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Human actions compromise the many life-supporting functions provided by the freshwater cycle. Yet, scientific understanding of anthropogenic freshwater change and its long-term evolution is limited. Using a multi-model ensemble of global hydrological models, we estimate how, over a 145-year industrial period, streamflow and soil moisture have deviated from pre-industrial baseline conditions (defined by 5th–95th percentiles, at 0.5° grid level and monthly time step). We find increased frequency of local deviations on ~45% of land area, mainly in regions under heavy direct or indirect human pressures. To estimate humanity’s aggregate impact on the freshwater cycle, we present the evolution of deviation occurrence at regional to global scales. Currently, local streamflow and soil moisture deviations occur on 18.2% and 15.8% of global land area, respectively, which is 8.0 and 4.7 percentage points beyond the ~3 percentage point wide pre-industrial variability envelope. Finally, we discuss applying our approach to define a planetary boundary for freshwater change. Our results indicate a substantial shift from stable pre-industrial streamflow and soil moisture conditions to persistently increasing change and a transgression of the freshwater change planetary boundary, calling for urgent actions to reduce human disturbance of the freshwater cycle.

Irrigation is one of the crucial Nature-Human interactions and also an anthropogenic forcing in the Earth system. The literature has shown that artificial water supply to soil for example water exploitation from groundwater for irrigation can alter water and heat budgets at the land surface, resulting in changes in regional climate and hydrological cycles. Due to the expected increase in irrigation to meet growing food demand, the impact of irrigation is likely to increase further in the future. Therefore, it is essential to consider to better understand the irrigation-induced changes in the various components of the Earth system, today and in the future.Our research aims to advance the quantitative understanding of the impact of irrigation and groundwater exploitation as anthropogenic drivers of regional climate and environmental changes. We developed an earth system modeling framework coupling the updated Earth system model, MIROC-ES2L (Model for Interdisciplinary Research on Climate, Earth System version 2 for Long-term simulations) and newly implemented hydrological human activity modules. This modeling framework enables to simulate a fully coupled Nature-Human system including water cycle dynamics related to irrigation.Our preliminary results show notable differences between simulations with and without the irrigation process. Here, we show the hydrological variables affected by irrigation and identify the regions and timings of significant impact. Further, we estimate the individual contribution of groundwater and surface water use to such impacts by irrigation.

Water scarcity is a growing concern in many regions worldwide, as demand for clean water increases and supply becomes increasingly uncertain under climate change. Already today, more than 4 billion people experience water scarcity at least one month per year (Mekonnen and Hoekstra, 2016). Developing socio-economic conditions and growing population increase water demands, while climate change leads to changes in freshwater availability. Most studies quantify water scarcity in discrete time windows, with fixed population and climate change signals (e.g., 30 years or long-term averages). Recently, however, Thiery et al. (2021) proposed a novel approach, in which climate change impacts are integrated over a person's lifetime. In this cohort perspective, lifetime impact values are comparable across generations and regions. Evaluating this perspective for natural hazards, they showed, for example, that a newborn will experience a sixfold increase in drought exposure compared to a 60-year-old (Thiery et al., 2021). In this study, we use this cohort perspective to study how much water scarcity a person experiences during their lifetime. Based on monthly fluctuations in water demand and availability, we estimate the total amount of water demand not met and refer to it as 'lifetime water deficit'. To this end, we use an ensemble of four global hydrological models (MATSIRO, CWatM, LPJmL and H08), each forced by four GCMs and two RCP scenarios from the InterSectoral Impact Model Intercomparison Project (ISIMIP2b). The simulations account for varying population and socio-economic conditions in the historical and future period, following the SSP2 scenario. Combined with country-based population, cohort distribution and life expectancies, lifetime water deficits are quantified for different generations on a country level. Our findings reveal high water lifetime deficit values for regions that are already water scarce today, such as the Mediterranean, North Africa and the Middle East. In these regions, more than 70% of the lifetime water demand is not met when needed. Further comparison reveals differences in spatial, intergenerational and climate change scenarios, and provides information on different scenarios. Overall, this study provides a new perspective on quantifying water scarcity and the climate and population impacts. References:Mekonnen, M. M., & Hoekstra, A. Y. (2016). Four billion people facing severe water scarcity. Science Advances, 2(2). https://doi.org/10.1126/sciadv.1500323Thiery, W., Lange, S., Rogelj, J., Schleussner, C. F., Gudmundsson, L., Seneviratne, S. I., Andrijevic, M., Frieler, K., Emanuel, K., Geiger, T., Bresch, D. N., Zhao, F., Willner, S. N., Büchner, M., Volkholz, J., Bauer, N., Chang, J., Ciais, P., Dury, M., … Wada, Y. (2021). Intergenerational inequities in exposure to climate extremes. Science, 374(6564), 158–160. https://doi.org/10.1126/science.abi7339

Global water models are widely used for policy-making and in scientific studies, but substantial inter-model differences highlight the need for additional evaluation. Here we evaluate global water models by assessing so-called functional relationships between system forcing and response variables. The more widely used comparisons between observed and simulated fluxes provide insight into model behavior for the representative area of an observation, and can therefore potentially improve the model for that area. Functional relationships, by contrast, aim to capture how system forcing and response variables co-vary across large scales, and thus offer the potential for model improvement over large areas. Using 30-year annual averages from 8 global water models, we quantify such functional relationships by calculating correlations between key forcing variables (precipitation, net radiation) and water fluxes (actual evapotranspiration, groundwater recharge, total runoff). We find strong disagreement for groundwater recharge, some disagreement for total runoff, and the best agreement for evapotranspiration. Observation- and theory-derived functional relationships show varying agreements with models, indicating where model representations and our process understanding are particularly uncertain. Overall, our results suggest that model improvement is most important for the representation of energy balance processes, recharge processes, and generally for model behavior in dry and cold regions. We argue that advancing our ability to simulate global hydrology requires a better perceptual understanding of the global water cycle. To evaluate if our models match that understanding, we should explore alternative evaluation strategies, such as the use of functional relationships.

The Integrated Assessment Model (IAM) MESSAGEix-GLOBIOM developed by IIASA is widely used to analyse global change and socioeconomic development scenarios within the energy and land systems across different scales. However, until now, the representation of impacts from climate impacts and water systems within the IAM has been limited. We present a new nexus module for MESSAGEix-GLOBIOM that improves the representation of climate impacts and enables the analysis of interactions between population, economic growth, energy, land, and water resources in a dynamic system. The module uses a spatially resolved representation of water systems to retain hydrological information without compromising computational feasibility. It maps simplified water availability and key infrastructure assumptions with the energy and land systems. The results of this study inform on the transformation pathways required under climate change impacts and mitigation scenarios. The pathways include multi-sectoral indicators highlighting the importance of water as a constraint in energy and land-use decisions and the implications of global responses to limited water availability from different sources, suggesting possible shifts in the energy and land sectors.

This study provides first insights into the micellization behavior and micellar morphologies of bicyclic amphiphiles in four different topologies: bicy-BCP-A, bicy-BCP-B, bicy-BCP-C, and bicy-BCP-D, consisting of poly(n-decyl glycidyl ether) and poly(2-(2-(2-methoxyethoxy)ethoxy)ethyl glycidyl ether) blocks in equivalent molar fractions. Quantitative synchrotron X-ray scattering analysis reveals that all bicyclic amphiphiles self-assemble into unimodal nanomicelles consisting of core, dense corona, and soft corona structural components. The micelles also demonstrate substantial size reductions (56.7-70.7%) compared to micelles of their linear counterpart (l-BCP). The critical micelle concentration, stability, and structural parameters (shape, size, and others) of nanomicelles are differentiated by controlling the bicyclic topology types. bicy-BCP-A, -B, and -C form oblate ellipsoidal micelles, whereas bicy-BCP-D and l-BCP assemble into prolate ellipsoidal micelles. The size is found to be in the following order: bicy-BCP-D < bicy-BCP-C < bicy-BCP-B < bicy-BCP-A << l-BCP. Furthermore, the structural stability is in the following order: l-BCP < bicyBCP-D << bicy-BCP-B < bicy-BCP-C < bicy-BCP-A. These results indicate that the topology-controlled bicyclic block copolymers can be used as a desirable platform for developing high-performance functional core-shell nanoparticles for advanced applications in various fields, including smart drug delivery, biomedical imaging, cosmetics, advanced coating appliances, and molecular electronics.

The nanoscale film morphologies of three-armed cage block copolymers showing three different variations (Cage-A, -B, and -C) have been investigated for the first time via synchrotron grazing incidence X-ray scattering. For all cage block copolymers, the individual block components revealed amorphous characteristics. Nevertheless, they all exhibited either cylindrical or lamellar phase-separated nanostructures. Key structural parameters such as domain spacing (d-spacing), structural ordering, and orientation varied depending on the cage topologies. In particular, the d-spacing of nanostructures ranged from 6.50 to 10.85 nm. Compared to their linear block copolymer analogues, the cage block copolymers achieved a 54.8–74.5% d-spacing reduction. Overall, structural parameters such as d-spacing, structural ordering, and orientation were found to be correlated with the topological confinement which originated from the molecular cage topology.

This study is the first quantitative synchrotron grazing incidence X-ray scattering investigation of nanoscale film morphologies of tricyclic block copolymers based on poly (n-decyl glycidyl ether) (PDGE) and poly (2-(2-(2-methoxyethoxy)-ethoxy)ethyl glycidyl ether) (PTEGGE) blocks in equivalent volume fractions. Both PDGE and PTEGGE blocks of the tricyclic block copolymers are amorphous, but copolymers exhibit phase-separated lamellar nanostructures due to block immiscibility. The lamellar structures vary in their structural parameters such as lamellar orientation and structural integrity stability depending on the degree of topological confinement effect taking effect. Interestingly, sub-10 nm domain spacings are established by all nanostructures, which are remarkably shorter than that of the linear analogue. These exceptionally short domain spacings are evident that the tricyclic block copolymer approach is highly efficient for developing high-performance nanolithographic materials for future advanced semiconductor applications.

Among many properties of cyclic block copolymers, the notable domain spacing (d-spacing) reduction offers nonlinear topology as an effective tool for developing block copolymers for nanolithography. However, the current consensus regarding the topology-morphology correlation is ambiguous and in need of more studies. Here we present the morphological investigation on nanoscale films of cyclic and tadpole-shaped poly(n-decyl glycidyl ether-block-2-(2-(2-methoxyethoxy)ethoxy)-ethyl glycidyl ether)s and their linear counterpart via synchrotron grazing-incidence X-ray scattering. All copolymers form phase-separated nanostructures, in which only the nonlinear copolymers form highly ordered and unidirectional nanostructures. Additionally, d-spacings of cyclic and tadpole-shaped block copolymers are 49.3-53.7% and 25.0-32.5% shorter than that of their linear counterpart, respectively, exhibiting greater or comparable d-spacing reductions against the experimentally and theoretically achieved values from the literature. Overall, this study demonstrates that cyclic and tadpole topologies can be utilized in developing materials with miniaturized dimensions, high structural ordering, and unidirectional orientation for various nanotechnology applications.

Terrestrial water storage (TWS) modulates the hydrological cycle and is a key determinant of water availability and an indicator of drought. While historical TWS variations have been increasingly studied, future changes in TWS and the linkages to droughts remain unexamined. Here, using ensemble hydrological simulations, we show that climate change could reduce TWS in many regions, especially those in the Southern Hemisphere. Strong inter-ensemble agreement indicates high confidence in the projected changes that are driven primarily by climate forcing rather than land and water management activities. Declines in TWS translate to increases in future droughts. By the late twenty-first century, the global land area and population in extreme-to-exceptional TWS drought could more than double, each increasing from 3% during 1976–2005 to 7% and 8%, respectively. Our findings highlight the importance of climate change mitigation to avoid adverse TWS impacts and increased droughts, and the need for improved water resource management and adaptation., Terrestrial water storage (TWS) modulates the hydrological cycle and is a key determinant of water availability and an indicator of drought. While historical TWS variations have been increasingly studied, future changes in TWS and the linkages to droughts remain unexamined. Here, using ensemble hydrological simulations, we show that climate change could reduce TWS in many regions, especially those in the Southern Hemisphere. Strong inter-ensemble agreement indicates high confidence in the projected changes that are driven primarily by climate forcing rather than land and water management activities. Declines in TWS translate to increases in future droughts. By the late twenty-first century, the global land area and population in extreme-to-exceptional TWS drought could more than double, each increasing from 3% during 1976–2005 to 7% and 8%, respectively. Our findings highlight the importance of climate change mitigation to avoid adverse TWS impacts and increased droughts, and the need for improved water resource management and adaptation. © 2021, The Author(s), under exclusive licence to Springer Nature Limited.

Future changes in the climate system could have significant impacts on the natural environment and human activities, which in turn affect changes in the climate system. In the interaction between natural and human systems under climate change conditions, land use is one of the elements that play an essential role. On the one hand, future climate change will affect the availability of water and food, which may impact land-use change. On the other hand, human-induced land-use change can affect the climate system through biogeophysical and biogeochemical effects. To investigate these interrelationships, we developed MIROC-INTEG-LAND (MIROC INTEGrated LAND surface model version 1), an integrated model that combines the land surface component of global climate model MIROC (Model for Interdisciplinary Research on Climate) with water resources, crop production, land ecosystem, and land-use models. The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balance, human water management, and crop growth incorporates a land use decision-making model based on economic activities. In MIROC-INTEG-LAND, spatially detailed information regarding water resources and crop yields is reflected in the prediction of future land-use change, which cannot be considered in the conventional integrated assessment models. In this paper, we introduce the details and interconnections of the submodels of MIROC-INTEG-LAND, compare historical simulations with observations, and identify various interactions between the submodels. By evaluating the historical simulation, we have confirmed that the model reproduces the observed states well. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand. The newly developed MIROC-INTEG-LAND could be combined with atmospheric and ocean models to develop an integrated earth system model to simulate the interactions among coupled natural–human earth system components.

Several studies have explored the interaction across the water, energy, and land (WEL) systems under the scope of policy analysis, highlighting the importance and usefulness of integrated approaches in exploring pathways for achieving the Sustainable Development Goals (SDGs) in the WEL sectors. However, most of these studies neglect the possible impact of climate change on the natural system (e.g. water cycle and crop yields changes) or on technologies (e.g. power plant potentials, desalination, etc.) because of the high complexity, interconnection and uncertainty of these impacts. Using the latest version of the MESSAGEix-GLOBIOM Integrated Assessment Model (IAM), we study the long-term resources, supply and demand of the energy, water and land sectors to determine the regional and sectoral investments required for achieving the SDGs. Here we show the implications of climate feedbacks for different regions and sectors under different climate mitigation scenarios. The largest component of climate impacts, and the highest source of uncertainty, are changes in water availability, which affect irrigation, provision of basic water and sanitation access, hydropower potential and the available technology options for cooling power plants.

IIASA’s Integrated Assessment Model (IAM), MESSAGEix-GLOBIOM is used in various assessments to understand scenarios of socio-economic development within the energy and land systems across scales (global, country, basin). However, the representation of climate impacts and water systems within IAMs until now has been limited. The study goes a step forward on improving the representation of climate impacts and the capability to analyze interactions between population, economic growth, energy, land, and water resources in a dynamic system simultaneously. It uses spatially resolved representation of water systems to retain hydrological information without compromising computational complexity, and simplified water availability and key infrastructure assumptions mapped with the energy and land systems. The results from this study inform the required regional and sectoral investments pathways across mitigation and non-mitigation pathways. The results also highlight the importance of water as a constraint in energy and land-use decisions and implications of global responses to the limited water availability from water resources – renewable water, non-renewable groundwater, desalinated water.

Future drought projection studies typically use multi-model ensemble climate and hydrological simulations. In particular, precipitation, soil moisture, and streamflow simulations are used to quantify the changes in meteorological, agricultural, and hydrological droughts under future climate. Many different drought indices have thus been developed and employed in these projections with different indices often leading to varying states of future droughts. Recently, terrestrial water storage (TWS) has also been used to examine future droughts considering integrated climatic and hydrologic impacts on water stores. This presentation will shed light on drought projections using precipitation, soil moisture, runoff, and TWS drought indices and highlight uncertainties in these projections, including those arising from differences in drought definition or the diversity in drought indices. The presentation will then discuss how the consideration of vulnerability alters drought risk projections, specifically by incorporating human development projections as a proxy of broad vulnerability. Results presented will be based on several dozen ensemble hydrological simulations that include multiple climate models, hydrological models, Representation Concentration Pathways (RCPs), and Shared Socioeconomic Pathways (SSPs). Emphasis will be placed on global scale analyses and regional projections over drought hotspots. The results have appeared in three recent publications.

Ongoing efforts in materials science have resulted in linear block copolymer systems that generate nanostructures via the phase separation of immiscible blocks; however, such systems are limited with regard to their domain miniaturization and lack of orientation control. We overcome these limitations through the bicyclic topological alteration of a block copolymer system. Grazing incidence X-ray scattering analysis of nanoscale polymer films revealed that bicyclic topologies achieve 51.3-72.8% reductions in domain spacing when compared against their linear analogue, which is more effective than the theoretical predictions for conventional cyclic topologies. Moreover, bicyclic topologies achieve unidirectional orientation and a morphological transformation between lamellar and cylindrical domains with high structural integrity. When the near-equivalent volume fraction between the blocks is considered, the formation of hexagonally packed cylindrical domains is particularly noteworthy. Bicyclic topological alteration is therefore a powerful strategy for developing advanced nanostructured materials for microelectronics, displays, and membranes.

Myeloid‐derived suppressor cells (MDSCs) play a crucial role in immunosuppression in tumor‐bearing hosts. MDSCs express arginase‐I and indoleamine 2,3‐dioxygenase; they suppress T‐cell function by reducing the levels of l‐arginine and l‐tryptophan, respectively. We examined the anticancer effects of supplementation of these amino acids in CT26 colon carcinoma‐bearing mice. Oral supplementation of l‐arginine or l‐tryptophan (30 mg/mouse) did not affect tumor growth, whereas oral supplementation of d‐arginine was lethal. Supplementation of l‐arginine showed a tendency to augment the efficacy of cyclophosphamide (CP). CP reduced the proportions of granulocytic MDSCs and increased the proportions of monocytic MDSCs in the spleen and tumor tissues of CT26‐bearing mice. l‐Arginine supplementation alone did not affect the MDSC subsets. CP treatment tended to reduce the plasma levels of l‐arginine in CT26‐bearing mice and significantly increased the number of tumor‐infiltrating CD8+ T cells. In addition, l‐arginine supplementation significantly increased the proportions of tumor peptide‐specific CD8+ T cells in draining lymph nodes. Importantly, additional supplementation of l‐arginine significantly increased the number of cured mice that were treated with CP and anti‐PD‐1 antibody. Totally, l‐arginine supplementation shows promise for boosting the therapeutic efficacy of chemoimmunotherapy., Combination treatment with cyclophosphamide and anti‐PD‐1 antibody significantly suppressed the tumor growth, but did not exert a curative effect. However, the addition of l‐arginine supplementation boosted to complete regression in the majority of mice.

Climate change is expected to exacerbate drought conditions over many global regions. However, the future risk posed by droughts depends not only on the climate-induced changes but also on the changes in societal exposure and vulnerability to droughts. Here we illustrate how the consideration of human vulnerability alters global drought risk associated with runoff (hydrological) and soil moisture (agriculture) droughts during the 21st-century. We combine the changes in drought frequency, population growth, and human development as a proxy of vulnerability to project global drought risk under plausible climate and socioeconomic development pathways. Results indicate that the shift toward a pathway of high greenhouse gas emissions and socioeconomic inequality leads to i) increased population exposure to runoff and soil moisture droughts by 81% and seven folds, respectively, and ii) a stagnation of human development. These consequences are more pronounced for populations living in low than in very high human development countries. In particular, Sub-Saharan Africa and South Asia, where the majority of the world's less developed countries are located, fare the worst in terms of future drought risk. The disparity in risk between low and very high human development countries can be substantially reduced in the presence of a shift toward a world of rapid and sustainable development that actively reduces social inequality and emissions. Our results underscore the importance of rapid human development in hotspots of drought risk where effective adaptation is most needed to reduce future drought impacts.

Droughts are anticipated to intensify in many parts of the world due to climate change. However, the issue of drought definition, namely the diversity of drought indices, makes it difficult to compare drought assessments. This issue is widely known, but its relative importance has never been quantitatively evaluated in comparison to other sources of uncertainty. Here, encompassing three drought categories (meteorological, agricultural, and hydrological droughts) with four temporal scales of interest, we evaluated changes in the drought frequency using multi-model and multi-scenario simulations to identify areas where the definition issue could result in pronounced uncertainties and to what extent. We investigated the disagreement in the signs of changes between drought definitions and decomposed the variance into four main factors: drought definitions, greenhouse gas concentration scenarios, global climate models, and global water models, as well as their interactions. The results show that models were the primary sources of variance over 82% of the global land area. On the other hand, the drought definition was the dominant source of variance in the remaining 17%, especially in parts of northern high-latitudes. Our results highlight specific regions where differences in drought definitions result in a large spread among projections, including areas showing opposite signs of significant changes. At a global scale, 7% of the variance resulted independently from the definition issue, and that value increased to 44% when 1st and 2nd order interactions were considered. The quantitative results suggest that by clarifying hydrological processes or sectors of interest, one could avoid these uncertainties in drought assessments to obtain a clearer picture of future drought change.

This study presents the development of a new bottom-up large-scale hydroeconomic model, Extended Continental-scale Hydroeconomic Optimization (ECHO), that works at a subbasin scale over a continent. The strength of ECHO stems from the integration of a detailed representation of local hydrological and technological constraints with regional and global policies, while accounting for the feedbacks between water, energy, and agricultural sectors. In this study, ECHO has been applied over Africa as a case study with the aim of demonstrating the benefits of this integrated hydroeconomic modeling framework. Results of this framework are overall consistent with previous findings evaluating the cost of water supply and adaptation to global changes in Africa. Moreover, results provide critical assessments of future investment needs in both supply- and demand-side water management options, economic implications of contrasting future socioeconomic and climate change scenarios, and the potential trade-offs among economic and environmental objectives. Overall, this study demonstrates the capacity of ECHO to address challenging research questions examining the sustainability of water supply and the impacts of water management on energy and food sectors and vice versa. As such, we propose ECHO as useful tool for water-related scenario analysis and management options evaluation.

Droughts are anticipated to intensify or become more frequent in many parts of the world due to climate change. However, the issue of drought definition, namely the diversity of drought definition, makes it difficult to compare drought projections and hampers overviewing future changes in drought. This issue is widely known and underscored in recent reports of the Intergovernmental Panel on Climate Change, but the relative importance of the issue and its spatial distribution have never been quantitatively evaluated compared to other sources of uncertainty.Here, using a multi-scenario and multi-model dataset with combinations of three climate change scenarios, four global climate models and seven global water models, we evaluated changes in the frequency of three categories of drought (meteorological, agricultural, and hydrological droughts) by a consistent standardized approach with four different temporal scales of accumulation periods to show how differences among the drought definitions could result in critical uncertainties. For simplicity, this study focuses on one drought index per drought category. Firstly we investigated the disagreement in the sign of changes between definitions, and then we decomposed the overall uncertainty to estimate the relative importance of each source of uncertainty. By a multifactorial ANOVA, uncertainty was decomposed into four main factors, namely drought definitions, climate change scenarios, global climate models and global water impact models, and their interactions.Our results highlight specific regions where the sign of change disagrees between drought definitions. Importantly, changes in drought frequency in such regions tended to be statistically insignificant with low ensemble member agreement. Drought definition attributed to18% of the main factor uncertainty at the global scale, and the definition was the dominant uncertainty source over 11% of the global land area. The contribution of difference in the drought category showed a higher contribution to overall uncertainty than the difference in scales. The contribution of scenario uncertainty was the least among the main factors in general, though it is a dominant factor in the far-future in a couple of hotspot regions such as the Mediterranean region. Overall, model uncertainties were the primary source of uncertainty, and the definition issue was less important over large areas. However, definition uncertainty was the primal uncertainty source with significant changes in particular regions, such as parts of high-latitude areas in the northern hemisphere. One needs to pay attention to these regions in overviewing future drought change. Nonetheless, what this study quantified is the relative importance of uncertainty stemming from drought definition that should be avoidable or reducible if one treats drought specifically. Our results indicate that we can reduce uncertainty in drought projections to some extent and get a clearer picture by clarifying hydrological processes or sectors of interest.

Billions of people rely on groundwater as being an accessible source of drinking water and for 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. Groundwater recharge is an important indicator for groundwater availability, but it is a water flux that is difficult to estimate as uncertainties in the water balance accumulate, leading to possibly large errors in particular in dry regions. 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). Pre-industrial 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 projected changes strongly vary among the different GHM-GCM combinations, and statistically significant changes are only computed for a few regions of the world. Statistically significant GWR increases are projected for northern Europe and some parts of the Arctic, East Africa, and India. Statistically significant decreases are simulated in southern Chile, parts of Brazil, central USA, the Mediterranean, and southeastern China. In some regions, reversals of groundwater recharge trends can be observed with global warming. Because most GHMs do not simulate the impact of changing atmospheric CO2 and climate on vegetation and, thus, evapotranspiration, we investigate how estimated changes in GWR are affected by the inclusion of these processes. In some regions, inclusion leads to differences in groundwater recharge changes of up to 100 mm per year. Most GHMs with active vegetation simulate less severe decreases in groundwater recharge than GHMs without active vegetation and, in some regions, even increases instead of decreases are simulated. However, in regions where GCMs predict decreases in precipitation and where groundwater availability is the most important, model agreement among GHMs with active vegetation is the lowest. Overall, large uncertainties in the model outcomes suggest that additional research on simulating groundwater processes in GHMs is necessary.

Global water models (GWMs) simulate the terrestrial water cycle, on the global scale, and are used to assess the impacts of climate change on freshwater systems. GWMs are developed within different modeling frameworks and consider different underlying hydrological processes, leading to varied model structures. Furthermore, the equations used to describe various processes take different forms and are generally accessible only from within the individual model codes. These factors have hindered a holistic and detailed understanding of how different models operate, yet such an understanding is crucial for explaining the results of model evaluation studies, understanding inter-model differences in their simulations, and identifying areas for future model development. This study provides a comprehensive overview of how state-of-the-art GWMs are designed. We analyze water storage compartments, water flows, and human water use sectors included in 16 GWMs that provide simulations for the Inter-Sectoral Impact Model Intercomparison Project phase 2b (ISIMIP2b). We develop a standard writing style for the model equations to further enhance model improvement, intercomparison, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Seven models used six compartments, while three models (JULES-W1, Mac-PDM.20, and VIC) used the lowest number, three compartments. WaterGAP2 simulates five human water use sectors, while four models (CLM4.5, CLM5.0, LPJmL, and MPI-HM) simulate only water used by humans for the irrigation sector. We conclude that even though hydrologic processes are often based on similar equations, in the end, these equations have been adjusted or have used different values for specific parameters or specific variables. Our results highlight that the predictive uncertainty of GWMs can be reduced through improvements of the existing hydrologic processes, implementation of new processes in the models, and high-quality input data.

Heat uptake is a key variable for understanding the Earth system response to greenhouse gas forcing. Despite the importance of this heat budget, heat uptake by inland waters has so far not been quantified. Here we use a unique combination of global‐scale lake models, global hydrological models and Earth system models to quantify global heat uptake by natural lakes, reservoirs, and rivers. The total net heat uptake by inland waters amounts to 2.6 ± 3.2 ×1020 J over the period 1900–2020, corresponding to 3.6% of the energy stored on land. The overall uptake is dominated by natural lakes (111.7%), followed by reservoir warming (2.3%). Rivers contribute negatively (‐14%) due to a decreasing water volume. The thermal energy of water stored in artificial reservoirs exceeds inland water heat uptake by a factor ∼10.4. This first quantification underlines that the heat uptake by inland waters is relatively small, but non‐negligible., Geophysical Research Letters, 47 (12), ISSN:0094-8276, ISSN:1944-8007