Construction of Minirhizotron Facilities for Investigating Root Zone Processes

Cai, Gaochao; Vanderborght, Jan; Klotzsche, Anja; Kruk, Jan van der; Neumann, Joschka; Hermes, Normen; Vereecken, Harry

doi:10.2136/vzj2016.05.0043

Cited by 56 publications

(93 citation statements)

References 40 publications

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“…The experimental setup of the plots was described in detail in Cai et al (2016) and the model setup and the inverse modeling procedure that was used to determine the parameters by Cai et al (2017). For more detailed information about the setup and the inverse modeling procedure, we refer the reader to these publications.…”

Section: Methodsmentioning

confidence: 99%

Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions

Cai¹,

Vanderborght²,

Langensiepen

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. How much water can be taken up by roots and how this depends on the root and water distributions in the root zone are important questions that need to be answered to describe water fluxes in the soil-plant-atmosphere system. Physically based root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but used or tested far less. This study aims at evaluating the simulated RWU of winter wheat using the empirical Feddes-Jarvis (FJ) model and the physically based Couvreur (C) model for different soil water conditions and soil textures compared to sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty, with each of three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities, and root distributions with depth. The two models simulated the lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and treatments which are accounted for by the C model, whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWU could be accounted for directly by the physically based RWU model but not by empirical models that use normalized root density functions.

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Section: Methodsmentioning

confidence: 99%

Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions

Cai¹,

Vanderborght²,

Langensiepen

et al. 2018

Hydrol. Earth Syst. Sci.

Self Cite

View full text Add to dashboard Cite

show abstract

“…A sensor network with TDR sensors and one tensiometer was installed at each borehole depth and each treatment plot. For each treatment plot, four TDRs per depth were installed that measure the SWC hourly (for more details, see Cai et al, 2016). The TDR sensors are a three‐rod system with a rod length of 200 mm and a rod separation of 26 mm.…”

Section: Methodsmentioning

confidence: 99%

Monitoring Soil Water Content Using Time‐Lapse Horizontal Borehole GPR Data at the Field‐Plot Scale

Klotzsche

Lärm

Vanderborght

et al. 2019

Vadose Zone Journal

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4‐yr monitoring of soil water content dynamics for different plant types. Horizontal crosshole GPR at the field‐plot scale sampled ∼65 m3. Natural, irrigated, and sheltered treatments in gravelly and clayey–silty soils. Consistent patches of soil water content were observed along horizontal slices using GPR. Results enable improved investigation of soil–plant–atmosphere interactions. Ground penetrating radar (GPR) has shown a high potential to derive soil water content (SWC) at different scales. In this study, we combined multiple horizontal GPR measurements at different depths to investigate the spatial and temporal variability of the SWC under cropped plots. The SWC data were analyzed for four growing seasons between 2014 and 2017, two soil types (gravelly and clayey–silty), two crops (wheat [Triticum aestivum L.] and maize [Zea mays L.]), and three different water treatments. We acquired more than 150 time‐lapse GPR datasets along 6‐m‐long horizontal crossholes at six depths. The GPR SWC distributions are distinct both horizontally and vertically for both soil types. A clear change in SWC can be observed at both sites between the surface layer (>0.3 m) and subsoil. Alternating patches of higher and lower SWC, probably caused by the soil heterogeneity, were observed along the horizontal SWC profiles. To investigate the changes in SWC with time, GPR and time‐domain reflectometry (TDR) data were averaged for each depth and compared with changes in precipitation, treatment, and soil type. The high‐temporal‐resolution TDR and the large‐sampling‐volume GPR show similar trends in SWC for both sites, but because of the different sensing volumes, different responses were obtained due to the spatial heterogeneity. A difference in spatial variation of the crosshole GPR SWC data was detected between maize and wheat. The results for this 4‐yr period indicate the potential of this novel experimental setup to monitor spatial and temporal SWC changes that can be used to study soil–plant–atmosphere interactions.

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“…The parameters of the van Genuchten (1980) soil water retention function were fitted using measured SWC and soil water head data (Cai et al, 2016) (Table 2). The parameters, Ks, l, h3h, h3l, and ωc of the FJ model, Krs, and Kcomp of the C model were inversely estimated by fitting simulated to hourly measured SWP and SWC.…”

Section: Inverse Modeling and Model Setupmentioning

confidence: 99%

“…The experimental set up of the plots was described in detail in Cai et al (2016) and the model setup and the inverse modeling procedure that was used to determine the parameters by Cai et al (2017). For more detailed information on the setup and the inverse modeling procedure, we refer the reader to these publications.…”

mentioning

confidence: 99%

Root growth, water uptake, and sap flow of winter wheat in response to different soil water availability

Cai

Vanderborght

Langensiepen

et al. 2017

Preprint

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Abstract. How much and where water is taken up by roots from the soil profile are important questions that need to be answered to close the soil water balance equation and to describe water fluxes in the soil-plant-atmosphere system. Physicallybased root water uptake (RWU) models that relate RWU to transpiration, root density, and water potential distributions have been developed but far less used or tested. This study aims at evaluating the simulated RWU of winter wheat by the empirical Feddes-Jarvis (FJ) model and the physically-based Couvreur (C) model for different soil water conditions and soil textures 5 against sap flow measurements. Soil water content (SWC), water potential, and root development were monitored noninvasively at six soil depths in two rhizotron facilities that were constructed in two soil textures: stony vs. silty with each three water treatments: sheltered, rainfed, and irrigated. Soil and root parameters of the two models were derived from inverse modeling and simulated RWU was compared with sap flow measurements for validation. The different soil types and water treatments resulted in different crop biomass, root densities and root distributions with depth. The two models simulated the 10 lowest RWU in the sheltered plot of the stony soil where RWU was also lower than the potential RWU. In the silty soil, simulated RWU was equal to the potential uptake for all treatments. The variation of simulated RWU among the different plots agreed well with measured sap flow but the C model predicted the ratios of the transpiration fluxes in the two soil types slightly better than the FJ model. The root hydraulic parameters of the C model could be constrained by the field data but not the water stress parameters of the FJ model. This was attributed to differences in root densities between the different soils and 15 treatments which are accounted for by the C model whereas the FJ model only considers normalized root densities. The impact of differences in root density on RWU could be accounted for directly by the physically-based RWU model but not by empirical models that use normalized root density functions.

show abstract

Construction of Minirhizotron Facilities for Investigating Root Zone Processes

Cited by 56 publications

References 40 publications

Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions

Root growth, water uptake, and sap flow of winter wheat in response to different soil water conditions

Monitoring Soil Water Content Using Time‐Lapse Horizontal Borehole GPR Data at the Field‐Plot Scale

Root growth, water uptake, and sap flow of winter wheat in response to different soil water availability

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