Simulation of stand transpiration based on a xylem water flow model for individual trees

Hentschel, Rainer; Bittner, Sebastian; Janott, Michael; Biernath, Christian; Holst, Jutta; Ferrio, Juan Pedro; Geßler, Arthur; Priesack, Eckart

doi:10.1016/j.agrformet.2013.08.002

Cited by 19 publications

(17 citation statements)

References 70 publications

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“…Water transport through tracheid aggregates or vessels inter‐connected by end‐wall pits in the water‐conducting tissues can be treated as analogous to porous medium flow (Edwards et al ., ; Tyree, ; Früh & Kurth, ; Kumagai, ; Aumann & Ford, ; Bohrer et al ., ; Chuang et al ., ; Hentschel et al ., ; Manzoni et al ., ,c, ). Thus, a mass conservation equation is combined with Darcy's law to describe the water movement at the tissue‐scale and is given as:

\begin{matrix} \frac{\partial V_{normals} false(z false) {normalθ}_{normalp} false(z, t false)}{\partial t} = - \frac{\partial q_{normalp}}{\partial z} d z \\ q_{normalp} = - A_{normals} false(z false) K_{normalp} false(θ_{p} false) \frac{\partial {normalψ}_{normalp}}{\partial z} \\ {normalψ}_{normalp} = {normalϕ}_{normalp} + ρ g z, \end{matrix}

V_{normals} false(z false) = \int_{z}^{z + Δ z} A_{normals} false(z false) d z

is the sapwood volume between height z and z + Δ z above the soil surface,

θ_{p}

is the plant (or xylem) water content,

q_{normalp} false(z false)

is the sap flow rate driven by gradients in total water potential

ψ_{p}

, ρ is the water density, g is the gravitational acceleration,

K_{p}

is the plant hydraulic specific conductivity, and …”

Section: Descriptionmentioning

confidence: 99%

The effect of plant water storage on water fluxes within the coupled soil–plant system

et al. 2016

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In addition to buffering plants from water stress during severe droughts, plant water storage (PWS) alters many features of the spatio-temporal dynamics of water movement in the soil-plant system. How PWS impacts water dynamics and drought resilience is explored using a multi-layer porous media model. The model numerically resolves soil-plant hydrodynamics by coupling them to leaf-level gas exchange and soil-root interfacial layers. Novel features of the model are the considerations of a coordinated relationship between stomatal aperture variation and whole-system hydraulics and of the effects of PWS and nocturnal transpiration (Fe,night) on hydraulic redistribution (HR) in the soil. The model results suggest that daytime PWS usage and Fe,night generate a residual water potential gradient (Δψp,night) along the plant vascular system overnight. This Δψp,night represents a non-negligible competing sink strength that diminishes the significance of HR. Considering the co-occurrence of PWS usage and HR during a single extended dry-down, a wide range of plant attributes and environmental/soil conditions selected to enhance or suppress plant drought resilience is discussed. When compared with HR, model calculations suggest that increased root water influx into plant conducting-tissues overnight maintains a more favorable water status at the leaf, thereby delaying the onset of drought stress.

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\begin{matrix} \frac{\partial V_{normals} false(z false) {normalθ}_{normalp} false(z, t false)}{\partial t} = - \frac{\partial q_{normalp}}{\partial z} d z \\ q_{normalp} = - A_{normals} false(z false) K_{normalp} false(θ_{p} false) \frac{\partial {normalψ}_{normalp}}{\partial z} \\ {normalψ}_{normalp} = {normalϕ}_{normalp} + ρ g z, \end{matrix}

V_{normals} false(z false) = \int_{z}^{z + Δ z} A_{normals} false(z false) d z

is the sapwood volume between height z and z + Δ z above the soil surface,

θ_{p}

is the plant (or xylem) water content,

q_{normalp} false(z false)

is the sap flow rate driven by gradients in total water potential

ψ_{p}

, ρ is the water density, g is the gravitational acceleration,

K_{p}

is the plant hydraulic specific conductivity, and …”

Section: Descriptionmentioning

confidence: 99%

The effect of plant water storage on water fluxes within the coupled soil–plant system

et al. 2016

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“…The root distribution function, RDF, is described by an exponential function similar to Hentschel et al . [], so that the root density decreases with increasing depth,

RDF(z) = λ β^{normal(z/ L)},

where β is the shape parameter within a range of 0 to 1 (when β equals to 1, RDF corresponds to a uniform root density, when β is close to 0, RDF shows a steep exponential decrease of root length density from soil surface to the bottom root zone). L is the root zone depth, and λ is a weighting parameter to make

\sum_{z = 0}^{L} RDF(z) = 1

, which means

λ = 1 / \sum_{z = 0}^{L} β^{normal(z/ L)}

.…”

Section: Model Conceptualization and Formulationmentioning

confidence: 99%

“…A similar approach can be found in Hentschel et al . []. The reduction function is used to represent the stress of environmental conditions on transpiration.…”

Section: Model Conceptualization and Formulationmentioning

confidence: 99%

A vegetation‐focused soil‐plant‐atmospheric continuum model to study hydrodynamic soil‐plant water relations

Deng

Guan

Hutson

et al. 2017

Water Resources Research

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A novel simple soil-plant-atmospheric continuum model that emphasizes the vegetation's role in controlling water transfer (v-SPAC) has been developed in this study. The v-SPAC model aims to incorporate both plant and soil hydrological measurements into plant water transfer modeling. The model is different from previous SPAC models in which v-SPAC uses (1) a dynamic plant resistance system in the form of a vulnerability curve that can be easily obtained from sap flow and stem xylem water potential time series and (2) a plant capacitance parameter to buffer the effects of transpiration on root water uptake. The unique representation of root resistance and capacitance allows the model to embrace SPAC hydraulic pathway from bulk soil, to soil-root interface, to root xylem, and finally to stem xylem where the xylem water potential is measured. The v-SPAC model was tested on a native tree species in Australia, Eucalyptus crenulata saplings, with controlled drought treatment. To further validate the robustness of the v-SPAC model, it was compared against a soil-focused SPAC model, LEACHM. The v-SPAC model simulation results closely matched the observed sap flow and stem water potential time series, as well as the soil moisture variation of the experiment. The v-SPAC model was found to be more accurate in predicting measured data than the LEACHM model, underscoring the importance of incorporating root resistance into SPAC models and the benefit of integrating plant measurements to constrain SPAC modeling.

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“…。随着技术进步, 液流估算技术越来越成熟 (Kume et al, 2012;Shinohara et al, 2013;Chang et al, 2014b;de Dios et al, 2015), 热比率法作为目前最先进的单木树干液流测量技术 (van de Wal et al, 2015), 测量精度已在全球诸多研究中得到广泛论证, 同时测量技术也在不断地完善和规范 (Shinohara et al, 2013;Chang et al, 2014a;Sus et al, 2014;de Dios et al, 2015;van de Wal et al, 2015;Su et al, 2016) Kume et al, 2012;Hentschel et al, 2013;Shinohara et al, 2013) (2)(3) …”

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基于热比率法的青海云杉林蒸腾量估算

杨军军¹,

Jian²,

封建民³

et al. 2018

Chin. J. Plant Ecol.

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Simulation of stand transpiration based on a xylem water flow model for individual trees

Cited by 19 publications

References 70 publications

The effect of plant water storage on water fluxes within the coupled soil–plant system

The effect of plant water storage on water fluxes within the coupled soil–plant system

A vegetation‐focused soil‐plant‐atmospheric continuum model to study hydrodynamic soil‐plant water relations

基于热比率法的青海云杉林蒸腾量估算

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