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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 8 m3/(capita yr) for Egypt to more than 1 million m3/(capita yr) for the Falkland Islands, the global average in the year 2000 being 2091 m3/(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.
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 15 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 25 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.
Within the framework of the Transboundary Waters Assessment Programme (TWAP), initiated by the Global Environment Facility (GEF), we contributed to a comprehensive baseline assessment of transboundary aquifers (TBAs) by quantifying different groundwater indicators using the global water resources and water use model WaterGAP 2.2. All indicators were computed under current (2010) and projected conditions in 2030 and 2050 for 91 selected TBAs larger than 20,000 km2 and for each nation’s share of the TBAs (TBA-CU: country unit). TBA outlines were provided by the International Groundwater Resources Assessment Centre (IGRAC). The set of indicators comprises groundwater recharge, groundwater depletion, per-capita groundwater recharge, dependency on groundwater, population density, and groundwater development stress (groundwater withdrawals to groundwater recharge). Only the latter four indicators were projected to 2030 and 2050. Current-state indicators were quantified using the Watch Forcing Data climate dataset, while projections were based on five climate scenarios that were computed by five global climate models for the high-emissions scenario RCP 8.5. Water use projections were based on the Shared Socio-economic Pathway SSP2 developed within ISI-MIP. Furthermore, two scenarios of future irrigated areas were explored. For individual water use sectors, the fraction of groundwater abstraction was assumed to remain at the current level.
According to our assessment, aquifers with the highest current groundwater depletion rates worldwide are not transboundary. Exceptions are the Neogene Aquifer System (Syria) with 53 mm/yr between 2000 and 2009 and the Indus River Plain aquifer (India) with 28 mm/yr. For current conditions, we identified 20 out of 258 TBA-CUs suffering from medium to very high groundwater development stress, which are located in the Middle East and North Africa region, in South Asia, China, and the USA. Considering projections, ensemble means of per-cent changes or percent point changes to current conditions were determined. Per-capita groundwater recharge is projected to decrease in 80-90% of all TBA-CUs until 2030/2050. Due to the strongly varying projections of the global climate models, we applied a worst-case scenario approach to define future hotspots of groundwater development stress, taking into account the strongest computed increase until either 2030 or 2050 among all scenarios and individual GCMs. Based on this approach, the number of TBA-CUs under at least medium groundwater development stress increases from 20 to 58, comprising all hotspots under current conditions. New hotspots are projected to develop mainly in Sub-Saharan Africa, China, and Mexico.
Groundwater recharge is the major limiting factor for the sustainable use of groundwater. To support water management in a globalized world, it is necessary to estimate, in a spatially resolved way, global-scale groundwater recharge. In this report, improved model estimates of diffuse groundwater recharge at the global-scale, with a spatial resolution of 0.5° by 0.5°, are presented. They are based on calculations of the global hydrological model WGHM (WaterGAP Global Hydrology Model) which, for semi-arid and arid areas of the globe, was tuned against independent point estimates of diffuse groundwater recharge. This has led to a decrease of estimated groundwater recharge under semi-arid and arid conditions as compared to the model results before tuning, and the new estimates are more similar to country level data on groundwater recharge. Using the improved model, the impact of climate change on groundwater recharge was simulated, applying two greenhouse gas emissions scenarios as interpreted by two different climate models.
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°×0.5°), 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.
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.
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 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.
This study presents a global scale analysis of cropping intensity, crop duration and fallow land extent computed by using the global dataset on monthly irrigated and rainfed crop areas MIRCA2000. MIRCA2000 was mainly derived from census data and crop calendars from literature. Global cropland extent was 16 million km2 around the year 2000 of which 4.4 million km2 (28%) was fallow, resulting in an average cropping intensity of 0.82 for total cropland extent and of 1.13 when excluding fallow land. The lowest cropping intensities related to total cropland extent were found for Southern Africa (0.45), Central America (0.49) and Middle Africa (0.54), while highest cropping intensities were computed for Eastern Asia (1.04) and Southern Asia (1.0). In remote or arid regions where shifting cultivation is practiced, fallow periods last 3–10 years or even longer. In contrast, crops are harvested two or more times per year in highly populated, often irrigated tropical or subtropical lowlands where multi-cropping systems are common. This indicates that intensification of agricultural land use is a strategy that may be able to significantly improve global food security. There exist large uncertainties regarding extent of cropland, harvested crop area and therefore cropping intensity at larger scales. Satellite imagery and remote sensing techniques provide opportunities for decreasing these uncertainties and to improve the MIRCA2000 inventory.
Global modelling of continental water storage changes : sensitivity to different climate data sets
(2007)
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.
A data set of monthly growing areas of 26 irrigated crops (MGAG-I) and related crop calendars (CC-I) was compiled for 402 spatial entities. The selection of the crops consisted of all major food crops including regionally important ones (wheat, rice, maize, barley, rye, millet, sorghum, soybeans, sunflower, potatoes, cassava, sugar cane, sugar beets, oil palm, rapeseed/canola, groundnuts/peanuts, pulses, citrus, date palm, grapes/vine, cocoa, coffee), major water-consuming crops (cotton), and unspecified other crops (other perennial crops, other annual crops, managed grassland). The data set refers to the time period 1998-2002 and has a spatial resolution of 5 arc minutes by 5 arc minutes which is 8 km by 8 km at the equator. This is the first time that a data set of cell-specific irrigated growing areas of irrigated crops with this spatial resolution was created. The data set is consistent to the irrigated area and water use statistics of the AQUASTAT programme of the Food and Agriculture Organization of the United Nations (FAO) (http://www.fao.org/ag/agl/aglw/aquastat/main/index.stm) and the Global Map of Irrigation Areas (GMIA) (http://www.fao.org/ag/agl/aglw/aquastat/irrigationmap/index.stm). At the cell-level it was tried to maximise consistency to the cropland extent and cropland harvested area from the Department of Geography and Earth System Science Program of the McGill University at Montreal, Quebec, Canada and the Center for Sustainability and the Global Environment (SAGE) of the University of Wisconsin at Madison, USA (http://www.geog.mcgill.ca/~nramankutty/ Datasets/Datasets.html and http://geomatics.geog.mcgill.ca/~navin/pub/Data/175crops2000/). The consistency between the grid product and the input data was quantified. MGAG-I and CC-I are fully consistent to each other on entity level. For input data other than CC-I, the consistency of MGAG-I on cell level was calculated. The consistency of MGAG-I with respect to the area equipped for irrigation (AEI) of GMIA and to the cropland extent of SAGE was characterised by the sum of the cell-specific maximum difference between the MGAG-I monthly total irrigated area and the reference area when the latter was exceeded in the grid cell. The consistency of the harvested area contained in MGAG-I with respect to SAGE harvested area was characterised by the crop-specific sum of the cell-specific difference between MGAG-I harvested area and the SAGE harvested area when the latter was exceeded in the grid cell. In all three cases, the sums are the excess areas that should not have been distributed under the assumption that the input data were correct. Globally, this cell-level excess of MGAG-I as compared to AEI is 331,304 ha or only about 0.12 % of the global AEI of 278.9 Mha found in the original grid. The respective cell-level excess of MGAG-I as compared to the SAGE cropland extent is 32.2 Mha, corresponding to about 2.2 % of the total cropland area. The respective cell-level excess of MGAG-I as compared to the SAGE harvested area is 27 % of the irrigated harvested area, or 11.5 % of the AEI. In a further step that will be published later also rainfed areas were compiled in order to form the Global data set of monthly irrigated and rainfed crop areas around the year 2000 (MIRCA2000). The data set can be used for global and continental-scale studies on food security and water use. In the future, it will be improved, e.g. with a better spatial resolution of crop calendars and an improved crop distribution algorithm. The MIRCA2000 data set, its full documentation together with future updates will be freely available through the following long-term internet site: http://www.geo.uni-frankfurt.de/ipg/ag/dl/forschung/MIRCA/index.html. The research presented here was funded by the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) within the framework of the research project entitled "Consistent assessment of global green, blue and virtual water fluxes in the context of food production: regional stresses and worldwide teleconnections". The authors thank Navin Ramankutty and Chad Monfreda for making available the current SAGE datasets on cropland extent (Ramankutty et al., 2008) and harvested area (Monfreda et al., 2008) prior to their publication.
A new version of a digital global map of irrigation areas was developed by combining irrigation statistics for 10825 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.
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.
In global hydrological models, groundwater (GW) is typically represented by a bucket-like linear groundwater reservoir. Reservoir models, however, (1) can only simulate GW discharge to surface water (SW) bodies but not recharge from SW to GW, (2) provide no information on the location of the GW table, and (3) assume that there is no GW flow among grid cells. This may lead, for example, to an underestimation of groundwater resources in semiarid areas where GW is often replenished by SW or to an underestimation of evapotranspiration where the GW table is close to the land surface. To overcome these limitations, it is necessary to replace the reservoir model in global hydrological models with a hydraulic head gradient-based GW flow model.
We present G3M, a new global gradient-based GW model with a spatial resolution of 5′ (arcminutes), which is to be integrated into the 0.5∘ WaterGAP Global Hydrology Model (WGHM). The newly developed model framework enables in-memory coupling to WGHM while keeping overall runtime relatively low, which allows sensitivity analyses, calibration, and data assimilation. This paper presents the G3M concept and model design decisions that are specific to the large grid size required for a global-scale model. Model results under steady-state naturalized conditions, i.e., neglecting GW abstractions, are shown. Simulated hydraulic heads show better agreement to observations around the world compared to the model output of de Graaf et al. (2015). Locations of simulated SW recharge to GW are found, as is expected, in dry and mountainous regions but areal extent of SW recharge may be underestimated. Globally, GW discharge to rivers is by far the dominant flow component such that lateral GW flows only become a large fraction of total diffuse and focused recharge in the case of losing rivers, some mountainous areas, and some areas with very low GW recharge. A strong sensitivity of simulated hydraulic heads to the spatial resolution of the model and the related choice of the water table elevation of surface water bodies was found. We suggest to investigate how global-scale groundwater modeling at 5′ spatial resolution can benefit from more highly resolved land surface elevation data.
To quantify water flows between groundwater (GW) and surface water (SW) as well as the impact of Abstract. To quantify water flows between groundwater (GW) and surface water (SW) as well as the impact of capillary rise on evapotranspiration by global hydrological models (GHMs), it is necessary to replace the bucket-like linear GW reservoir model typical for hydrological models with a fully integrated gradient-based GW flow model. Linear reservoir models can only simulate GW discharge to SW bodies, provide no information on the location of the GW table and assume that there is no GW flow among grid cells. A gradient-based GW model simulates not only GW storage but also hydraulic head, which together with information on SW table elevation enables the quantification of water flows from GW to SW and vice versa. In addition, hydraulic heads are the basis for calculating lateral GW flow among grid cells and capillary rise.
G³M is a new global gradient-based GW model with a spatial resolution of 5' that will replace the current linear GW reservoir in the 0.5° WaterGAP Global Hydrology Model (WGHM). The newly developed model framework enables inmemory coupling to WGHM while keeping overall runtime relatively low, allowing sensitivity analyses and data assimilation. This paper presents the G³M concept and specific model design decisions together with results under steady-state naturalized conditions, i.e. neglecting GW abstractions. Cell-specific conductances of river beds, which govern GW-SW interaction, were determined based on the 30'' steady-state water table computed by Fan et al. (2013). Together with an appropriate choice for the effective elevation of the SW table within each grid cell, this enables a reasonable simulation of drainage from GW to SW such that, in contrast to the GW model of de Graaf et al. (2015, 2017), no additional drainage based on externally provided values for GW storage above the floodplain is required in G³M. Comparison of simulated hydraulic heads to observations around the world shows better agreement than de Graaf et al. (2015). In addition, G³M output is compared to the output of two established macro-scale models for the Central Valley, California, and the continental United States, respectively. As expected, depth to GW table is highest in mountainous and lowest in flat regions. A first analysis of losing and gaining rivers and lakes/wetlands indicates that GW discharge to rivers is by far the dominant flow, draining diffuse GW recharge, such that lateral flows only become a large fraction of total diffuse and focused recharge in case of losing rivers and some areas with very low GW recharge. G³M does not represent losing rivers in some dry regions. This study presents the first steps towards replacing the linear GW reservoir model in a GHM while improving on recent efforts, demonstrating the feasibility of the approach and the robustness of the newly developed framework.
Assessment of ecologically relevant hydrological change in China due to water use and reservoirs
(2008)
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.
Analyzing the impact of streamflow drought on hydroelectricity production: a global-scale study
(2021)
Electricity production by hydropower is negatively affected by drought. To understand and quantify risks of less than normal streamflow for hydroelectricity production (HP) at the global scale, we developed an HP model that simulates time series of monthly HP worldwide and thus enables analyzing the impact of drought on HP. The HP model is based on a new global hydropower database (GHD), containing 8,716 geo-localized plant records, and on monthly streamflow values computed by the global hydrological model WaterGAP with a spatial resolution of 0.5°. The GHD includes 44 attributes and covers 91.8% of the globally installed capacity. The HP model can reproduce HP trends, seasonality, and interannual variability that was caused by both (de)commissioning of hydropower plants and hydrological variability. It can also simulate streamflow drought and its impact on HP reasonably well. Global risk maps of HP reduction were generated for both 0.5° grid cells and countries, revealing that 67 out of the 134 countries with hydropower suffer, in 1 out of 10 years, from a reduction of more than 20% of mean annual HP and 18 countries from a reduction of more than 40%. The developed HP model enables advanced assessments of drought impacts on hydroelectricity at national to international levels.
Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future.
Wetlands such as bogs, swamps, or freshwater marshes are hotspots of biodiversity. For 5.1 million km2 of inland wetlands, the dynamics of area and water storage, which strongly impact biodiversity and ecosystem services, were simulated using the global hydrological model WaterGAP. For the first time, the impacts of both human water use and man‐made reservoirs (WUR) and future climate change (CC) on wetlands around the globe were quantified. WUR impacts are concentrated in arid/semiarid regions, where WUR decreased mean wetland water storage by more than 5% on 8.2% of the mean wetland area during 1986–2005 (Am), with highest decreases in groundwater depletion area. Using output of three climate models, CC impacts on wetlands were quantified, distinguishing unavoidable impacts [i.e., at 2 °C global warming (GW)] from avoidable impacts (difference between 3 °C and 2 °C impacts). Even unavoidable CC impacts are projected to be much larger than WUR impacts, also in arid/semiarid regions. On most wetland area with reliable estimates, avoidable CC impacts are more than twice as large as unavoidable impacts. In case of 2 °C GW, half of Am is estimated to be unaffected by mean storage changes of more than 5%, but only one third in case of 3 °C GW. Temporal variability of water storage will increase for most wetlands. Wetlands in dry regions will be affected the most, particularly by water storage decreases in the dry season. Different from wealthier countries, low‐income countries will dominantly suffer from a decrease in wetland water storage due to CC.