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Cited by 217Hydrology and Watershed Management StudiesWater resources management and optimizationGeophysics and Gravity Measurements

High‐resolution modeling of human and climate impacts on global water resources

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Wada, Yoshihide, de Graaf, Inge E. M., van Beek, Ludovicus P. H.·2016·Journal of Advances in Modeling Earth Systems
DOI 10.1002/2015ms000618
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Abstract

A number of global hydrological models [GHMs) have been developed in recent decades in order to understand the impacts of climate variability and human activities on water resources availability. The spatial resolution of GHMs is mostly constrained at a 0.5° by 0.5° grid [∼50km by ∼50km at the equator). However, for many of the water‐related problems facing society, the current spatial scale of GHMs is insufficient to provide locally relevant information. Here using the PCR‐GLOBWB model we present for the first time an analysis of human and climate impacts on global water resources at a 0.1° by 0.1° grid [∼10km by ∼10km at the equator) in order to depict more precisely regional variability in water availability and use. Most of the model input data (topography, vegetation, soil properties, routing, human water use) have been parameterized at a 0.1° global grid and feature a distinctively higher resolution. Distinct from many other GHMs, PCR‐GLOBWB includes groundwater representation and simulates groundwater heads and lateral groundwater flows based on MODFLOW with existing geohydrological information. This study shows that global hydrological simulations at higher spatial resolutions are feasible for multi‐decadal to century periods.

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  • These regions are mainly located in the midwestern and western CONUS, where high evaporation conditions and numerous dams coincide with complex water use processes that current models cannot simulate well.

    “These regions are mainly located in the midwestern and western CONUS, where high evaporation conditions (Heidari et al., 2020) and numerous dams (Bellmore et al., 2017) coincide with complex water use processes (Wada et al., 2016) that current models cannot simulate well.”

    From Ensembling differentiable process-based and data-driven models with diverse meteorological forcing datasets to advance streamflow simulation (2025) · cites this paper as Wada et al., 2016

    Section 5.1 says the authors’ model omits artificial water diversions and may overestimate the effect of water consumption on streamflow in parts of the United States. This supports difficulty modeling some water-use processes, but not the broader assertion that current models cannot simulate complex water use well across the midwestern and western CONUS. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Research works printed but not linked: 81

  1. Alcamo, J., M. Fl€ orke, and M. M€ arker (2007), Future long-term changes in global water resources driven by socio-economic and climatic changes, Hydrol. Sci. J., 52, 247-275, doi:10.1623/hysj.52.2.247. · DOI
  2. Arnell, N. W. (1999), Climate change and global water resources, Global Environ. Change, 9, 31-49, doi:10.1016/S0959-3780(99)00017-5. · DOI
  3. Arnell, N. W. (2004), Climate change and global water resources: SRES emissions and socio-economic scenarios, Global Environ. Change, 14, 31-52, doi:10.1016/j.gloenvcha.2003.10.006. · DOI
  4. Bierkens, M. F. P., et al. (2015), Hyper-resolution global hydrological modelling: What is next?, Hydrol. Processes, 29, 310-320, doi:10.1002/ hyp.10391. · DOI
  5. Bondeau, A., P. C. Smith, S. Zaehle, S. Schaphoff, W. Lucht, W. Cramer, D. Gerten, M. Reichstein, and B. Smith (2007), Modelling the role of agriculture for the 20th century, Global Change Biol., 13, 679-706, doi:10.1111/j.1365-2486.2006.01305.x. · DOI
  6. Dai, A. (2013), Increasing drought under global warming: Reconciling observed and model-simulated changes, Nat. Clim. Change, 3, 52-58, doi:10.1038/nclimate1633. · DOI · Paper page
  7. Dankers, R., et al. (2014), First look at changes in flood hazard in the Inter-Sectoral Impact Model Intercomparison Project ensemble, Proc. Natl. Acad. Sci. U. S. A., 111(9), 3257-3261, doi:10.1073/pnas.1302078110. · DOI
  8. Dee, D. P., et al. (2011), The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. R. Meteorol. Soc., 137, 553-597, doi:10.1002/qj.828. · DOI · Paper page
  9. de Graaf, I. E. M., L. P. H. van Beek, Y. Wada, and M. F. P. Bierkens (2014), Dynamic attribution of global water demand to surface water and groundwater resources: Effects of abstractions and return flows on river discharges, Adv. Water Resour., 64, 21-33, doi:10.1016/ j.advwatres.2013.12.002. · DOI
  10. de Graaf, I. E. M., E. H. Sutanudjaja, L. P. H. van Beek, and M. F. P. Bierkens (2015), A high-resolution global-scale groundwater model, Hydrol. Earth Syst. Sci., 19, 823-837, doi:10.5194/hess-19-823-2015. · DOI
  11. oll, P., and S. Siebert (2002), Global modeling of irrigation water requirements, Water Resour. Res., 38(4), 1037, doi:10.1029/ 2001WR000355. · DOI
  12. D€ oll, P., F. Kaspar, and B. Lehner (2003), A global hydrological model for deriving water availability indicators: Model tuning and validation, J. Hydrol., 270, 105-134, doi:10.1016/S0022-1694(02)00283-4. · DOI · Paper page
  13. D€ oll, P., H. Hoffmann-Dobrev, F. T. Portmann, S. Siebert, A. Eicker, M. Rodell, and G. Strassberg (2012), Impact of water withdrawals from groundwater and surface water on continental water storage variations, J. Geodyn., 59-60, doi:10.1016/j.jog.2011.05.001. · DOI
  14. Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley (2003), Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res., 108(D22), 8851, doi:10.1029/2002JD003296. · DOI
  15. Elliott, J., et al. (2014), Constraints and potentials of future irrigation water availability on agricultural production under climate change, Proc. Natl. Acad. Sci. U. S. A., 111(9), 3239-3244, doi:10.1073/pnas.1222474110. · DOI
  16. Falkenmark, M., J. W. Kijne, B. Taron, G. Murdoch, M. V. K. Sivakumar, and E. Craswell (1997), Meeting water requirements of an expanding world population [and discussion], Philos. Trans. R. Soc. London B, 352, 929-936, doi:10.1098/rstb.1997.0072. · DOI
  17. Famiglietti, J. S., M. Lo, S. L. Ho, J. Bethune, K. J. Anderson, T. H. Syed, S. C. Swenson, C. R. de Linage, and M. Rodell (2011), Satellites measure recent rates of groundwater depletion in California's Central Valley, Geophys. Res. Lett., 38, L03403, doi:10.1029/2010GL046442. · DOI
  18. Fan, Y., H. Li, and G. Miguez-Macho (2013), Global patterns of groundwater table depth, Science, 339, 940-943, doi:10.1126/ science.1229881. · DOI
  19. Feyen, L., and R. Dankers (2009), Impact of global warming on streamflow drought in Europe, J. Geophys. Res., 114, D17116, doi:10.1029/ 2008JD011438. Food and Agriculture Organization of the United Nations (FAO) (2003), Digital Soil Map of the World, Version 3.6, Rome. [Available at http:// www.fao.org/nr/land/soils/digital-soil-map-of-the-world.] · DOI
  20. Gain, A. K., and Y. Wada (2014), Assessment of future water scarcity at different spatial and temporal scales of the Brahmaputra River Basin, Water Resour. Manage., 28, 999-1012, doi:10.1007/s11269-014-0530-5. · DOI
  21. Gerten, D., S. Schaphoff, and W. Lucht (2007), Potential future changes in water limitation of the terrestrial biosphere, Clim. Change, 80, 277-299, doi:10.1007/s10584-006-9104-8. · DOI
  22. Gleeson, T., and Y. Wada (2013), Assessing regional groundwater stress for nations using multiple data sources with the groundwater foot- print, Environ. Res. Lett., 8, 044010, doi:10.1088/1748-9326/8/4/044010. · DOI
  23. Gleeson, T., L. Smith, N. Moosdorf, J. Hartmann, H. H. D€ urr, A. H. Manning, L. P. H. van Beek, and A. M. Jellinek (2011), Mapping permeability over the surface of the Earth, Geophys. Res. Lett., 38, L02401, doi:10.1029/2010GL045565. · DOI
  24. Gleeson, T., Y. Wada, M. F. P. Bierkens, and L. P. H. van Beek (2012), Water balance of global aquifers revealed by groundwater footprint, Nature, 488, 197-200, doi:10.1038/nature11295. · DOI · Paper page
  25. Gleeson, T., N. Moosdorf, J. Hartmann, and L. P. H. van Beek (2014), A glimpse beneath earth's surface: GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity, Geophys. Res. Lett., 41, 3891-3898, doi:10.1002/2014GL059856. · DOI
  26. Gleick, P. H. (2003), Global freshwater resources: Soft-path solutions for the 21st century, Science, 302, 1524-1528, doi:10.1126/ science.1089967. · DOI
  27. Gleick, P. H. (2010), Roadmap for sustainable water resources in southwestern North America, Proc. Natl. Acad. Sci. U. S. A., 107, 21,300- 21,305, doi:10.1073/pnas.1005473107. · DOI
  28. Haddeland, I., et al. (2014), Global water resources affected by human interventions and climate change, Proc. Natl. Acad. Sci. U. S. A., 111(9), 3251-3256, doi:10.1073/pnas.1302078110. · DOI
  29. Hagemann, S., and L. D. Gates (2003), Improving a sub-grid runoff parameterization scheme for climate models by the use of high resolu- tion data derived from satellite observations, Clim. Dyn., 21, 349-359, doi:10.1007/s00382-003-0349-x. · DOI
  30. Hanasaki, N., S. Kanae, and T. Oki (2006), A reservoir operation scheme for global river routing models, J. Hydrol., 327, 22-41, doi:10.1016/ j.jhydrol.2005.11.011. · DOI
  31. Hanasaki, N., S. Kanae, T. Oki, K. Masuda, K. Motoya, N. Shirakawa, Y. Shen, and K. Tanaka (2008a), An integrated model for the assessment of global water resources-Part 1: Model description and input meteorological forcing, Hydrol. Earth Syst. Sci., 12, 1007-1025, doi: 10.5194/hess-12-1007-2008. · DOI
  32. Hanasaki, N., S. Kanae, T. Oki, K. Masuda, K. Motoya, N. Shirakawa, Y. Shen, and K. Tanaka (2008b), An integrated model for the assessment of global water resources-Part 2: Applications and assessments, Hydrol. Earth Syst. Sci., 12, 1027-1037, doi:10.5194/hess-12-1027-2008. · DOI
  33. Hartmann, J., and N. Moosdorf (2012), The new global lithological map database GLiM: A representation of rock properties at the Earth sur- face, Geochem. Geophys. Geosyst., 13, Q12004, doi:10.1029/2012GC004370. · DOI
  34. Hoekstra, A. Y., M. M. Mekonnen, A. K. Chapagain, R. E. Mathews, and B. D. Richter (2012), Global monthly water scarcity: Blue water foot- prints versus blue water availability, PLoS One, 7, e32688, doi:10.1371/journal.pone.0032688. · DOI
  35. Jung, M., et al. (2010), Recent decline in the global land evapotranspiration trend due to limited moisture supply, Nature, 467, 951-954, doi:10.1038/nature09396. · DOI
  36. Konikow, L. F. (2011), Contribution of global groundwater depletion since 1900 to sea-level rise, Geophys. Res. Lett., 38, L17401, doi: 10.1029/2011GL048604. · DOI
  37. Konikow, L. F., and E. Kendy (2005), Groundwater depletion: A global problem, Hydrogeol. J., 13, 317-320, doi:10.1007/s10040-004-0411-8. · DOI
  38. Kummu, M., P. J. Ward, H. de Moel, and O. Varis (2010), Is physical water scarcity a new phenomenon? Global assessment of water shortage over the last two millennia, Environ. Res. Lett., 5, 034006, doi:10.1088/1748-9326/5/3/034006. · DOI
  39. Landerer F. W., and S. C. Swenson (2012), Accuracy of scaled GRACE terrestrial water storage estimates. Water Resour. Res., 48, W04531, doi: 10.1029/2011WR011453. · DOI
  40. Lehner, B., et al. (2011), High-resolution mapping of the world's reservoirs and dams for sustainable river-flow management, Frontiers Ecol. Environ., 9, 494-502, doi:10.1890/100125. · DOI · Paper page
  41. Liu, J., and H. Yang (2010), Spatially explicit assessment of global consumptive water uses in cropland: Green and blue water, J. Hydrol., 384, 187-297, doi:10.1016/j.jhydrol.2009.11.024. · DOI
  42. Mitchell, T. D., and P. D. Jones (2005), An improved method of constructing a database of monthly climate observations and associated high-resolution grids, Int. J. Clim., 25, 693-712, doi:10.1002/joc.1181. · DOI
  43. Pokhrel, Y., N. Hanasaki, S. Koirala, J. Cho, P. J.-F. Yeh, H. Kim, S. Kanae, and T. Oki (2012), Incorporating anthropogenic water regulation modules into a land surface model, J. Hydrometeorol., 13, 255-269, doi:10.1175/JHM-D-11-013. · DOI
  44. Portmann, F. T., S. Siebert, and P. D€ oll (2010), MIRCA2000-Global monthly irrigated and rainfed crop areas around the year 2000: A new high-resolution data set for agricultural and hydrological modeling, Global Biogeochem. Cycles, 24, GB1011, doi:10.1029/2008GB003435. · DOI
  45. Prudhomme, C., et al. (2014), Drought in the 21st century: A multi-model ensemble experiment to assess global change, quantify uncer- tainty and identify 'hotspots', change, Proc. Natl. Acad. Sci. U. S. A., 111(9), 3262-3267, doi:10.1073/pnas.1222473110. · DOI
  46. Rodell, M., I. Velicogna, and J. S. Famiglietti (2009), Satellite-based estimates of groundwater depletion in India, Nature, 460, 999-1002, doi: 10.1038/nature08238. · DOI
  47. Rost, S., D. Gerten, A. Bondeau, W. Luncht, J. Rohwer, and S. Schaphoff (2008), Agricultural green and blue water consumption and its influ- ence on the global water system, Water Resour. Res., 44, W09405, doi:10.1029/2007WR006331. · DOI
  48. Scanlon, B. R., I. Jolly, M. Sophocleous, and L. Zhang (2007), Global impacts of conversions from natural to agricultural ecosystems on water resources: Quantity versus quality, Water Resour. Res., 43, W03437, doi:10.1029/2006WR005486. · DOI · Paper page
  49. Scanlon, B. R., C. C. Faunt, L. Longuevergne, R. C. Reedy, W. M. Alley, V. L. McGuire, and P. B. McMahon (2012a), Groundwater depletion and sustainability of irrigation in the U.S. High Plains and Central Valley, Proc. Natl. Acad. Sci. U. S. A., 109, 9320-9325, doi:10.1073/ pnas.1200311109. · DOI
  50. Scanlon, B. R., L. Longuevergne, and D. Long (2012b), Ground referencing GRACE satellite estimates of groundwater storage changes in the California Central Valley, USA, Water Resour. Res., 48, W04520, doi:10.1029/2011WR011312. · DOI
  51. Schewe, J., et al. (2014), Multi-model assessment of water scarcity under climate change, Proc. Natl. Acad. Sci. U. S. A., 111(9), 3245-3250, doi:10.1073/pnas.1222460110. · DOI
  52. Seager, R. (2007), The turn of the century North American Drought: Global context, dynamics, and past analogs, J. Clim., 20, 5527-5552, doi:10.1175/2007JCLI1529. · DOI
  53. Sheffield, J., and E. F. Wood (2007), Characteristics of global and regional drought, 1950-2000: Analysis of soil moisture data from off-line simulation of the terrestrial hydrologic cycle, J. Geophys. Res., 112, D17115, doi:10.1029/2006JD008288. · DOI
  54. Shiklomanov, I. A. (2000a), World water resources and water use: Present assessment and outlook for 2025, in World Water Scenarios Analy- ses, edited by F. R. Rijsberman, pp. 160-203, Earthscan, London, U. K.
  55. Shiklomanov, I. A. (2000b), Appraisal and assessment of world water resources, Water Int., 25, 11-32, doi:10.1080/02508060008686794. · DOI
  56. Siebert, S., and P. D€ oll (2010), Quantifying blue and green virtual water contents in global crop production as well as potential production losses without irrigation, J. Hydrol., 384, 198-217, doi:10.1016/j.jhydrol.2009.07.031. · DOI · Paper page
  57. Siebert, S., J. Burke, J. M. Faures, K. Frenken, J. Hoogeveen, P. D€ oll, and F. T. Portmann (2010), Groundwater use for irrigation -a global inventory, Hydrol. Earth Syst. Sci., 14, 1863-1880, doi:10.5194/hess-14-1863-2010. · DOI
  58. Sutanudjaja, E. H., L. P. H. van Beek, S. M. de Jong, F. C. van Geer, and M. F. P. Bierkens (2014), Calibrating a large-extent high-resolution coupled groundwater-land surface model using soil moisture and discharge data, Water Resour. Res., 50, 687-705, doi:10.1002/2013WR013807. · DOI
  59. Tang, Q., T. Oki, S. Kanae, and H. Hu (2007), The inuence of precipitation variability and partial irrigation within grid cells on a hydrological simulation, J. Hydrometeorol., 8, 499-512, doi:10.1175/JHM589. · DOI
  60. Taylor, R. G., et al. (2013), Groundwater and climate change, Nat. Clim. Change, 3, 322-329, doi:10.1038/nclimate1744. · DOI
  61. Tiwari, V.M., J. Wahr, and S. Swenson (2009), Dwindling groundwater resources in northern India, from satellite gravity observations, Geo- phys. Res. Lett., 36, L18401, doi:10.1029/2009GL039401. · DOI
  62. Todini, E. (1996), The ARNO rainfall-runoff model, J. Hydrol., 175, 339-382, doi:10.1016/S0022-1694(96)80016-3. · DOI
  63. Trenberth, K. E., G. W. Branstator, and P. A. Arkin (1988), Origins of the 1988 North American Drought, Science, 242, 1640-1645, doi:10.1126/ science.242.4886.1640. · DOI
  64. Uppala, S. M., et al. (2005), The ERA-40 re-analysis, Q. J. R. Meteorol. Soc., 131, 2961-3012, doi:10.1256/qj.04.176. · DOI
  65. Van Beek, L. P. H., Y. Wada, and M. F. P. Bierkens (2011), Global monthly water stress: 1. Water balance and water availability, Water Resour. Res., 47, W07517, doi:10.1029/2010WR009791. · DOI · Paper page
  66. Van Dijk, A. I. J. M., L. J. Renzullo, Y. Wada, and P. Tregoning (2014), A global water cycle reanalysis (2003-2012) merging satellite gravime- try and altimetry observations with a hydrological multi-model ensemble, Hydrol. Earth Syst. Sci., 18, 2955-2973, doi:10.5194/hess-18- 2955-2014. · DOI
  67. V€ or€ osmarty, C. J., B. M. Fekete, M. Meybeck, and R. B. Lammers (2000), Global system of rivers: Its role in organizing continental land mass and defining land-to-ocean linkages, Global Biogeochem. Cycles, 14(2), 599-621, doi:10.1029/1999GB900092. · DOI
  68. V€ or€ osmarty, C. J., C. Leveque, and C. Revenga (2005), Freshwater ecosystems, in Millennium Ecosystem Assessment, vol. 1, Conditions and Trends, edited by C. Caudill et al., chap. 7, pp. 165-207, Island Press, Washington, D. C. V€ or€ osmarty, C. J., P. McIntyre, M. O. Gessner, D. Dudgeon, A. Prusevich, P. Green, S. Glidden, S. E. Bunn, C. A. Sullivan, and C. R. Liermann (2010), Global threats to human water security and river biodiversity, Nature, 467, 555-561, doi:10.1038/nature09440. · DOI · Paper page
  69. Wada, Y., and L. Heinrich (2013), Assessment of transboundary aquifers of the world-vulnerability arising from human water use, Environ. Res. Lett., 8, 024003, doi:10.1088/1748-9326/8/2/024003. · DOI
  70. Wada, Y., L. P. H. van Beek, and M. F. P. Bierkens (2011a), Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability, Hydrol. Earth Syst. Sci., 15, 3785-3808, doi:10.5194/hess-15-3785-2011. · DOI
  71. Wada, Y., L. P. H. van Beek, D. Viviroli, H. H. D€ urr, R. Weingartner, and M. F. P. Bierkens (2011b), Global monthly water stress: 2. Water demand and severity of water stress, Water Resour. Res., 47, W07518, doi:10.1029/2010WR009792. · DOI
  72. Wada, Y., L. P. H. van Beek, and M. F. P. Bierkens (2012a), Nonsustainable groundwater sustaining irrigation: A global assessment, Water Resour. Res., 48, W00L06, doi:10.1029/2011WR010562. · DOI
  73. Wada, Y., L. P. H. van Beek, F. C. Sperna Weiland, B. F. Chao, Y.-H. Wu, and M. F. P. Bierkens (2012b), Past and future contribution of global groundwater depletion to sea-level rise, Geophys. Res. Lett., 39, L09402, doi:10.1029/2012GL051230. · DOI
  74. Wada, Y., L. P. H. van Beek, N. Wanders, and M. F. P. Bierkens (2013), Human water consumption intensifies hydrological drought world- wide, Environ. Res. Lett., 8, 034036, doi:10.1088/1748-9326/8/3/034036. Journal of Advances in Modeling Earth Systems 10.1002/2015MS000618 · DOI
  75. Wada, Y., D. Wisser, and M. F. P. Bierkens (2014), Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources, Earth Syst. Dyn., 5, 15-40, doi:10.5194/esd-5-15-2014. · DOI
  76. Wid en-Nilsson, E., S. Halldin, and C.-Y. Xu (2007), Global water-balance modelling with WASMOD-M: Parameter estimation and regionaliza- tion, J. Hydrol., 340, 105-118, doi:10.1016/j.jhydrol.2007.04.002. · DOI
  77. Wisser, D., S. Frolking, E. M. Douglas, B. M. Fekete, C. J. V€ or€ osmarty, and A. H. Schumann (2008), Global irrigation water demand: Variability and uncertainties arising from agricultural and climate data sets, Geophys. Res. Lett., 35, L24408, doi:10.1029/2008GL035296. · DOI
  78. Wisser, D., B. M. Fekete, C. J. V€ or€ osmarty, and A. H. Schumann (2010), Reconstructing 20th century global hydrography: A contribution to the Global Terrestrial Network-Hydrology (GTN-H), Hydrol. Earth Syst. Sci., 14, 1-24, doi:10.5194/hess-14-1-2010. · DOI
  79. Wood, E. F., D. P. Lettenmaier, and V. G. Zartarian (1992), A land-surface hydrology parameterization with subgrid variability for general cir- culation models, J. Geophys. Res., 97(D3), 2717-2728, doi:10.1029/91JD01786. · DOI
  80. Wood, E. F., et al. (2011), Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water, Water Resour. Res., 47, W05301, doi:10.1029/2010WR010090. · DOI
  81. World Resources Institute (WRI) (1998), World Resources: A Guide to the Global Environment 1998-99, Washington, D. C. Journal of Advances in Modeling Earth Systems 10.1002/

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Authors
Wada, Y., de Graaf, I. E. M., & van Beek, L. P. H.
Affiliations
  • Goddard Institute for Space Studies (US)
  • Department of Physical Geography Utrecht University 3584 CS Utrecht Netherlands
Corresponding author
Wada, Yoshihide
ORCID
Wada, Yoshihide
Venue
Journal of Advances in Modeling Earth Systems
Publisher
American Geophysical Union (AGU)
Published
2016-05-22
Volume
8
Issue
2
Pages
735-763
ISSN
1942-2466 (ISSN-L)
DOI
10.1002/2015ms000618
OpenAlex
W2344700162
Cited by
217
References
4
Citations by year
2026: 22 · 2025: 19 · 2024: 25 · 2023: 28 · 2022: 31 · 2021: 34 · 2020: 20 · 2019: 14 · 2018: 10 · 2017: 14
FWCI
6.72
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Advances in Modeling Earth Systems (publishedVersion, cc-by-nc-nd)
  • IIASA PURE (International Institute of Applied Systems Analysis) (acceptedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion, cc-by-nc-nd)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by-nc-nd)
  • Japan Geoscience Union
Funders
Japan Society for the Promotion of Science (JSPS) (JSPS-2014-878)
Topics
  • Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
  • Physical Sciences › Engineering › Ocean Engineering › Water resources management and optimization
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Geophysics and Gravity Measurements
Keywords
global hydrological modelling, high-resolution hydrological modeling, human impacts on water resources, climate impacts on water resources, water availability, water consumption, groundwater head, lateral groundwater flow, MODFLOW, PCR-GLOBWB, climate variability

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