Surveys in Geophysics

, Volume 35, Issue 6, pp 1311–1331

Seasonal Water Storage Variations as Impacted by Water Abstractions: Comparing the Output of a Global Hydrological Model with GRACE and GPS Observations

  • Petra Döll
  • Mathias Fritsche
  • Annette Eicker
  • Hannes Müller Schmied
Article

Abstract

Better quantification of continental water storage variations is expected to improve our understanding of water flows, including evapotranspiration, runoff and river discharge as well as human water abstractions. For the first time, total water storage (TWS) on the land area of the globe as computed by the global water model WaterGAP (Water Global Assessment and Prognosis) was compared to both gravity recovery and climate experiment (GRACE) and global positioning system (GPS) observations. The GRACE satellites sense the effect of TWS on the dynamic gravity field of the Earth. GPS reference points are displaced due to crustal deformation caused by time-varying TWS. Unfortunately, the worldwide coverage of the GPS tracking network is irregular, while GRACE provides global coverage albeit with low spatial resolution. Detrended TWS time series were analyzed by determining scaling factors for mean annual amplitude (fGRACE) and time series of monthly TWS (fGPS). Both GRACE and GPS indicate that WaterGAP underestimates seasonal variations of TWS on most of the land area of the globe. In addition, seasonal maximum TWS occurs 1 month earlier according to WaterGAP than according to GRACE on most land areas. While WaterGAP TWS is sensitive to the applied climate input data, none of the two data sets result in a clearly better fit to the observations. Due to the low number of GPS sites, GPS observations are less useful for validating global hydrological models than GRACE observations, but they serve to support the validity of GRACE TWS as observational target for hydrological modeling. For unknown reasons, WaterGAP appears to fit better to GPS than to GRACE. Both GPS and GRACE data, however, are rather uncertain due to a number of reasons, in particular in dry regions. It is not possible to benefit from either GPS or GRACE observations to monitor and quantify human water abstractions if only detrended (seasonal) TWS variations are considered. Regarding GRACE, this is mainly caused by the attenuation of the TWS differences between water abstraction variants due to the filtering required for GRACE TWS. Regarding GPS, station density is too low. Only if water abstractions lead to long-term changes in TWS by depletion or restoration of water storage in groundwater or large surface water bodies, GRACE may be used to support the quantification of human water abstractions.

Keywords

GRACE GPS Global hydrological model Water storage Water abstractions 

References

  1. Alkama R, Decharme B, Douville H, Becker M, Cazenave A, Sheffield J, Voldoire A, Tyteca S, Le Moigne P (2010) Global evaluation of the ISBA–TRIP continental hydrological system. Part I: comparison to GRACE terrestrial water storage estimates and in situ river discharges. J Hydrom 11(3):583–600. doi:10.1175/2010JHM1211.1 CrossRefGoogle Scholar
  2. Bettadpur SV (2012) Insights into the Earth system mass variability from CSR-RL05 GRACE gravity fields. EGU General Assembly Conference Abstracts. http://meetingorganizer.copernicus.org/EGU2012/EGU2012-6409.pdf
  3. Cheng M (2004) Variations in the Earth's oblateness during the past 28 years. J Geophys Res 109(B9):B09402. doi:10.1029/2004JB003028 Google Scholar
  4. Clarke PJ, Lavallée DA, Blewitt G, van Dam TM, Wahr JM (2005) Effect of gravitational consistency and mass conservation on seasonal surface mass loading models. Geophys Res Lett 32(8):L08306. doi:10.1029/2005GL022441 Google Scholar
  5. Crétaux J, Jelinski W, Calmant S, Kouraev A, Vuglinski V, Bergé-Nguyen M et al (2011) SOLS: a lake database to monitor in the near real time water level and storage variations from remote sensing data. Adv Space Res 47(9):1497–1507. doi:10.1016/j.asr.2011.01.004 CrossRefGoogle Scholar
  6. Dahle C, Flechtner F, Gruber C, König D, König R, Michalak G, Neumayer K (2012) GFZ GRACE level-2 processing standards document for level-2 product release 0005. Geoforschungszentrum (GFZ) PotsdamGoogle Scholar
  7. Döll P, Fiedler K (2008) Global-scale modeling of groundwater recharge. Hydrol Earth Syst Sci 12(3):863–885. doi:10.5194/hess-12-863-2008 CrossRefGoogle Scholar
  8. Döll P, Siebert S (2002) Global modeling of irrigation water requirements. Water Resour Res 38 (4):8-1– 8-10. doi:10.1029/2001WR000355 Google Scholar
  9. Döll P, Kaspar F, Lehner B (2003) A global hydrological model for deriving water availability indicators: model tuning and validation. J Hydrol 270(1–2):105–134. doi:10.1016/S0022-1694(02)00283-4 CrossRefGoogle Scholar
  10. Döll P, Fiedler K, Zhang J (2009) Global-scale analysis of river flow alterations due to water withdrawals and reservoirs. Hydrol Earth Syst Sci 6:2413–2432. doi:10.5194/hess-13-2413-2009 CrossRefGoogle Scholar
  11. Döll P, Hoffmann-Dobrev H, Portmann FT, Siebert S, Eicker A, Rodell M et al (2012) Impact of water withdrawals from groundwater and surface water on continental water storage variations. J Geodyn 59–60:143–156. doi:10.1016/j.jog.2011.05.001 CrossRefGoogle Scholar
  12. Famiglietti JS, Lo M, Ho SL, Bethune J, Anderson KJ, Syed TH et al (2011) Satellites measure recent rates of groundwater depletion in California's Central Valley. Geophys Res Lett 38(3):L03403. doi:10.1029/2010GL046442 Google Scholar
  13. Fersch B, Kunstmann H, Bárdossy A, Devaraju B, Sneeuw N (2012) Continental-scale basin water storage variation from global and dynamically downscaled atmospheric water budgets in comparison with GRACE-derived observations. J Hydrom 13(5):1589–1603. doi:10.1175/JHM-D-11-0143.1 CrossRefGoogle Scholar
  14. Flechtner F (2007) AOD1B product description document for product releases 01–04. Technical Report, Geoforschungszentrum (GFZ) PotsdamGoogle Scholar
  15. Friedl MA, Sulla-Menashe D, Tan B, Schneider A, Ramankutty N, Sibley A, Huang X (2010) MODIS Collection 5 global land cover: algorithm refinements and characterization of new datasets. Remote Sens Env 114(1):168–182. doi:10.1016/j.rse.2009.08.016 CrossRefGoogle Scholar
  16. Fritsche M, Döll P, Dietrich R (2012) Global-scale validation of model-based load deformation of the Earth's crust from continental watermass and atmospheric pressure variations using GPS. J Geodyn 59–60:133–142. doi:10.1016/j.jog.2011.04.001 CrossRefGoogle Scholar
  17. Grippa M, Kergoat L, Frappart F, Araud Q, Boone A, de Rosnay P et al (2011) Land water storage variability over West Africa estimated by gravity recovery and climate experiment (GRACE) and land surface models. Water Resour Res 47(5):W05549. doi:10.1029/2009WR008856 CrossRefGoogle Scholar
  18. Harris I, Jones P, Osborn T, Lister D (2013) Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 dataset. Int J Climatol 34:623–642. doi:10.1002/joc.3711 Google Scholar
  19. Hunger M, Döll P (2008) Value of river discharge data for global-scale hydrological modeling. Hydrol Earth Syst Sci 12(3):841–861. doi:10.5194/hess-12-841-2008 CrossRefGoogle Scholar
  20. Kusche J (2007) Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models. J Geod 81(11):733–749. doi:10.1007/s00190-007-0143-3 CrossRefGoogle Scholar
  21. Kusche J, Schmidt R, Petrovic S, Rietbroek R (2009) Decorrelated GRACE time-variable gravity solutions by GFZ, and their validation using a hydrological model. J Geod 83(10):903–913. doi:10.1007/s00190-009-0308-3 CrossRefGoogle Scholar
  22. Landerer FW, Dickey JO, Güntner A (2010) Terrestrial water budget of the Eurasian pan-Arctic from GRACE satellite measurements during 2003-2009. J Geophys Res 115:D23115. doi:10.1029/2010JD014584 CrossRefGoogle Scholar
  23. Mayer-Gürr T, Kurtenbach E, Eicker A (2010) ITG-Grace2010 gravity field model. Institut für Geodäsie und Geoinformation Universität Bonn. http://www.igg.uni-bonn.de/apmg/index.php?id=itg-grace2010
  24. McGuire V (2011) Water-level changes in the High Plains Aquifer, predevelopment to 2007, 2007–08, and 2008–09, and change in water storage, predevelopment to 2009. U.S. Geological Survey Scientific Investigations Report:2011-5089Google Scholar
  25. Müller Schmied H, Eisner S, Franz D, Wattenbach M, Portmann FT, Flörke M, Döll P (2014) Sensitivity of simulated global-scale freshwater fluxes and storages to input data, hydrological model structure, human water use and calibration. Hydrol Earth Syst Sci Discuss 11:1583–1649. doi:10.5194/hessd-11-1583-2014
  26. Pedinotti V, Boone A, Decharme B, Crétaux JF, Mognard N, Panthou G et al (2012) Evaluation of the ISBA-TRIP continental hydrologic system over the Niger basin using in situ and satellite derived datasets. Hydrol Earth Syst Sci 16(6):1745–1773. doi:10.5194/hess-16-1745-2012 CrossRefGoogle Scholar
  27. Riegger J, Tourian M, Devaraju B, Sneeuw N (2012) Analysis of grace uncertainties by hydrological and hydro-meteorological observations. J Geodyn 59–60:16–27. doi:10.1016/j.jog.2012.02.001 CrossRefGoogle Scholar
  28. Rietbroek R, Brunnabend S, Kusche J, Schröter J (2012a) Resolving sea level contributions by identifying fingerprints in time-variable gravity and altimetry. J Geodyn 59–60:72–81. doi:10.1016/j.jog.2011.06.007 CrossRefGoogle Scholar
  29. Rietbroek R, Fritsche M, Brunnabend S, Daras I, Kusche J, Schröter J et al (2012b) Global surface mass from a new combination of GRACE, modelled OBP and reprocessed GPS data. J Geodyn 59–60:64–71. doi:10.1016/j.jog.2011.02.003 CrossRefGoogle Scholar
  30. Rost S, Gerten D, Bondeau A, Lucht W, Rohwer J, Schaphoff S (2008) Agricultural green and blue water consumption and its influence on the global water system. Water Resour Res 44(9):W09405. doi:10.1029/2007WR006331 CrossRefGoogle Scholar
  31. Schmidt R, Schwintzer P, Flechtner F, Reigber C, Güntner A, Döll P et al (2006) GRACE observations of changes in continental water storage. Glob Plan Change 50(1–2):112–126. doi:10.1016/j.gloplacha.2004.11.018 CrossRefGoogle Scholar
  32. Schneider U, Becker A, Finger P, Meyer-Christoffer A, Ziese M, Rudolf B (2013) GPCC's new land surface precipitation climatology based on quality-controlled in situ data and its role in quantifying the global water cycle. Theor Appl Climatol. doi:10.1007/s00704-013-0860-x Google Scholar
  33. Strassberg G, Scanlon BR, Chambers D (2009) Evaluation of groundwater storage monitoring with the GRACE satellite: case study of the high plains aquifer, central United States. Water Resour Res 45(5):W05410. doi:10.1029/2008WR006892 CrossRefGoogle Scholar
  34. Tiwari VM, Wahr J, Swenson S (2009) Dwindling groundwater resources in northern India, from satellite gravity observations. Geophys Res Lett 36(18):L18401. doi:10.1029/2009GL039401 CrossRefGoogle Scholar
  35. Vergnes J-P, Decharme B (2012) A simple groundwater scheme in the TRIP river routing model: global off-line evaluation against GRACE terrestrial water storage estimates and observed river discharges. Hydrol Earth Syst Sci 16:3889–3908. doi:10.5194/hess-16-3889-2012 CrossRefGoogle Scholar
  36. Wada Y, van Beek LPH, Bierkens MFP (2012) Nonsustainable groundwater sustaining irrigation: a global assessment. Water Resour Res 48:W00L06. doi:10.1029/2011WR010562
  37. Wahr J, Molenaar M, Bryan F (1998) Time variability of the Earth's gravity field: hydrological and oceanic effects and their possible detection using GRACE. J Geophys Res 103(B12):30205–30229. doi:10.1029/98JB02844 CrossRefGoogle Scholar
  38. Wang D (2012) Evaluating interannual water storage changes at watersheds in Illinois based on long-term soil moisture and groundwater level data. Water Resour Res 48(3):W03502. doi:10.1029/2011WR010759 CrossRefGoogle Scholar
  39. Weedon GP, Gomes S, Viterbo P, Shuttleworth WJ, Blyth E, Österle H et al (2011) Creation of the WATCH Forcing Data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J Hydrom 12(5):823–848. doi:10.1175/2011JHM1369.1 CrossRefGoogle Scholar
  40. Werth S, Güntner A (2010) Calibration analysis for water storage variability of the global hydrological model WGHM. Hydrol Earth Syst Sci 14(1):59–78CrossRefGoogle Scholar
  41. Xie H, Longuevergne L, Ringler C, Scanlon BR (2012) Calibration and evaluation of a semi-distributed watershed model of Sub-Saharan Africa using GRACE data. Hydrol Earth Syst Sci 16(9):3083–3099. doi:10.5194/hess-16-3083-2012 CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Petra Döll
    • 1
  • Mathias Fritsche
    • 2
  • Annette Eicker
    • 3
  • Hannes Müller Schmied
    • 1
  1. 1.Institute of Physical GeographyUniversity of FrankfurtFrankfurtGermany
  2. 2.Institute of Planetary GeodesyTechnical University DresdenDresdenGermany
  3. 3.Institute of Geodesy and GeoinformationUniversity of BonnBonnGermany

Personalised recommendations