Quantifying the Sensitivity of Land-Surface Models to Hydrodynamic Stress Limitations on Transpiration

Evapotranspiration is a major forcing function of Earth's climate, providing the link for the soil-plant-atmosphere continuum. Stomata conductance, which governs transpiration, also provides the link between latent heat flux and carbon uptake rates. Current land-surface models couple stomata conductance and soil moisture through empirical relationships. This approach does not take advantage of recent advances in our understanding of water flow and storage in trees or of tree and canopy structure. The lack of mechanistic representation of the tree-hydrodynamic process should therefore lead to typical intra-daily patterns of error in results of current models.We use a comparison between observational data and model outputs to characterize the patterns of intra-daily error in simulated water flux. Through the use of the North American Carbon Program (NACP) dataset, more than 10 years of water flux data for 25 Fluxnet sites has been analyzed. The diurnal pattern of latent heat flux error from each of the 10 land-surface models represented in this study allows for categorization and evaluation based on models’ ability to predict the fast temporal dynamics of transpiration in different ecosystems and atmospheric forcing. Distinct error patterns occur when soil moisture is non-limiting, when the soil is near the wilting point, when VPD is not limiting, and when VPD is high. Although model error patterns are site specific, there are models that are more likely to favor one pattern above the other based on the stomata conductance scheme used and its sensitivity to VPD and soil moisture. We contrast these error patterns with sap flux, soil moisture, and leaf water potential measurements conducted in a Northern forest at the University of Michigan Biological Station (UMBS) in Pellston, MI, one of the Fluxnet sites included in the NACP analysis. The co-analysis of the physical process of water transport in the UMBS forest with the errors in model simulated latent heat flux reveals that model error is largest and most variable when moisture conditions are moderate to limiting and vegetative dynamics dominate. We find that models do best when moisture conditions are non-limiting, but have trouble resolving the fast dynamics of transpiration.

Name thesis:degree_name

Master of Science

Level thesis:degree_level

masters

Discipline thesis:degree_discipline

Civil Engineering

Grantor dc:publisher

The Ohio State University

Year dc:date

2013

Author dc:creator

• Matheny, Ashley Michelle

Contributors dc:contributor

• Bohrer, Gil

• Civil Engineering
• Environmental Engineering
• Environmental Science
• Transpiration
• Land Surface Modeling
• Sap Flux
• UMBS
• Hydrodynamic Stress

Statement dc:rights

• unrestricted
• This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.

Language dc:language

English

Repository record dc:identifier

http://rave.ohiolink.edu/etdc/view?acc_num=osu1364572098

OAI identifier oai:identifier

oai:etd.ohiolink.edu:osu1364572098