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As climate change brings about hotter and often drier summers, an improved understanding of how irrigation requirements vary according to climatic conditions is of increasing importance. Within Germany, temperate conditions have historically enabled most agriculture to be supplied solely by green water, but recent crop yield reductions and crop failures have demonstrated its increased vulnerability to climatic conditions. The raster-based mGROWA hydrological water balance model was implemented over all agricultural areas in Germany for the period 1961–2020 at a high spatial (200 m) and temporal (daily) resolution. Grid-cells were each assigned one of 10 major crop classes, which account for 86.7 % of all agricultural areas in Germany, and effectively all irrigated areas. Using crop-specific irrigation rules that reflect actual practices, irrigation requirements were simulated for all crop areas. To investigate the relationship between climatic water balance over the crop growing season and irrigation requirements, the simulated annual irrigation requirements were compared with the standardised precipitation-evapotranspiration index (SPEI-6), calculated at the end of September. Through this comparison, irrigation requirements could be characterised for near-normal and dry conditions, and results were aggregated to the district level. Additionally, using district-level data on the areas with irrigation infrastructure, the actual water used for irrigation was estimated. The results highlight marked increases in irrigation requirements in dry conditions compared to near-normal conditions (median increase of 72 %), which are more pronounced over crops in silty soils than in sandy soils. The results also demonstrate how the increased irrigation requirements in dry years are in many cases higher than what is suggested by guidelines for irrigation management in Germany. This study provides important information for actors related to the agricultural sector and water management and is based on a robust and transferable framework to quantify how irrigation requirements vary according to climatic variability and local soil conditions. [Display omitted] • Irrigation requirements were simulated using mGROWA for agricultural areas in Germany. • Sharp increases in irrigation requirements were shown to occur in drought periods. • In dry years, irrigation requirements were highly pronounced for crops in silty soils. • Irrigation volumes were estimated by considering irrigation infrastructure data. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: Bankfull flow is a relevant parameter in the field of large scale modelling especially for the analysis of environmental flows and flood related hydrological processes. In our case, bankfull flow data were required within the SCENES project in order to analyse ecological important inundation events at selected grid cells of a European raster. In practise, the determination of bankfull flow is a complex task even on local scale. Subsequent to a literature survey of bankfull flow studies, this paper describes a method which can be applied to estimate bankfull flow on a global or continental grid cell raster. The method is based on the partial duration series approach taking into account a 40-years time series of daily discharge data modelled by the global water model WaterGAP. An increasing threshold censoring procedure, a declustering scheme and the generalised Pareto distribution are applied. Modelled bankfull flow values are then validated by different efficiency criteria against bankfull flows observed at gauging stations in Europe. Thereby, the impact of (i) the applied distribution function, (ii) the threshold setting in the partial duration series, (iii) the climate input data and (iv) applying the annual maxima series are evaluated and compared to the proposed approach. The results show that bankfull flow can be reasonably estimated with a high model efficiency (E 1 =0.71) and weighted correlation (ωr 2 =0.90) as well as a systematic overestimation of 22.8%. Finally it turned out that in our study focusing on hydrological extremes, the appliance of the daily climate input data is a basic requirement. While the choice of the distribution function had no significant impact on the final results, the threshold setting in the partial duration series was crucial. [Copyright &y& Elsevier]

It is nowadays a hot topic to apply machine learning (ML) algorithms to illustrate water temperature dynamics in lentic waters. Due to the limited amount of in-situ temperature measurements from traditional sampling programmes, most of the related studies, however, restricted their analysis within the surface and rarely checked the results for whole depth profiles. Moreover, capability of such methods in projecting thermal dynamics under future climate conditions is even less illustrated. To fill the gap, we collected an unparalleled huge database including 9 million water temperature measurements, from 2013 to 2022, in Rappbode Reservoir, Germany as well as the corresponding climatic and hydrological observations, to train three commonly used ML models (Random Forest, XGBoost, and Long Short-Term Memory) and comprehensively evaluate their performance in reproducing thremal structure within the whole water column. We also systemically compared such simulation results with a well-established process-driven model (CE-QUAL-W2). Going beyond a pure reproduction of observatiosn, we further evaluated the ability of CE-QUAL-W2 and ML models in projecting thermal dynamics under RCP8.5 climate scenario up to 2100. Our results suggested three ML methods yielded high accuracy in capturing water temperature dynamics from the surface (epilimnion) to bottom (hypolimnion), and also satisfactorily reproduced temporal development of the stratification pattern, with the results corresponding well with those from CE-QUAL-W2. By contrast, the projections by ML models were rather insensitive to future climate warming under RCP8.5 comparing with those by CE-QUAL-W2, pointing to an important risk whenever ML-based models are extrapolated beyond their training data range. Supported by millions of in situ measurements, our research clearly illustrated the opportunities (limits) of ML models in projecting thermal dynamics in deep waters, and the conclusion also provides key guidance for scientists to select the appropriate tools in projecting water temperature, and other environmental factors, under changing climate. [Display omitted] • An unparalleled temperature database was collected to test performance of ML models. • ML models captured the seasonal temperature pattern from top to bottom water layers. • ML models accurately reproduced the temporal development of stratification structure. • Extrapolation in ML models should be cautious under climate warming conditions. [ABSTRACT FROM AUTHOR]

Water - Global Assessment and Prognosis (WaterGAP) is a modelling approach for quantifying water resources and water use for all land areas of the Earth that has served science and society since 1996. In this paper, the refinements, new algorithms and new data of the most recent model version v2.2e are described, together with a thorough evaluation of simulated water use, streamflow and total water storage anomaly against observation data. WaterGAP v2.2e improves the handling of inland sinks and now excludes not only large but also small man-made reservoirs when simulating naturalized conditions. The reservoir and non-irrigation water use data were updated. In addition, the model was calibrated against an updated and extended dataset of streamflow observations at 1509 gauging stations. The model can now be started using pre-scribed water storages and other conditions, which facilitates data assimilation as well as near real-time monitoring and forecast simulations. For specific applications, the model can consider the output of a glacier model, approximate the effect of rising CO2 concentrations on evapotranspiration or calculate the water temperature in rivers. In the paper, the publicly available standard model output is described and caveats of the model version are provided alongside the description of the model setup in the ISIMIP3 framework. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper aims to evaluate sources of uncertainty in projected hydrological changes under climate change in twelve large-scale river basins worldwide, considering the mean flow and the two runoff quantiles Q (high flow), and Q (low flow). First, changes in annual low flow, annual high flow and mean annual runoff were evaluated using simulation results from a multi-hydrological-model (nine hydrological models, HMs) and a multi-scenario approach (four Representative Concentration Pathways, RCPs, five CMIP5 General Circulation Models, GCMs). Then, three major sources of uncertainty (from GCMs, RCPs and HMs) were analyzed using the ANOVA method, which allows for decomposing variances and indicating the main sources of uncertainty along the GCM-RCP-HM model chain. Robust changes in at least one runoff quantile or the mean flow, meaning a high or moderate agreement of GCMs and HMs, were found for five river basins: the Lena, Tagus, Rhine, Ganges, and Mackenzie. The analysis of uncertainties showed that in general the largest share of uncertainty is related to GCMs, followed by RCPs, and the smallest to HMs. The hydrological models are the lowest contributors of uncertainty for Q and mean flow, but their share is more significant for Q. [ABSTRACT FROM AUTHOR]

In regional climate impact studies, good performance of regional models under present/historical climate conditions is a prerequisite for reliable future projections. This study aims to investigate the overall performance of 9 hydrological models for 12 large-scale river basins worldwide driven by the reanalysis climate data from the Water and Global Change (WATCH) project. The results serve as the basis of the application of regional hydrological models for climate impact assessment within the second phase of the Inter-Sectoral Impact Model Intercomparison project (ISI-MIP2). The simulated discharges by each individual hydrological model, as well as the ensemble mean and median series were compared against the observed discharges for the period 1971-2001. In addition to a visual comparison, 12 statistical criteria were selected to assess the fidelity of model simulations for monthly hydrograph, seasonal dynamics, flow duration curves, extreme floods and low flows. The results show that most regional hydrological models reproduce monthly discharge and seasonal dynamics successfully in all basins except the Darling in Australia. The moderate flow and high flows (0.02-0.1 flow exceedance probabilities) are also captured satisfactory in many cases according to the performance ratings defined in this study. In contrast, the simulation of low flow is problematic for most basins. Overall, the ensemble discharge statistics exhibited good agreement with the observed ones except for extremes in particular basins that need further scrutiny to improve representation of hydrological processes. The performances of both the conceptual and process-based models are comparable in all basins. [ABSTRACT FROM AUTHOR]

The growing geographic disconnect between consumption of goods, the extraction and processing of resources, and the environmental impacts associated with production activities makes it crucial to factor global trade into sustainability assessments. Using an empirically validated environmentally extended global trade model, we examine the relationship between two key resources underpinning economies and human well-being--energy and freshwater. A comparison of three energy sectors (petroleum, gas, and electricity) reveals that freshwater consumption associated with gas and electricity production is largely confined within the territorial boundaries where demand originates. This finding contrasts with petroleum, which exhibits a varying ratio of territorial to international freshwater consumption, depending on the origin of demand. For example, although the United States and China have similar demand associated with the petroleum sector, international freshwater consumption is three times higher for the former than the latter. Based on mapping patterns of freshwater consumption associated with energy sectors at subnational scales, our analysis also reveals concordance between pressure on freshwater resources associated with energy production and freshwater scarcity in a number of river basins globally. These energy-driven pressures on freshwater resources in areas distant from the origin of energy demand complicate the design of policy to ensure security of fresh water and energy supply. Although much of the debate around energy is focused on greenhouse gas emissions, our findings highlight the need to consider the full range of consequences of energy production when designing policy. [ABSTRACT FROM AUTHOR]

Scenario development methods get to grips with taking a long-term view on complex issues such as climate change through involvement of stakeholders. Many of the recent (global) scenario exercises have been structured according to a Story-and-Simulation approach. Although elaborately studied, conceptual and practical issues remain in linking qualitative stories and quantitative models. In this paper, we show how stakeholders can directly estimate model parameter values using a three-step approach called Fuzzy Set Theory. We focus on the effect of multiple iterations between stories and models. Results show that we were successful in quickly delivering stakeholder-based quantification of key model parameters, with full consistency between linguistic terms used in stories and numeric values. Yet, values changed strongly from one iteration to the next. A minimum of two and preferably at least three iterations is needed to harmonise stories and models. We conclude that the application of Fuzzy Set Theory enabled a highly valuable, structured and reproducible process to increase consistency between stories and models, but that future work is needed to show its true potential, particularly related to the effect of iterations. Additionally, the number of tools that need to be applied in a short period of time to execute a Story-And-Simulation approach introduces drawbacks that need to be studied. However, an approach such as Story-And-Simulation is indispensable and effective in marrying the perspectives of scientists and other stakeholders when studying complex systems and complex problems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces an approach to route discharge with a variable river flow velocity based on the Manning–Strickler formula within large scale hydrological models. The approach has been developed for the global scale hydrological model WaterGAP and model results have been analyzed focusing on Europe. The goal was to find a method that is simple enough to derive the required parameters from globally available data while being sophisticated enough to deliver realistic flow velocity estimates for a large variety of environmental conditions. The river bed roughness (Manning’s n) is approximated in a spatially explicit way based on topography, the location of urban population, and river sinuosity. The hydraulic radius is estimated from actual river discharge, and river bed slope is derived by combining a high resolution DEM, a 5arc min drainage direction map, and river sinuosity. The modeled river flow velocity has been validated against data of US gauging stations. The representation of lateral transport has clearly been improved compared to the constant flow velocity applied in older model versions. The effect of incorporating variable flow velocities as compared to a constant flow velocity is largest on flood discharge, which generally increases in large rivers. The impact on monthly discharge hydrographs is marginal only. WaterGAP has been driven by three climate change projections for the 2050s to assess climate change impacts on flow velocity, and on the residence time of water in the European river system. Results indicate a decrease in residence times for Northern Europe and an increase for parts of the Mediterranean. [Copyright &y& Elsevier]

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 achieved with WaterGAP 2.2d model output. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

A correction is presented to the article "Evaluation of an ensemble of regional hydrological models in 12 large-scale river basins worldwide" that was published online on January 6, 2017.

Governments, development banks, corporations, and nonprofits are increasingly considering the potential contribution of watershed conservation activities to secure clean water for cities and to reduce flood risk. These organizations, however, often lack decision-relevant, initial screening information across multiple cities to identify which specific city-watershed combinations present not only water-related risks but also potentially attractive opportunities for mitigation via natural infrastructure approaches. To address this need, this paper presents a novel methodology for a continental assessment of the potential for watershed conservation activities to improve surface drinking water quality and mitigate riverine and stormwater flood risks in 70 major cities across Latin America. We used publicly available geospatial data to analyze 887 associated watersheds. Water quality metrics assessed the potential for agricultural practices, afforestation, riparian buffers, and forest conservation to mitigate sediment and phosphorus loads. Flood reduction metrics analyzed the role of increasing infiltration, restoring riparian wetlands, and reducing connected impervious surface to mitigate riverine and stormwater floods for exposed urban populations. Cities were then categorized based on relative opportunity potential to reduce identified risks through watershed conservation activities. We find high opportunities for watershed activities to mitigate at least one of the risks in 42 cities, potentially benefiting 96 million people or around 60% of the urbanites living in the 70 largest cities in Latin America. We estimate water quality could be improved for 72 million people in 27 cities, riverine flood risk mitigated for 5 million people in 13 cities, and stormwater flooding mitigated for 44 million people in 14 cities. We identified five cities with the potential to simultaneously enhance water quality and mitigate flood risks, and in contrast, six cities where conservation efforts are unlikely to meaningfully mitigate either risk. Institutions investing in natural infrastructure to improve water security in Latin America can maximize their impact by focusing on specific watershed conservation activities either for cleaner drinking water or flood mitigation in cities identified in our analysis where these interventions are most likely to reduce risk. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The dataset presented here consists of an ensemble of 10 global hydrological and land surface models for the period 1979–2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state of the art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominated regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3 yr−1 (334 kg m−2 yr−1), while the ensemble mean of total evaporation was 537 kg m−2 yr−1. All data are made available openly through a Water Cycle Integrator portal (WCI, wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. [ABSTRACT FROM AUTHOR]

Municipal water systems provide crucial services for human well-being, and will undergo a major transformation this century following global technological, socioeconomic and environmental changes. Future demand scenarios integrating these drivers over multi-decadal planning horizons are needed to develop effective adaptation strategies. This paper presents a new long-term scenario modeling framework that projects future daily municipal water demand at a 1/8° global spatial resolution. The methodology incorporates improved representations of important demand drivers such as urbanization and climate change. The framework is applied across multiple future socioeconomic and climate scenarios to explore municipal water demand uncertainties over the 21st century. The scenario analysis reveals that achieving a low-carbon development pathway can potentially reduce global municipal water demands in 2060 by 2–4%, although the timing and scale of impacts vary significantly with geographic location. [ABSTRACT FROM AUTHOR]

The dataset presented here consists of an ensemble of ten global hydrological and land surface models for the period 1979-2012 using a reanalysis-based meteorological forcing dataset (0.5° resolution). The current dataset serves as a state-of-the-art in current global hydrological modelling and as a benchmark for further improvements in the coming years. A signal-to-noise ratio analysis revealed low inter-model agreement over (i) snow-dominate regions and (ii) tropical rainforest and monsoon areas. The large uncertainty of precipitation in the tropics is not being reflected in the ensemble runoff. Verification of the results against benchmark datasets for evapotranspiration, snow cover, snow water equivalent, soil moisture anomaly and total water storage anomaly using the tools from The International Land Model Benchmarking Project (ILAMB) showed overall useful model performance, while the ensemble mean generally outperformed the single model estimates. The results also show that there is currently no single best model for all variables and that model performance is spatially variable. In our unconstrained model runs the ensemble mean of total runoff into the ocean was 46 268 km3/yr (334 kg/m2/yr) while the ensemble mean of total evaporation was 537 kg/m2/yr. All data are made available openly through a Water Cycle Integrator portal (WCI, http://wci.earth2observe.eu), and via a direct http and ftp download. The portal follows the protocols of the open geospatial consortium such as OPeNDAP, WCS and WMS. [ABSTRACT FROM AUTHOR]

Future renewable water resources are likely to be insufficient to meet water demand for human use and minimum environmental flow requirements in many European regions. Hence, fair and equitable water allocation to different water use sectors and environmental needs is important for climate change adaptation in order to reduce negative effects on human well-being and aquatic ecosystems. We applied a system of coupled sectoral metamodels of water availability and water use in the domestic, manufacturing industry, electricity generation, and agricultural sectors to simulate the effects of generic water allocation schemes (WAS) at the European level. The relative performance of WAS in balancing adverse impacts on the water use sectors and aquatic ecosystems was analysed for an ensemble of 16 scenarios for the 2050s, which were built from the combination of four socio-economic scenarios, developed in the CLIMSAVE project, and four climate projections based on IPCC A1. The results indicate that significant physical water shortages may result from climate and socio-economic change in many regions of Europe, particularly in the Mediterranean. In the energy sector, average annual water demand can largely be met even in water allocation schemes that deprioritise the sector. However, prioritisation of agricultural water demand has significant adverse impacts on the domestic and manufacturing industry sectors. Cross-sectoral impacts were found to be lowest if at least one of the domestic and manufacturing sectors is assigned higher priority than agriculture. We conclude that adapting spatial patterns of water-intensive activities to renewable water availability across Europe, such as shifting irrigated agriculture to less water-stressed basins, could be an effective demand-side adaptation measure, and thus a candidate for support through EU policy. [ABSTRACT FROM AUTHOR]

Humans directly change the dynamics of the water cycle through dams constructed for water storage, and through water withdrawals for industrial, agricultural, or domestic purposes. Climate change is expected to additionally affect water supply and demand. Here, analyses of climate change and direct human impacts on the terrestrial water cycle are presented and compared using a multimodel approach. Seven global hydrological models have been forced with multiple climate projections, and with and without taking into account impacts of human interventions such as dams and water withdrawals on the hydrological cycle. Model results are analyzed for different levels of global warming, allowing for analyses in line with temperature targets for climate change mitigation. The results indicate that direct human impacts on the water cycle in some regions, e.g., parts of Asia and in the western United States, are of the same order of magnitude, or even exceed impacts to be expected for moderate levels of global warming (+2 K). Despite some spread in model projections, irrigation water consumption is generally projected to increase with higher global mean temperatures. Irrigation water scarcity is particularly large in parts of southern and eastern Asia, and is expected to become even larger in the future. [ABSTRACT FROM AUTHOR]

We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400- 1,400 Pcal (8-24% of present-day total) when CO2 fertilization effects are accounted for or 1,400-2,600 Pcal (24-43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20-60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600-2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required. [ABSTRACT FROM AUTHOR]

The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty. [ABSTRACT FROM AUTHOR]

Water scarcity in Central Asia was analyzed by using two water scarcity indices at the scale of sub-basin areas (SBAs): water stress index (consumption-to-availability ratio) and water shortage index (water availability per capita). These indices were calculated for a baseline scenario that included virtual water flows, and again for a scenario where international trade was eliminated, thus assessing the role of virtual water flows in water scarcity. Over 80% of the study area population suffers from water stress and approximately 50% from water shortage as well. Removing virtual water flows considerably decreased water scarcity for approximately half the population. Reducing the exports of water-intensive products could thus be an option, along with other more traditional measures, for alleviating water scarcity in Central Asia. [ABSTRACT FROM AUTHOR]

Abstract: Irrigated cropland plays a crucial role for agricultural production but has also been identified as a major user of global freshwater resources. The amount of irrigation water needed depends on climate conditions and socio-economic factors (e.g. amount of crop production and technology). In this study we analyze the development of irrigated area and the corresponding net irrigation water requirements for pan-Europe using a spatially explicit land-use model (LandSHIFT) together with a hydrology and water-use model (WaterGAP3). Four simulation experiments for the assessment of irrigation water requirements were conducted: (1) irrigated area for the base year 2000 under climate normal conditions, (2) irrigated area for 2000 with two climate scenarios for 2050, (3) two scenarios for changing irrigated area until 2050 under climate normal conditions and (4) the two irrigated area scenarios in combination with the climate scenarios. Results show that under baseline conditions yearly irrigation water requirements sum up to 53billion m3. The expansion of irrigated area strongly depends on the combination of socio-economic drivers and climate change. Generally, the two analyzed climate scenarios lead to an expansion of irrigated area which we explain by negative effects of increasing air temperatures on crop growth conditions. Analysing the irrigated area scenarios and climate scenarios separately, we find that the effect of land-use change on net irrigation water requirements is larger than the climate effect. Combined analysis of socio-economic and climate drivers reveal that the expansion of irrigated area is not directly correlated to the changes of irrigation water requirements as the adaptation of sowing dates to the changing climatic conditions might help to overcome seasonal water deficits. The study underlines the importance of considering both the change of irrigated area and agricultural management as well as hydrology aspects in regional water use analysis and shows that simulation models can serve as tools to provide this information to the development of regional water management strategies. [Copyright &y& Elsevier]

An appropriate hydrological regime within a wetland is essential to maintain its goods and services. This regime is related to the source of the water, which differs for particular kinds of wetlands. This paper presents an overview of the ecosystem services of European wetlands, based on a representative sample of 102 protected wetlands larger than 5000 ha, and the implications of hydrological alterations caused by future climate and socio-economic changes. Six major ecosystem services of wetlands were assessed namely: biodiversity in terms of plants and animals, biomass production, nutrient removal, carbon storage and fish production. Data showed that, on average, four services were present in each wetland. The impact of climate change, water management and land-use change was examined under different future scenarios. Major potential changes in hydrological regime (i.e. precipitation, groundwater recharge and river flow) were quantified up to the 2050s using simulated runoff and river flow data of the WaterGAP model driven by the climate input of two different general circulation models (GCMs), IPCM4 and MIMR. Thresholds of hydrological change that would endanger each ecosystem service were identified. The impacts of future scenarios were distributed across Europe with potential threats to ecosystem services of European wetlands resulting in the loss of between 26 and 46% of all identified ecosystem services in 2050. The models and scenarios suggest that the most significant loss of ecosystem services is likely to occur in Central Europe (Hungary, Germany, France, Belarus, Poland). In general, the most fragile services (the largest number lost) are projected to be those connected to the surface water dynamics—mostly the services of wetland birds and fish spawning. Ecosystem services dependent on groundwater dynamics and water balance changes are seemingly more buffered against the expected hydrological stress. Editor D. Koutsoyiannis Citation Okruszko, T., Duel, H., Acreman, M., Grygoruk, M., Flörke, M. and Schneider, C., 2011. Broad-scale ecosystem services of European wetlands—overview of the current situation and future perspectives under different climate and water management scenarios. Hydrological Sciences Journal, 56 (8), 1501–1517. [ABSTRACT FROM PUBLISHER]

Human appropriation of renewable freshwater (HARF) is a measure for the influence of human activities on the global water cycle. It describes the fraction of accessible water that is directly used by human-dominated systems. We present a comprehensive model-based analysis of HARF for crop production on the African continent. Our analysis includes the components evapotranspiration from cropland ("green" water fluxes) and water used for cropland irrigation (crop-related fraction of "blue" water fluxes). Model experiments were conducted for two scenarios with a time horizon of 2050, taking into account the combined effects of land-use change, climate change, and technological change. For the year 2000, evapotranspiration from Africa's rainfed cropland (green water flux) is estimated to be 1085 km³/yr, whereas the abstraction of water for irrigation purposes from the renewable water resources (blue water flux) is estimated to be approximately 180 km³/yr. According to the model experiments, between 2000-2050, an area between 1.25 million km² and 1.56 million km² of natural biomes will be converted to cropland. Consequently, for 2050, evapotranspiration from rainfed cropland is substantially greater than in 2000, ranging from 1870-2040 km³/yr, depending on the scenario, and irrigation abstraction increases up to 194-330 km³/yr. These findings point out the significant role of water appropriated for rainfed crop production in the continental water cycle, in contrast to the sum of water appropriated for irrigation. Furthermore, they suggest that it would be worthwhile to look for opportunities to reduce the amount of water evaporated and transpired from cropland to increase the "water productivity" of cropland. Finally, they indicate that under the given scenarios, this additional production is very likely to come at the cost of the extent of natural biomes and their associated ecosystem services. [ABSTRACT FROM AUTHOR]

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. Unlabelled Image • We present an approach to construct river basin water quality monitoring networks. • This approach uses pollutant estimates from WorldQual to detect non-compliance areas. • This approach is applicable to any river basin worldwide of any size. • Its approach is one of stage-based multi-objective optimization (MOABC). • This can be used to establish a new network and able to be augmented progressively. [ABSTRACT FROM AUTHOR]