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A better understanding of the food–water nexus requires the development of an integrated model that can simultaneously simulate food production and the requirements and availability of water resources. H08 is a global hydrological model that considers human water use and management (e.g., reservoir operation and crop irrigation). Although a crop growth sub-model has been included in H08 to estimate the global crop-specific calendar, its performance as a yield simulator is poor, mainly because a globally uniform parameter set was used for each crop type. In addition, the effects of CO2 fertilization and vapor pressure deficit on crop yield were not considered. Here, through country-wise parameter calibration and algorithm improvement, we enhanced H08 to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. The simulated crop yield was compared with the Food and Agriculture Organization (FAO) national yield statistics and the global dataset of historical yield for major crops (GDHY) gridded yield estimates with respect to mean bias (across nations) and time series correlation (for individual nations). Our results showed that the effects of CO2 fertilization and vapor pressure deficit had opposite impacts on crop yield. The simulated yield showed good consistency with FAO national yield. The mean biases of the major producer countries were considerably reduced to 2 %, 2 %, −2 %, and −1 % for maize, wheat, rice, and soybean, respectively. The capacity of our model to capture the interannual yield variability observed in FAO yield was limited, although the performance of our model was comparable to that of other mainstream global crop models. The grid-level analysis showed that our model showed a similar spatial pattern to that of the GDHY yield in terms of reproducing the temporal variation over a wide area, although substantial differences were observed in other places. Using the enhanced model, we quantified the contributions of irrigation to global food production and compared our results to an earlier study. Overall, our improvements enabled H08 to estimate crop production and hydrology in a single framework, which will be beneficial for global food–water nexus studies in relation to climate change.

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 the riverine ecosystems, but at the global scale, the assessment of EFs is associated with high uncertainty related to the hydrological data and EF methods employed. Here, we present a novel, in-depth global EF assessment using environmental flow envelopes (EFEs). Sub-basin-specific EFEs are determined for approximately 4400 sub-basins at a monthly time resolution, and their derivation considers the methodological uncertainties related to global-scale EF studies. In addition to a lower bound of discharge based on existing EF methods, we introduce an upper bound of discharge in the EFE. This upper bound enables areas to be identified where streamflow has substantially increased above natural levels. Further, instead of only showing whether EFs are violated over a time period, we quantify, for the first time, the frequency, severity, and trends of EFE violations during the recent historical period. Discharge was derived from global hydrological model outputs from the ISIMIP 2b ensemble. We use pre-industrial (1801–1860) quasi-natural discharge together with a suite of hydrological EF methods to estimate the EFEs. We then compare the EFEs with recent historical (1976–2005) discharge to assess the violations of the EFE. These violations most commonly manifest as insufficient streamflow during the low-flow season, with fewer violations during the intermediate-flow season, and only a few violations during the high-flow season. The EFE violations are widespread and occur in half of the sub-basins of the world during more than 5 % of the months between 1976 and 2005, which is double compared with the pre-industrial period. The trends in EFE violations have mainly been increasing, which will likely continue in the future with the projected hydroclimatic changes and increases in anthropogenic water use. Indications of increased upper extreme streamflow through EFE upper bound violations are relatively scarce and dispersed. Although local fine-tuning is necessary for practical applications, and further research on the coupling between quantitative discharge and riverine ecosystem responses at the global scale is required, the EFEs provide a quick and globally robust way of determining environmental flow allocations at the sub-basin scale to inform global research and policies on water resources management.

Human-controlled reservoirs have a large influence on the global water cycle. While global hydrological models use generic parameterizations to model dam operations, the representation of reservoir regulation is still lacking in many Earth system models. Here we implement and evaluate a widely used reservoir parametrization in the global river-routing model mizuRoute, which operates on a vector-based river network resolving individual lakes and reservoirs and is currently being coupled to an Earth system model. We develop an approach to determine the downstream area over which to aggregate irrigation water demand per reservoir. The implementation of managed reservoirs is evaluated by comparing them to simulations ignoring inland waters and simulations with reservoirs represented as natural lakes using (i) local simulations for 26 individual reservoirs driven by observed inflows and (ii) global-domain simulations driven by runoff from the Community Land Model. The local simulations show the clear added value of the reservoir parametrization, especially for simulating storage for large reservoirs with a multi-year storage capacity. In the global-domain application, the implementation of reservoirs shows an improvement in outflow and storage compared to the no-reservoir simulation, but a similar performance is found compared to the natural lake parametrization. The limited impact of reservoirs on skill statistics could be attributed to biases in simulated river discharge, mainly originating from biases in simulated runoff from the Community Land Model. Finally, the comparison of modelled monthly streamflow indices against observations highlights that including dam operations improves the streamflow simulation compared to ignoring lakes and reservoirs. This study overall underlines the need to further develop and test runoff simulations and water management parameterizations in order to improve the representation of anthropogenic interference of the terrestrial water cycle in Earth system models.

Water diversion systems play crucial roles in assuaging flood risk by diverting and redistributing water within and among basins. For flood and drought assessments, including investigations of the effects of diversion systems on river discharge worldwide, the explicit inclusion of these systems into global hydrological models (GHMs) is essential. However, such representation remains in the pioneering stage because of complex canal operations and insufficient data. Therefore, we developed a regionalized canal operation scheme and implemented it in the H08 GHM for flood diversion in the Chao Phraya River basin (CPRB), Thailand, which is a complex river network with several natural and artificial diversion canals and has been subject to severe flooding in the past, including recent years. Region-specific validation results revealed that the enhanced H08 model with the regionalized diversion scheme could effectively simulate the observed flood diversion pattern in the CPRB. Diverted water comprises approximately 49 % of the annual average river discharge in the CPRB. The simulations further confirmed that the presented canal scheme had the potential to reduce flood risk in the basin by significantly reducing the number of flooding days. A generalized canal scheme with simple input data settings was also constructed for future global applications, providing insights into the maximum level of discharge reduction achievable with diversion of nearly 57 % of the annual average river discharge of the CPRB. Overall, the enhanced H08 model with canal schemes can be adapted and applied to different contexts and regions, accounting for the characteristics of each river network by maintaining the basic principles unaltered.

Global hydrological models that include human activities are powerful tools for assessing water availability and use at global and continental scales. Such models are typically applied at a spatial resolution of 30 arcmin (approximately 50 km). In recent years, some 5 arcmin (9 km) applications have been reported but with numerous technical challenges, including the validation of calculations for more than 1 × 106 grid cells and the conversion of simulation results into meaningful information relevant to water resource management. Here, the H08 global water resources model was applied in two ways to Kyushu island in Japan at a resolution of 1 arcmin (2 km), and the detailed results were compared. One method involved feeding interpolated global meteorological and geographic data into the default global model (GLB; in accordance with previous high-resolution applications). For the other method, locally derived boundary conditions were input to the localized model (LOC; this method can be easily extended and applied to other regions, at least across Japan). The results showed that the GLB cannot easily reproduce the historical record, especially for variables related to human activities (e.g., dam operation and water withdrawal). LOC is capable of estimating natural and human water balance components at daily timescales and providing reliable information for regional water resource assessment. The results highlight the importance of improving data preparation and modeling methods to represent water management and use in hyper-resolution global hydrology simulations.

Process-based models are powerful tools for simulating the economic impacts of climate change, but they are computationally expensive. In order to project climate-change impacts under various scenarios, produce probabilistic ensembles, conduct online coupled simulations, or explore pathways by numerical optimization, the computational and implementation cost of economic impact calculations should be reduced. To do so, in this study, we developed various emulators that mimic the behaviours of simulation models, namely economic models coupled with bio/physical-process-based impact models, by statistical regression techniques. Their performance was evaluated for multiple sectors and regions. Among the tested emulators, those composed of artificial neural networks, which can incorporate non-linearities and interactions between variables, performed better particularly when finer input variables were available. Although simple functional forms were effective for approximating general tendencies, complex emulators are necessary if the focus is regional or sectoral heterogeneity. Since the computational cost of the developed emulators is sufficiently small, they could be used to explore future scenarios related to climate-change policies. The findings of this study could also help researchers design their own emulators in different situations.

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 modelling 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 16 state-of-the-art GWMs are designed. We analyse water storage compartments, water flows, and human water use sectors included in models 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 enhance model intercomparison, improvement, and communication. In this study, WaterGAP2 used the highest number of water storage compartments, 11, and CWatM used 10 compartments. Six models used six compartments, while four models (DBH, 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 for the irrigation sector. We conclude that, even though hydrological processes are often based on similar equations for various processes, in the end these equations have been adjusted or models have used different values for specific parameters or specific variables. The similarities and differences found among the models analysed in this study are expected to enable us to reduce the uncertainty in multi-model ensembles, improve existing hydrological processes, and integrate new processes.

Many scenarios of future climate evolution and its anthropogenic drivers include considerable amounts of bioenergy as a fuel source, as a negative emission technology, and for providing electricity. The associated freshwater abstractions for irrigation of dedicated biomass plantations might be substantial and therefore potentially increase water limitation and stress in affected regions; however, assumptions and quantities of water use provided in the literature vary strongly. This paper reviews existing global assessments of freshwater abstractions for bioenergy production and puts these estimates into the context of scenarios of other water-use sectors. We scanned the available literature and (out of 430 initial hits) found 16 publications (some of which include several bioenergy-water-use scenarios) with reported values on global irrigation water abstractions for biomass plantations, suggesting water withdrawals in the range of 128.4 to 9000 km3 yr−1, which would come on top of (or compete with) agricultural, industrial, and domestic water withdrawals. To provide an understanding of the origins of this large range, we present the diverse underlying assumptions, discuss major study differences, and calculate an inverse water-use efficiency (iwue), which facilitates comparison of the required freshwater amounts per produced biomass harvest. We conclude that due to the potentially high water demands and the tradeoffs that might go along with them, bioenergy should be an integral part of global assessments of freshwater demand and use. For interpreting and comparing reported estimates of possible future bioenergy water abstractions, full disclosure of parameters and assumptions is crucial. A minimum set should include the complete water balances of bioenergy production systems (including partitioning of blue and green water), bioenergy crop species and associated water-use efficiencies, rainfed and irrigated bioenergy plantation locations (including total area and meteorological conditions), and total biomass harvest amounts. In the future, a model intercomparison project with standardized parameters and scenarios would be helpful.

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.

Large-scale deployment of bioenergy plantations would have adverse effects on water resources. There is an increasing need to ensure the appropriate inclusion of the bioenergy crops in global hydrological models. Here, through parameter calibration and algorithm improvement, we enhanced the global hydrological model H08 to simulate the bioenergy yield from two dedicated herbaceous bioenergy crops: Miscanthus and switchgrass. Site-specific evaluations showed that the enhanced model had the ability to simulate yield for both Miscanthus and switchgrass, with the calibrated yields being well within the ranges of the observed yield. Independent country-specific evaluations further confirmed the performance of the H08 (v.bio1). Using this improved model, we found that unconstrained irrigation more than doubled the yield under rainfed condition, but reduced the water use efficiency (WUE) by 32 % globally. With irrigation, the yield in dry climate zones can exceed the rainfed yields in tropical climate zones. Nevertheless, due to the low water consumption in tropical areas, the highest WUE was found in tropical climate zones, regardless of whether the crop was irrigated. Our enhanced model provides a new tool for the future assessment of bioenergy–water tradeoffs.

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.

The medium-entropy alloy CrCoNi is known to have exceptional mechanical properties. To clarify its local structure, we performed extended x-ray absorption fine structure measurement of CrCoNi. The structural disorder is larger in Cr sites than in other constituent elements, which is consistent with the larger atomic displacement of the Cr atoms predicted by previous first-principles calculations. The Cr atom has a solute-type characteristic that induces local disorder. The differences in local disorder among the constituent elements decrease as the annealing time increases in the temperature range in which a short-range order develops.

Human water withdrawal has increasingly altered the global water cycle in past decades, yet our understanding of its driving forces and patterns is limited. Reported historical estimates of sectoral water withdrawals are often sparse and incomplete, mainly restricted to water withdrawal estimates available at annual and country scales, due to a lack of observations at seasonal and local scales. In this study, through collecting and consolidating various sources of reported data and developing spatial and temporal statistical downscaling algorithms, we reconstruct a global monthly gridded (0.5°) sectoral water withdrawal dataset for the period 1971–2010, which distinguishes six water use sectors, i.e., irrigation, domestic, electricity generation (cooling of thermal power plants), livestock, mining, and manufacturing. Based on the reconstructed dataset, the spatial and temporal patterns of historical water withdrawal are analyzed. Results show that total global water withdrawal has increased significantly during 1971–2010, mainly driven by the increase in irrigation water withdrawal. Regions with high water withdrawal are those densely populated or with large irrigated cropland production, e.g., the United States (US), eastern China, India, and Europe. Seasonally, irrigation water withdrawal in summer for the major crops contributes a large percentage of total annual irrigation water withdrawal in mid- and high-latitude regions, and the dominant season of irrigation water withdrawal is also different across regions. Domestic water withdrawal is mostly characterized by a summer peak, while water withdrawal for electricity generation has a winter peak in high-latitude regions and a summer peak in low-latitude regions. Despite the overall increasing trend, irrigation in the western US and domestic water withdrawal in western Europe exhibit a decreasing trend. Our results highlight the distinct spatial pattern of human water use by sectors at the seasonal and annual timescales. The reconstructed gridded water withdrawal dataset is open access, and can be used for examining issues related to water withdrawals at fine spatial, temporal, and sectoral scales.

Humans abstract water from various sources to sustain their livelihood and society. Some global hydrological models (GHMs) include explicit schemes of human water abstraction, but the representation and performance of these schemes remain limited. We substantially enhanced the water abstraction schemes of the H08 GHM. This enabled us to estimate water abstraction from six major water sources, namely, river flow regulated by global reservoirs (i.e., reservoirs regulating the flow of the world's major rivers), aqueduct water transfer, local reservoirs, seawater desalination, renewable groundwater, and nonrenewable groundwater. In its standard setup, the model covers the whole globe at a spatial resolution of 0.5° × 0.5°, and the calculation interval is 1 day. All the interactions were simulated in a single computer program, and all water fluxes and storage were strictly traceable at any place and time during the simulation period. A global hydrological simulation was conducted to validate the performance of the model for the period of 1979–2013 (land use was fixed for the year 2000). The simulated water fluxes for water abstraction were validated against those reported in earlier publications and showed a reasonable agreement at the global and country level. The simulated monthly river discharge and terrestrial water storage (TWS) for six of the world's most significantly human-affected river basins were compared with gauge observations and the data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission. It is found that the simulation including the newly added schemes outperformed the simulation without human activities. The simulated results indicated that, in 2000, of the 3628±75 km3 yr−1 global freshwater requirement, 2839±50 km3 yr−1 was taken from surface water and 789±30 km3 yr−1 from groundwater. Streamflow, aqueduct water transfer, local reservoirs, and seawater desalination accounted for 1786±23, 199±10, 106±5, and 1.8±0 km3 yr−1 of the surface water, respectively. The remaining 747±45 km3 yr−1 freshwater requirement was unmet, or surface water was not available when and where it was needed in our simulation. Renewable and nonrenewable groundwater accounted for 607±11 and 182±26 km3 yr−1 of the groundwater total, respectively. Each source differed in its renewability, economic costs for development, and environmental consequences of usage. The model is useful for performing global water resource assessments by considering the aspects of sustainability, economy, and environment.

Over recent decades, the global population has been rapidly increasing and human activities have altered terrestrial water fluxes to an unprecedented extent. 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 for increased 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 have incorporated human impacts on the hydrological cycle, yet the representation of human activities in hydrological models remains challenging. In this paper we provide a synthesis of progress in the development and application of human impact modelling 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.

Seawater desalination is a practical technology for providing fresh water to coastal arid regions. Indeed, the use of desalination is rapidly increasing due to growing water demand in these areas and decreases in production costs due to technological advances. In this study, we developed a model to estimate the areas where seawater desalination is likely to be used as a major water source and the likely volume of production. The model was designed to be incorporated into global hydrological models (GHMs) that explicitly include human water usage. The model requires spatially detailed information on climate, income levels, and industrial and municipal water use, which represent standard input/output data in GHMs. The model was applied to a specific historical year (2005) and showed fairly good reproduction of the present geographical distribution and national production of desalinated water in the world. The model was applied globally to two periods in the future (2011–2040 and 2041–2070) under three distinct socioeconomic conditions, i.e., SSP (shared socioeconomic pathway) 1, SSP2, and SSP3. The results indicate that the usage of seawater desalination will have expanded considerably in geographical extent, and that production will have increased by 1.4–2.1-fold in 2011–2040 compared to the present (from 2.8 × 109 m3 yr−1 in 2005 to 4.0–6.0 × 109 m3 yr−1), and 6.7–17.3-fold in 2041–2070 (from 18.7 to 48.6 × 109 m3 yr−1). The estimated global costs for production for each period are USD 1.1–10.6 × 109 (0.002–0.019 % of the total global GDP), USD 1.6–22.8 × 109 (0.001–0.020 %), and USD 7.5–183.9 × 109 (0.002–0.100 %), respectively. The large spreads in these projections are primarily attributable to variations within the socioeconomic scenarios.

To sustain growing food demand and increasing standard of living, global water use increased by nearly 6 times during the last 100 years, and continues to grow. As water demands get closer and closer to the water availability in many regions, each drop of water becomes increasingly valuable and water must be managed more efficiently and intensively. However, soaring water use worsens water scarcity conditions already prevalent in semi-arid and arid regions, increasing uncertainty for sustainable food production and economic development. Planning for future development and investments requires that we prepare water projections for the future. However, estimations are complicated because the future of the world's waters will be influenced by a combination of environmental, social, economic, and political factors, and there is only limited knowledge and data available about freshwater resources and how they are being used. The Water Futures and Solutions (WFaS) initiative coordinates its work with other ongoing scenario efforts for the sake of establishing a consistent set of new global water scenarios based on the shared socio-economic pathways (SSPs) and the representative concentration pathways (RCPs). The WFaS "fast-track" assessment uses three global water models, namely H08, PCR-GLOBWB, and WaterGAP. This study assesses the state of the art for estimating and projecting water use regionally and globally in a consistent manner. It provides an overview of different approaches, the uncertainty, strengths and weaknesses of the various estimation methods, types of management and policy decisions for which the current estimation methods are useful. We also discuss additional information most needed to be able to improve water use estimates and be able to assess a greater range of management options across the water–energy–climate nexus.

Future projections on irrigation water under a changing climate are highly dependent on meteorological data derived from general circulation models (GCMs). Since climate projections include biases, bias correction is widely used to adjust meteorological elements, such as the atmospheric temperature and precipitation, but less attention has been paid to biases in humidity. Hence, in many cases, uncorrected humidity data have been directly used to analyze the impact of future climate change. In this study, we examined how the biases remaining in the humidity data of five GCMs propagate into the estimation of irrigation water demand and consumption from rivers using the global hydrological model (GHM) H08. First, to determine the effects of humidity bias across GCMs, we ran H08 with GCM-based meteorological forcing data sets distributed by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). A state-of-the-art bias correction method was applied to the data sets without correcting biases in humidity. Differences in the monthly relative humidity amounted to 11.7 to 20.4 % RH (percentage relative humidity) across the GCMs and propagated into differences in the estimated irrigation water demand, resulting in a range between 1152.6 and 1435.5 km3 yr−1 for 1971–2000. Differences in humidity also propagated into future projections. Second, sensitivity analysis with hypothetical humidity biases of ±5 % RH added homogeneously worldwide revealed the large negative sensitivity of irrigation water abstraction in India and East China, which are heavily irrigated. Third, we performed another set of simulations with bias-corrected humidity data to examine whether bias correction of the humidity can reduce uncertainties in irrigation water across the GCMs. The results showed that bias correction, even with a primitive methodology that only adjusts the monthly climatological relative humidity, helped reduce uncertainties across the GCMs: by using bias-corrected humidity data, the uncertainty ranges of irrigation water demand across the five GCMs were successfully reduced from 282.9 to 167.0 km3 yr−1 for the present period, and from 381.1 to 214.8 km3 yr−1 for the future period (RCP8.5, 2070–2099). Although different GHMs have different sensitivities to atmospheric humidity because different types of potential evapotranspiration formulae are implemented in them, bias correction of the humidity should be applied to forcing data, particularly for the evaluation of evapotranspiration and irrigation water.

The intensity, duration, and geographic extent of floods in Bangladesh mostly depend on the combined influences of three river systems, the Ganges, Brahmaputra and Meghna (GBM). In addition, climate change is likely to have significant effects on the hydrology and water resources of the GBM basin and may ultimately lead to more serious floods in Bangladesh. However, the assessment of climate change impacts on the basin-scale hydrology by using well-calibrated hydrologic modeling has seldom been conducted in the GBM basin due to the lack of observed data for calibration and validation. In this study, a macroscale hydrologic model H08 has been applied over the basin at a relatively fine grid resolution (10 km) by integrating the fine-resolution DEM (digital elevation model) data for accurate river networks delineation. The model has been calibrated via the analysis of model parameter sensitivity and validated based on long-term observed daily streamflow data. The impacts of climate change (considering a high-emissions path) on runoff, evapotranspiration, and soil moisture are assessed by using five CMIP5 (Coupled Model Intercomparison Project Phase 5) GCMs (global circulation models) through three time-slice experiments; the present-day (1979–2003), the near-future (2015–2039), and the far-future (2075–2099) periods. Results show that, by the end of 21st century, (a) the entire GBM basin is projected to be warmed by ~4.3 °C; (b) the changes of mean precipitation (runoff) are projected to be +16.3% (+16.2%), +19.8% (+33.1%), and +29.6% (+39.7%) in the Brahmaputra, Ganges, and Meghna, respectively; and (c) evapotranspiration is projected to increase for the entire GBM (Brahmaputra: +16.4%, Ganges: +13.6%, Meghna: +12.9%) due to increased net radiation as well as warmer temperature. Future changes of hydrologic variables are larger in the dry season (November–April) than in the wet season (May–October). Amongst the three basins, the Meghna shows the highest increase in runoff, indicating higher possibility of flood occurrence. The uncertainty due to the specification of key model parameters in model predictions is found to be low for estimated runoff, evapotranspiration and net radiation. However, the uncertainty in estimated soil moisture is rather large with the coefficient of variation ranging from 14.4 to 31% among the three basins.

Water supply sources for irrigation (e.g. rivers and reservoirs) are critically important for agricultural productivity. The current rapid increase in irrigation water use is considered unsustainable and threatens food production. In this study, we estimated the time-varying dependence of irrigation water requirements from water supply sources, with a particular focus on variations in irrigation area during past (1960–2001) and future (2002–2050) periods using the global water resources model, H08. The H08 model can simulate water requirements on a daily basis at a resolution of 1.0° × 1.0° latitude and longitude. The sources of irrigation water requirements in the past simulations were specified using four categories: rivers (RIV), large reservoirs (LR) with a storage capacity greater than 1.0 × 109 m3, medium-size reservoirs (MSR) with storage capacities ranging from 1.0 × 109 m3 to 3.0 × 106 m3, and non-local non-renewable blue water (NNBW). The simulated results from 1960 to 2001 showed that RIV, MSR and NNBW increased significantly from the 1960s to the early 1990s globally, but LR increased at a relatively low rate. After the early 1990s, the increase in RIV declined as it approached a critical limit, due to the continued expansion of irrigation area. MSR and NNBW increased significantly, during the same time period, following the expansion of the irrigation area and the increased storage capacity of the medium-size reservoirs. We also estimated future irrigation water requirements from the above four water supply sources and an additional water supply source (ADD) in three future simulation designs; irrigation area change, climate change, and changes in both irrigation area and climate. ADD was defined as a future increase in NNBW. After the 2020s, MSR was predicted to approach the critical limit, and ADD would account for 11–23% of the total requirements in the 2040s.

The international trade of food commodities links water and food systems, with important implications for both water and food security. The embodied water resources associated with food trade are referred to as "virtual water trade". We present the first study of the impact of climate change on global virtual water trade flows and associated savings for the year 2030. In order to project virtual water trade and savings under climate change, it is essential to obtain projections of both bilateral crop trade and the virtual water content of crops in each country of production. We use the Global Trade Analysis Project model to estimate bilateral crop trade under changes in agricultural productivity for rice, soy, and wheat. We use the H08 global hydrologic model to determine the impact of climatic changes to crop evapotranspiration for rice, soy, and wheat in each country of production. Then, we combine projections of bilateral crop trade with estimates of virtual water content to obtain virtual water trade flows under climate change. We find that the total volume of virtual water trade is likely to go down under climate change, due to decreased crop trade from higher crop prices under scenarios of declining crop yields and due to decreased virtual water content under high agricultural productivity scenarios. However, the staple food trade is projected to save more water across most climate change scenarios, largely because the wheat trade re-organizes into a structure where large volumes of wheat are traded from relatively water-efficient exporters to less efficient importers.

A global water scarcity assessment for the 21st century was conducted under the latest socio-economic scenario for global change studies, namely Shared Socio-economic Pathways (SSPs). SSPs depict five global situations with substantially different socio-economic conditions. In the accompanying paper, a water use scenario compatible with the SSPs was developed. This scenario considers not only quantitative socio-economic factors such as population and electricity production but also qualitative ones such as the degree of technological change and overall environmental consciousness. In this paper, water availability and water scarcity were assessed using a global hydrological model called H08. H08 simulates both the natural water cycle and major human activities such as water abstraction and reservoir operation. It simulates water availability and use at daily time intervals at a spatial resolution of 0.5° × 0.5°. A series of global hydrological simulations were conducted under the SSPs, taking into account different climate policy options and the results of climate models. Water scarcity was assessed using an index termed the Cumulative Abstraction to Demand ratio, which is expressed as the accumulation of daily water abstraction from a river divided by the daily consumption-based potential water demand. This index can be used to express whether renewable water resources are available from rivers when required. The results suggested that by 2071–2100 the population living under severely water-stressed conditions for SSP1-5 will reach 2588–2793 × 106 (39–42% of total population), 3966–4298 × 106 (46–50%), 5334–5643 × 106 (52–55%), 3427–3786 × 106 (40–45%), 3164–3379 × 106 (46–49%) respectively, if climate policies are not adopted. Even in SSP1 (the scenario with least change in water use and climate) global water scarcity increases considerably, as compared to the present-day. This is mainly due to the growth in population and economic activity in developing countries, and partly due to hydrological changes induced by global warming.

A novel global water scarcity assessment for the 21st century is presented in a two-part paper. In this first paper, water use scenarios are presented for the latest global hydrological models. The scenarios are compatible with the socio-economic scenarios of the Shared Socio-economic Pathways (SSPs), which are a part of the latest set of scenarios on global change developed by the integrated assessment, the IAV (climate change impact, adaptation, and vulnerability assessment), and the climate modeling community. The SSPs depict five global situations based on substantially different socio-economic conditions during the 21st century. Water use scenarios were developed to reflect not only quantitative socio-economic factors, such as population and electricity production, but also key qualitative concepts such as the degree of technological change and overall environmental consciousness. Each scenario consists of five factors: irrigated area, crop intensity, irrigation efficiency, and withdrawal-based potential industrial and municipal water demands. The first three factors are used to estimate the potential irrigation water demand. All factors were developed using simple models based on a literature review and analysis of historical records. The factors are grid-based at a spatial resolution of 0.5° × 0.5° and cover the whole 21st century in five-year intervals. Each factor shows wide variation among the different global situations depicted: the irrigated area in 2085 varies between 2.7 × 106 and 4.5 × 106 km2, withdrawal-based potential industrial water demand between 246 and 1714 km3 yr−1, and municipal water between 573 and 1280 km3 yr−1. The water use scenarios can be used for global water scarcity assessments that identify the regions vulnerable to water scarcity and analyze the timing and magnitude of scarcity conditions.

Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.

To assess global water resources from the perspective of subannual variation in water availability and water use, an integrated water resources model was developed. In a companion report, we presented the global meteorological forcing input used to drive the model and six modules, namely, the land surface hydrology module, the river routing module, the crop growth module, the reservoir operation module, the environmental flow requirement module, and the anthropogenic withdrawal module. Here, we present the results of the model application and global water resources assessments. First, the timing and volume of simulated agriculture water use were examined because agricultural use composes approximately 85% of total consumptive water withdrawal in the world. The estimated crop calendar showed good agreement with earlier reports for wheat, maize, and rice in major countries of production. In major countries, the error in the planting date was ±1 mo, but there were some exceptional cases. The estimated irrigation water withdrawal also showed fair agreement with country statistics, but tended to be underestimated in countries in the Asian monsoon region. The results indicate the validity of the model and the input meteorological forcing because site-specific parameter tuning was not used in the series of simulations. Finally, global water resources were assessed on a subannual basis using a newly devised index. This index located water-stressed regions that were undetected in earlier studies. These regions, which are indicated by a gap in the subannual distribution of water availability and water use, include the Sahel, the Asian monsoon region, and southern Africa. The simulation results show that the reservoir operations of major reservoirs (>1 km3) and the allocation of environmental flow requirements can alter the population under high water stress by approximately −11% to +5% globally. The integrated model is applicable to assessments of various global environmental projections such as climate change.

To assess global water availability and use at a subannual timescale, an integrated global water resources model was developed consisting of six modules: land surface hydrology, river routing, crop growth, reservoir operation, environmental flow requirement estimation, and anthropogenic water withdrawal. The model simulates both natural and anthropogenic water flow globally (excluding Antarctica) on a daily basis at a spatial resolution of 1°×1° (longitude and latitude). This first part of the two-feature report describes the six modules and the input meteorological forcing. The input meteorological forcing was provided by the second Global Soil Wetness Project (GSWP2), an international land surface modeling project. Several reported shortcomings of the forcing component were improved. The land surface hydrology module was developed based on a bucket type model that simulates energy and water balance on land surfaces. The crop growth module is a relatively simple model based on concepts of heat unit theory, potential biomass, and a harvest index. In the reservoir operation module, 452 major reservoirs with >1 km3 each of storage capacity store and release water according to their own rules of operation. Operating rules were determined for each reservoir by an algorithm that used currently available global data such as reservoir storage capacity, intended purposes, simulated inflow, and water demand in the lower reaches. The environmental flow requirement module was newly developed based on case studies from around the world. Simulated runoff was compared and validated with observation-based global runoff data sets and observed streamflow records at 32 major river gauging stations around the world. Mean annual runoff agreed well with earlier studies at global and continental scales, and in individual basins, the mean bias was less than ±20% in 14 of the 32 river basins and less than ±50% in 24 basins. The error in the peak was less than ±1 mo in 19 of the 27 basins and less than ±2 mo in 25 basins. The performance was similar to the best available precedent studies with closure of energy and water. The input meteorological forcing component and the integrated model provide a framework with which to assess global water resources, with the potential application to investigate the subannual variability in water resources.

China is the largest electricity producer in the world and more than 70% of its electricity is from coal-fired power plants where water is an indispensable input, primarily for cooling purposes. Water shortages could hamper coal-fired power plants productions and result in economic losses. In this study, we simulate monthly river flows in China on a 0.5° × 0.5° spatial resolution using a calibrated physically based hydrological model, H08, that incorporates human interventions during the current (1981–2014) and future period 2050s (2035–2065) under two carbon emission scenarios Representative Concentration Pathway 2.6 and 8.5. Water demands by individual power plants are calculated based on plant-level data. We define power plants as facing low-flow water risks when the monthly 10 year return low flow is projected to be below the plant’s water withdrawal requirement. We find that around 10% of China’s coal-fired power capacities face low-flow water risks from July to October (the monsoon peak in the eastern Asia), and 20% the rest of the year. Particularly in the North Grid, around 35% to 60% of its regional coal-fired power capacity is at such risks from December to June. Under climate change, low-flow amounts are expected to increase in the current dry northern China except decreasing in the northwest, which is expected to alleviate the low flow water risks facing coal power plants in China except in the Northwest Inland River Basin. In the East and South Grids, if their growing electricity demands continue depending on coal, increasing utilization rate of coal power facilities can lead to heightened demand-driven water risks.

Magnetic structures of the noncentrosymmetric magnet Sr 2 MnSi 2 O 7 were examined through neutron diffraction for powder and single-crystalline samples, as well as magnetometry measurements. All allowed magnetic structures for space group P42 1 m with the magnetic wavevector q m = (0, 0, ½) were refined via irreducible representation and magnetic space group analyses. The compound was refined to have in-plane magnetic moments within the magnetic space group Cmc2 1 .1' c (No. 36.177) under zero field, which can be altered to P2 1 2 1 2 1 .1' c (No. 19.28) above μ 0 H = 0.067 (5) T to align induced weak-ferromagnetic components within one layer on the ab plane. All refined parameters are provided following the recent framework based upon the magnetic space group, which better conveys when exchanging crystallographic information for commensurate magnetic structures.

Weyl semimetals resulting from either inversion ( P ) or time-reversal ( T ) symmetry breaking have been revealed to show the record-breaking large optical response due to intense Berry curvature of Weyl-node pairs. Different classes of Weyl semimetals with both P and T symmetry breaking potentially exhibit optical magnetoelectric (ME) responses, which are essentially distinct from the previously observed optical responses in conventional Weyl semimetals, leading to the versatile functions such as directional dependence for light propagation and gyrotropic effects. However, such optical ME phenomena of (semi)metallic systems have remained elusive so far. Here, we show the large nonlinear optical ME response in noncentrosymmetric magnetic Weyl semimetal PrAlGe, in which the polar structural asymmetry and ferromagnetic ordering break P and T symmetry. We observe the giant second harmonic generation (SHG) arising from the P symmetry breaking in the paramagnetic phase, being comparable to the largest SHG response reported in Weyl semimetal TaAs. In the ferromagnetically ordered phase, it is found that interference between this nonmagnetic SHG and the magnetically induced SHG emerging due to both P and T symmetry breaking results in the magnetic field switching of SHG intensity. Furthermore, such an interference effect critically depends on the light-propagating direction. The corresponding magnetically induced nonlinear susceptibility is significantly larger than the prototypical ME material, manifesting the existence of the strong nonlinear dynamical ME coupling. The present findings establish the unique optical functionality of P - and T -symmetry broken ME topological semimetals., Competing Interests: Competing interests statement:The authors declare no competing interest.

A single-component molecular radical crystal of Co III (tbp˙ - )(CN) 2 , where tbp = tetrabenzoporphyrinato ligand, exhibiting a diamond lattice was fabricated as a potential candidate for a three-dimensional Dirac electron system. Band structure calculations revealed that the Fermi energy level was located at the Dirac point. A small electrical resistivity of 160 Ω cm was observed at 2 K under the application of 2.4 GPa. Furthermore, substituting Co III by Fe III or Mn III led to the introduction of local magnetic moments into the diamond-lattice system. M III (tbp˙ - )L 2 crystals will open up uncharted fields in the study of the Dirac electron systems.

The last 12 months have provided further evidence of the potential for cascading ecological and socio-political crises that were warned of 12 months ago. Then a consensus statement from the Regional Action on Climate Change Symposium warned: "the Earth's climatic, ecological, and human systems are converging towards a crisis that threatens to engulf global civilization within the lifetimes of children now living." Since then, the consequences of a broad set of extreme climate events (notably droughts, floods, and fires) have been compounded by interaction with impacts from multiple pandemics (including COVID-19 and cholera) and the Russia-Ukraine war. As a result, new connections are becoming visible between climate change and human health, large vulnerable populations are experiencing food crises, climate refugees are on the move, and the risks of water, food, and climate disruption have been visibly converging and compounding. Many vulnerable populations now face serious challenges to adapt. In light of these trends, this year, RACC identifies a range of measures to be taken at global and regional levels to bolster the resilience of these populations in the face of such emerging crises. In particular, at all scales, there is a need for globally available local data, reliable analytic techniques, community capacity to plan adaptation strategies, and the resources (scientific, technical, cultural, and economic) to implement them. To date, the rate of growth of the support for climate change resilience lags behind the rapid growth of cascading and converging risks. As an urgent message to COP27, it is proposed that the time is now right to devote much greater emphasis, global funding, and support to the increasing adaptation needs of vulnerable populations., (© The Author(s) 2022.)

The countries of Southeast Asia are projected to experience severe flood damage and economic impacts from climate change, compared with the global average. Hence adaptation by incorporating infrastructures is essential, but it has been seldom explicitly included in the simulations projecting climate change impacts on flood risk in these countries. Quantifying the effects of infrastructure is the key to climate change impact and adaptation assessment. Therefore, this study was conducted in the Chao Phraya River Basin (CPRB) in Thailand to examine the adaptation potential of (i) existing structural and non-structural measures that include reservoir and diversion dams, diversion canals, and water retention areas, and (ii) the combined adaptation measures, a combination of alterations made to the existing diversion canals and retention areas, on reducing future floods using the H08 global hydrological model (GHM). The results revealed that the impact of existing measures on the future flood reduction was smaller than the increase caused by warming in the CPRB. Conversely, the combined adaptation measures successfully mitigated the effect of warming by redirecting nearly 50 % of the diverted river flow to the ocean and storing 30 % of the diverted flow in the retention areas. Although a remarkable reduction was noted in the basin-wide flood risk, the effect of adaptation measures greatly varied across the basin. The combined adaptation measures largely reduced the number of flooding days by close to 100 at many of the considered stations within the basin, except for extreme flood events (historical 1-percentile flood events). This further reveals that the feasibility of adaptation measures in alleviating the extreme future floods will be limited in flood-vulnerable basins and thus require area-based prioritization for flood management. The modelling framework implemented in this study can be easily adapted to different GHMs and regions and should be examined for their applicability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The chemical carrier doping of molecular Mott insulators has been poorly investigated to date due to its difficulty. In this study, iodine doping of a molecular Mott insulator, lithium phthalocyanine crystallized in the x-form (x-LiPc), was performed to obtain metallic x-LiPcI. Crystal structure analysis revealed that iodine atoms penetrated channels of x-LiPc and formed one-dimensional chains. The Raman spectroscopy of x-LiPcI indicated the existence of linear I 5 - , demonstrating a transition from a half-filled band of the Mott insulating state to a 2/5-filled band of the metallic state. Electrical resistivity measurements confirmed the metallic nature of x-LiPcI, whereas a thermally activated behavior was observed for pristine x-LiPc. Furthermore, the x-LiPc Mott insulator was reproduced by dedoping iodine from x-LiPcI, suggesting that the electronic state can be reversibly tuned between the Mott insulating and metallic states by chemical doping and dedoping., (© 2022 Wiley-VCH GmbH.)