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Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration
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Abstract
Abstract. 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 (Water – Global Assessment and Prognosis) 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/refinements, consideration of human water use and calibration (or no calibration) against observed mean river discharge. In a modeling 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. The basin-specific calibration approach for WaterGAP was found to have the largest effect on grid cell fluxes as well as on global AET (actual evapotranspiration) and discharge into oceans for the period 1971–2000. Regarding grid cell fluxes, climate forcing ranks second before land cover input. Global water storage trends are most sensitive to model refinements (mainly modeling of groundwater depletion) and consideration of human water use. The best fit to observed time series of monthly river discharge or discharge seasonality is obtained with the standard WaterGAP 2.2 model version which is calibrated and driven by daily reanalysis-based WFD/WFDEI (combination of Watch Forcing Data based on ERA40 and Watch Forcing Data based on ERA-Interim) climate data. Discharge computed by a calibrated model version using monthly CRU TS (Climate Research Unit time-series) 3.2 and GPCC (Global Precipitation Climatology Center) v6 climate input reduced the fit to observed discharge for most stations. Taking into account uncertainties of climate and land cover data, global 1971–2000 discharge into oceans and inland sinks ranges between 40 000 and 42 000 km3 yr−1. Global actual evapotranspiration, with 70 000 km3 yr−1, is rather unaffected by climate and land cover uncertainties. Human water use reduced river discharge by 1000 km3 yr−1, such that 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 shortwave radiation data, resulting in strongly different actual 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 present.
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“Furthermore, WaterGAP is calibrated to estimate discharge from major river systems (Alcamo et al., 2003;Müller Schmied et al., 2014).This means that while the renewable part of groundwater is considered, fossil groundwater is omitted.”
From Life cycle assessment and water use impacts of lithium production from salar deposits: Challenges and opportunities (2024) · cites this paper as Müller Schmied et al., 2014
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“AWARE, based on the WaterGap 2.2 global hydrological model (Müller Schmied et al., 2014), quantifies the relative amount of fresh water remaining after the demands of aquatic ecosystems and anthropogenic activities are met.”
From Life cycle assessment and water use impacts of lithium production from salar deposits: Challenges and opportunities (2024) · cites this paper as Müller Schmied et al., 2014
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Cites
River flow forecasting through conceptual models part I — A discussion of principles
Nash, J. E., & Sutcliffe, J. V. (1970) · Journal of Hydrology · doi:10.1016/0022-1694(70)90255-6 · Cited by 24,401
Updated world map of the Köppen-Geiger climate classification
(2007) · doi:10.5194/hess-11-1633-2007 · Cited by 13,640
World map of the Köppen-Geiger climate classification updated
Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006) · Meteorologische Zeitschrift · doi:10.1127/0941-2948/2006/0130 · Cited by 11,456
On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters
Priestley, C. H. B., & Taylor, R. J. (1972) · Monthly Weather Review · doi:10.1175/1520-0493(1972)100 · Cited by 6,545
Updated high‐resolution grids of monthly climatic observations – the CRU TS3 .10 Dataset
Harris, I. C., Jones, P. D., Osborn, T. J., & Lister, D. (2013) · International Journal of Climatology · doi:10.1002/joc.3711 · Cited by 6,326
Global hydrological cycles and world water resources
Oki, T., & Kanae, S. (2006) · Science · doi:10.1126/science.1128845 · Cited by 4,392
Improvements to a MODIS global terrestrial evapotranspiration algorithm
Mu, Q., Zhao, M., & Running, S. W. (2011) · Remote Sensing of Environment · doi:10.1016/j.rse.2011.02.019 · Cited by 2,915
High‐resolution mapping of the world's reservoirs and dams for sustainable river‐flow management
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., et al. (2011) · Frontiers in Ecology and the Environment · doi:10.1890/100125 · Cited by 2,515
Self-citationNew Global Hydrography Derived from Spaceborne Elevation Data
Lehner, B., Verdin, K., & Jarvis, A. (2008) · Eos, Transactions American Geophysical Union · doi:10.1029/2008eo100001 · Cited by 2,411
Development and validation of a global database of lakes, reservoirs and wetlands
Lehner, B., & Döll, P. (2004) · Journal of Hydrology · doi:10.1016/j.jhydrol.2004.03.028 · Cited by 2,380
Self-citation
Research works printed but not linked: 4
- Alcamo, J., Leemans, R., and Kreileman, E. (Eds.): Global Change Scenarios of the 21st Century – Results from the IMAGE 2.1 Model, Pergamon, Oxford, 1998.
- Kaspar, F.: Entwicklung und Unsicherheitsanalyse eines globalen hydrologischen Modells, Ph.D. thesis, University of Kassel, Kassel, Germany, 2003.
- Schulze, K. and Döll, P.: Neue Ansätze zur Modellierung von Schneeakkumulation und -schmelze im globalen Wassermodell WaterGAP, in: Tagungsband zum 7. Workshop zur großskaligen Modellierung in der Hydrologie, edited by: Ludwig, R., Reichert, D., and Mauser, W., Kassel University Press, Kassel, 2004.
- Shuttleworth, W. J.: Evaporation, in: Handbook of Hydrology, edited by: Maidment, D. R., McGraw-Hill, New York, 4.1–4.53, 1993.
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A spatially explicit assessment of water use by the global semiconductor industry
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Self-citationOussou, F. E., Ndehedehe, C. E., Oloukoi, J., Yalo, N., Boukari, M., & Diaw, A. T. (2022) · Journal of Hydrology Regional Studies · doi:10.1016/j.ejrh.2021.100987 · Cited by 21
Ju, J., Wu, C., Li, J., Yeh, P. J. ‐., & Hu, B. X. (2023) · Journal of Hydrology · doi:10.1016/j.jhydrol.2023.129137 · Cited by 21
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Schmied, H. M., Adam, L., Eisner, S., Fink, G., Flörke, M., Kim, H., Oki, T., Portmann, F. T., Reinecke, R., Riedel, C., et al. (2016) · Proceedings of the International Association of Hydrological Sciences · doi:10.5194/piahs-374-53-2016 · Cited by 18
Self-citationCastro, A. L. D. A., Andrade, E. P., Costa, M. D. A., Santos, T. D. L., Ugaya, C. M. L., & de Figueirêdo, M. C. B. (2018) · Environmental Impact Assessment Review · doi:10.1016/j.eiar.2018.05.004 · Cited by 18
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Li, Q., Pan, Y., Zhang, C., & Gong, H. (2023) · Remote Sensing · doi:10.3390/rs15112744 · Cited by 18
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Schulze, K., Kusche, J., Gerdener, H., Döll, P., & Schmied, H. M. (2024) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2023ms004092 · Cited by 15
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Boulangé, J., Hanasaki, N., Satoh, Y., Yokohata, T., Shiogama, H., Burek, P., Thiery, W., Gerten, D., Schmied, H. M., Wada, Y., et al. (2021) · Environmental Research Letters · doi:10.1088/1748-9326/ac27cc · Cited by 15
Singh, A., Seitz, F., Eicker, A., & Güntner, A. (2016) · Remote Sensing · doi:10.3390/rs8110953 · Cited by 15
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Gleeson, T., Wagener, T., Döll, P., Zipper, S. C., West, C., Wada, Y., Taylor, R. G., Scanlon, B. R., Rosolem, R., Rahman, S., et al. (2020) · doi:10.5194/hess-2020-378 · Cited by 14
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Gerdener, H., Kusche, J., Schulze, K., Ghazaryan, G., & Dubovyk, O. (2022) · Journal of Hydrology · doi:10.1016/j.jhydrol.2022.128096 · Cited by 13
Wan, W., Döll, P., & Zheng, H. (2022) · Water Resources Research · doi:10.1029/2022wr032380 · Cited by 13
Self-citationBen-Salem, N., Reinecke, R., Copty, N. K., Gómez‐Hernández, J. J., Varouchakis, E. Α., Karatzas, G. P., Rode, M., & Jomaa, S. (2023) · Journal of Hydrology · doi:10.1016/j.jhydrol.2023.130207 · Cited by 13
Keune, J., Sulis, M., & Kollet, S. J. (2019) · Journal of Advances in Modeling Earth Systems · doi:10.1029/2019ms001657 · Cited by 14
Cole, A., & Boutt, D. F. (2021) · Frontiers in Water · doi:10.3389/frwa.2021.645634 · Cited by 13
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Hernández‐Espriú, A., Wolaver, B. D., Arciniega‐Esparza, S., Scanlon, B. R., Young, M. H., Nicot, J., Macías-Medrano, S., & Breña‐Naranjo, J. A. (2019) · Journal of Environmental Management · doi:10.1016/j.jenvman.2018.11.123 · Cited by 12
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Gelfan, A. N., & Kalugin, A. (2021) · Water Resources · doi:10.1134/s0097807821060063 · Cited by 12
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Tao, D., Shi, H., Gao, C., Zhan, J., & Ke, X. (2020) · Remote Sensing · doi:10.3390/rs12152408 · Cited by 11
Giuntoli, I., Villarini, G., Prudhomme, C., Mallakpour, I., & Hannah, D. M. (2015) · Journal of Geophysical Research Atmospheres · doi:10.1002/2015jd023401 · Cited by 11
Wang, L., Zhu, M., Zhong, Y., Sun, J., & Peng, Z. (2023) · Geodesy and Geodynamics · doi:10.1016/j.geog.2023.07.009 · Cited by 10
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The environmental cost of a reference withdrawal from surface waters: Definition and geography
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Cartograms Facilitate Communication of Climate Change Risks and Responsibilities
Döll, P. (2017) · Earth s Future · doi:10.1002/2017ef000677 · Cited by 10
Self-citationIntroducing a nested multimedia fate and transport model for organic contaminants (NEM)
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Fernández, R., & Sayama, T. (2015) · Hydrological Research Letters · doi:10.3178/hrl.9.75 · Cited by 10
Rateb, A., Scanlon, B. R., & Fakhreddine, S. (2022) · Springer eBooks · doi:10.1007/978-3-030-88874-9_4 · Cited by 10
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Davin, K., Koslowski, M., Dorber, M., & Hertwich, E. G. (2024) · Journal of Industrial Ecology · doi:10.1111/jiec.13556 · Cited by 9
Rhouma, A., Seitfudem, G., Jeitany, J. E., Pacetti, T., Brouwer, F., & Gil, J. M. (2025) · Environmental and Sustainability Indicators · doi:10.1016/j.indic.2025.100640 · Cited by 9
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Lambert, F. H., Allan, R. P., Behrangi, A., Byrne, M. P., Ceppi, P., Chadwick, R. S., Durack, P. J., Fosser, G., Fowler, H. J., Greve, P., et al. (2025) · Wiley Interdisciplinary Reviews Climate Change · doi:10.1002/wcc.70005 · Cited by 9
Abbas, A., Yang, Y., Pan, M., Tramblay, Y., Shen, C., Ji, H., Gebrechorkos, S. H., Pappenberger, F., Pyo, J., Feng, D., et al. (2026) · Hydrology and earth system sciences · doi:10.5194/hess-30-3399-2026 · Cited by 13
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Metadata
- Authors
- Müller Schmied, H., Eisner, S., Franz, D., Wattenbach, M., Portmann, F. T., Flörke, M., & Döll, P.
- Affiliations
- University of Kassel (DE)
- GFZ Helmholtz Centre for Geosciences (DE)
- Goethe University Frankfurt (DE)
- Corresponding author
- Eisner, S.
- Franz, D.
- Wattenbach, M.
- Venue
- Hydrology and Earth System Sciences
- Publisher
- Copernicus GmbH
- Published
- 2014-09-10
- Volume
- 18
- Issue
- 9
- Pages
- 3511-3538
- ISSN
- 1027-5606 (ISSN-L)
- 1607-7938
- OpenAlex
- W2114721961
- Cited by
- 415
- References
- 100
- Citations by year
- 2026: 13 · 2025: 36 · 2024: 26 · 2023: 38 · 2022: 32 · 2021: 66 · 2020: 51 · 2019: 37 · 2018: 36 · 2017: 33 · 2016: 25 · 2015: 16 · 2014: 6
- FWCI
- 20.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Hydrology and earth system sciences (publishedVersion, cc-by)
- Publication Database GFZ (GFZ German Research Centre for Geosciences) (submittedVersion, cc-by)
- Publication Database GFZ (GFZ German Research Centre for Geosciences) (submittedVersion, other-oa)
- Publication Server of Goethe University Frankfurt am Main (Goethe University Frankfurt) (submittedVersion, cc-by)
- Topics
- Physical Sciences › Environmental Science › Water Science and Technology › Hydrology and Watershed Management Studies
- Physical Sciences › Earth and Planetary Sciences › Geophysics › Geophysics and Gravity Measurements
- Physical Sciences › Environmental Science › Environmental Engineering › Soil Moisture and Remote Sensing
- Keywords
- freshwater flux, model uncertainty, human water use, river discharge, actual evapotranspiration, radiative forcing, land cover, model calibration, groundwater depletion, renewable water resources, climate reanalysis data, CRU TS, shortwave radiation
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