Comparing root water uptake profile estimations from an isotope-calibrated mechanistic model and a mixing model

Yamanaka, Tsutomu; Kimura, Takeo; Sun, Xinchao; Kato, Hiroaki; Onda, Yuichi

doi:10.3178/hrl.11.161

Cited by 3 publications

(11 citation statements)

References 45 publications

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“…The performance of water flux estimation by the isoRHEA model has been validated for a Chamaecyparis obtusa stand (Yamanaka et al, ), whereas it was not validated for the other stands. Uncertainties in assigned parameter values (e.g., stomatal resistance) may introduce errors to the flux estimation.…”

Section: Resultsmentioning

confidence: 99%

“…myrsinaefolia and undergrowth were not apparent. Therefore, we considered isotopic fractionation due to soil evaporation on the basis of the Craig–Gordon model (Craig & Gordon, ; Yamanaka et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…Analogous to Ohm's law, the root water uptake by trees for each species is given as:

U_{r} = \frac{ψ_{rc} - ψ}{r_{italictot}} = \frac{ψ_{rc} - ψ}{r_{sm} + r_{rs} + r_{rx}},

ψ_{rc} = \frac{((), \sum_{i = 1}^{n} \frac{ψ}{r_{italictot}}) - T_{r}}{\sum_{i = 1}^{n} \frac{1}{r_{italictot}}},

where U r (kg m −2 s −1 ) is the root water uptake from each soil layer for each species, ψ rc (J kg −1 ) is the plant water potential at the root crown, ψ (J kg −1 ) is the water potential in a soil layer, r tot (m 4 s −1 kg −1 ) is the total resistance, r sm (m 4 s −1 kg −1 ) is the soil matrix resistance, r rs (m 4 s −1 kg −1 ) is the root surface resistance, r rx (m 4 s −1 kg −1 ) is the root xylem resistance, i is the layer number, and n is the total number of the soil layers, and T r (kg m −2 s −1 ) is the transpiration rate for each species. The three resistances can be given as (modified from Yamanaka et al, ):

r_{sm} = \frac{1}{4 π K_{ψ} L_{r} Δ_{z}},

r_{rs} = \frac{θ_{sat} r_{rs}^{*}}{θ L_{r} Δ_{z}},

r_{rx} = \frac{r_{rx}^{*} z}{τ_{r} L_{r}},

…”

Section: Methodsmentioning

confidence: 99%

“…is the root surface resistance, r rx (m 4 s −1 kg −1 ) is the root xylem resistance, i is the layer number, and n is the total number of the soil layers, and T r (kg m −2 s −1 ) is the transpiration rate for each species. The three resistances can be given as (modified from Yamanaka et al, 2017): is the root tortuosity parameter. Consequently, RWUP is determined by the difference in water potential and resistance to the water flow within the root-soil system like a parallel circuit, as schematically illustrated in Figure 2.…”

Section: Model and Datamentioning

confidence: 99%

“…However, Ogle, Wolpert, and Reynolds (2004) developed a more comprehensive algorithm that reconstructs RWUP with an inverse estimation technique. In the present study, we employed an isotopeincorporated mechanistic model (Yamanaka, Kimura, Sun, Kato, & Onda, 2017) for reconstructing not only RWUP but also water balance and root zone hydrology.…”

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confidence: 99%

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Root functional change achieves water source separation under vegetation succession

Yamanaka

2018

Ecohydrology

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Water source separation can be one of strategies for different plant species to coexist in a community. This study first demonstrates mechanisms of water source separation during vegetation succession. An isotope‐incorporated mechanistic model was employed to simulate the xylem water isotopic composition and the root water uptake profile for a Pinus densiflora–Quercus myrsinaefolia mixed stand undergoing secondary succession and a pure P. densiflora stand before succession. In the mixed stand, the model successfully simulated the xylem water isotopic composition on the assumption that the root surface resistance per unit length of root (rrs*) decreases with increasing depth for P. densiflora but is constant for Q. myrsinaefolia. Uptake fraction for P. densiflora was greater in deeper zones but in shallower for Q. myrsinaefolia. In contrast, in the pure stand, a constant rrs* for P. densiflora gave good reproducibility in isotope simulation and shallow water uptake dominated. These findings highlight root functional change as a mechanism of water source separation; pre‐existing P. densiflora trees decrease their deep‐root rrs* to compensate for an increase in shallow‐root rrs*. This mechanism was caused by competition against invading Q. myrsinaefolia trees.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…Analogous to Ohm's law, the root water uptake by trees for each species is given as:

U_{r} = \frac{ψ_{rc} - ψ}{r_{italictot}} = \frac{ψ_{rc} - ψ}{r_{sm} + r_{rs} + r_{rx}},

ψ_{rc} = \frac{((), \sum_{i = 1}^{n} \frac{ψ}{r_{italictot}}) - T_{r}}{\sum_{i = 1}^{n} \frac{1}{r_{italictot}}},

r_{sm} = \frac{1}{4 π K_{ψ} L_{r} Δ_{z}},

r_{rs} = \frac{θ_{sat} r_{rs}^{*}}{θ L_{r} Δ_{z}},

r_{rx} = \frac{r_{rx}^{*} z}{τ_{r} L_{r}},

…”

Section: Methodsmentioning

confidence: 99%

Section: Model and Datamentioning

confidence: 99%

mentioning

confidence: 99%

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Root functional change achieves water source separation under vegetation succession

Yamanaka

2018

Ecohydrology

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A process‐based water stable isotope mixing model for plant water sourcing

Neil,

Fu,

2024

Ecohydrology

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Stable isotopes of hydrogen and oxygen in water are common tools for investigating water uptake apportionment, but many of the existing methods rely on simple linear mixing approaches that do not mechanistically incorporate additional information about site physical properties and conditions. Here, we develop a ‘physically based root water uptake isotope mixing estimation’ model (PRIME) that combines a continuous and parametric probability density function for root water uptake with site physical data in a process‐based linear mixing framework. To demonstrate the application of PRIME, water uptake patterns of boreal forest Pinus banksiana trees were estimated on four dates in 2019. To aid in validation, estimates were compared with that of the Bayesian linear mixing model framework, MixSIAR. The two approaches provided similar results, but due to its continuous and parametric nature, PRIME provided estimates of superior resolution, certainty, and model parsimony. Although both models incorporate additional physical information into their mixing frameworks, PRIME does so in a mechanistic manner, thereby reflecting the relevant hydrological processes more effectively than the purely empirical approach taken by MixSIAR. Furthermore, because PRIME uses a continuous function to describe the predicted uptake pattern, it allows users to quantify water uptake with essentially infinite resolution, through integration over the desired depth ranges. These findings demonstrate the advantages of utilizing a continuous, parametric, and process‐based mixing model to estimate root water uptake apportionment, thus providing a relatively simple yet powerful tool with which to approach plant water sourcing.

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Evapotranspirational processes in a dry deciduous forest in Cambodia: clarifying the respective contributions of overstory and understory vegetation to the hydrologic cycle

Iida

Shimizu

Tamai

et al. 2022

Nihon Suimon Kagaku Kaishi

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Comparing root water uptake profile estimations from an isotope-calibrated mechanistic model and a mixing model

Cited by 3 publications

References 45 publications

Root functional change achieves water source separation under vegetation succession

Root functional change achieves water source separation under vegetation succession

A process‐based water stable isotope mixing model for plant water sourcing

Evapotranspirational processes in a dry deciduous forest in Cambodia: clarifying the respective contributions of overstory and understory vegetation to the hydrologic cycle

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