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Improving the representation of vegetation-atmosphere interactions through plant-hydrodynamics models
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| Created: | Aug 20, 2018 at 6:41 p.m. | |
| Last updated: | Aug 20, 2018 at 6:43 p.m. | |
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Abstract
Hydrologic Feedbacks with Ecosystems
Chair: Gretchen Miller (Texas A&M University)
Advancements in ecohydrology have highlighted the importance of feedbacks between vegetation and the hydroclimate, with their subsequent impacts on water and food supplies. In this session, we discuss these feedbacks across a range of ecosystems and scales, highlighting recent and developing improvements in their modeling.
"Improving the representation of vegetation-atmosphere interactions through plant-hydrodynamics models"
Speaker: Ashley Matheny (University of Texas at Austin)
Vegetation provides a critical pathway for water transport from the land surface to the atmosphere; yet, the ability of vegetation to actively modulate water uptake and release makes this a challenging process for land-atmosphere models to capture. Recently, a number of physical process models of water flow through vegetation have come to the fore. These models draw a parallel between vegetation’s conductive tissues and porous media. The FETCH2 scalable vegetation model uses a simplified form of the Richards equation to simulate water movement within trees while allowing for dynamic changes in hydraulic conductance and capacitance. In this manner, FETCH2 can capture divergent hydrodynamic behaviors among species in the same ecosystem in manners that standard land-atmosphere models cannot. FETCH2 and other mechanistic vegetation models stand to promote significant improvements to our ability to model transpiration at local to global scales. In particular, this new class of plant hydraulics models stands to revolutionize the way models capture the effects of drought, land use and land cover change, and climate change on the hydrologic and carbon cycles as well as on vegetation demography.
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| Title | Owners | Sharing Status | My Permission |
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| CUAHSI's 2018 Biennial Colloquium | Liz Tran | Public & Shareable | Open Access |
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This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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