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

In many temperate regions globally, sufficient precipitation and moderate temperatures have meant that green water has sufficed for agriculture. However, the effects of climate change demonstrate that additional crop water is now more frequently required in many of these areas, particularly for dry summer years, with irrigation demands expected to continue increasing. In Germany, this effect has become noticeable over previous years, exemplified by the reduced crop yields in the recent summer droughts of 2018 and 2020.Our study, performed within the scope of the WADKlim project, identifies critical hotspots for water stress through high-resolution hydrological modelling and statistical analyses to determine groundwater recharge and theoretical irrigation requirements from now until 2100. We set up and calibrated the mGROWA hydrological model over a historical period (1961-2020) at a high spatial (100 m) and temporal (daily) resolution. The calibrated model was then run until 2100 for three climate scenarios (1 x RCP2.6; 2 x RCP8.5), which were selected as a stress test for the system. As model outputs, we derived the spatio-temporal patterns of groundwater recharge as well as crop water requirements, through the application of irrigation rules typical for Germany and accounting for the spatial distribution of different crop types. We converted the theoretical crop water requirements into requirements only for areas that are equipped for irrigation, incorporating multiple scenarios for the rate at which irrigation infrastructure could expand in Germany.Our results demonstrate the large spatial and interannual variations in irrigation demands throughout Germany. We quantify how the multiplicative effect of warmer and drier summers in combination with increased areas equipped for irrigation is expected to strain water resources in the future. For example, we estimate that mean annual irrigation demands in Germany could increase by as much as 700% by 2075-2100, considering the “worst-case” scenario of climate projection and increase in irrigated areas. Regarding groundwater availability, owing to the expected increase in winter precipitation in Germany, our modelling results show pronounced regional variations in whether or not annual groundwater recharge is expected to increase in the future. Finally, we included estimates of other water requirements and aggregated the results to determine overall water demands at the district level and calculate ratios of water use to groundwater recharge per district. Our results highlight the hotspots in Germany where water stress is expected to increase the most throughout the 21st century, which could likely lead to conflict between different water users (agricultural, industry, public supply).Determining the spatio-temporal characteristics of how water stress will change requires comprehensive assessments of water availability, crop water requirements, areas equipped for irrigation infrastructure, and other water uses. In addition, the large variability in climate projections means that results from such assessments provide large ranges of expected water stress conditions. We have developed and tested a comprehensive methodology for identifying and mapping water hotspots, which we implemented for Germany using three climate projections. Our methodology is transferable to similar (data-rich) regions, and can also be applied for a complete ensemble of climate projections.

Renewable energy generation has great potential to reduce greenhouse gas emissions, however, it may exacerbate other environmental impacts, such as water scarcity, elsewhere in the supply chain. Here, we reveal a wide range of global environmental impacts of concentrated solar power, run-of-river hydropower, and biomass burning compared to classical coal-fired power: Spatially explicit life cycle impact assessment is used to evaluate their supply chains with respect to demand for energy, land, material, and water, greenhouse gas emissions, and impacts on human health and ecosystem quality with a focus on mining. Hotspot analyses in terms of location and type of impact show that there is no clear preference for any of the technologies, mainly because water consumption is often critical on-site. The examined concentrated solar power plant is the least suitable for a sustainable energy transition: Its spatial hotspots are spreading the furthest globally and may exceed those of coal combustion in number and severity. The presented methodology is the basis to mitigate such environmental hotspots.

Summary Background Increasing human demand for water and changes in water availability due to climate change threatens water security worldwide. Additionally, exploitation of water resources induces stress on freshwater environments, leading to biodiversity loss and reduced ecosystem services. We aimed to conduct a spatially detailed assessment of global human water stress for low to high environmental flow (EF) protection. Methods In this modelling study, we used the LISFLOOD model to generate daily natural flows without anthropogenic water use for 1980–2018. On the basis of these flows, we selected three EF methods (EF with high ecological protection [EFPROT], EF with minimum flow requirements [EFMIN], and variable monthly flow [EFVMF]) to calculate monthly EFs. We assessed monthly consumptive water use for industry, agricultural crops, livestock, municipalities, and energy production for 2010. We then estimated the corresponding number of people under water stress per month on a global and national level using a spatially detailed population database for 2010. Findings We estimate that 3·2 billion (EFPROT), 2·4 billion (EFVMF), and 2·2 billion (EFMIN) people lived under water stress for at least 1 month per year, corresponding to 46%, 35%, and 32% of the world's population in 2010, respectively. Around 80% of people living under water stress lived in Asia; in particular, India, Pakistan, and northeast China. Compared with EFMIN, imposing EFPROT globally would have put between 710 million (March) to 1 billion (June) additional people under water stress on a monthly basis, whereas this would have been 72 million (August) to 218 million (April) additional people if EFVMF were imposed. Interpretation Ensuring high ecological protection would put nearly half of the world's population (3·2 billion people) under water stress for at least 1 month per year. Policy makers and water managers have to make an important trade-off when allocating limited water resources between direct human needs and the environment. A better understanding of local ecosystem needs is crucial to alleviating current and future human water stress, while sustaining healthy ecosystems. Funding None.

Intensive groundwater abstraction has augmented socio-economic development worldwide but threatens the sustainability of groundwater resources. Spatiotemporal analysis of groundwater storage changes is a prerequisite to sustainable water resource management over river basins. To estimate the groundwater storage changes/anomalies (GWCs) in the Indus River Basin (IRB), where observation wells are sparse, Gravity Recovery and Climate Experiment, the Global Land Data Assimilation System, and the WaterGAP Hydrological Model data were employed. The groundwater storage changes and controlling factors were investigated at three tier levels (TTLs), i.e., the basin, river reach, and region, to explore their implications on regional water resource management and provide management options at each level. Overall, the IRB groundwater declined from January 2003 to December 2016, with a relatively higher rate during 2003–2009 than during 2010–2016. Spatially, according to a reach-specific analysis, 24%, 14%, and 2% of the upper, middle, and lower reaches of the IRB, respectively, were indicated by a ‘severe groundwater decline’ over the entire period (i.e., 2003–2016). The GRACE-based GWCs were validated with in situ data of two heterogeneous regions, i.e., Kabul River Basin (KRB) and Lower Bari Doab Canal (LBDC). The analysis showed a correlation (R2) of 0.77 for LBDC and 0.29 for KRB. This study’s results reveal that climatic variations (increase in evapotranspiration); anthropogenic activities, i.e., pumping for irrigation; and water allocations in these regions mainly drive the groundwater storage changes across the Indus Basin.

Extending assessments of climate change‐induced range shifts via correlative species distribution models by including species traits is crucial for conservation planning. However, comprehensive assessments of future distribution scenarios incorporating responses of biotic factors are poorly investigated. Therefore, the aim of our study was to extend the understanding about the combined usage of species traits data and species distribution models for different life stages and distribution scenarios. We combine global model predictions for the 2050s and thermal performances of Salmo trutta and Salmo salar under consideration of different life stages (adults, juveniles, eggs), timeframes (monthly, seasonally, yearly), and dispersal scenarios (no dispersal, free dispersal, restricted dispersal). We demonstrate that thermal performances of different life stages will either increase or decrease for certain time periods. Model predictions and thermal performances imply range declines and poleward shifts. Dispersal to suitable habitats will be an important factor mitigating warming effects; however, dams may block paths to areas linked to high performances. Our results emphasize enhanced inclusion of critical periods for species and proper dispersal solutions in conservation planning., For Salmo trutta and Salmo salar, we combine species distribution models with thermal performance curves for different life stages, time frames, and dispersal scenarios to assess future impacts of climate change. We show varying thermal performances for different life stages and time periods, range declines, and adverse impacts of dispersal barriers. Our results emphasize enhanced inclusion of critical time periods and consideration of dispersal possibilities. ​

SummaryClimate change presents a particularly complex challenge in the context of flyway scale conservation of migratory bird species as it requires coordinated action by multiple countries along these species’ migratory routes. Coordinating conservation responses requires understanding the vulnerability of species and their habitats to climate change at the flyway scale throughout each species’ annual cycle. To contribute to such understanding, we used species distribution models to assess the exposure to climate change of waterbird species that are the focus of the Agreement on the Conservation of African-Eurasian Migratory Waterbirds (AEWA). We found that the species with the smallest proportion of their current range projected to be climatically suitable by 2050 (those whose distributions respond to changes in water availability but that do not perform synchronised migration) are dispersive species in the Afrotropical biogeographic realm, and migratory species in their breeding season, particularly Arctic breeding waders. These species also have the most limited availability of newly suitable areas. Projections for most other Palearctic migratory waterbird species suggest that losses of suitable areas in their current passage and wintering ranges may be largely offset by new areas becoming climatically suitable. The majority of migratory Palearctic waterbirds in the breeding season and Afrotropical waterbirds are widely dispersed with only a small proportion of their populations currently supported by ‘Critical Sites’ (i.e. sites that are either important for Globally Threatened Species or support 1% of the bioregional population of any waterbird species). This makes it unlikely that climate change adaptation measures focusing only on key sites will be sufficient to counter the predicted range losses. Therefore, climate change adaptation responses should also be implemented at the landscape scale for Afrotropical waterbirds and for breeding populations of Palearctic migrant waterbirds.

The supply of surface water by century-old infrastructure causes substantial water loss and triggers huge abstractions of groundwater, resulting in low irrigation efficiency. We evaluated the irrigation performance (application and conveyance efficiencies) and water availability (supply-demand) from the field to the Mungi Distributary canal level in Punjab, Pakistan. Between April–September 2019 and 2020, we monitored water delivery in the canal network, soil moisture content in cotton fields, and the canal and groundwater quality. The crops’ actual evapotranspiration was estimated using the AquaCrop model. We found conveyance efficiencies >90% for minor distributaries, 70–89% for watercourses, and ~75% for field ditches per kilometer. Field application efficiency was >90% for drip and ~35% for flood basin, whereas for raised-bed furrow, conventional furrow, and ridge-furrow irrigation methods, it varied between 44% and 83%. The deficits of canal water supply versus demand for cotton fields ranged from 45% to 73%, whereas the Mungi Distributary canal water showed a 68.6% and 19.8% shortfall in the April–September and October–March seasons of 2018/2019, respectively. The study suggests prioritizing improvements to field water application rather than canals with better water quality; additionally, surplus water from the Mungi canal in November and December could be stored for later use.

Despite their importance for biodiversity and ecosystem services, wetlands are among the most threatened ecosystems globally. The conservation of many migratory waterbirds depends on the conservation of a network of key sites along their flyways. However, the suitability of these sites is changing under climate change, and it is important that management of individual sites in the network adapts to these changes. Using bioclimatic models that also account for changes in inundation, we found that projected climate change will reduce habitat suitability for waterbirds at 57.5% of existing Critical Sites within Africa-Eurasia, varying from 20.1% in Eastern Europe to 87.0% in Africa. African and Middle East sites are particularly threatened, comprising 71 of the 100 most vulnerable sites. By highlighting priority sites for conservation and classifying Critical Sites into Climate Change Adaptation Strategy (CCAS) classes, our results can be used to support the climate change adaptation of both individual sites and the entire site network.

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

Renewable energies play a key role in avoiding carbon dioxide emissions from fossil electricity generation. However, support for certain renewable energy technologies focused only on greenhouse gas reduction can reinforce other environmental impacts and thus shift the problems. The authors therefore compare three forms of renewable electricity generation, namely concentrated solar power, run-of-river hydropower and sugarcane bagasse burning, to classical electricity generation from hard coal combustion with respect to their contribution to regional water scarcity. In a comparative life cycle impact assessment the quantitative and qualitative demand for water is assessed in a comprehensive conceptual framework against the background of regional water availability. A spatially explicit analysis reveals hotspots of water use along the case studies’ supply chains with a strong focus on mining activities. For this purpose, the global supply chains of nine mineral resources (aluminium, clay, coal, copper, gypsum, iron, lime, lithium and phosphate) were regionalised at mine site level in advance, so that contributions to environmental impacts can be assigned to single mine clusters. Next to the locations of the case studies itself, about 40 % of all contributions are associated with mining activities. Hard coal mining in Russian and Chinese mines as well as in South Africa as part of the supply chains of all case studies makes up the largest share of this. Further contributions are from mining of iron ore in Australian mines and copper extraction in Chinese, North American and Peruvian mines. However, up to 65 % of the life cycle impacts cannot be spatially analysed due to limited data availability. These findings indicate that a detailed investigation of mining supply chains is necessary to compare power generation technologies in a meaningful way. Results also show that sugarcane bagasse burning, if used as by-product and not as waste, is responsible for the largest contributions to all indicators, suggesting that targeted use of biomass for electricity generation is not is not very effective in reducing global environmental impacts, such as contribution to water scarcity.

WaterGAP is a global hydrological model that quantifies human use of groundwater and surface water as well as water flows and water storage and thus water resources on all land areas of the Earth. Since 1996, it has served to assess water resources and water stress both historically and in the future, in particular under climate change. It has improved our understanding of continental water storage variations, with a focus on overexploitation and depletion of water resources. In this paper, we describe the most recent model version WaterGAP 2.2d, including the water use models, the linking model that computes net abstractions from groundwater and surface water and the WaterGAP Global Hydrology Model WGHM. Standard model output variables that are freely available at a data repository are explained. In addition, the most requested model outputs, total water storage anomalies, streamflow and water use, are evaluated against observation data. Finally, we show examples of assessments of the global freshwater system that can be done with WaterGAP2.2d model output.

Water scarcity threatens people in various regions, and has predominantly been studied from a water quantity perspective only. Here we show that global water scarcity is driven by both water quantity and water quality issues, and quantify expansions in clean water technologies (i.e. desalination and treated wastewater reuse) to ‘reduce the number of people suffering from water scarcity’ as urgently required by UN’s Sustainable Development Goal 6. Including water quality (i.e. water temperature, salinity, organic pollution and nutrients) contributes to an increase in percentage of world’s population currently suffering from severe water scarcity from an annual average of 30% (22%–35% monthly range; water quantity only) to 40% (31%–46%; both water quantity and quality). Water quality impacts are in particular high in severe water scarcity regions, such as in eastern China and India. In these regions, excessive sectoral water withdrawals do not only contribute to water scarcity from a water quantity perspective, but polluted return flows degrade water quality, exacerbating water scarcity. We show that expanding desalination (from 2.9 to 13.6 billion m3 month−1) and treated wastewater uses (from 1.6 to 4.0 billion m3 month−1) can strongly reduce water scarcity levels and the number of people affected, especially in Asia, although the side effects (e.g. brine, energy demand, economic costs) must be considered. The presented results have potential for follow-up integrated analyses accounting for technical and economic constraints of expanding desalination and treated wastewater reuse across the world.

Ensuring adequate freshwater quality is an important aspect of integrated environmental management and sustainable development. One contribution towards this end is to monitor the water quality of river basins. An important issue in constructing a water quality monitoring network is how to allocate the stations. This is usually done by using in situ measurements of pollutants together with other information. A stage-based optimization approach has been developed to find the optimal sites to allocate the monitoring stations. The proposed approach constructs a network in a sequence of stages without the need for in situ pollution measurements. Instead, it uses pollutant estimates from the WorldQual model together with other social and hydrological criteria. The approach is computationally efficient and provides an ordered list of stations that can be used to initialize or augment a water quality network. This is especially relevant for consideration by developing countries since, with this approach, they can get an overview of their river basins, and then prioritize the initial distributions of the networks. The approach was applied successfully to the 741,751 km2 of the Jubba River basin, but it is applicable to river basins of any size.

Several model inter-comparison projects (MIPs) have been carried out recently by the climate, hydrological, agricultural and other modelling communities to quantify modelling uncertainties and improve modelling systems. Here we focus on MIP design for large-scale water quality models. Water quality MIPs can be useful to improve our understanding of pollution problems and facilitate the development of harmonized estimates of current and future water quality. This can provide new opportunities for assessing robustness in estimates of water quality hotspots and trends, improve understanding of processes, pollution sources, water quality model uncertainties, and to identify priorities for water quality data collection and monitoring. Water quality MIP design should harmonize relevant model input datasets, use consistent spatial/temporal domains and resolutions, and similar output variables to improve understanding of water quality modelling uncertainties and provide harmonized water quality data that suit the needs of decision makers and other users.

Freshwater availability is of vital importance for humans, freshwater biota and ecosystem functions. In the past decades, global hydrological models (GHMs) were developed to improve understanding of the global freshwater situation in a globalized word, by filling gaps in observational coverage and assessing scenarios of the future under consideration of different socioeconomic developments and climate change. The Water Global Assessment and Prognosis (WaterGAP) model was one of the first GHMs developed to evaluate freshwater resources and their use for both historical and future conditions. It consists of five water use models (for irrigation, domestic, cooling of thermal power plants, manufacturing, and livestock sectors) and the WaterGAP Global Hydrology Model (WGHM). Recently, the latest model version, WaterGAP 2.2d, was finalized, containing a number of enhancements and revisions such as a river storage-based flow velocity approach, improvements in modelling groundwater recharge in dry environments and integration of historical development of irrigated areas.This presentation provides an overview about the WaterGAP 2.2d scheme and features, assesses global freshwater resources (runoff and streamflow) and water balance components, and provides insights to evaluation results against observed streamflow, GRACE total water storage and the AQUASTAT database.

Water scarcity threatens people in various regions, and has predominantly been studied from a water quantity perspective. However, the provision of water for human uses and environmental health is dependent on both sufficient water availability but also appropriate water quality for the intended use.Our study presents the first estimates of global water scarcity driven by both water quantity and water quality issues and including impacts of desalination and treated waste-water reuse. We have developed a new water scarcity framework combining model simulations of multiple global hydrological models and global surface water quality models (water temperature, salinity, organic pollution, nutrients) and spatially-explicit datasets of desalination and treated wastewater reuse capacities globally.Our results show that 40% of the world’s population currently lives in regions with severe water scarcity, which is driven by a combination of water quantity and quality issues. Impacts of water quality are in particular high in river basins in eastern China. Here, excessive water withdrawals and polluted return flows degrade water quality, exacerbating water scarcity. Our results show that expanding desalination and treated wastewater reuse capacities can strongly reduce water scarcity in most river basins, although the side-effects (e.g. brine production, high energy demands and costs) must be considered. We conclude that effective water scarcity reduction requires that we expand our focus from conventional measures, which mainly focus on improving water supply for sectoral uses, to solutions that also promote water quality improvements.

The planetary boundaries framework has proven useful for many global sustainability contexts, but is challenging to apply to freshwater, which is spatially heterogeneous, part of complex socio-ecological systems and often dominated by local dynamics. To date, the planetary boundary for water has been simplistically defined by as the global rate of blue water consumption, functioning as a proxy for water partitioning in the global hydrological cycle, and considering impacts on rivers’ environmental flow requirements. We suggest the current planetary boundary should be replaced since it does not adequately represent the influence of water in critical Earth System functions such as regional climate and biodiversity. We review the core functions of water in the Earth System and set out a roadmap towards a more robust, holistic, and locally applicable water planetary boundary. We propose defining the boundary using four core functions of water (hydroclimatic regulation, hydroecological regulation, storage, and transport) in conjunction with five water stores (surface water, atmospheric water, soil moisture, groundwater and frozen water). Through the functions, the stores are inextricably interconnected with the atmosphere, land, ocean and biosphere. The roadmap outlined here suggests how to move towards setting six new water planetary sub-boundaries. This ambitious scientific and policy Grand Challenge that could substantially improve our understanding and management of water cycle modifications in the Earth System and provide a complementary approach to existing water management tools.

Eutrophication is a major water quality issue in lakes worldwide and is principally caused by the loadings of phosphorus from catchment areas. It follows that to develop strategies to mitigate eutrophication, we must have a good understanding of the amount, sources, and trends of phosphorus pollution. This paper provides the first consistent and harmonious estimates of current phosphorus loadings to the world's largest 100 lakes, along with the sources of these loadings and their trends. These estimates provide a perspective on the extent of lake eutrophication worldwide, as well as potential input to the evaluation and management of eutrophication in these lakes. We take a modeling approach and apply the WorldQual model for these estimates. The advantage of this approach is that it allows us to fill in large gaps in observational data. From the analysis, we find that about 66 of the 100 lakes are located in developing countries and their catchments have a much larger average phosphorus yield than the lake catchments in developed countries (11.1 versus 0.7 kg TP km−2 year−1). Second, the main source of phosphorus to the examined lakes is inorganic fertilizer (47% of total). Third, between 2005–2010 and 1990–1994, phosphorus pollution increased at 50 out of 100 lakes. Sixty percent of lakes with increasing pollution are in developing countries. P pollution changed primarily due to changing P fertilizer use. In conclusion, we show that the risk of P‐stimulated eutrophication is higher in developing countries.

Urban water demand will increase by 80% by 2050, while climate change will alter the timing and distribution of water. Here we quantify the magnitude of these twin challenges to urban water security, combining a dataset of urban water sources of 482 of the world’s largest cities with estimates of future water demand, based on the Intergovernmental Panel on Climate Change (IPCC)’s Fifth Assessment scenarios, and predictions of future water availability, using the WaterGAP3 modelling framework. We project an urban surface-water deficit of 1,386–6,764 million m³. More than 27% of cities studied, containing 233 million people, will have water demands that exceed surface-water availability. An additional 19% of cities, which are dependent on surface-water transfers, have a high potential for conflict between the urban and agricultural sectors, since both sectors cannot obtain their estimated future water demands. In 80% of these high-conflict watersheds, improvements in agricultural water-use efficiency could free up enough water for urban use. Investments in improving agricultural water use could thus serve as an important global change adaptation strategy. Rising population and changes in water supply under climate change affect cities globally. This study finds that in 27% of cities studied, water demand is likely to exceed availability by 2050, with many other cities competing with agriculture on water needs.

Water quality monitoring is important for the management of freshwater resources in river basins. Allocation of monitoring stations is the first step in the design of a water quality network. For this task, planning objectives are identified and a Multi-Objective Artificial Bee Colony-based optimization algorithm is designed and implemented in a Geographic Information System framework. Specifically, the number of stations is minimized in a range of values at the same time that the detection of lower compliance areas, the affected population and the relative importance of the river stretches are maximized. The estimation of pollutant parameters such as Biochemical Oxygen Demand, Faecal Coliform Bacteria or Total Dissolved Solids is performed by using the WorldQual model. This allows to objectively allocate monitoring stations to rivers where no real measurements are available, and thus it is especially relevant to allocate water quality stations for the first time. This approach has been tested on the Great Fish River basin (South Africa), finding networks improving the values of the objective functions between 22.22% and 47.83% with respect to the ones of the current network. Moreover, the solution analysis provides insightful and valuable information to the decision maker.

This paper presents one of the first quantitative scenario assessments for future water supply and demand in Asia to 2050. The assessment, developed by the Water Futures and Solutions (WFaS) initiative, uses the latest set of global climate change and socioeconomic scenarios and state-of-the-art global hydrological models. In Asia, water demand for irrigation, industry and households is projected to increase substantially in the coming decades (30-40% by 2050 compared to 2010). These changes are expected to exacerbate water stress, especially in the current hotspots such as north India and Pakistan, and north China. By 2050, 20% of the land area in the Asia-Pacific region, with a population of 1.6-2 billion, is projected to experience severe water stress. We find that socioeconomic changes are the main drivers of worsening water scarcity in Asia, with climate change impacts further increasing the challenge into the 21st century. Moreover, a detailed basin-level analysis of the hydro-economic conditions of 40 Asian basins shows that although the coping capacity of all basins is expected to improve due to GDP growth, some basins continuously face severe water challenges. These basins will potentially be home to up to 1.6 billion people by mid-21st century.

Riparian wetlands have been disappearing at an accelerating rate. Their ecological integrity as well as their vital ecosystem services for humankind depend on regular patterns of inundation and drying provided by natural flow regimes. However, river hydrology has been altered worldwide. Dams cause less variable flow regimes and water abstractions decrease the amount of flow so that ecologically important flood pulses are often reduced. Given growing population pressure and projected climate change, immediate action is required. However, the implementation of counteractive measures is often a complex task. This study develops a screening tool for assessing hydrological threats to riparian wetlands on global scales. The approach is exemplified on 93 Ramsar sites, many of which are located in transboundary basins. First, the WaterGAP3 hydrological modeling framework is used to quantitatively compare current and future modified flow regimes to reference flow conditions. In our simulations current water resource management seriously impairs riparian wetland inundation at 29 % of the analyzed sites. A further 8 % experience significantly reduced flood pulses. In the future, eastern Europe, western Asia, as well as central South America could be hotspots of further flow modifications due to climate change. Second, a qualitative analysis of the 93 sites determined potential impact on overbank flows resulting from planned or proposed dam construction projects. They take place in one-third of the upstream areas and are likely to impair especially wetlands located in South America, Asia, and the Balkan Peninsula. Third, based on the existing legal/institutional framework and water resource availability upstream, further qualitative analysis evaluated the capacity to preserve overbank flows given future streamflow changes due to dam construction and climate change. Results indicate hotspots of vulnerability exist, especially in northern Africa and the Persian Gulf.

Water scarcity has become a major constraint to socio-economic development and a threat to livelihood in increasing parts of the world. Since the late 1980s, water scarcity research has attracted much political and public attention. We here review a variety of indicators that have been developed to capture different characteristics of water scarcity. Population, water availability and water use are the key elements of these indicators. Most of the progress made in the last few decades has been on the quantification of water availability and use by applying spatially explicit models. However, challenges remain on appropriate incorporation of green water (soil moisture), water quality, environmental flow requirements, globalization and virtual water trade in water scarcity assessment. Meanwhile, inter- and intra- annual variability of water availability and use also calls for assessing the temporal dimension of water scarcity. It requires concerted efforts of hydrologists, economists, social scientists, and environmental scientists to develop integrated approaches to capture the multi-faceted nature of water scarcity.

The Selenga River is the main artery feeding Lake Baikal. It has a catchment of ~450000 km² in the boundary region between Northern Mongolia and Southern Siberia. Climate, land use and dynamic socioeconomic changes go along with rising water abstractions and contaminant loads originating from mining sites and urban wastewater. In the future, these pressures might have negative impacts on the ecosystems of Lake Baikal and the Selenga River Delta, which is an important wetland region in itself and forms the last geobiochemical barrier before the Selenga drains into Lake Baikal. The following study aims to assess current trends in hydrology and water quality in the Selenga-Baikal basin, identify their drivers and to set up models (WaterGAP3 framework and ECOMAG) for the prediction of future changes. Of particular relevance for hydrological and water quality changes in the recent past were climate and land use trends as well as contaminant influx from mining areas and urban settlements. In the near future, additional hydrological modifications due to the construction of dams and abstractions/water diversions from the Selenga’s Mongolian tributaries could lead to additional alterations.

Continental-scale water quality modeling is a new scientific approach concerned with computing the level of water pollution for several river basins at once. Uncertainties in these models, and in models of smaller scale, arise especially from the specification of model parameters. To identify and analyze these uncertainties we perform a global sensitivity and uncertainty analysis using Latin Hypercube Sampling on the WorldQual water quality model. The focus of the analysis is the river pathogen model of WorldQual as applied to rivers in Africa. This is the first uncertainty and sensitivity analysis performed on a continental-scale pathogen river pollution model. The median output uncertainty of the model (coefficient of variation, based on log-transformed data), assuming plausible estimates of 42 parameter uncertainties, was 10.7%; 90% of grid cells had output uncertainties below 23%. The parameters making the largest contribution to this uncertainty (in order of importance) are the pathogen waste loading per capita, the in-stream settling velocity of pathogens, the percentage of population in a river basin connected to a sewer system, and the raw effluent concentration from the manufacturing sector. Over the continental study area, model output uncertainty and the most sensitive parameters were found to have a highly irregular spatial pattern. This finding suggests that model performance is a strong function of local and regional conditions and that reducing the uncertainty of a single parameter may not lead to large improvements in model performance over the entire continent. A more efficient approach would be to improve model performance region-by-region and improve the estimation of specific parameters known to have a large influence on model uncertainty in those regions. The analysis showed that only four parameters dominate output uncertainty over 93% of the study area, implying that model performance can be substantially improved by reducing the uncertainty of a small number of parameters.

The paper investigates climate change impacts on streamflow seasonality for a set of eleven representative large river basins covering all continents and a wide range of climatic and physiographic settings. Based on an ensemble of nine regional hydrological models driven by climate projections derived from five global circulation models under four representative concentration pathways, we analyzed the median and range of projected changes in seasonal streamflow by the end of the twenty-first century and examined the uncertainty arising from the different members of the modelling chain. Climate change impacts on the timing of seasonal streamflow were found to be small except for two basins. In many basins, we found an acceleration of the existing seasonality pattern, i.e. high-flows are projected to increase and/or low-flows are projected to decrease. In some basins the hydrologic projections indicate opposite directions of change which cancel out in the ensemble median, i.e., no robust conclusions could be drawn. In the majority of the basins, differences in projected streamflow seasonality between the low emission pathway and the high emission pathway are small with the exception of four basins. For these basins our results allow conclusions on the potential benefits (or adverse effects) of avoided GHG emissions for the seasonal streamflow regime.