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

水循环 生物地球化学循环 地球系统科学 环境科学 蒸散量 全球变化 背景(考古学) 持续性 水资源 环境资源管理 地球科学 气候变化 地理 地质学 生态学 化学 海洋学 考古 环境化学 生物
作者
Eric F. Wood,Joshua K. Roundy,Tara J. Troy,Rens van Beek,Marc F. P. Bierkens,Eleanor Blyth,Ad de Roo,Petra Döll,M. B. Ek,J. S. Famiglietti,David Gochis,Nick van de Giesen,Paul R. Houser,Peter R. Jaffé,Stefan Kollet,Bernhard Lehner,Dennis P. Lettenmaier,C. D. Peters‐Lidard,Murugesu Sivapalan,Justin Sheffield,Andrew J. Wade,P. G. Whitehead
出处
期刊:Water Resources Research [Wiley]
卷期号:47 (5) 被引量:769
标识
DOI:10.1029/2010wr010090
摘要

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 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.

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