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Although river discharge simulations from global hydrological models have undergone extensive validation, there has been less validation of reservoir operations, primarily because of limited observational data. However, recent advancements in satellite remote sensing technology have facilitated the collection of valuable data regarding water surface area and elevation, thereby providing the ability to validate reservoir storage. In this study, we sought to establish a methodology for validation and intercomparison of reservoir storage within global hydrological model simulations using satellite-derived data. Accordingly, we chose two satellite-derived reservoir operation products, DAHITI and GRSAD, to create monthly time series storage data for seven reservoirs in the contiguous United States (CONUS), with access to long-term ground truth data (the total catchment area accounts for about 9% of CONUS). We assessed two global hydrological models that participated in the Inter Sectoral Model Intercomparison Project (ISIMIP) Phase 3 project, H08 and WaterGAP2, with three distinct forcing datasets: GSWP3-W5E5 (GW), CR20v3-W5E5 (CW), and CR20v3-ERA5 (CE). The results indicated that WaterGAP2 generally outperforms H08; the CW forcing dataset demonstrated superior results compared with GW and CE; the DAHITI showed better consistency with ground observations than GRSAD if temporal coverage is sufficient. Overall, our study emphasizes the potential uses of satellite remote sensing data in reservoir operations validation and underscores the importance of normalization and decomposition techniques for improved validation efficacy. The results highlight the relative performances of different hydrological models and forcing datasets, yielding insights concerning future advancements in reservoir simulation and operational studies. [ABSTRACT FROM AUTHOR]

Human actions and climate change have drastically altered river flows across the world, resulting in adverse effects on riverine ecosystems. Environmental flows (EFs) have emerged as a prominent tool for safeguarding riverine ecosystems. However, at the global scale, the assessment of EFs is associated with significant uncertainty. Here, we present a novel method to determine EFs by Environmental Flow Envelopes (EFE), which is an envelope of variability bounded by discharge limits within which riverine ecosystems are not seriously compromised. The EFE is defined globally in approximately 4,400 sub-basins at monthly time resolution, considering also the methodological uncertainties related with global EF studies. In addition to a lower bound of discharge, the EFE introduces an upper bound of discharge, identifying areas where streamflow has increased substantially. Further, instead of only showing whether EFs are violated, as commonly done, we quantify, for the first time, the frequency, severity, and trends of EFE violations, which can be considered as potential threats to riverine ecosystems. We use pre-industrial (1801-1860) quasi-natural discharge and a suite of hydrological EFR methods and global hydrological models to estimate EFE, applying data from the ISIMIP 2b ensemble. We then compare the EFEs to recent past (1976-2005) discharge to assess the violations of the EFE. We found that the EFE violations most commonly manifest themselves by insufficient streamflow during the low flow season, with less violations during intermediate flow season, and only few violations during high flow season. These violations are widespread: discharge in half of the sub-basins of the world has violated the EFE during more than 5 % of the months between 1976 and 2005. The trends in EFE violations have mainly been increasing during the past decades and will likely remain problematic with projected increases in anthropogenic water use and hydroclimatic changes. Indications of excessive streamflow through EFE upper bound violations are relatively scarce and spatially distributed, although signs of increasing trends can be identified and potentially attributed to climate change. While the EFE provides a quick and globally robust way of determining environmental flow allocations at the sub-basin scale, local fine-tuning is necessary for practical applications and further research on the coupling between quantitative discharge and riverine ecosystem responses is required. [ABSTRACT FROM AUTHOR]

Billions of people rely on groundwater as an accessible source for drinking water and irrigation, especially in times of drought. Its importance will likely increase with a changing climate. It is still unclear, however, how climate change will impact groundwater systems globally and thus the availability of this vital resource. This study investigates uncertainties in groundwater recharge projections using a multi-model ensemble of eight global hydrological models (GHMs) that are driven by the bias-adjusted output of four global circulation models (GCMs). Preindustrial and current groundwater recharge values are compared with recharge for different global warming (GW) levels as a result of three representative concentration pathways (RCPs). Results suggest that the uncertainty range is extensive, and projections with confidence can only be made for specific regions of the world. In some regions, reversals of groundwater recharge trends can be observed with global warming. On average, a consistent median increase of groundwater recharge in northern Europe of 19 % and a decrease of 10 % in the Amazon at 3 °C GW compared to preindustrial levels are simulated. In the Mediterranean, a 2 °C GW leads to a reduction of GWR of 38 %. Because most GHMs do not include CO2 driven vegetation processes, we investigate how, including the effect of evolving CO2 concentrations into the calculation of future groundwater recharge impacts the results. In some regions, the inclusion of these processes leads to differences in groundwater recharge changes of up to 100 mm year-1. Overall, models that include CO2 driven vegetation processes simulate less severe decreases of groundwater recharge and in some regions even increases instead of decreases. In regions where GCMs predict decreases in precipitation, and groundwater availability is most important, the model agreement among GHMs with dynamic vegetation is lowest in contrast to GHMs without, which show a high agreement. [ABSTRACT FROM AUTHOR]

Continental water mass change affects ocean mass change (OMC). Assessing the net contribution, however, remains a challenge. We present an integrated version of the WaterGAP global hydrological model that is able to simulate total continental water storage anomalies (TWSA) over the global continental area (except Greenland and Antarctica) consistently by integrating the output from the global glacier model of Marzeion et al. (2012) as an input to WaterGAP. Monthly time series of global mean TWSA obtained with an ensemble of four variants of the integrated model, corresponding to different precipitation input and irrigation water use assumptions, were validated against an ensemble of four TWSA solutions based on GRACE satellite gravimetry over January 2003 to August 2016. The overall fit to GRACE, measured by the Nash-Sutcliffe efficiency (NSE) coefficient, was found to be 0.87. By decomposing the original TWSA signal into its seasonal, linear trend and inter-annual components, we find that the seasonal amplitude and phase are very well reproduced (NSE=0.88), the linear trend is overestimated by 30-50% (NSE=0.65) and inter-annual variability is captured to a certain extent (NSE=0.57) by the integrated model. During the period 1948-2016, we find that continents lost 34-41mm of sea level equivalent (SLE) to the oceans, with global glacier mass loss accounting for 81% of the cumulated mass loss and glacier-free land water storage anomalies (LWSA) accounting for the remaining 19%. Over 1948-2016, the mass gain on land from impoundment of water in man-made reservoirs, equivalent to 8mm SLE, was offset by the mass loss from water abstractions, amounting to 15-21mm SLE and reflecting a cumulated groundwater depletion of 13-19mm SLE. Climate-driven LWSA are highly sensitive to precipitation input and correlate with El Niño Southern Oscillation multi-year modulations. Significant uncertainty remains in trends of modelled LWSA, which are highly sensitive to simulation of irrigation water use and man-made reservoirs. [ABSTRACT FROM AUTHOR]

To improve the understanding of trends in extreme flows related to flood events at the global scale, historical and future changes of annual maximum streamflow are investigated, using a comprehensive streamflow archive and six global hydrological models. The models' capacity to characterise trends in annual maximum streamflow is evaluated across 3,666 river gauge locations over the period from 1971 to 2005, focusing on four aspects of trends over continental and global scale: (i) mean, (ii) standard deviation, (iii) percentage of locations showing significant trends and (iv) spatial pattern. Compared to observed trends, simulated trends driven by observed climate forcing generally have a higher mean, lower spread, and a similar percentage of locations showing significant trends. Models show a moderate capacity to simulate spatial patterns of historical trends, with approximately only 12-25 % of the spatial variance of observed trends across all gauge stations accounted for by the simulations. Interestingly, there are significant differences between trends simulated by GHMs forced with historical climate and forced by bias corrected climate model output during the historical period, suggesting the important role of the stochastic natural (decadal, inter-annual) climate variability. Significant differences were found in simulated flood trend results when averaged only at gauged locations compared to when averaging across all simulated grid cells, highlighting the potential for bias toward well-observed regions in the state-of-understanding of changes in floods. Future climate projections (simulated under RCP2.6 and RCP6.0 greenhouse gas concentration scenario) suggest a potentially high level of change in individual regions, with up to 35 % of cells showing a statistically significant trend (increase or decrease) and greater changes indicated for the higher concentration pathway. Importantly, the observed streamflow database under-samples the percentage of high-risk locations under RCP6.0 greenhouse gas concentration scenario by more than an order of magnitude (0.9 % compared to 11.7 %). This finding indicates a highly uncertain future for both flood-prone communities and decision makers in the context of climate change. [ABSTRACT FROM AUTHOR]

Human activities, as well as climate change, have had increasing impacts on natural hydrological systems, particularly streamflow. However, quantitative assessments of these impacts are lacking on large scales. In this study, we use the simulations from six global hydrological models driven by three meteorological forcings to investigate direct human impact (DHI) and climate change impact on streamflow in China. Results show that, in the sub-periods of 1971-1990 and 1991-2010, one-fifth to one-third of mean annual streamflow (MAF) reduced due to DHI in northern basins and much smaller (<4%) MAF reduced in southern basins. From 1971-1990 to 1991-2010, total MAF changes range from -13% to 10% across basins, wherein the relative contributions of DHI change and climate change show distinct spatial patterns. DHI change caused decreases in MAF in 70% of river segments, but climate change dominated the total MAF changes in 88% of river segments of China. In most northern basins, climate change results in changes of -9% to 18% of MAF, while DHI change results in decreases of 2% to 8% in MAF. In contrast with the impacts of climate change that may increase or decrease streamflow, DHI change almost always contributes to decreases in MAF over time, wherein water withdrawals are supposed to be the major impact on streamflow. This quantitative assessment can be a reference for attribution of streamflow changes at large scales despite uncertainty remains. We highlight the significant DHI in northern basins and the necessity to modulate DHI through improved water management towards a better adaptation to future climate change. [ABSTRACT FROM AUTHOR]

Over the last decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes at an unprecedented scale. The phenomenal growth of the human footprint has significantly modified hydrological processes in various ways (e.g., irrigation, artificial dams, and water diversion) and at various scales (from a watershed to the globe). During the early 1990s, awareness of the potential water scarcity led to the first detailed global water resource assessments. Shortly thereafter, in order to analyse the human perturbation on terrestrial water resources, the first generation of large-scale hydrological models (LHMs) was produced. However, at this early stage few models considered the interaction between terrestrial water fluxes and human activities, including water use and reservoir regulation, and even fewer models distinguished water use from surface water and groundwater resources. Since the early 2000s, a growing number of LHMs are incorporating human impacts on hydrological cycle, yet human representations in hydrological models remain challenging. In this paper we provide a synthesis of progress in the development and application of human impact modeling in LHMs. We highlight a number of key challenges and discuss possible improvements in order to better represent the human-water interface in hydrological models. [ABSTRACT FROM AUTHOR]

Land surface and hydrologic models (LSM/HM) are used at diverse spatial resolutions ranging from 1-10 km in catchment-scale applications to over 50 km in global-scale applications. Application of the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the model resolution and fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent and realistic parameter fields for land surface geophysical properties. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB and WaterGAP models are conducted to demonstrate the pitfalls of poor parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. We provide a short review of existing parameter regionalization techniques and discuss a method for obtaining seamless hydrological predictions of water fluxes and states across multiple spatial resolutions. The multiscale parameter regionalization (MPR) technique is a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. A general model protocol is presented to describe how MPR can be applied to a specific model, with an example of this application using the PCR-GLOBWB model. Applying MPR to PCR-GLOBWB substantially improves the flux-matching condition. Estimation of evapotranspiration without MPR at 5 arcmin and 30 arcmin spatial resolutions for the Rhine river basin results in a difference of approximately 29 %. Applying MPR reduce this difference to 9 %. For total soil water, the differences without and with MPR are 25 % and 7 %, respectively. [ABSTRACT FROM AUTHOR]