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Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial WaterMonitoring 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 (approx.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(exp 9) 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.
Document ID
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
External Source(s)
Wood, Eric F.
(Princeton Univ. Princeton, NJ, United States)
Roundy, Joshua K.
(Princeton Univ. Princeton, NJ, United States)
Troy, Tara J.
(Princeton Univ. Princeton, NJ, United States)
van Beek, L. P. H.
(Utrecht Univ. Utrecht, Netherlands)
Bierkens, Marc F. P.
(Utrecht Univ. Utrecht, Netherlands)
Blyth, Eleanor
(Natural Environmental Research Council London, United Kingdom)
de Roo, Ad
(Joint Research Centre of the European Communities Ispra, Italy)
Doell. Petra
(Johann-Wolfgang-Goethe-Univ. Frankfurt am Main, Germany)
Ek, Mike
(National Centers for Environmental Prediction MD, United States)
Famiglietti, James
(California Univ. Irvine, CA, United States)
Gochis, David
(National Center for Atmospheric Research Boulder, CO, United States)
van de Giesen, Nick
(Delft Univ. of Technology Delft, Netherlands)
Houser, Paul
(George Mason Univ. Fairfax, VA, United States)
Jaffe, Peter R.
(Princeton Univ. Princeton, NJ, United States)
Kollet, Stefan
(Bonn Univ. Germany)
Lehner, Bernhard
(McGill Univ. Montreal, Quebec, Canada)
Lettenmaier, Dennis P.
(Washington Univ. Seattle, WA, United States)
Peters-Lidard, Christa
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Sivpalan, Murugesu
(Illinois Univ. at Urbana-Champaign Urbana, IL, United States)
Sheffield, Justin
(Princeton Univ. Princeton, NJ, United States)
Wade, Andrew
(Reading Univ. United Kingdom)
Whitehead, Paul
(Oxford Univ. Oxford, United Kingdom)
Date Acquired
August 25, 2013
Publication Date
May 6, 2011
Publication Information
Publication: Water Resources Research
Volume: 47
Subject Category
Earth Resources And Remote Sensing
Report/Patent Number
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