Bayesian inference of hydraulic properties in and around a white fir using a process-based ecohydrologic model

E. C. Massoud; A. J. Purdy; B. O. Christoffersen; L. S. Santiago; C. Xu

doi:10.1016/j.envsoft.2019.01.022

Bayesian inference of hydraulic properties in and around a white fir using a process-based ecohydrologic model

E. C. Massoud, A. J. Purdy, B. O. Christoffersen, L. S. Santiago, C. Xu

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We present a parameter estimation study of the Soil-Tree-Atmosphere Continuum (STAC) model, a process-based model that simulates water flow through an individual tree and its surrounding root zone. Parameters are estimated to optimize the model fit to observations of sap flux, stem water potential, and soil water storage made for a white fir (Abies concolor) in the Sierra Nevada, California. Bayesian inference is applied with a likelihood function that considers temporal correlation of the model errors. Key vegetation properties are estimated, such as the tree's root distribution, tolerance to drought, and hydraulic conductivity and retention functions. We find the model parameters are relatively non-identifiable when considering just soil water storage. Overall, by utilizing multiple processes (e.g. sap flow, stem water potential, and soil water storage) during the parameter estimation, we find the simulations of the soil and tree water properties to be more accurate when compared to observed data.

Original language	English
Pages (from-to)	76-85
Number of pages	10
Journal	Environmental Modelling and Software
Volume	115
DOIs	https://doi.org/10.1016/j.envsoft.2019.01.022
State	Published - May 2019
Externally published	Yes

Funding

The authors appreciate support from the SCGSR fellowship of the Department of Energy (E.M.), the UC-Lab Fees Research Program Award 237285 (E.M.), the LFR-18-542511 (C.X.), and the DOE Office of Science Next Generation Ecosystem Experiment at Tropics (NGEE-T) project (C.X.). The authors are also grateful to Dr. Jasper A. Vrugt for providing the tools needed to conduct this study, including the STAC model source code, the calibration data from the KREW site, as well as discussion that inspired ideas.

Funders	Funder number
DOE Office of Science
U.S. Department of Energy	237285, LFR-18-542511

Keywords

Climate
Ecohydrology
Hydraulics
MCMC
Parameter estimation
Vegetation

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10.1016/j.envsoft.2019.01.022

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title = "Bayesian inference of hydraulic properties in and around a white fir using a process-based ecohydrologic model",

abstract = "We present a parameter estimation study of the Soil-Tree-Atmosphere Continuum (STAC) model, a process-based model that simulates water flow through an individual tree and its surrounding root zone. Parameters are estimated to optimize the model fit to observations of sap flux, stem water potential, and soil water storage made for a white fir (Abies concolor) in the Sierra Nevada, California. Bayesian inference is applied with a likelihood function that considers temporal correlation of the model errors. Key vegetation properties are estimated, such as the tree's root distribution, tolerance to drought, and hydraulic conductivity and retention functions. We find the model parameters are relatively non-identifiable when considering just soil water storage. Overall, by utilizing multiple processes (e.g. sap flow, stem water potential, and soil water storage) during the parameter estimation, we find the simulations of the soil and tree water properties to be more accurate when compared to observed data.",

keywords = "Climate, Ecohydrology, Hydraulics, MCMC, Parameter estimation, Vegetation",

author = "Massoud, {E. C.} and Purdy, {A. J.} and Christoffersen, {B. O.} and Santiago, {L. S.} and C. Xu",

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doi = "10.1016/j.envsoft.2019.01.022",

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AU - Massoud, E. C.

AU - Purdy, A. J.

AU - Christoffersen, B. O.

AU - Santiago, L. S.

AU - Xu, C.

PY - 2019/5

Y1 - 2019/5

N2 - We present a parameter estimation study of the Soil-Tree-Atmosphere Continuum (STAC) model, a process-based model that simulates water flow through an individual tree and its surrounding root zone. Parameters are estimated to optimize the model fit to observations of sap flux, stem water potential, and soil water storage made for a white fir (Abies concolor) in the Sierra Nevada, California. Bayesian inference is applied with a likelihood function that considers temporal correlation of the model errors. Key vegetation properties are estimated, such as the tree's root distribution, tolerance to drought, and hydraulic conductivity and retention functions. We find the model parameters are relatively non-identifiable when considering just soil water storage. Overall, by utilizing multiple processes (e.g. sap flow, stem water potential, and soil water storage) during the parameter estimation, we find the simulations of the soil and tree water properties to be more accurate when compared to observed data.

AB - We present a parameter estimation study of the Soil-Tree-Atmosphere Continuum (STAC) model, a process-based model that simulates water flow through an individual tree and its surrounding root zone. Parameters are estimated to optimize the model fit to observations of sap flux, stem water potential, and soil water storage made for a white fir (Abies concolor) in the Sierra Nevada, California. Bayesian inference is applied with a likelihood function that considers temporal correlation of the model errors. Key vegetation properties are estimated, such as the tree's root distribution, tolerance to drought, and hydraulic conductivity and retention functions. We find the model parameters are relatively non-identifiable when considering just soil water storage. Overall, by utilizing multiple processes (e.g. sap flow, stem water potential, and soil water storage) during the parameter estimation, we find the simulations of the soil and tree water properties to be more accurate when compared to observed data.

KW - Climate

KW - Ecohydrology

KW - Hydraulics

KW - MCMC

KW - Parameter estimation

KW - Vegetation

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M3 - Article

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SP - 76

EP - 85

JO - Environmental Modelling and Software

JF - Environmental Modelling and Software

ER -

Bayesian inference of hydraulic properties in and around a white fir using a process-based ecohydrologic model

Abstract

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Keywords

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