWA are sourced from high mountains. This shows the disproportional relevance of these regions, constituting only around one-third of the total mountain area. Furthermore, our results show an increasing dependence of lowlands on mountain runoff contributions.

Hydrological models play a vital role in projecting future changes in streamflow. Despite the strong awareness of non-stationarity in hydrological system characteristics, model parameters are typically assumed to be stationary and derived through calibration on past conditions. Integrating the dynamics of system change in hydrological models remains challenging due to uncertainties related to future changes in climate and ecosystems. Nevertheless, there is increasing evidence that vegetation adjusts its root zone storage capacity – considered a critical parameter in hydrological models – to prevailing hydroclimatic conditions. This adaptation of the root zone to moisture deficits can be estimated by the Memory Method. When combined with long-term water budget estimates in the Budyko framework, the Memory method offers a promising approach to estimate future climate-vegetation interaction and thus time-variable parameters in process-based hydrological models. Our study provides an exploratory analysis of non-stationary parameters for root zone storage capacity in hydrological models for projecting streamflow in six catchments in the Austrian Alps, specifically investigating how future changes in root zone storage impact modeled streamflow. Using the Memory method, we derive climate-based parameter estimates of the root zone storage capacity under historical and projected future climate conditions. These climate-based estimates are then implemented in our hydrological model to assess the resultant impact on modeled past and future streamflow. Our findings indicate that climate-based parameter estimations significantly narrow the parameter ranges linked to root zone storage capacity. This contrasts with the broader ranges obtained solely through calibration. Moreover, using projections from 14 climate models, our findings indicate a substantial increase in the root zone storage capacity parameters across all catchments in the future, ranging from +10 % to +100 %. Despite these alterations, the model performance remains relatively consistent when evaluating past streamflow, independent of using calibrated or climate-based estimations for the root zone storage capacity parameter. Additionally, no significant differences are found when modeling future streamflow when including future climate-induced adaptation of the root zone storage capacity in the hydrological model. Variations in annual mean, maximum, and minimum flows remain within a 5 % range, with slight increases found for monthly streamflow and runoff coefficients. Our research shows that although climate-induced changes in root zone storage capacity occur, they do not notably affect future streamflow projections in the Alpine catchments under study. Our findings suggest that incorporating a dynamic representation of the root zone storage capacity parameter may not be crucial for modeling streamflow in humid and energy-limited catchments. However, our observations indicate relatively larger changes in root zone storage capacity within the less humid catchments, corresponding to higher variations in modeled future streamflow. This suggests a potentially higher importance of dynamic representations of root zone characteristics in arid regions and underscores the necessity for further research on non-stationarity in these regions. [ABSTRACT FROM AUTHOR]

Glaciers are present in many large river basins, and due to climate change, they are undergoing considerable changes in terms of area, volume, magnitude and seasonality of runoff. Although the spatial extent of glaciers is very limited in most large river basins, their role in hydrology can be substantial because glaciers store large amounts of water at varying timescales. Large-scale hydrological models are an important tool to assess climate change impacts on water resources in large river basins worldwide. Nevertheless, glaciers remain poorly represented in large-scale hydrological models. Here we present a coupling between the large-scale glacier model Open Global Glacier Model (OGGM) v1.5.3 and the large-scale hydrological model Community Water Model (CWatM) V1.08. We evaluated the improved glacier representation in the coupled model against the baseline hydrological model for four selected river basins at 5 arcmin resolution and globally at 30 arcmin resolution, focusing on future discharge projections under low- and high-emission scenarios. We find that increases in future discharge are attenuated, whereas decreases are exacerbated when glaciers are represented explicitly in the large-scale hydrological model simulations. This is explained by a projected decrease in glacier-sourced runoff in almost all basins. Calibration can compensate for lacking glacier representation in large-scale hydrological models in the past. Nevertheless, only an improved glacier representation can prevent underestimating future discharge changes, even far downstream at the outlets of large glacierized river basins. Therefore, incorporating a glacier representation into large-scale hydrological models is important for climate change impact studies, particularly when focusing on summer months or extreme years. The uncertainties in glacier-sourced runoff associated with inaccurate precipitation inputs require the continued attention and collaboration of glacier and hydrological modelling communities. [ABSTRACT FROM AUTHOR]

Hydrological regimes of alpine catchments are expected to be strongly affected by climate change mostly due to their dependence on snow and ice dynamics. While seasonal changes have been studied extensively, studies on changes in the timing and magnitude of annual extremes remain rare. This study investigates the effects of climate change on runoff patterns in six contrasting alpine catchments in Austria using a process-based semi-distributed hydrological model and projections from 14 regional climate and global climate model combinations for RCP 4.5 and RCP 8.5. The study catchments represent a spectrum of different hydrological regimes, from pluvial-nival to nivo-glacial, as well as distinct topographies and land forms, characterizing different elevation zones across the Eastern Alps to provide a comprehensive picture of future runoff changes. The climate projections are used to model river runoff in 2071–2100, which are then compared to the 1981–2010 reference period for all study catchments. Changes in timing and magnitude of annual maximum and minimum flows as well as in monthly runoff and snow melt are quantified and analyzed. Our results indicate a substantial shift to earlier occurrences in annual maximum flows by 9 to 31 days and an extension of the potential flood season by one to three months for high-elevation catchments. For low-elevation catchments, changes in timing of annual maximum flows are less pronounced. Magnitudes of annual maximum flows are likely to increase by 2–18% under RCP 4.5, while no clear changes are projected for four catchments under RCP 8.5. The latter is caused by a pronounced increase in evaporation and decrease in snow melt contributions which offset increases in precipitation. Minimum annual runoff occur 13–31 days earlier in the winter months for high-elevation catchments, whereas for low-elevation catchments a shift from winter to autumn by about 15–100 days is projected. While all catchments show an increase in mean magnitude of minimum flows by 7–30% under RCP 4.5, this is only the case for four catchments under RCP 8.5. Our results suggest a relationship between the elevation of catchments and changes in timing of annual maximum and minimum flows. For the magnitude of the extreme flows, a relationship is found between catchment elevation and annual minimum flows, whereas this relationship is lacking between elevation and annual maximum flow. [ABSTRACT FROM AUTHOR]