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Several safe boundaries of critical Earth system processes have already been crossed due to human perturbations; not accounting for their interactions may further narrow the safe operating space for humanity. Using expert knowledge elicitation, we explored interactions among seven variables representing Earth system processes relevant to food production, identifying many interactions little explored in Earth system literature. We found that green water and land system change affect other Earth system processes strongly, while land, freshwater and ocean components of biosphere integrity are the most impacted by other Earth system processes, most notably blue water and biogeochemical flows. We also mapped a complex network of mechanisms mediating these interactions and created a future research prioritization scheme based on interaction strengths and existing knowledge gaps. Our study improves the understanding of Earth system interactions, with sustainability implications including improved Earth system modelling and more explicit biophysical limits for future food production.

Droughts that exceed the magnitudes of historical variation ranges could occur increasingly frequently under future climate conditions. However, the time of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and existing water resource management measures and estimate the time of the first emergence of unprecedented regional drought conditions centered on the low-flow season. The times are detected for several subcontinental-scale regions, and three regions, namely, Southwestern South America, Mediterranean Europe, and Northern Africa, exhibit particularly robust results under the high-emission scenario. These three regions are expected to confront unprecedented conditions within the next 30 years with a high likelihood regardless of the emission scenarios. In addition, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. However, appropriate and prior adaptation measures are considered indispensable when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons.

This deposit contains the LPJmL model simulation outputs of mean monthly root-zone soil moisture ("LPJmL_rzsm_hist.zip") and the data underlying the plot in Fig. 3 ("Fig_3_plotdata.xlsx") in the article: Wang-Erlandsson, L., Tobian, A., van der Ent, R. J., Fetzer, I., te Wierik, S., Porkka, M., Staal, A., Jaramillo, F., Dahlmann, H., Singh, C., Greve, P., Gerten, D., Keys, P.W., Gleeson, T, Cornell, S. E., Steffen, W., Bai, X., Rockström, J., (2022): A planetary boundary for green water. Nature Reviews Earth & Environment. For method description, please refer to the article. Files in the folder "LPJmL_rzsm_hist.zip" are named as NN_rzsm_hist_M.tif, in which: NN refers to the name of an Earth system model, of which the outputs were used as forcing in the LPJmL runs rzsm refers to "root zone soil moisture" hist refers to historical period 1850-2014 M refers to name of month (jan for January etc.)

Freshwater ecosystems have been degraded due to intensive freshwater abstraction. Therefore, environmental flow requirements (EFRs) methods have been proposed to maintain healthy rivers and/or restore river flows. In this study, we used the Variable Monthly Flow (VMF) method to calculate the transgression of freshwater planetary boundaries: (1) natural deficits in which flow does not meet EFRs due to climate variability, and (2) anthropogenic deficits caused by water abstractions. The novelty is that we calculated spatially and cumulative monthly water deficits by river types including the frequency, magnitude and causes of environmental flow (EF) deficits (climatic and/or anthropogenic). Water deficit was found to be a regional rather than a global concern (less than 5% of total discharge). The results show that, from 1960 to 2000, perennial rivers with low flow alteration, such as the Amazon, had an EF deficit of 2-12% of the total discharge, and that the climate deficit was responsible for up to 75% of the total deficit. In rivers with high seasonality and high water abstractions such as the Indus, the total deficit represents up to 130% of its total discharge, 85% of which is due to withdrawals. We highlight the need to allocate water to humans and ecosystems sustainably. This article is part of the Royal Society Science+ meeting issue 'Drought risk in the Anthropocene'.

Future flood and drought risks have been predicted to transition from moderate to high levels at global warmings of 1.5 °C and 2.0 °C above pre-industrial levels, respectively. However, these results were obtained by approximating the equilibrium climate using transient simulations with steadily warming. This approach was recently criticised due to the warmer global land temperature and higher mean precipitation intensities of the transient climate in comparison with the equilibrium climate. Therefore, it is unclear whether floods and droughts projected under a transient climate can be systematically substituted for those occurring in an equilibrated climate. Here, by employing a large ensemble of global hydrological models (HMs) forced by global climate models, we assess the validity of estimating flood and drought characteristics under equilibrium climates from transient simulations. Differences in flood characteristics under transient and equilibrium climates could be largely ascribed to natural variability, indicating that the floods derived from a transient climate reasonably approximate the floods expected in an equally warm, equilibrated climate. By contrast, significant differences in drought intensity between transient and equilibrium climates were detected over a larger global land area than expected from natural variability. Despite the large differences among HMs in representing the low streamflow regime, we found that the drought intensities occurring under a transient climate may not validly represent the intensities in an equally warm equilibrated climate for approximately 6.7% of the global land area.

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.

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 me

Bioenergy with carbon capture and storage (BECCS) is considered an important negative emissions (NEs) technology, but might involve substantial irrigation on biomass plantations. Potential water stress resulting from the additional withdrawals warrants evaluation against the avoided climate change impact. Here we quantitatively assess potential side effects of BECCS with respect to water stress by disentangling the associated drivers (irrigated biomass plantations, climate, land use patterns) using comprehensive global model simulations. By considering a widespread use of irrigated biomass plantations, global warming by the end of the 21st century could be limited to 1.5 °C compared to a climate change scenario with 3 °C. However, our results suggest that both the global area and population living under severe water stress in the BECCS scenario would double compared to today and even exceed the impact of climate change. Such side effects of achieving substantial NEs would come as an extra pressure in an already water-stressed world and could only be avoided if sustainable water management were implemented globally.

The extent and impact of climate‐related extreme events depend on the underlying meteorological, hydrological, or climatological drivers as well as on human factors such as land use or population density. Here we quantify the pure effect of historical and future climate change on the exposure of land and population to extreme climate impact events using an unprecedentedly large ensemble of harmonized climate impact simulations from the Inter‐Sectoral Impact Model Intercomparison Project phase 2b. Our results indicate that global warming has already more than doubled both the global land area and the global population annually exposed to all six categories of extreme events considered: river floods, tropical cyclones, crop failure, wildfires, droughts, and heatwaves. Global warming of 2°C relative to preindustrial conditions is projected to lead to a more than fivefold increase in cross‐category aggregate exposure globally. Changes in exposure are unevenly distributed, with tropical and subtropical regions facing larger increases than higher latitudes. The largest increases in overall exposure are projected for the population of South Asia.

The planetary boundaries framework defines the "safe operating space for humanity" represented by nine global processes that can destabilize the Earth System if perturbed. The water planetary boundary attempts to provide a global limit to anthropogenic water cycle modifications, but it has been challenging to translate and apply it to the regional and local scales at which water problems and management typically occur. We develop a cross-scale approach by which the water planetary boundary could guide sustainable water management and governance at subglobal contexts defined by physical features (e.g., watershed or aquifer), political borders (e.g., city, nation, or group of nations), or commercial entities (e.g., corporation, trade group, or financial institution). The application of the water planetary boundary at these subglobal contexts occurs via two approaches: (i) calculating fair shares, in which local water cycle modifications are compared to that context's allocation of the global safe operating space, taking into account biophysical, socioeconomic, and ethical considerations; and (ii) defining a local safe operating space, in which interactions between water stores and Earth System components are used to define local boundaries required for sustaining the local water system in stable conditions, which we demonstrate with a case study of the Cienaga Grande de Santa Marta wetlands in Colombia. By harmonizing these two approaches, the water planetary boundary can ensure that water cycle modifications remain within both local and global boundaries and complement existing water management and governance approaches.

To improve the understanding of trends in extreme flows related to flood events at the global scale, historical and future changes of annual maxima of 7 d streamflow are investigated, using a comprehensive streamflow archive and six global hydrological models. The models' capacity to characterise trends in annual maxima of 7 d streamflow at the continental and global scale is evaluated across 3666 river gauge locations over the period from 1971 to 2005, focusing on four aspects of trends: (i) mean, (ii) standard deviation, (iii) percentage of locations showing significant trends and (iv) spatial pattern. Compared to observed trends, simulated trends driven by observed climate forcing generally have a higher mean, lower spread and a similar percentage of locations showing significant trends. Models show a low to moderate capacity to simulate spatial patterns of historical trends, with approximately only from 12 % to 25 % of the spatial variance of observed trends across all gauge stations accounted for by the simulations. Interestingly, there are statistically significant differences between trends simulated by global hydrological models (GHMs) forced with observational climate and by those forced by bias-corrected climate model output during the historical period, suggesting the important role of the stochastic natural (decadal, inter-annual) climate variability. Significant differences were found in simulated flood trends when averaged only at gauged locations compared to those averaged across all simulated grid cells, highlighting the potential for bias toward well-observed regions in our understanding of changes in floods. Future climate projections (simulated under the RCP2.6 and RCP6.0 greenhouse gas concentration scenarios) suggest a potentially high level of change in individual regions, with up to 35 % of cells showing a statistically significant trend (increase or decrease; at 10 % significance level) and greater changes indicated for the higher concentrati

Importance of evaluation of global hydrological models (gHMs) before doing climate impact assessment was underlined in several studies. The main objective of this study is to evaluate the performance of six gHMs in simulating observed discharge for a set of 57 large catchments applying common metrics with thresholds for the monthly and seasonal dynamics and summarize them estimating an aggregated index of model performance for each model in each basin. One model showed a good performance, and other five showed a weak or poor performance in most of the basins. In 15 catchments, evaluation results of all models were poor. The model evaluation was supplemented by climate impact assessment for a subset of 12 representative catchments using (1) usual ensemble mean approach and (2) weighted mean approach based on model performance, and the outcomes were compared. The comparison of impacts in terms of mean monthly and mean annual discharges using two approaches has shown that in four basins, differences were negligible or small, and in eight catchments, differences in mean monthly, mean annual discharge or both were moderate to large. The spreads were notably decreased in most cases when the second method was applied. It can be concluded that for improving credibility of projections, the model evaluation and application of the weighted mean approach could be recommended, especially if the mean monthly (seasonal) impacts are of interest, whereas the ensemble mean approach could be applied for projecting the mean annual changes. The calibration of gHMs could improve their performance and, consequently, the credibility of projections.

Increasing population, change in consumption habits, and climate change will likely increase the competition for freshwater resources in the future. Exploring ways to improve water productivity especially in food and livestock systems is important for tackling the future water challenge. Here we combine detailed data on feed use and livestock production with Food and Agriculture Organization of the United Nations (FAO) statistics and process‐based crop‐water model simulations to comprehensively assess water use and water productivity in the global livestock sector. We estimate that, annually, 4,387 km3 of blue and green water is used for the production of livestock feed, equaling about 41% of total agricultural water use. Livestock water productivity (LWP; protein produced per m3 of water) differs by several orders of magnitude between livestock types, regions, and production systems, indicating a large potential for improvements. For pigs and broilers, we identify large opportunities to increase LWP by increasing both feed water productivity (FWP; feed produced per m3 of water) and feed use efficiency (FUE; protein produced per kg of feed) through better crop and livestock management. Even larger opportunities to increase FUE exist for ruminants, while the overall potential to increase their FWP is low. Substantial improvements of FUE can be achieved for ruminants by supplementation with feed crops, but the lower FWP of these feed crops compared to grazed biomass limits possible overall improvements of LWP. Therefore, LWP of ruminants, unlike for pigs and poultry, does not always benefit from a trend toward intensification, as this is often accompanied by increasing crop supplementation.

In environmental management and sustainability there is an increasing interest in measurement and accounting of beneficial impact—as an incentive to action, as a communication tool, and to move toward a positive, constructive approach focused on opportunities rather than problems. One approach uses the metaphor of a “handprint,” complementing the notion of environmental footprints, which have been widely adopted for impact measurement and accounting. We analyze this idea by establishing core principles of handprint thinking: Handprint encourages actions with positive impacts and connects to analyses of footprint reductions but adds value to them and addresses the issue of what action should be taken. We also identify five key questions that need to be addressed and decisions that need to be made in performing a (potentially quantitative) handprint assessment, related to scoping of the improvement to be made, how it is achieved, and how credit is assigned, taking into account constraints on action. A case study of the potential water footprint reduction of an average Finn demonstrates how handprint thinking can be a natural extension of footprint reduction analyses. We find that there is a diversity of possible handprint assessments that have the potential to encourage doing good. Their common foundation is “handprint thinking.”

The planetary boundaries framework proposes quantified guardrails to human modification of global environmental processes that regulate the stability of the planet and has been considered in sustainability science, governance, and corporate management. However, the planetary boundary for human freshwater use has been critiqued as a singular measure that does not reflect all types of human interference with the complex global water cycle and Earth System. We suggest that the water planetary boundary will be more scientifically robust and more useful in decision-making frameworks if it is redesigned to consider more specifically how climate and living ecosystems respond to changes in the different forms of water on Earth: atmospheric water, frozen water, groundwater, soil moisture, and surface water. This paper provides an ambitious scientific road map to define a new water planetary boundary consisting of sub-boundaries that account for a variety of changes to the water cycle.

This study presents a novel application of machine learning to deliver optimised, multi-model combinations (MMCs) of Global Hydrological Model (GHM) simulations. We exemplify the approach using runoff simulations from five GHMs across 40 large global catchments. The benchmarked, median performance gain of the MMC solutions is 45% compared to the best performing GHM and exceeds 100% when compared to the EM. The performance gain offered by MMC suggests that future multi-model applications consider reporting MMCs, alongside the EM and intermodal range, to provide end-users of GHM ensembles with a better contextualised estimate of runoff. Importantly, the study highlights the difficulty of interpreting complex, non-linear MMC solutions in physical terms. This indicates that a pragmatic approach to future MMC studies based on machine learning methods is required, in which the allowable solution complexity is carefully constrained.

Human activities have a profound influence on river discharge, hydrological extremes, and water-related hazards. In this study, we compare the results of five state-of-the-art global hydrological models (GHMs) with observations to examine the role of human impact parameterizations (HIP) in the simulation of the mean, high, and low flows. The analysis is performed for 471 gauging stations across the globe and for the period 1971-2010. We find that the inclusion of HIP improves the performance of GHMs, both in managed and near-natural catchments. For near-natural catchments, the improvement in performance results from improvements in incoming discharges from upstream managed catchments. This finding is robust across GHMs, although the level of improvement and reasons for improvement vary greatly by GHM. The inclusion of HIP leads to a significant decrease in the bias of long-term mean monthly discharge in 36-73% of the studied catchments, and an improvement in modelled hydrological variability in 31-74% of the studied catchments. Including HIP in the GHMs also leads to an improvement in the simulation of hydrological extremes, compared to when HIP is excluded. Whilst the inclusion of HIP leads to decreases in simulated high-flows, it can lead to either increases or decreases in low-flows. This is due to the relative importance of the timing of return flows and reservoir operations and their associated uncertainties. Even with the inclusion of HIP, we find that model performance still not optimal. This highlights the need for further research linking the human management and hydrological domains, especially in those areas with a dominant human impact. The large variation in performance between GHMs, regions, and performance indicators, calls for a careful selection of GHMs, model components, and evaluation metrics in future model applications.

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 scale, due to a lack of observations at local and seasonal time 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 degree) 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 global total water withdrawal has increased significantly during 1971–2010, mainly driven by the increase of 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 annual total 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 ann

Global-scale hydrological models are routinely used to assess water scarcity, flood hazards and droughts worldwide. Recent efforts to incorporate anthropogenic activities in these models have enabled more realistic comparisons with observations. Here we evaluate simulations from an ensemble of six models participating in the second phase of the Inter-Sectoral Impact Model Inter-comparison Project (ISIMIP2a). We simulate monthly runoff in 40 catchments, spatially distributed across eight global hydrobelts. The performance of each model and the ensemble mean is examined with respect to their ability to replicate observed mean and extreme runoff under human-influenced conditions. Application of a novel integrated evaluation metric to quantify the models' ability to simulate timeseries of monthly runoff suggests that the models generally perform better in the wetter equatorial and northern hydrobelts than in drier southern hydrobelts. When model outputs are temporally aggregated to assess mean annual and extreme runoff, the models perform better. Nevertheless, we find a general trend in the majority of models towards the overestimation of mean annual runoff and all indicators of upper and lower extreme runoff. The models struggle to capture the timing of the seasonal cycle, particularly in northern hydrobelts, while in southern hydrobelts the models struggle to reproduce the magnitude of the seasonal cycle. It is noteworthy that over all hydrological indicators, the ensemble mean fails to perform better than any individual model?a finding that challenges the commonly held perception that model ensemble estimates deliver superior performance over individual models. The study highlights the need for continued model development and improvement. It also suggests that caution should be taken when summarising the simulations from a model ensemble based upon its mean output.

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© 2017 by the author. The Planetary Boundaries (PB) framework represents a significant advance in specifying the ecological constraints on human development. However, to enable decision-makers in business and public policy to respect these constraints in strategic planning, the PB framework needs to be developed to generate practical tools. With this objective in mind, we analyse the recent literature and highlight three major scientific and technical challenges in operationalizing the PB approach in decision-making: first, identification of thresholds or boundaries with associated metrics for different geographical scales; second, the need to frame approaches to allocate fair shares in the 'safe operating space' bounded by the PBs across the value chain and; third, the need for international bodies to co-ordinate the implementation of the measures needed to respect the Planetary Boundaries. For the first two of these challenges, we consider how they might be addressed for four PBs: climate change, freshwater use, biosphere integrity and chemical pollution and other novel entities. Four key opportunities are identified: (1) development of a common system of metrics that can be applied consistently at and across different scales; (2) setting 'distance from boundary' measures that can be applied at different scales; (3) development of global, preferably open-source, databases and models; and (4) advancing understanding of the interactions between the different PBs. Addressing the scientific and technical challenges in operationalizing the planetary boundaries needs be complemented with progress in addressing the equity and ethical issues in allocating the safe operating space between companies and sectors.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.This article is part of a Special Issue on “Hydrological Model Intercomparison for Climate Impact Assessment” edited by Valentina Krysanova and Fred Hattermann.

Safeguarding river ecosystems is a precondition for attaining the UN Sustainable Development Goals (SDGs) related to water and the environment, while rigid implementation of such policies may hamper achievement of food security. River ecosystems provide life-supporting functions that depend on maintaining environmental flow requirements (EFRs). Here we establish gridded process-based estimates of EFRs and their violation through human water withdrawals. Results indicate that 41% of current global irrigation water use (997 km3 per year) occurs at the expense of EFRs. If these volumes were to be reallocated to the ecosystems, half of globally irrigated cropland would face production losses of ≥10%, with losses of ∼20–30% of total country production especially in Central and South Asia. However, we explicitly show that improvement of irrigation practices can widely compensate for such losses on a sustainable basis. Integration with rainwater management can even achieve a 10% global net gain. Such management interventions are highlighted to act as a pivotal target in supporting the implementation of the ambitious and seemingly conflicting SDG agenda.

Global hydrological models (GHMs) have been applied to assess global flood hazards, but their capacity to capture the timing and amplitude of peak river discharge—which is crucial in flood simulations—has traditionally not been the focus of examination. Here we evaluate to what degree the choice of river routing scheme affects simulations of peak discharge and may help to provide better agreement with observations. To this end we use runoff and discharge simulations of nine GHMs forced by observational climate data (1971–2010) within the ISIMIP2a project. The runoff simulations were used as input for the global river routing model CaMa-Flood. The simulated daily discharge was compared to the discharge generated by each GHM using its native river routing scheme. For each GHM both versions of simulated discharge were compared to monthly and daily discharge observations from 1701 GRDC stations as a benchmark. CaMa-Flood routing shows a general reduction of peak river discharge and a delay of about two to three weeks in its occurrence, likely induced by the buffering capacity of floodplain reservoirs. For a majority of river basins, discharge produced by CaMa-Flood resulted in a better agreement with observations. In particular, maximum daily discharge was adjusted, with a multi-model averaged reduction in bias over about 2/3 of the analysed basin area. The increase in agreement was obtained in both managed and near-natural basins. Overall, this study demonstrates the importance of routing scheme choice in peak discharge simulation, where CaMa-Flood routing accounts for floodplain storage and backwater effects that are not represented in most GHMs. Our study provides important hints that an explicit parameterisation of these processes may be essential in future impact studies.

Human impacts increasingly affect the global hydrological cycle and indeed dominate hydrological changes in some regions. Hydrologists have sought to identify the human-impact-induced hydrological variations via parameterizing anthropogenic water uses in global hydrological models (GHMs). The consequently increased model complexity is likely to introduce additional uncertainty among GHMs. Here, using four GHMs, between-model uncertainties are quantified in terms of the ratio of signal to noise (SNR) for average river flow during 1971–2000 simulated in two experiments, with representation of human impacts (VARSOC) and without (NOSOC). It is the first quantitative investigation of between-model uncertainty resulted from the inclusion of human impact parameterizations. Results show that the between-model uncertainties in terms of SNRs in the VARSOC annual flow are larger (about 2% for global and varied magnitude for different basins) than those in the NOSOC, which are particularly significant in most areas of Asia and northern areas to the Mediterranean Sea. The SNR differences are mostly negative (−20% to 5%, indicating higher uncertainty) for basin-averaged annual flow. The VARSOC high flow shows slightly lower uncertainties than NOSOC simulations, with SNR differences mostly ranging from −20% to 20%. The uncertainty differences between the two experiments are significantly related to the fraction of irrigation areas of basins. The large additional uncertainties in VARSOC simulations introduced by the inclusion of parameterizations of human impacts raise the urgent need of GHMs development regarding a better understanding of human impacts. Differences in the parameterizations of irrigation, reservoir regulation and water withdrawals are discussed towards potential directions of improvements for future GHM development. We also discuss the advantages of statistical approaches to reduce the between-model uncertainties, and the importance of calibration of GHMs for not o

Rising atmospheric CO2 concentrations ([CO2]) are expected to enhance photosynthesis and reduce crop water use1. However, there is high uncertainty about the global implications of these effects for future crop production and agricultural water requirements under climate change. Here we combine results from networks of field experiments1, 2 and global crop models3 to present a spatially explicit global perspective on crop water productivity (CWP, the ratio of crop yield to evapotranspiration) for wheat, maize, rice and soybean under elevated [CO2] and associated climate change projected for a high-end greenhouse gas emissions scenario. We find CO2 effects increase global CWP by 10[0;47]%–27[7;37]% (median[interquartile range] across the model ensemble) by the 2080s depending on crop types, with particularly large increases in arid regions (by up to 48[25;56]% for rainfed wheat). If realized in the fields, the effects of elevated [CO2] could considerably mitigate global yield losses whilst reducing agricultural consumptive water use (4–17%). We identify regional disparities driven by differences in growing conditions across agro-ecosystems that could have implications for increasing food production without compromising water security. Finally, our results demonstrate the need to expand field experiments and encourage greater consistency in modelling the effects of rising [CO2] across crop and hydrological modelling communities.

Russia's boreal forests provide numerous important ecosystem functions and services, but they are being increasingly affected by climate change. This review presents an overview of observed and potential future climate change impacts on those forests with an emphasis on their aggregate carbon balance and processes driving changes therein. We summarize recent findings highlighting that radiation increases, temperature-driven longer growing seasons and increasing atmospheric CO2 concentrations generally enhance vegetation productivity, while heat waves and droughts tend to decrease it. Estimates of major carbon fluxes such as net biome production agree that the Russian forests as a whole currently act as a carbon sink, but these estimates differ in terms of the magnitude of the sink due to different methods and time periods used. Moreover, models project substantial distributional shifts of forest biomes, but they may overestimate the extent to which the boreal forest will shift poleward as past migration rates have been slow. While other impacts of current climate change are already substantial, and projected impacts could be both large-scale and disastrous, the likelihood for (climate-driven) disturbances such as fires and insect outbreaks, which are expected to increase in the future. We conclude that the mpacts of climate change on Russia's boreal forest are often superimposed by other environmental and societal changes in a complex way, and the interaction of these developments could exacerbate both existing and projected future challenges. Hence, development of adaptation and mitigation strategies for Russia's forests is strongly advised.