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Root water uptake is a major process controlling water balance and accounts for about 60% of global terrestrial evapotranspiration. The root system employs different strategies to better exploit available soil water, however, the regulation of water uptake under the spatiotemporal heterogeneous and uneven distribution of soil water is still a major question. To tackle this question, we need to understand how plants cope with this heterogeneity by adjustment of above ground responses to partial rhizosphere drying. Therefore, we use R-SWMS simulating soil water flow, flow towards the roots, and radial and the axial flow inside the root system to perform numerical experiments on a 9-cell gridded rhizotrone (50 cm×50 cm). The water potentials in each cell can be varied and fixed for the period of simulation and no water flow is allowed between cells while roots can pass over the boundaries. Then a static mature maize root architecture to different extents invaded in all cells is subjected to the various arrangements of cells' soil water potentials. R-SWMS allows determining possible hydraulic lift in drier areas. With these simulations, the variation of root water and leaf water potential will be determined and the role of root length density in each cell and corresponding average soil-root water potential will be statistically discussed.

Recent advances in scaling up water flows on root system networks hold promise for improving predictions of water uptake at large scales. These developments are particularly timely, as persistent difficulties in getting Earth system models to accurately represent soil-root water flows, especially under drying or heterogeneous soil moisture conditions, are now a major obstacle describing the water limitation of terrestrial fluxes.One recently developed upscaling formalism has been shown to be both free of discretisation error in flow predictions regardless of scale and with computational cost linearly diminishing with the number of soil subdomains considered. What has been missing from this approach, however, is a proven method to apply it generally – i.e. to an arbitrary root system architecture discretised on an arbitrary grid.The work presented here demonstrates a general algorithm that can be applied to a wide range of root system architectures (the only assumption being that only one lateral root originates at one point along a parent root) discretised on a grid consisting of a series of soil layers of variable thickness, as is common in Earth system models. It is further shown theoretically that both of these restrictions can in principle be relaxed and that this approach can in principle be extended to conditions of soil moisture heterogeneity – i.e. situations where each root segment in a soil grid cell faces a different water potential at the soil-root interface.This work represents both a practical advance bringing broad applicability to this upscaling approach and a major theoretical advance as exact solutions for water uptake under conditions of soil moisture heterogeneity within grid cells were previously unknown. While obtaining exact solutions despite heterogeneity within the grid cell requires a way of finding the overall mean soil water potential faced by the plant, this advance nevertheless points to possible directions of future research for overcoming the major hurdle of soil moisture heterogeneity.

The fundamental question as to what triggers stomatal closure during soil drying remains contentious. Thus, we urgently need to improve our understanding of stomatal response to water deficits in soil and atmosphere. Here, we investigated the role of soil-plant hydraulic conductance (Ksp) on transpiration (E) and stomata regulation. We used a root pressure chamber to measure the relation between E, leaf xylem water potential (ψleaf-x) and soil water potential (ψsoil) in tomato. Additional measurements of ψleaf-x were performed with unpressurized plants. A soil-plant hydraulic model was used to simulate E(ψleaf-x) for decreasing ψsoil. In wet soils, E(ψleaf-x) had a constant slope while in dry soils the slope decreased, with ψleaf-x rapidly and nonlinearly decreasing for moderate increases in E. The ψleaf-x measured in pressurized and unpressurized plants matched well, which indicates that the shoot hydraulic conductance did not decrease during soil drying and that the decrease in Ksp is caused by a decrease in soil-root conductance. The decrease of E matched well the onset of hydraulic nonlinearity. Our findings demonstrate that stomatal closure prevents the drop in ψleaf-x caused by a decrease in Ksp and elucidate a strong correlation between stomatal regulation and belowground hydraulic limitation.

Plant water uptake from soil is an important component of terrestrial water cycle with strong links to the carbon cycle and the land surface energy budget. To simulate the relation between soil water content, root distribution, and root water uptake, models should represent the hydraulics of the soil-root system and describe the flow from the soil towards root segments and within the 3D root system architecture according to hydraulic principles. We have recently demonstrated how macroscopic relations that describe the lumped water uptake by all root segments in a certain soil volume, e.g. in a thin horizontal soil layer in which soil water potentials are uniform, can be derived from the hydraulic properties of the 3D root architecture. The flow equations within the root system can be scaled up exactly and the total root water uptake from a soil volume depends on only two macroscopic characteristics of the root system: the root system conductance, Krs, and the uptake distribution from the soil when soil water potentials in the soil are uniform, SUF. When a simple root hydraulic architecture was assumed, these two characteristics were sufficient to describe root water uptake from profiles with a non-uniform water distribution. This simplification gave accurate results when root characteristics were calculated directly from the root hydraulic architecture. In a next step, we investigate how the resistance to flow in the soil surrounding the root can be considered in a macroscopic root water uptake model. We specifically investigate whether the macroscopic representation of the flow in the root architecture, which predicts an effective xylem water potential at a certain soil depth, can be coupled with a model that describes the transfer from the soil to the root using a simplified representation of the root distribution in a certain soil layer, i.e. assuming a uniform root distribution.

Sustaining world food production under a changing climate and a growing population demands for higher optimization of agricultural resources including water. This requires an accurate understanding and prediction of root water uptake from soils, which depends on several root traits. The role of root hairs in root water uptake is still under debate, with experimental data that both prove and reject the hypothesis that root hairs can facilitate root water uptake, especially under drought conditions. Our objective was to investigate the effect of root hairs in maize at the field scale. A wildtype maize variety (with root hairs) and a hairless mutant were grown in two substrates (loam and sand) at a field site near Halle, Germany (Vetterlein et al., 2020, JPLN). Transpiration, leaf water potential, soil water content and potentials were monitored during 2019 and 2020. Root length density and leaf area were measured at four different plant development stages. A version of Hydrus 1D coupled with Couvreur’s macroscopic root water uptake model (Couvreur et al., 2012, HESS) was parameterized and used to further investigate soil-water relations in this field experiment. In both years, plants emptied the available water in the profile by July, and relied on rain and irrigation afterwards. Non-significant differences in cumulative water losses from the soil, estimated from soil water content measurements, were observed among the four treatments in both years. These results are in agreement with simulated water losses, which also showed small differences in cumulative transpiration among treatments. Mutant plants developed significantly smaller shoots while transpiring similar water volumes as wildtype plants, indicating lower water use efficiency. While there was no visible effect of the genotype in the soil-water relations, a clear effect of the soil type was observed. Simulated collar water potentials and field observations of rolled leaves indicated water stress occurred first in the loam compared to the sand treatments. Plants grew faster in the loam, leading to earlier onset of water stress. Even though plants in the loam produced less roots than in the sand, the onset of stress was not caused by the smaller root system since simulations presuming a larger root system did not predict a later onset of stress. Similarly, a simulation run using a smaller root system in the sandy soil did not predict a significantly earlier onset of stress. Finally, although our model simulations considered only differences in root density among treatments and did not consider different root or rhizosphere properties of the different soils and genotypes, it simulated the observed water dynamics well. Water depletion in the loamy soil was simulated earlier than it was measured. We hypothesize that this is caused by changing root hydraulic properties when roots develop and mature, and suggest that young roots do not start taking up water immediately. Nevertheless, the data quantity and quality obtained in this field experiment exposes the difficulties and challenges we face to monitor water potentials and fluxes in the soil-plant continuum in annual grasses at the field scale.

Minimizing water limitation during growth of agricultural crops is crucial to unlocking full yield potentials. Crop yield losses vary according to timing and severity of water limitations, but even short-term droughts can be a major cause of yield losses. While the potential influence of deep roots on water uptake has been highlighted numerous times, the actual contribution of deep roots to water uptake is yet to be revealed. The objective of this study is to get an understanding of what limits deep water uptake by deep-rooted crops under topsoil water limitations.We found that deep-rooted crops experience water limitations despite access to water stored in the deep soil and we hypothesize that deep water uptake by deep-rooted crops is limited by 1) the hydraulic conductivity of the deeper part of the root zone, arising from limited root length density in combination with the hydraulic resistance of the roots or 2) by a hormonal response arising from the plant sensing dry conditions in the shallow soil leading to stomata closure, to conserve water. The two hypotheses can of course not be valid simultaneously, but both might be valid under certain conditions, at certain times or for certain species.In a large-scale semi-field setup, we grow oil seed rape and by combining measures of root development, root hydraulic conductivity, transpiration, stomatal conductance, ABA concentrations and soil water content from a large scale semi-field setup with a mechanistic 3-D root-soil modelling approach (R-SWMS), we are able to us distinguish various scenarios and to evaluate what limits deep water uptake.

Plant transpiration and root water uptake are dependent on multiple traits that interact with site soil characteristics and environmental factors such as radiation, atmospheric temperature, relative humidity, and soil-moisture content. Models of root architecture and functions are increasingly employed to simulate root-soil interactions. Root water uptake is thereby affected by the root hydraulic architecture, soil moisture conditions, soil hydraulic properties, and the transpiration demand as controlled by atmospheric conditions. Stomatal conductance plays a vital role in regulating transpiration in plants. We performed simulations of plant water uptake for plants having different mechanisms to control transpiration, spanned by isohydric/anisohydric spectrum. Isohydric plants follow the strategy to close their stomata in order to maintain the leaf water potential at a constant level, while anisohydric plants leave their stomata open when leaf water potentials fall due to drought stress. Modelling the stomatal regulation effectively will result in a more reliable model that will regulate the excessive loss of water. We implemented hydraulic and chemical stomatal control of root water uptake following the current approach where stomatal control is regulated by simulated water potential and/or chemical signal concentration. In order to maintain water uptake from dry soil, low plant water potentials are required, which may lead to reversible or permanent cavitation. We parameterise our model with field data, including climate data and soil hydraulic properties under different tillage conditions. This helps us to understand the behaviour of different crops under drought conditions and predict at which growing stage the stress hits the plant. We conducted the simulations for different scenarios to study the effect of hydraulic and chemical regulation on root system performance under drought stress.

In the past decade, plant root water uptake (RWU) has been a major focus of ecohydrological studies employing water stable isotopes. The interest of the isotopic community for RWU rose concomitantly to the development of open-access multi-source mixing models based on Bayesian inference. Another more general reason was certainly the decrease in analytical cost with the advent of isotope-specific laser absorption spectrometry. The isotopic methodology used to determine relative profiles of RWU works on the premises that (i) RWU does not fractionate stable isotopes in water and (ii) the isotopic composition of water inside the xylem vessel of the last non-evaporating part of the plant (typically the stem) is that of RWU. Following a simple mass balance approach, the isotopic composition of RWU can be linked back by inversion to contributions to RWU (i.e., relative RWU) of a set of potential water sources (of known isotopic compositions) originating from the soil profile.In recent research, the preferred tool for inverting water isotope data was Bayesian models and the literature shows that only a handful of studies complemented isotope analysis with observation of plant water status and flow. Consequently, most of the gathered information on RWU cannot be used to test hypotheses on which are built physically-based soil-root water flow models. The authors have on the other hand initiated an effort within the framework of dual experimental-modeling approaches, where tightly-controlled experiments are thought and prepared in order to validate, parameterize models, or test hypotheses. The present contribution gives an overview of the different attempts at integrating both water and isotope observations types and confronting them to model simulations explicitly accounting for root system architecture and hydraulic properties. It addresses the meaningfulness and limitations of isotope data, especially in the context of labeling experiments when treated with statistical (e.g. Bayesian) models. We finally propose a way forward and present improvements to be achieved on both experimental and modeling sides to increase the reliability and precision of isotope-derived estimates of RWU.

Estimating plant uptake of soil water has been a persistent problem in process-based earth system models (ESMs). Initially ignored altogether, plant access to soil water was long modelled with heuristic approaches at large scales. These formulations are currently being replaced as ESMs begin to incorporate more detailed plant hydraulics schemes based on the soil-plant-atmosphere continuum concept. While the new schemes greatly improve mechanistic description of aboveground plant hydraulics, they have given rise to various issues belowground, from excessive hydraulic redistribution to numerical instability. As detailed 3D descriptions of root systems and water flow equations on the soil-root domain have been established, the key challenge is how to scale them up to relevant scales, reducing computational cost to a trivial level without loss of accuracy. Here, we set out a mathematical framework that incorporates recent advances in this area and allows us to relate them to each other. Comparing and contrasting different models, formulated in a novel matrix form of the water flow problem in the root system, allows us to make inferences about their suitability for use in upscaling. We are able to show how to avoid discretization error in the upscaled root scheme, as well as which upscaling method offers full generality, and which yields the computationally simplest forms. These theoretical results are fully supported by numerical simulations of fully explicit 3D root systems and their upscaled versions. Improved performance of the upscaled models is also demonstrated in an application to field data from the Wind River Crane flux tower site (reduced model bias, root mean squared error, and increased robustness of fitted parameters). Root water uptake equations can now be scaled up without discretization error for arbitrary root systems. The chief remaining source of error is soil moisture heterogeneity within discretized soil elements where it is assumed uniform by any given model (e.g. within each vertical layer). The main task for future work thus becomes to achieve a correspondingly accurate description for soil moisture heterogeneity. Some of the upscaling approaches compared here offer hints at potential next steps in this direction.

Isotopic labeling techniques have the potential to minimize the uncertainty of plant root water uptake (RWU) profiles estimated through multi-source (statistical) modeling, by artificially enhancing soil water isotopic gradient. Furthermore, physical models can account for hydrodynamic constraints to RWU if simultaneous soil and plant water status data is available. In this study, a population of tall fescue (Festuca arundinacae cv Soni) was grown in a macro-rhizotron setup under semi-controlled conditions to monitor such variables for a 34-hours long period following the oxygen stable isotopic (18O) labeling of deep soil water. Aboveground variables included tiller and leaf water oxygen isotopic compositions as well as leaf water potential (ψleaf), relative humidity, and transpiration rate. Belowground profiles of root length density (RLD), soil water content and isotopic composition were also sampled. While there were strong correlations between hydraulic variables as well as between isotopic variables, the experimental results underlined the discrepancy between variations of hydraulic and isotopic variables. In order to dissect the problem, we reproduced both types of observations with a one-dimensional physical model of water flow in the soil-plant domain, for 60 different realistic RLD profiles. While simulated ψleaf followed clear temporal variations with little differences across plants as if they were “on board of the same rollercoaster”, simulated δtiller values within the plant population were rather heterogeneous (“swarm-like”) with relatively little temporal variation and a strong sensitivity to rooting depth. The physical model thus suggested that the discrepancy between isotopic and hydraulic observations was logical, as the variability captured by the former was spatial and may not correlate with the temporal dynamics of the latter. For comparison purposes a Bayesian statistical model was also used to simulate RWU. While they predicted relatively similar cumulative RWU profiles, the physical model could differentiate spatial from temporal dynamics of the isotopic signature, and supported that the local increase of soil water content and formation of a peak of labelled water observed overnight were due to hydraulic lift.

Electrical anisotropy is a typical feature observed in geology and can be used to characterize sub-surface heterogeneity (Al-Hazaimay et al., 2016). In soil-root medium, the effective electrical anisotropy factor (EAF) in electrical conductivity (EC) is due to root processes such as root water uptake, root architectural evolution, exudation and solute uptake. Under homogeneous soil conditions, (i.e. well irrigated scenario and no water uptake pattern in the soil) and with root water uptake (Javaux et al., 2008), we hypothesize that EAF of soil-root medium could contain information on root architecture (geometrical indices) and thus can be used for phenotyping root systems. To support our hypothesis, we performed 2D finite-element modeling of these properties in terms of EC distribution for a series of simulated root systems, with explicit representation of the root architecture in the finite-element mesh. We then find the correlation between geometry of root network and EAF and assess under what condition will there exist high correlation and hence EAF could provide information on root architecture. Root architecture was explicitly resolved in the finite element mesh along with root water uptake (Javaux et al., 2008). To parameterize the model, we measured complex conductivity of Maize root segments at different frequencies (IP spectra). The roots elements in the finite element mesh had frequency dependent electrical properties, including the resolution of cortex and stele. Effective electrical anisotropy and geometrical anisotropy are examined for different synthetic root architecture generated in Crootbox software. We then relate the modeled effective electrical anisotropy to the geometrical anisotropy of root structure. To formulate geometrical anisotropy, we discuss different approaches. We also demonstrate high correlation between geometrical anisotropy of root networks and simulated electrical anisotropy of effective conductivity of soil-root continuum. The understanding of relation between geometry of root network, electrical conductivity contrast between soil-root and effective electrical property of soil-root continuum is very important to monitor rooted zone via electrical methods and our modeling results helps to give insight.

Climatic projections indicate that Europe should face a significant change in seasonal rainfall distribution, with up to 25% less precipitations in Summer by the end of the 21st century.. The yield of grasslands, that make for a large part of Belgian agricultural system, would be amongst the most affected by these new scenarios of water deficit. The ovseral goal of the ForDrought project, launched at UCLouvain in 2012, is to improve the performance of forage crops to cope with climate change. The specific objectives of this study were to observe the responses of root systems of grassland plants exposed to a water deficit and to assess the value of plant species association. The species studied were Dactylis glomerata and Medicago sativa. Large pits were dug on the border of experimental plots of pure and mixed composition, exposed or not to a one-month long summer drought, to carry out different root system observations. The number of roots in each pit were counted following the trench profile method. In addition, roots were extracted from vertical and horizontal soil cores and root DNA was analysed to determine the specific root distribution of each species. The parcels were harvested and yield measured four times over the course of one year. Finally, the soil profile and the depth of the ploughpan for each plot were also determined. The results showed that a water deficit had an impact on the root density of both species. However, this impact differed between species: Medicago had more roots when exposed to the deficit while Dactylis tended to produce fewer roots. The genetic analysis turned out to be biased against Dactylis which could not be detected when it was mixed with Medicago, despite many protocol adjustments were implemented to circumvent the problem. The yield was negatively impacted by water deficit, for all plots. The association of species did not produce any clear effect on the yield. However, the soil observation showed that the ploughpan was abnormally thick in all of plots, which may have limited the expression of the species specificities and of the differences between pure and mixed stands.

Existing literature about maize root system hydraulic and architectural properties is abundant and can serve as input for contrasted root system hydraulic architecture generation tools. Therefore observations of root hydraulic and architectural phenes in field and/or laboratory experiments must be first converted into parameters for feeding root growth model and water flow algorithms. MARSHAL aims at gathering the existing information about the maize plant and at making it available for the community. Existing maize root system architecture parameterizations as well as measured hydraulic functions were gathered in a common database and linked with the state-of-art model of the water transfer in the soil-plant-atmosphere continuum. MARSHAL is as an online and flexible tool that generates contrasted root system hydraulic architectures using this database, calculates the water flow within the root system under user-provided boundary conditions (transpiration and soil water potential distribution) and calculates plant-scale macroscopic parameters. The generated root systems hydraulic architectures can be saved in common formats such as RSML to be easily imported in other models. Finally, MARSHAL is coupled with sensitivity and optimization algorithms in order to investigate the sensitive input parameters for a used-defined objective function or to provide an optimal set of parameters that minimizes an error function, alongside with parameter uncertainty. As illustration of the model potentiality, we used MARSHAL to generate maize contrasted hydraulic architectures and we compared them with plant-scale observations of both architecture (root length density profile field measurements) and hydraulics (root system conductance measurements). The macroscopic parameters could be easily fitted with the model and the observed local variability of root phenes determined. The hydraulic architectures were then used as contrasted genotypes in a water flow model of the soil-plant-atmosphere continuum to highlight G x E interactions and they indeed performed differently in contrasted pedo-climatic conditions. Finally, MARSHAL served to validate a fully analytical model of the root system hydraulic architecture and to calculate the sensitivity of mature root system conductance, depth of standard uptake, volume and convex hull volume to the input parameters.

Many hydrological models including root water uptake (RWU) do not consider the dimension of root system hydraulic architecture (HA) because explicitly solving water flow in such a complex system is too time consuming. However, they might lack process understanding when basing RWU and plant water stress predictions on functions of variables such as the root length density distribution. On the basis of analytical solutions of water flow in a simple HA, we developed an "implicit" model of the root system HA for simulation of RWU distribution (sink term of Richards' equation) and plant water stress in three-dimensional soil water flow models. The new model has three macroscopic parameters defined at the soil element scale, or at the plant scale, rather than for each segment of the root system architecture: the standard sink fraction distribution SSF, the root system equivalent conductance Krs and the compensatory RWU conductance Kcomp. It clearly decouples the process of water stress from compensatory RWU, and its structure is appropriate for hydraulic lift simulation. As compared to a model explicitly solving water flow in a realistic maize root system HA, the implicit model showed to be accurate for predicting RWU distribution and plant collar water potential, with one single set of parameters, in dissimilar water dynamics scenarios. For these scenarios, the computing time of the implicit model was a factor 28 to 214 shorter than that of the explicit one. We also provide a new expression for the effective soil water potential sensed by plants in soils with a heterogeneous water potential distribution, which emerged from the implicit model equations. With the proposed implicit model of the root system HA, new concepts are brought which open avenues towards simple and mechanistic RWU models and water stress functions operational for field scale water dynamics simulation.

A good understanding of the soil water content (SWC) distribution at the field scale is essential to improve the management of water, soil and crops. Recent studies proved that electrical resistivity tomography (ERT) opens interesting perspectives in the determination of the SWC distribution in 3 dimensions (3-D). We conducted this study (1) to check and validate the sensitivity of ERT for monitoring SWC distribution in a maize field during the late growing season; and (2) to investigate how maize plants and precipitations affect the dynamics of SWC distribution. We used time domain reflectometry (TDR) measurements to validate ERT-inverted SWC values. We also calculated the evolution of water mass balance to check whether ERT was capable of giving a reliable estimate of soil water stock evolution. We observe that ERT is able to give the same average SWC as TDR (R2 = 0.98). In addition, we showed that ERT give better estimates of the water stock than TDR thanks to its higher spatial resolution. The high resolution of ERT measurements also allows the discrimination of SWC heterogeneities. The SWC distribution shows that alternation of maize rows and inter-rows is the main influencing factor of the SWC distribution. The drying patterns are linked to the root profiles, with drier zones under the maize rows. During small dry periods, the SWC decrease occurs mainly in the two upper soil horizons and in the inter-row area. At the opposite, precipitations increase the SWC mostly under the maize rows and at the upper soil layer. Nevertheless, the total amount of rainfall during the growing season is not sufficient to modify the SWC patterns induced by the maize rows. During the experimental time, the SWC redistribution hardly occurred from maize rows to the inter-rows but lateral redistribution from the inter-row to the maize rows induced by potential gradient generates SWC decrease in the inter-rows area and in the deeper soil horizons.