Hyperresolution global land surface modeling: Meeting a grand challenge for monitoring Earth's terrestrial water

  • Eric F. Wood
    Department of Civil and Environmental Engineering Princeton University Princeton New Jersey USA
  • Joshua K. Roundy
    Department of Civil and Environmental Engineering Princeton University Princeton New Jersey USA
  • Tara J. Troy
    Department of Civil and Environmental Engineering Princeton University Princeton New Jersey USA
  • L. P. H. van Beek
    Department of Physical Geography Utrecht University Utrecht Netherlands
  • Marc F. P. Bierkens
    Department of Physical Geography Utrecht University Utrecht Netherlands
  • Eleanor Blyth
    Centre for Ecology and Hydrology Wallingford UK
  • Ad de Roo
    Institute for Environment and Sustainability European Commission Joint Research Centre Ispra Italy
  • Petra Döll
    Institute of Physical Geography Goethe University Frankfurt Frankfurt am Main Germany
  • Mike Ek
    Environmental Modeling Center National Centers for Environmental Prediction Suitland Maryland USA
  • James Famiglietti
    UC Center for Hydrologic Modeling University of California Irvine California USA
  • David Gochis
    Research Applications Laboratory National Center for Atmospheric Research Boulder Colorado USA
  • Nick van de Giesen
    Department of Water Management Delft University of Technology Delft Netherlands
  • Paul Houser
    Department of Geography and GeoInformation Science George Mason University Fairfax Virginia USA
  • Peter R. Jaffé
    Department of Civil and Environmental Engineering Princeton University Princeton New Jersey USA
  • Stefan Kollet
    Meteorological Institute Bonn University Bonn Germany
  • Bernhard Lehner
    Department of Geography McGill University Montreal, Quebec Canada
  • Dennis P. Lettenmaier
    Department of Civil and Environmental Engineering University of Washington Seattle Washington USA
  • Christa Peters‐Lidard
    Hydrological Sciences Branch NASA Goddard Space Flight Center Greenbelt Maryland USA
  • Murugesu Sivapalan
    Department of Civil and Environmental Engineering and Department of Geography University of Illinois at Urbana‐Champaign Urbana Illinois USA
  • Justin Sheffield
    Department of Civil and Environmental Engineering Princeton University Princeton New Jersey USA
  • Andrew Wade
    School of Human and Environmental Science University of Reading Reading UK
  • Paul Whitehead
    School of Geography and the Environment University of Oxford Oxford UK

書誌事項

公開日
2011-05
権利情報
  • http://onlinelibrary.wiley.com/termsAndConditions#vor
DOI
  • 10.1029/2010wr010090
公開者
American Geophysical Union (AGU)

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説明

<jats:p>Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (∼10–100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface‐subsurface interactions due to fine‐scale topography and vegetation; improved representation of land‐atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10<jats:sup>9</jats:sup> unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a “grand challenge” to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.</jats:p>

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