Dynamics of Terrestrial Water Storage Change from Satellite and Surface Observations and Modeling

Qiuhong Tang Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

Search for other papers by Qiuhong Tang in
Current site
Google Scholar
PubMed
Close
,
Huilin Gao Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

Search for other papers by Huilin Gao in
Current site
Google Scholar
PubMed
Close
,
Pat Yeh Institute of Industrial Science, University of Tokyo, Tokyo, Japan

Search for other papers by Pat Yeh in
Current site
Google Scholar
PubMed
Close
,
Taikan Oki Institute of Industrial Science, University of Tokyo, Tokyo, Japan

Search for other papers by Taikan Oki in
Current site
Google Scholar
PubMed
Close
,
Fengge Su Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

Search for other papers by Fengge Su in
Current site
Google Scholar
PubMed
Close
, and
Dennis P. Lettenmaier Department of Civil and Environmental Engineering, University of Washington, Seattle, Washington

Search for other papers by Dennis P. Lettenmaier in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

Terrestrial water storage (TWS) is a fundamental component of the water cycle. On a regional scale, measurements of terrestrial water storage change (TWSC) are extremely scarce at any time scale. This study investigates the feasibility of estimating monthly-to-seasonal variations of regional TWSC from modeling and a combination of satellite and in situ surface observations based on water balance computations that use ground-based precipitation observations in both cases. The study area is the Klamath and Sacramento River drainage basins in the western United States (total area of about 110 000 km2). The TWSC from the satellite/surface observation–based estimates is compared with model results and land water storage from the Gravity Recovery and Climate Experiment (GRACE) data. The results show that long-term evapotranspiration estimates and runoff measurements generally balance with observed precipitation, suggesting that the evapotranspiration estimates have relatively small bias for long averaging times. Observations show that storage change in water management reservoirs is about 12% of the seasonal amplitude of the TWSC cycle, but it can be up to 30% at the subbasin scale. Comparing with predevelopment conditions, the satellite/surface observation–based estimates show larger evapotranspiration and smaller runoff than do modeling estimates, suggesting extensive anthropogenic alteration of TWSC in the study area. Comparison of satellite/surface observation–based and GRACE TWSC shows that the seasonal cycle of terrestrial water storage is substantially underestimated by GRACE.

Corresponding author address: Dennis P. Lettenmaier, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195-2700. Email: dennisl@u.washington.edu

Abstract

Terrestrial water storage (TWS) is a fundamental component of the water cycle. On a regional scale, measurements of terrestrial water storage change (TWSC) are extremely scarce at any time scale. This study investigates the feasibility of estimating monthly-to-seasonal variations of regional TWSC from modeling and a combination of satellite and in situ surface observations based on water balance computations that use ground-based precipitation observations in both cases. The study area is the Klamath and Sacramento River drainage basins in the western United States (total area of about 110 000 km2). The TWSC from the satellite/surface observation–based estimates is compared with model results and land water storage from the Gravity Recovery and Climate Experiment (GRACE) data. The results show that long-term evapotranspiration estimates and runoff measurements generally balance with observed precipitation, suggesting that the evapotranspiration estimates have relatively small bias for long averaging times. Observations show that storage change in water management reservoirs is about 12% of the seasonal amplitude of the TWSC cycle, but it can be up to 30% at the subbasin scale. Comparing with predevelopment conditions, the satellite/surface observation–based estimates show larger evapotranspiration and smaller runoff than do modeling estimates, suggesting extensive anthropogenic alteration of TWSC in the study area. Comparison of satellite/surface observation–based and GRACE TWSC shows that the seasonal cycle of terrestrial water storage is substantially underestimated by GRACE.

Corresponding author address: Dennis P. Lettenmaier, Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195-2700. Email: dennisl@u.washington.edu

Save
  • Abdulla, F. A., Lettenmaier D. P. , Wood E. F. , and Smith J. A. , 1996: Application of a macroscale hydrologic model to estimate the water balance of the Arkansas-Red River basin. J. Geophys. Res., 101 , 74497459.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alley, W. M., Healy R. W. , LaBaugh J. W. , and Reilly T. E. , 2002: Flow and storage in groundwater systems. Science, 296 , 19851991.

  • Alsdorf, D. E., Rodríguez E. , and Lettenmaier D. P. , 2007: Measuring surface water from space. Rev. Geophys., 45 , RG2002. doi:10.1029/2006RG000197.

    • Search Google Scholar
    • Export Citation
  • Altese, E., Bolognani O. , Mancini M. , and Troch P. A. , 1996: Retrieving soil moisture over bare soil from ERS 1 synthetic aperture radar data: Sensitivity analysis based on a theoretical surface scattering model and field data. Water Resour. Res., 32 , 653661.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Belward, A. S., Estes J. E. , and Kline K. D. , 1999: The IGBP-DIS global 1-km land-cover data set DISCover: A project overview. Photogramm. Eng. Remote Sens., 65 , 10131020.

    • Search Google Scholar
    • Export Citation
  • Bengtsson, L., Hagemann S. , and Hodges K. I. , 2004: Can climate trends be calculated from reanalysis data? J. Geophys. Res., 109 , D11111. doi:10.1029/2004JD004536.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Carlson, T. N., Gillies R. R. , and Schmugge T. J. , 1995: An interpretation of methodologies for indirect measurements of soil water content. Agric. For. Meteor., 77 , 265278.

    • Search Google Scholar
    • Export Citation
  • Cayan, D. R., 1996: Interannual climate variability and snowpack in the western United States. J. Climate, 9 , 928948.

  • Chambers, D. P., 2006: Evaluation of new GRACE time-variable gravity data over the ocean. J. Geophys. Res., 33 , L17603. doi:10.1029/2006GL027296.

    • Search Google Scholar
    • Export Citation
  • Cherkauer, K. A., and Lettenmaier D. P. , 1999: Hydrologic effects of frozen soils in the upper Mississippi River basin. J. Geophys. Res., 104 , 1959919610.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Courault, D., Seguin B. , and Olioso A. , 2005: Review on estimation of evapotranspiration from remote sensing data: From empirical to numerical modeling approaches. Irrig. Drain. Syst., 19 , 223249.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Daly, C., Neilson R. P. , and Phillips D. L. , 1994: A statistical–topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteor., 33 , 140158.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Daly, C., Gibson W. P. , Taylor G. H. , Johnson G. L. , and Pasteris P. , 2002: A knowledge-based approach to the statistical mapping of climate. Int. J. Climatol., 16 , 841859.

    • Search Google Scholar
    • Export Citation
  • Gao, H., Wood E. F. , Drusch M. , Crow W. , and Jackson T. J. , 2004: Using a microwave emission model to estimate soil moisture from ESTAR observations during SGP99. J. Hydrometeor., 5 , 4963.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gillies, R. R., Kustas W. P. , and Humes K. S. , 1997: A verification of the triangle method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface radiant temperature. Int. J. Remote Sens., 18 , 31453166.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haddeland, I., Lettenmaier D. P. , and Skaugen T. , 2006: Effects of irrigation on the water and energy balances of the Colorado and Mekong river basins. J. Hydrol., 324 , 210223. doi:10.1016/j.jhydrol.2005.09.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hall, D. K., Riggs G. A. , Salomonson V. V. , Di Girolamo N. E. , and Bayr K. L. , 2002: MODIS snow-cover products. Remote Sens. Environ., 83 , 181194.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirschi, M., Seneviratne S. I. , and Schär C. , 2006: Seasonal variations in terrestrial water storage for major midlatitude river basins. J. Hydrometeor., 7 , 3960.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirschi, M., Seneviratne S. I. , Hagemann S. , and Schär C. , 2007: Analysis of seasonal terrestrial water storage variations in regional climate simulations over Europe. J. Geophys. Res., 112 , D22109. doi:10.1029/2006JD008338.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoffmann, J., Galloway D. L. , and Zebker H. A. , 2001: Calibrating a Regional Ground-Water Flow and Subsidence Model in Antelope Valley, California, Using InSAR-Derived Subsidence Maps. Eos, Trans. Amer. Geophys. Union, 82 .(Fall Meeting Suppl.). Abstract H41E-0320.

    • Search Google Scholar
    • Export Citation
  • Jackson, T. J., 1997: Soil moisture estimation using special satellite microwave/imager satellite data over a grassland region. Water Resour. Res., 33 , 14751484.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiang, L., and Islam S. , 2001: Estimation of surface evaporation map over southern Great Plains using remote sensing data. Water Resour. Res., 37 , 329340.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77 , 437471.

  • Kelly, R. E., Chang A. T. , Tsang L. , and Foster J. L. , 2003: A prototype AMSR-E global snow area and snow depth algorithm. IEEE Trans. Geosci. Remote Sens., 41 , 230242. doi:10.1109/TGRS.2003.809118.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lettenmaier, D. P., and Famiglietti J. S. , 2006: Hydrology: Water from on high. Nature, 444 , 562563. doi:10.1038/444562a.

  • Liang, X., Lettennmaier D. P. , Wood E. F. , and Burges S. J. , 1994: A simple hydrologically based model of land surface water and energy fluxes for general circulation models. J. Geophys. Res., 99 , 1441514428.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lohmann, D., Nolte-Holube R. , and Raschke E. , 1996: A large-scale horizontal routing model to be coupled to land surface parametrization schemes. Tellus, 48A , 708721. doi:10.1034/j.1600-0870.1996.t01-3-00009.x.

    • Search Google Scholar
    • Export Citation
  • Lohmann, D., Raschke E. , Nijssen B. , and Lettenmaier D. P. , 1998: Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model. Hydrol. Sci. J., 43 , 131141.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maurer, E. P., O’Donnell G. M. , Lettenmaier D. P. , and Roads J. O. , 2001: Evaluation of the land surface water budget in NCEP/NCAR and NCEP/DOE reanalyses using an off-line hydrologic model. J. Geophys. Res., 106 , 1784117862.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maurer, E. P., Wood A. W. , Adam J. C. , Lettenmaier D. P. , and Nijssen B. , 2002: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States. J. Climate, 15 , 32373251.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Menzel, W. P., and Purdom J. F. W. , 1994: Introducing GOES-I: The first of a new generation of geostationary operational environmental satellites. Bull. Amer. Meteor. Soc., 75 , 757782.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mitchell, K. E., and Coauthors, 2004: The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. J. Geophys. Res., 109 , D07S90. doi:10.1029/2003JD003823.

    • Search Google Scholar
    • Export Citation
  • Nash, J. E., and Sutcliffe J. V. , 1970: River flow forecasting through conceptual models part I—A discussion of principles. J. Hydrol., 10 , 282290. doi:10.1016/0022-1694(70)90255-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nijssen, B., Lettenmaier D. P. , Liang X. , Wetzel S. W. , and Wood E. F. , 1997: Streamflow simulation for continental-scale river basins. Water Resour. Res., 33 , 711724.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nijssen, B., Schnur R. , and Lettenmaier D. P. , 2001: Global retrospective estimation of soil moisture using the Variable Infiltration Capacity land surface model, 1980–93. J. Climate, 14 , 17901808.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nishida, K., Nemani R. R. , Running S. W. , and Glassy J. M. , 2003: An operational remote sensing algorithm of land surface evaporation. J. Geophys. Res., 108 , 4270. doi:10.1029/2002JD002062.

    • Search Google Scholar
    • Export Citation
  • Njoku, E. G., Jackson T. J. , Lakshmi V. , Chan T. K. , and Nghiem S. V. , 2003: Soil moisture retrieval from AMSR-E. IEEE Trans. Geosci. Remote Sens., 41 , 215229. doi:10.1109/TGRS.2002.808243.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Oki, T., and Kanae S. , 2006: Global hydrological cycles and world water resources. Science, 313 , 10681072.

  • Oki, T., Musiake K. , Matsuyama H. , and Masuda K. , 1995: Global atmospheric water balance and runoff from large river basins. Hydrol. Processes, 9 , 655678.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pinker, R. T., and Laszlo I. , 1992: Modeling surface solar irradiance for satellite applications on a global scale. J. Appl. Meteor., 31 , 194211.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ramillien, G., Frappart F. , Güntner A. , Ngo-Duc T. , Cazenave A. , and Laval K. , 2006: Time variations of the regional evapotranspiration rate from Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry. Water Resour. Res., 42 , W10403. doi:10.1029/2005WR004331.

    • Search Google Scholar
    • Export Citation
  • Ramsay, B. H., 1998: The interactive multisensor snow and ice mapping system. Hydrol. Processes, 12 , 15371546.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Risley, J. C., Hess G. W. , and Fisher B. J. , 2006: An assessment of flow data from Klamath River sites between Link River Dam and Keno Dam, south-central Oregon. U.S. Geological Survey Scientific Investigations Rep. 2006-5212, 38 pp.

    • Search Google Scholar
    • Export Citation
  • Robock, A., Vinnikov K. Y. , Srinivasan G. , Entin J. K. , Hollinger S. E. , Speranskaya N. A. , Liu S. , and Namkhai A. , 2000: The Global Soil Moisture Data Bank. Bull. Amer. Meteor. Soc., 81 , 12811299.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodell, M., and Famiglietti J. S. , 1999: Detectability of variations in continental water storage from satellite observations of the time dependent gravity field. Water Resour. Res., 35 , 27052723.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Rodell, M., Famiglietti J. S. , Chen J. , Seneviratne S. I. , Viterbo P. , Holl S. , and Wilson C. R. , 2004: Basin scale estimates of evapotranspiration using GRACE and other observations. Geophys. Res. Lett., 31 , L20504. doi:10.1029/2004GL020873.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roerink, G. J., Su Z. , and Menenti M. , 2000: S-SEBI: a simple remote sensing algorithm to estimate the surface energy balance. Phys. Chem. Earth, 25B , 147157.

    • Search Google Scholar
    • Export Citation
  • Schultz, G. A., Hornbogen M. , Viterbo P. , and Noilhan J. , 1995: Coupling large-scale hydrological and atmospheric models. IAHS Special Publication 3, 96 pp.

    • Search Google Scholar
    • Export Citation
  • Seneviratne, S. I., Viterbo P. , Lüthi D. , and Schär C. , 2004: Inferring changes in terrestrial water storage using ERA-40 reanalysis data: The Mississippi River basin. J. Climate, 17 , 20392057.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seo, K-W., Wilson C. R. , Famiglietti J. S. , Chen J. L. , and Rodell M. , 2006: Terrestrial water mass load changes from Gravity Recovery and Climate Experiment (GRACE). Water Resour. Res., 42 , W5417. doi:10.1029/2005WR004255.

    • Search Google Scholar
    • Export Citation
  • Serreze, M. C., Clark M. P. , Armstrong R. L. , McGinnis D. A. , and Pulwarty R. S. , 1999: Characteristics of the Western United States snowpack from Snowpack Telemetry (SNOTEL) data. Water Resour. Res., 35 , 21452160.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Su, F., Adam J. C. , Trenberth K. E. , and Lettenmaier D. P. , 2006: Evaluation of surface water fluxes of the pan-Arctic land region with a land surface model and ERA-40 reanalysis. J. Geophys. Res., 111 , D05110. doi:10.1029/2005JD006387.

    • Search Google Scholar
    • Export Citation
  • Tang, Q., Oki T. , Kanae S. , and Hu H. , 2007a: The influence of precipitation variability and partial irrigation within grid cells on a hydrological simulation. J. Hydrometeor., 8 , 499512.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tang, Q., Wood A. W. , and Lettenmaier D. P. , 2007b: Near real time evapotranspiration estimation using remote sensing data. Eos, Trans. Amer. Geophys. Union, 88 .(Fall Meeting Suppl.). Abstract H31A-0127.

    • Search Google Scholar
    • Export Citation
  • Tang, Q., Oki T. , Kanae S. , and Hu H. , 2008: Hydrological cycles change in the Yellow River basin during the last half of the 20th century. J. Climate, 21 , 17901806.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tang, Q., Peterson S. , Cuenca R. H. , Hagimoto Y. , and Lettenmaier D. P. , 2009a: Satellite-based near-real-time estimation of irrigated crop water consumption. J. Geophys. Res., 114 , D05114. doi:10.1029/2008JD010854.

    • Search Google Scholar
    • Export Citation
  • Tang, Q., Rosenberg E. A. , and Lettenmaier D. P. , 2009b: Use of satellite data to assess the impacts of irrigation withdrawals on Upper Klamath Lake, Oregon. Hydrol. Earth Syst. Sci., 13 , 617627.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tapley, B. D., Bettadpur S. , Ries J. C. , Thompson P. F. , and Watkins M. M. , 2004: GRACE measurements of mass variability in the Earth system. Science, 305 , 503505. doi:10.1126/science.1099192.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Troch, P., Durcik M. , Seneviratne S. , Hirschi M. , Teuling A. , Hurkmans R. , and Hasan S. , 2007: New data sets to estimate terrestrial water storage change. Eos, Trans. Amer. Geophys. Union, 88 .doi:10.1029/2007EO450001.

    • Search Google Scholar
    • Export Citation
  • Uppala, S. M., and Coauthors, 2005: The ERA-40 Re-Analysis. Quart. J. Roy. Meteor. Soc., 131 , 29613012. doi:10.1256/qj.04.176.

  • Wahr, J., Molenaar M. , and 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 , 3020530229.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wahr, J., Swenson S. , Zlotnicki V. , and Velicogna I. , 2004: Time-variable gravity from GRACE: First results. Geophys. Res. Lett., 31 , L11501. doi:10.1029/2004GL019779.

    • Search Google Scholar
    • Export Citation
  • Xie, P., Chen M. , Yang S. , Yatagai A. , Hayasaka T. , Fukushima Y. , and Liu C. , 2007: A gauge-based analysis of daily precipitation over East Asia. J. Hydrometeor., 8 , 607626.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yeh, P. J-F., and Famiglietti J. S. , 2008: Regional terrestrial water storage change and evapotranspiration from terrestrial and atmospheric water balance computations. J. Geophys. Res., 113 , D09108. doi:10.1029/2007JD009045.

    • Search Google Scholar
    • Export Citation
  • Zhu, C., and Lettenmaier D. P. , 2007: Long-term climate and derived surface hydrology and energy flux data for Mexico: 1925–2004. J. Climate, 20 , 19361946.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 2021 1065 69
PDF Downloads 678 125 11