Watershed Reanalysis of Water and Carbon Cycle Models at a Critical Zone Observatory. Yu, X., Duffy, C., Kaye, J., Crow, W., Bhatt, G., & Shi, Y. Remote Sensing of the Terrestrial Water Cycle, 206:493, 2014. ![Watershed Reanalysis of Water and Carbon Cycle Models at a Critical Zone Observatory [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex This chapter compares the physics-based watershed model Penn State Integrated Hydrologic Model (PIHM) and an ecophysiological model BioGeochemical Cycles (Biome-BGC) to gain insight into the strengths and weakness of each in the context of a new watershed sensor and reanalysis data set. To bring in correspondence with the intensive regional observation, the chapter focuses on model evaluation and assessment of coupling with primary objectives to (a) demonstrate how hydrological and biogeochemical models could resolve the multiple sources of high-resolution regional observation, (b) determine how coupled models could help with the interpretation of interaction between water and carbon cycles, and (c) how these, in turn, influence the evolution and design of process-based coupling in the future generations of integrated environmental models.
@article{yu_watershed_2014,
title = {Watershed {Reanalysis} of {Water} and {Carbon} {Cycle} {Models} at a {Critical} {Zone} {Observatory}},
volume = {206},
url = {http://dx.doi.org/10.1002/9781118872086.ch31},
doi = {10.1002/9781118872086.ch31},
abstract = {This chapter compares the physics-based watershed model Penn State Integrated Hydrologic Model (PIHM) and an ecophysiological model BioGeochemical Cycles (Biome-BGC) to gain insight into the strengths and weakness of each in the context of a new watershed sensor and reanalysis data set. To bring in correspondence with the intensive regional observation, the chapter focuses on model evaluation and assessment of coupling with primary objectives to (a) demonstrate how hydrological and biogeochemical models could resolve the multiple sources of high-resolution regional observation, (b) determine how coupled models could help with the interpretation of interaction between water and carbon cycles, and (c) how these, in turn, influence the evolution and design of process-based coupling in the future generations of integrated environmental models.},
journal = {Remote Sensing of the Terrestrial Water Cycle},
author = {Yu, Xuan and Duffy, Christopher and Kaye, Jason and Crow, Wade and Bhatt, Gopal and Shi, Yuning},
year = {2014},
pages = {493},
}
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