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Improving the representation of hydrologic processes in Earth System Models
Author(s) -
Clark Martyn P.,
Fan Ying,
Lawrence David M.,
Adam Jennifer C.,
Bolster Diogo,
Gochis David J.,
Hooper Richard P.,
Kumar Mukesh,
Leung L. Ruby,
Mackay D. Scott,
Maxwell Reed M.,
Shen Chaopeng,
Swenson Sean C.,
Zeng Xubin
Publication year - 2015
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2015wr017096
Subject(s) - water cycle , hydrological modelling , benchmarking , earth system science , environmental science , hydrology (agriculture) , environmental resource management , process (computing) , temporal scales , scale (ratio) , computer science , climatology , geography , geology , business , ecology , oceanography , geotechnical engineering , cartography , marketing , biology , operating system
Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large‐scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater‐surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.