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In the last few years, the world has experienced numerous extreme droughts with adverse direct, cascading, and systemic impacts. Despite more frequent and severe events, drought risk assessment is still incipient compared to that of other meteorological and climate hazards. This is mainly due to the complexity of drought, the high level of uncertainties in its analysis, and the lack of community agreement on a common framework to tackle the problem. Here, we outline that to effectively assess and manage drought risks, a systemic perspective is needed. We propose a novel drought risk framework that highlights the systemic nature of drought risks, and show its operationalization using the example of the 2022 drought in Europe. This research emphasizes that solutions to tackle growing drought risks should not only consider the underlying drivers of drought risks for different sectors, systems or regions, but also be based on an understanding of sector/system interdependencies, feedbacks, dynamics, compounding and concurring hazards, as well as possible tipping points and globally and/or regionally networked risks. Plain Language Summary: In recent years, the world has faced severe and frequent droughts, resulting in significant direct and indirect impacts. However, our understanding and assessment of drought risks are still limited which has important implications for risk management. Here, we propose a new approach—a systemic perspective on drought risks—to effectively assess and manage drought risks. Our framework highlights the interconnected nature of drought risks, impacts and responses. We demonstrate the framework's application by analyzing the 2022 drought in Europe. This research emphasizes the need for a comprehensive understanding of drought risks and offers a practical tool for policymakers and researchers to guide future drought risk research and policy. Key Points: Drought risks are on the rise and their effects are increasingly felt across communities, economic sectors, ecosystems, borders and entire societiesTo effectively assess and manage drought risks, a systemic perspective is neededWe propose a novel systemic framework to better inform drought risk research and policy [ABSTRACT FROM AUTHOR]

Seasonal water storage fluctuations are critical for evaluating water scarcity linked to climate forcing and human intervention. Here we compare seasonal changes in land total water storage anomalies using seven global hydrologic and land surface models (WGHM, PCR‐GLOBWB, and five GLDAS models) to GRACE satellite data in 183 river basins globally. This work builds on previous analysis that focused on total water storage anomaly trends. Results show that most models underestimate seasonal water storage amplitudes in tropical and (semi)arid basins and land surface models generally overestimate amplitudes in northern basins. Some models (CLM‐5.0 and PCR‐GLOBWB) agree better with GRACE than others. Causes of model‐GRACE discrepancies are attributed to missing storage compartments (e.g., surface water and/or groundwater) and underestimation of modeled storage capacities in tropical basins and to variations in modeled fluxes in northern basins. This study underscores the importance of considering water storage, in addition to water fluxes, to improve global models. Plain Language Summary: We are relying more and more on global models to understand the water cycle, but we need to assess the reliability of model output. In this study we compare seasonal amplitudes in land total water storage from global models with those from GRACE satellite data in river basins globally. We found that seasonal amplitudes in total water storage account for more than half of the total signal, except in semiarid basins. Seasonal amplitudes are highest in tropical basins and lowest in semiarid basins. Some models agree better with GRACE than others (CLM‐5.0 and PCR‐GLOBWB). Most models underestimate GRACE‐derived seasonal amplitudes in tropical and semiarid basins but overestimate seasonal amplitudes in northern high latitude basins. The main cause of the discrepancies in tropical basins is likely insufficient storage capacity and lack of surface water inundation to accommodate the large seasonal storage variations. In northern high latitude basins, differences in snow physics and evapotranspiration increase seasonal amplitudes in water storage in newer versions of land surface models, overestimating GRACE‐derived seasonal amplitudes and reducing agreement with GRACE relative to earlier versions. Reliable models of seasonal variations in water storage are critical for assessing water scarcity, estimating response to climate extremes, and managing water resources. Key Points: Modeled seasonal amplitudes are underestimated in tropical and semiarid basins and overestimated in northern basins relative to GRACEModel‐GRACE discrepancies are attributed to insufficient storage capacities in tropical basins and biases in fluxes in northern basinsThis study highlights the value of using water storage, in addition to traditional water flux, in assessing and improving global models [ABSTRACT FROM AUTHOR]

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making. [ABSTRACT FROM AUTHOR]

Treating and reusing municipal wastewater for urban agriculture raises water productivity. This paper developed a methodology to quantify water flows and productivity of a proposed infrastructure including water supply, sanitation, wastewater treatment and water reuse for agriculture. The methodology consists in calculating the pathogen reduction achieved with wastewater treatment, designing a crop scheme for the irrigation with treated water, modeling irrigation requirements and quantifying water flows with mathematical material flow analysis. This methodology was applied for the current state and with the planned facility in semi-arid Namibia. This infrastructure has the potential to raise water productivity by +10% as household water use increases with improved sanitation. Compared to not reusing the water for agriculture, water productivity can be raised by +39%. This methodology allowed the consideration of the impact of facility user behavior on water flows and found that water productivity increases less than computed with a fixed wastewater inflow. [ABSTRACT FROM PUBLISHER]

Irrigation intensifies land use by increasing crop yield but also impacts water resources. It affects water and energy balances and consequently the microclimate in irrigated regions. Therefore, knowledge of the extent of irrigated land is important for hydrological and crop modelling, global change research, and assessments of resource use and management. Information on the historical evolution of irrigated lands is limited. The new global historical irrigation data set (HID) provides estimates of the temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5 arcmin resolution. We collected sub-national irrigation statistics from various sources and found that the global extent of AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. We developed eight gridded versions of time series of AEI by combining sub-national irrigation statistics with different data sets on the historical extent of cropland and pasture. Different rules were applied to maximize consistency of the gridded products to sub-national irrigation statistics or to historical cropland and pasture data sets. The HID reflects very well the spatial patterns of irrigated land as shown on historical maps for the western United States (around year 1900) and on a global map (around year 1960). Mean aridity on irrigated land increased and mean natural river discharge on irrigated land decreased from 1900 to 1950 whereas aridity decreased and river discharge remained approximately constant from 1950 to 2005. [ABSTRACT FROM AUTHOR]

Editor D. Koutsoyiannis [ABSTRACT FROM AUTHOR]

Global-scale assessments of freshwater fluxes and storages by hydrological models under historic climate conditions are subject to a variety of uncertainties. Using the global hydrological model WaterGAP 2.2, we investigated the sensitivity of simulated freshwater fluxes and water storage variations to five major sources of uncertainty: climate forcing, land cover input, model structure, consideration of human water use and calibration (or no calibration). In a modelling experiment, five variants of the standard version of WaterGAP 2.2 were generated that differed from the standard version only regarding the investigated source of uncertainty. Sensitivity was analyzed by comparing water fluxes and water storage variations computed by the variants to those of the standard version, considering both global averages and grid cell values for the time period 1971-2000. The basin-specific calibration approach for WaterGAP, which forces simulated mean annual river discharge to be equal to observed values at 1319 gauging stations (representing 54% of global land area except Antarctica and Greenland), has the highest effect on modelled water fluxes and leads to the best fit of modelled to observed monthly and seasonal river discharge. Alternative state-of-the-art climate forcings rank second regarding the impact on grid cell specific fluxes and water storage variations, and their impact is ubiquitous and stronger than that of alternative land cover inputs. The diverse model refinements during the last decade lead to an improved fit to observed discharge, and affect globally averaged fluxes and storage values (the latter mainly due to modelling of groundwater depletion) but only affect a relatively small number of grid cells. Considering human water use is important for the global water storage trend (in particular in the groundwater compartment) but impacts on water fluxes are rather local and only important where water use is high. The best fit to observed time series of monthly river discharge (Nash-Sutcliffe criterion) or discharge seasonality is obtained with the standard WaterGAP 2.2 model version which is calibrated and driven by a sequence of two time series of daily observation-based climate forcings, WFD/WFDEI. Discharge computed by a calibrated model version using monthly CRU 3.2 and GPCC v6 climate input reduced the fit to observed discharge for most stations. Taking into account the investigated uncertainties of climate and land cover data, we estimate that the global 1971-2000 discharge into oceans and inland sinks is between 40 000 and 42 000 km³ yr-1. The range is mainly due differences in precipitation data that affect discharge in uncalibrated river basins. Actual evapotranspiration, with approximately 70 000 km³ yr-1, is rather unaffected by climate and land cover in global sum but differs spatially. Human water use is calculated to reduce river discharge by approximately 1000 km³ yr-1. Thus, global renewable water resources are estimated to range between 41 000 and 43 000 km³ yr-1. The climate data sets WFD (available until 2001) and WFDEI (starting in 1979) were found to be inconsistent with respect to short wave radiation data, resulting in strongly different potential evapotranspiration. Global assessments of freshwater fluxes and storages would therefore benefit from the development of a global data set of consistent daily climate forcing from 1900 to current. [ABSTRACT FROM AUTHOR]

Water footprints have been proposed as sustainability indicators, relating the consumption of goods like food to the amount of water necessary for their production and the impacts of that water use in the source regions. We further developed the existing water footprint methodology, by globally resolving virtual water flows from production to consumption regions for major food crops at 5 arcmin spatial resolution. We distinguished domestic and international flows, and assessed local impacts of export production. Applying this method to three exemplary cities, Berlin, Delhi and Lagos, we find major differences in amounts, composition, and origin of green and blue virtual water imports, due to differences in diets, trade integration and crop water productivities in the source regions. While almost all of Delhi's and Lagos' virtual water imports are of domestic origin, Berlin on average imports from more than 4000 km distance, in particular soy (livestock feed), coffee and cocoa. While 42% of Delhi's virtual water imports are blue water based, the fractions for Berlin and Lagos are 2 and 0.5%, respectively, roughly equal to the water volumes abstracted in these two cities for domestic water use. Some of the external source regions of Berlin's virtual water imports appear to be critically water scarce and/or food insecure. However, for deriving recommendations on sustainable consumption and trade, further analysis of context-specific costs and benefits associated with export production will be required. [ABSTRACT FROM AUTHOR]

Water footprints have been proposed as sustainability indicators, relating the consumption of goods like food to the amount of water necessary for their production and the impacts of that water use in the source regions. We have further developed the existing water footprint methodology by globally resolving virtual water flows and import and source regions at 5 arc minutes spatial resolution, and by assessing local impacts of export production. Applying this method to three exemplary cities, Berlin, Delhi and Lagos, we find major differences in amounts, composition, and origin of green and blue virtual water imports, due to differences in diets, trade integration and crop water productivities in the source regions. While almost all of Delhi's and Lagos' virtual water imports are of domestic origin, Berlin on average imports from more than 4000 km distance, in particular soy (livestock feed), coffee and cocoa. While 42% of Delhi's virtual water imports are blue water based, the fractions for Berlin and Lagos are 2 % and 0.5%, respectively, roughly equal to local drinking water abstractions of these cities. Some of the external source regions of Berlin's virtual water imports appear to be critically water scarce and/or food insecure. However for deriving recommendations on sustainable consumption and trade, further analysis of context-specific costs and benefits associated with export production will be required. [ABSTRACT FROM AUTHOR]

Floodplains play an important role in the terrestrial water cycle and are very important for biodiversity. Therefore, an improved representation of the dynamics of floodplain water flows and storage in global hydrological and land surface models is required. To support model validation, we combined monthly time series of satellite-derived inundation areas (Papa et al., 2010) with data on irrigated rice areas (Portmann et al., 2010). In this way, we obtained global-scale time series of naturally inundated areas (NIA), with monthly values of inundation extent during 1993-2004 and a spatial resolution of 0.5°. For most grid cells (0.5°x0.5°), the mean annual maximum of NIA agrees well with the static open water extent of the Global Lakes and Wetlands database (GLWD) (Lehner and Döll, 2004), but in 16% of the cells NIA is larger than GLWD. In some regions, like Northwestern Europe, NIA clearly overestimates inundated areas, probably because of confounding very wet soils with inundated areas. In other areas, such as South Asia, it is likely that NIA can help to enhance GLWD. NIA data will be very useful for developing and validating a floodplain modeling algorithm for the global hydrological model WGHM. For example, we found that monthly NIAs correlate with observed river discharges. [ABSTRACT FROM AUTHOR]

River flow regimes, including long-term average flows, seasonality, low flows, high flows and other types of flow variability, play an important role for freshwater ecosystems. Thus, climate change affects freshwater ecosystems not only by increased temperatures but also by altered river flow regimes. However, with one exception, transferable quantitative relations between flow alterations and ecological responses have not yet been derived. While discharge decreases are generally considered to be detrimental for ecosystems, the effect of future discharge increases is unclear. As a first step towards a global-scale analysis of climate change impacts on freshwater ecosystems, we quantified the impact of climate change on five ecologically relevant river flow indicators, using the global water model WaterGAP 2.1g to simulate monthly time series of river discharge with a spatial resolution of 0.5 degrees. Four climate change scenarios based on two global climate models and two greenhouse gas emissions scenarios were evaluated. We compared the impact of climate change by the 2050s to the impact of water withdrawals and dams on natural flow regimes that had occurred by 2002. Climate change was computed to alter seasonal flow regimes significantly (i.e. by more than 10%) on 90% of the global land area (excluding Greenland and Antarctica), as compared to only one quarter of the land area that had suffered from significant seasonal flow regime alterations due to dams and water withdrawals. Due to climate change, the timing of the maximum mean monthly river discharge will be shifted by at least one month on one third on the global land area, more often towards earlier months (mainly due to earlier snowmelt). Dams and withdrawals had caused comparable shifts on less than 5% of the land area only. Long-term average annual river discharge is predicted to significantly increase on one half of the land area, and to significantly decrease on one quarter. Dams and withdrawals had led to significant decreases on one sixth of the land area, and nowhere to increases. Thus, by the 2050s, climate change may have impacted ecologically relevant river flow characteristics more strongly than dams and water withdrawals have up to now. The only exception refers to the decrease of the statistical low flow Q90, with significant decreases both by past water withdrawals and future climate change on one quarter of the land area. However, dam impacts are likely underestimated by our study. Considering long-term average river discharge, only a few regions, including Spain, Italy, Iraq, Southern India, Western China, the Australian Murray Darling Basin and the High Plains Aquifer in the USA, all of them with extensive irrigation, are expected to be less affected by climate change than by past anthropogenic flow alterations. In some of these regions, climate change will exacerbate the discharge reductions, while in others climate change provides opportunities for reducing past reductions. Emissions scenario B2 leads to only slightly reduced alterations of river flow regimes as compared to scenario A2 even though emissions are much smaller. The differences in alterations resulting from the two applied climate models are larger than those resulting from the two emissions scenarios. Based on general knowledge about ecosystem responses to flow alterations and data related to flow alterations by dams and water withdrawals, we expect that the computed climate change induced river flow alterations will impact freshwater ecosystems more strongly than past anthropogenic alterations. [ABSTRACT FROM AUTHOR]

River flow regimes, including long-term average flows, seasonality, low flows, high flows and other types of flow variability, play an important role for freshwater ecosystems. Thus, climate change affects freshwater ecosystems not only by increased temperatures but also by altered river flow regimes. However, with one exception, transferable quantitative relations between flow alterations and ecosystem responses have not yet been derived. While discharge decreases are generally considered to be detrimental for ecosystems, the effect of future discharge increases is unclear. As a first step towards a global-scale analysis of climate change impacts on freshwater ecosystems, we quantified the impact of climate change on five ecologically relevant river flow indicators, using the global water model WaterGAP 2.1g to simulate monthly time series of river discharge with a spatial resolution of 0.5 degrees. Four climate change scenarios based on two global climate models and two greenhouse gas emissions scenarios were evaluated. We compared the impact of climate change by the 2050s to the impact of water withdrawals and dams on natural flow regimes that had occurred by 2002. Climate change was computed to alter seasonal flow regimes significantly (i.e. by more than 10%) on 90% of the global land area (excluding Greenland and Antarctica), as compared to only one quarter of the land area that had suffered from significant seasonal flow regime alterations due to dams and water withdrawals. Due to climate change, the timing of the maximum mean monthly river discharge will be shifted by at least one month on one third on the global land area, more often towards earlier months (mainly due to earlier snowmelt). Dams and withdrawals had caused comparable shifts on less than 5% of the land area only. Long-term average annual river discharge is predicted to significantly increase on one half of the land area, and to significantly decrease on one quarter. Dams and withdrawals had led to significant decreases on one sixth of the land area, and nowhere to increases. Thus, by the 2050s, climate change will have impacted ecologically relevant river flow characteristics much more strongly than dams and water withdrawals have up to now. The only exception refers to the decrease of the statistical low flow Q90, with significant decreases both by past water withdrawals and future climate change on one quarter of the land area. Considering long-term average river discharge, only a few regions, including Spain, Italy, Iraq, Southern India, Western China, the Australian Murray Darling Basin and the High Plains Aquifer in the USA, all of them with extensive irrigation, are expected to be less affected by climate change than by past anthropogenic flow alterations. In some of these regions, climate change will exacerbate the discharge reduction. Emissions scenario B2 leads to only slightly reduced alterations of river flow regimes as compared to scenario A2 even though emissions are much smaller. The differences in alterations resulting from the two applied climate models are larger than those resulting from the two emissions scenarios. Based on general knowledge about ecosystem responses to flow alterations and data related to flow alterations by dams and water withdrawals, we expect that the computed climate change induced river flow alterations will impact freshwater ecosystems more strongly than past anthropogenic alterations. [ABSTRACT FROM AUTHOR]

Global-scale information on natural river flows and anthropogenic river flow alterations is required to identify areas where aqueous ecosystems are expected to be strongly degraded. Such information can support the identification of environmental flow guidelines and a sustainable water management that balances the water demands of humans and ecosystems. This study presents the first global assessment of the anthropogenic alteration of river flow regimes, in particular of flow variability, by water withdrawals and dams/reservoirs. Six ecologically relevant flow indicators were quantified using an improved version of the global water model WaterGAP. WaterGAP simulated, with a spatial resolution of 0.5 degree, river discharge as affected by human water withdrawals and dams around the year 2000, as well as naturalized discharge without this type of human interference. Compared to naturalized conditions, long-term average global discharge into oceans and internal sinks has decreased by 2.7% due to water withdrawals, and by 0.8% due to dams. Mainly due to irrigation, long-term average river discharge and statistical low flow Q90 (monthly river discharge that is exceeded in 9 out of 10 months) have decreased by more than 10% on one sixth and one quarter of the global land area (excluding Antarctica and Greenland), respectively. Q90 has increased significantly on only 5% of the land area, downstream of reservoirs. Due to both water withdrawals and reservoirs, seasonal flow amplitude has decreased significantly on one sixth of the land area, while interannual variability has increased on one quarter of the land area mainly due to irrigation. It has decreased on only 8% of the land area, in areas downstream of reservoirs where consumptive water use is low. The impact of reservoirs is likely underestimated by our study as small reservoirs are not taken into account. Areas most affected by anthropogenic river flow alterations are the Western and Central USA, Mexico, the western coast of South America, the Mediterranean rim, Southern Africa, the semi-arid and arid countries of the Near East and Western Asia, Pakistan and India, Northern China and the Australian Murray-Darling Basin, as well as some Arctic rivers. Due to a large number of uncertainties related e.g. to the estimation of water use and reservoir operation rules, the analysis is expected to provide only first estimates of river flow alterations that should be refined in the future. [ABSTRACT FROM AUTHOR]

Global-scale information on natural river flows and anthropogenic river flow alterations is required to identify areas where aqueous ecosystems are expected to be strongly degraded. Such information can support the identification of environmental flow guide- 5 lines and a sustainable water management that balances the water demands of humans and ecosystems. This study presents the first global assessment of the anthropogenic alteration of river flow regimes by water withdrawals and dams, focusing in particular on the change of flow variability. Six ecologically relevant flow indicators were quantified using an improved version of the global water model WaterGAP. WaterGAP simulated, with a spatial resolution of 0.5 degree, river discharge as affected by human water withdrawals and dams, as well as naturalized discharge without this type of human interference. Mainly due to irrigation, long-term average river discharge and statistical low flow Q90 (monthly river discharge that is exceeded in 9 out of 10 months) have decreased by more than 10% on one sixth and one quarter of the global land area (excluding Antarctica and Greenland), respectively. Q90 has increased significantly on only 5% of the land area, downstream of reservoirs. Due to both water withdrawals and dams, seasonal flow amplitude has decreased significantly on one sixth of the land area, while interannual variability has increased on one quarter of the land area mainly due to irrigation. It has decreased on only 8% of the land area, in areas with little consumptive water use that are downstream of dams. Areas most affected by anthropogenic river flow alterations are the western and central USA, Mexico, the western coast of South America, the Mediterranean rim, Southern Africa, the semi-arid and arid countries of the Near East and Western Asia, Pakistan and India, Northern China and the Australian Murray-Darling Basin, as well as some Arctic rivers. Due to a large number of uncertainties related e.g. to the estimation of water use and reservoir operation rules, the analysis is expected to provide only first estimates of river flow alterations that should be refined in the future. [ABSTRACT FROM AUTHOR]

As China's economy booms, increasing water use has significantly affected hydro-geomorphic processes and thus the ecology of surface waters. A large variety of hydrological changes arising from human activities such as reservoir construction and management, water abstraction, water diversion and agricultural land expansion have been sustained throughout China. Using the global scale hydrological and water use model WaterGAP, natural and anthropogenically altered flow conditions are calculated, taking into account flow alterations due to human water consumption and 580 large reservoirs. The impacts resulting from water consumption and reservoirs have been analyzed separately. A modified "Indicators of Hydrologic Alteration" approach is used to describe the human pressures on aquatic ecosystems due to anthropogenic alterations in river flow regimes. The changes in long-term average river discharge, average monthly mean discharge and coefficients of variation of monthly river discharges under natural and impacted conditions are compared and analyzed. The indicators show very significant alterations of natural river flow regimes in a large part of northern China and only minor alterations in most of southern China. The detected large alterations in long-term average river discharge, the seasonality of flows and the inter-annual variability in the northern half of China are very likely to have caused significant ecological impacts. [ABSTRACT FROM AUTHOR]

Long-term average groundwater recharge, which is equivalent to renewable groundwater resources, is the major limiting factor for the sustainable use of groundwater. Compared to surface water resources, groundwater resources are more protected from pollution, and their use is less restricted by seasonal and inter-annual flow variations. To support water management in a globalized world, it is necessary to estimate groundwater recharge at the global scale. Here, we present a best estimate of global-scale long-term average diffuse groundwater recharge (i.e. renewable groundwater resources) that has been calculated by the most recent version of the WaterGAP Global Hydrology Model WGHM (spatial resolution of 0.5° by 0.5°, daily time steps). The estimate was obtained using two state-of-the-art global data sets of gridded observed precipitation that we corrected for measurement errors, which also allowed to quantify the uncertainty due to these equally uncertain data sets. The standard WGHM groundwater recharge algorithm was modified for semi-arid and arid regions, based on independent estimates of diffuse groundwater recharge, which lead to an unbiased estimation of groundwater recharge in these regions. WGHM was tuned against observed long-term average river discharge at 1235 gauging stations by adjusting, individually for each basin, the partitioning of precipitation into evapotranspiration and total runoff. We estimate that global groundwater recharge was 12 666 km³/yr for the climate normal 1961-1990, i.e. 32% of total renewable water resources. In semi-arid and arid regions, mountainous regions, permafrost regions and in the Asian Monsoon region, groundwater recharge accounts for a lower fraction of total runoff, which makes these regions particularly vulnerable to seasonal and inter-annual precipitation variability and water pollution. Average per-capita renewable groundwater resources of countries vary between 8m³/(capita yr) for Egypt to more than 1 millionm³/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091m³/(capita yr). Regarding the uncertainty of estimated groundwater resources due to the two precipitation data sets, deviation from the mean is 1.1% for the global value, and less than 1% for 50 out of the 165 countries considered, between 1 and 5% for 62, between 5 and 20% for 43 and between 20 and 80% for 10 countries. Deviations at the grid scale can be much larger, ranging between 0 and 186 mm/yr. [ABSTRACT FROM AUTHOR]

Long-term average groundwater recharge, which is equivalent to renewable groundwater resources, is the major limiting factor for the sustainable use of groundwater. Compared to surface water resources, groundwater resources are more protected from pollution, and their use is less restricted by seasonal and inter-annual flow variations. To support water management in a globalized world, it is necessary to estimate groundwater recharge at the global scale. Here, we present a best estimate of global-scale long-term average diffuse groundwater recharge (i.e. renewable groundwater resources) that has been calculated by the most recent version of the WaterGAP Global Hydrology Model WGHM (spatial resolution of 0.5° by 0.5°, daily time steps). The estimate was obtained using two state-of-the art global data sets of gridded observed precipitation that we corrected for measurement errors, which also allowed to quantify the uncertainty due to these equally uncertain data sets. The standard WGHM groundwater recharge algorithm was modified for semi-arid and arid regions, based on independent estimates of diffuse groundwater recharge, which lead to an unbiased estimation of groundwater recharge in these regions. WGHM was tuned against observed long-term average river discharge at 1235 gauging stations by adjusting, individually for each basin, the partitioning of precipitation into evapotranspiration and total runoff. We estimate that global groundwater recharge was 12 666 km3/yr for the climate nor20 mal 1961-1990, i.e. 32% of total renewable water resources. In semi-arid and arid regions, mountainous regions, permafrost regions and in the Asian Monsoon region, groundwater recharge accounts for a lower fraction of total runoff, which makes these regions particularly vulnerable to seasonal and inter-annual precipitation variability and water pollution. Average per-capita renewable groundwater resources of countries vary between 8m3/(capita yr) for Egypt to more than 1 million m3/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091m3/(capita yr). Regarding the uncertainty of estimated groundwater resources due to the two precipitation data sets, deviation from the mean is less than 1% for 50 out of the 165 countries considered, between 1 and 5% for 62, between 5 and 20% for 43 and between 20 and 80% for 10 countries. Deviations at the grid scale can be much larger, ranging between 0 and 186 mm/yr. [ABSTRACT FROM AUTHOR]

This paper investigates the value of observed river discharge data for global-scale hydrological modeling of a number of flow characteristics that are required for assessing water resources, flood risk and habitat alteration of aqueous ecosystems. An improved version of WGHM (WaterGAP Global Hydrology Model) was tuned in a way that simulated and observed long-term average river discharges at each station become equal, using either the 724-station dataset (V1) against which former model versions were tuned or a new dataset (V2) of 1235 stations and often longer time series. WGHM is tuned by adjusting one model parameter () that affects runoff generation from land areas, and, where necessary, by applying one or two correction factors, which correct the total runoff in a sub-basin (areal correction factor) or the discharge at the station (station correction factor). The study results are as follows. (1) Comparing V2 to V1, the global land area covered by tuning basins increases by 5%, while the area where the model can be tuned by only adjusting increases by 8% (546 vs. 384 stations). However, the area where a station correction factor (and not only an areal correction factor) has to be applied more than doubles (389 vs. 93 basins), which is a strong drawback as use of a station correction factor makes discharge discontinuous at the gauge and inconsistent with runoff in the basin. (2) The value of additional discharge information for representing the spatial distribution of long-term average discharge (and thus 20 renewable water resources) with WGHM is high, particularly for river basins outside of the V1 tuning area and for basins where the average sub-basin area has decreased by at least 50% in V2 as compared to V1. For these basins, simulated long-term average discharge would differ from the observed one by a factor of, on average, 1.8 and 1.3, respectively, if the additional discharge information were not used for tuning. The value tends to be higher in semi-arid and snow-dominated regions where hydrological models are less reliable than in humid areas. The deviation of the other simulated flow characteristics (e.g. low flow, inter-annual variability and seasonality) from the observed values also decreases significantly, but this is mainly due to the better representation of average discharge but not of variability. (3) The optimal sub-basin size for tuning depends on the modeling purpose. On the one hand, small basins between 9000 and 20 000km2 show a much stronger improvement in model performance due to tuning than the larger basins, which is related to the lower model performance (with and without tuning), with basins over 60 000 km2 performing best. On the other hand, tuning of small basins decreases model consistency, as almost half of them require a station correction factor. [ABSTRACT FROM AUTHOR]

Since 2002, the GRACE satellite mission provides estimates of the Earth's dynamic gravity field with unprecedented accuracy. Differences between monthly gravity fields contain a clear hydrological signal due to continental water storage changes. In order to evaluate GRACE results, the state-of-the-art WaterGAP Global Hydrological Model (WGHM) is applied to calculate terrestrial water storage changes on a global scale. WGHM is driven by different climate data sets to analyse especially the influence of different precipitation data on calculated water storage. The data sets used are the CRU TS 2.1 climate data set, the GPCC Full Data Product for precipitation and data from the ECMWF integrated forecast system. A simple approach for precipitation correction is introduced. WGHM results are then compared with GRACE data. The use of different precipitation data sets leads to considerable differences in computed water storage change for a large number of river basins. Comparing model results with GRACE observations shows a good spatial correlation and also a good agreement in phase. However, seasonal variations of water storage as derived from GRACE tend to be significantly larger than those computed by WGHM, regardless of which climate data set is used. [ABSTRACT FROM AUTHOR]

A new version of a digital global map of irrigation areas was developed by combining irrigation statistics for 10 825 sub-national statistical units and geo-spatial information on the location and extent of irrigation schemes. The map shows the percentage of each 5 arc minute by 5 arc minute cell that was equipped for irrigation around the year 2000. It is thus an important data set for global studies related to water and land use. This paper describes the data set and the mapping methodology and gives, for the first time, an estimate of the map quality at the scale of countries, world regions and the globe. Two indicators of map quality were developed for this purpose, and the map was compared to irrigated areas as derived from two remote sensing based global land cover inventories. We plan to further improve that data set; therefore comments, information and data that might contribute to that effort are highly welcome. [ABSTRACT FROM AUTHOR]

Water scarcity is rapidly increasing in many regions. In a novel, multi-model assessment, we examine how human interventions (HI: land use and land cover change, man-made reservoirs and human water use) affected monthly river water availability and water scarcity over the period 1971-2010. Here we show that HI drastically change the critical dimensions of water scarcity, aggravating water scarcity for 8.8% (7.4-16.5%) of the global population but alleviating it for another 8.3% (6.4-15.8%). Positive impacts of HI mostly occur upstream, whereas HI aggravate water scarcity downstream; HI cause water scarcity to travel downstream. Attribution of water scarcity changes to HI components is complex and varies among the hydrological models. Seasonal variation in impacts and dominant HI components is also substantial. A thorough consideration of the spatially and temporally varying interactions among HI components and of uncertainties is therefore crucial for the success of water scarcity adaptation by HI. [ABSTRACT FROM AUTHOR]

A correction to the article "Small-scale water reuse for urban agriculture in Namibia: Modeling water flows and productivity" that was published in the previous issue is presented.