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Summary: We investigate the impact of a 20‐yr irrigation on root water uptake (RWU) and drought stress release in a naturally dry Scots pine forest.We use a combination of electrical resistivity tomography to image RWU, drone flights to image the crown stress and sensors to monitor soil water content.Our findings suggest that increased water availability enhances root growth and resource use efficiency, potentially increasing trees' resistance to future drought conditions by enabling water uptake from deeper soil layers.This research highlights the significant role of ecological memory and legacy effects in determining tree responses to environmental changes. [ABSTRACT FROM AUTHOR]

Modeling unsaturated flow through soils with water uptake by plant root has many applications in agriculture and water resources management. In this study, our aim is to develop efficient numerical techniques for solving the Richards equation with a sink term due to plant root water uptake. The Feddes model is used for water absorption by plant roots, and the van-Genuchten model is employed for capillary pressure. We introduce a numerical approach that combines the localized exponential radial basis function (EXP-RBF) method for space and the second-order backward differentiation formula (BDF2) for temporal discretization. The localized RBF methods eliminate the need for mesh generation and avoid ill-conditioning problems. This approach yields a sparse matrix for the global system, optimizing memory usage and computational time. The proposed implicit EXP-RBF techniques have advantages in terms of accuracy and computational efficiency thanks to the use of BDF2 and the localized RBF method. Modified Picards iteration method for the mixed form of the Richards equation is employed to linearize the system. Various numerical experiments are conducted to validate the proposed numerical model of infiltration with plant root water absorption. The obtained results conclusively demonstrate the effectiveness of the proposed numerical model in accurately predicting soil moisture dynamics under water uptake by plant roots. The proposed numerical techniques can be incorporated in the numerical models where unsaturated flows and water uptake by plant roots are involved such as in hydrology, agriculture, and water management. • We propose implicit EXP-RBF techniques for infiltration in soils with water uptake by plant roots. • Localized exponential radial basis function method is used in space. • BDF2 is used for temporal discretization. • The proposed techniques have advantages in terms of accuracy and computational efficiency. • The numerical model is accurate in predicting soil moisture under water uptake by plant roots. [ABSTRACT FROM AUTHOR]

This study discusses infiltration in six irrigation channel types with root water uptake in four types of roots. The mathematical model for the infiltration problem is the Richards equation. This equation is then transformed into a modified Helmholtz equation using the Kirchhoff transformation, dimensionless variables. Subsequently, a numerical solution of the modified Helmholtz equation is obtained using the Dual Reciprocity Boundary Element Method (DRBEM) with a predictor–corrector scheme to result in the numerical values of suction potential, water content, and root water uptake function. In addition, the amount of water absorbed by each root and the water distribution pattern in the channel can be obtained and compared. The results indicate that the minimum water content values occur in both impermeable rectangular and trapezoidal channels, and the highest water uptake values are also observed in the impermeable channels. This is consistent with the physical conditions; as in impermeable channels, water loss downward is limited, and water tends to flow toward the plants. [ABSTRACT FROM AUTHOR]

Acute shortage of water resources and high unproductive water losses are the key problems of irrigated agriculture in arid regions. One of the possible solutions is to optimize soil water retention using natural and synthetic polymer water absorbers. Our approach uses the HYDRUS-1D design to optimize the placement of organic water absorbents such as peat and composite hydrogels in the soil profile in the form of water-storing capillary barriers. Field testing of the approach used a water balance greenhouse experiment with the cultivation of butternut squash (butternut squash (Cucurbita moschata (Duchesne, 1786)) under sprinkler irrigation with measurement of the soil moisture profile and unproductive water losses in the form of lysimetric water outflow. In addition, the biodegradation rate of organic water absorbents was studied at the soil surface and at a depth of 20 cm. Organic capillary barriers reduced unproductive water losses by 40–70%, retaining water in the topsoil and increasing evapotranspiration by 70–130% with a corresponding increase in plant biomass and fruit yield. The deepening of organic soil modifiers to the calculated depth not only allowed capillary barriers to form, but also prevented their biodegradation. The best results in soil water retention, plant growth and yield according to the "dose-effect" criterion were obtained for a composite superabsorbent with peat filling of an acrylic polymer matrix. The study showed good compliance between the HYDRUS design and the actual efficiency of capillary barriers as an innovative technology for irrigated agriculture using natural and synthetic water absorbents. [ABSTRACT FROM AUTHOR]

The depth‐wise distribution of root water uptake is typically inferred through linear mixing models that utilize knowledge of stable water isotopes in soil and plants. However, these existing models often represent the water uptake profile in discrete segments, potentially introducing significant uncertainty and bias into results. In this study, we introduced a novel root water uptake mixing model that combines a Bayesian linear mixing framework with a continuous root water uptake pattern, named CrisPy. To evaluate the performance of CrisPy, we conducted virtual and field‐based tests under several types of prior information. CrisPy showed accurate and robust reconstruction of the true root water uptake profile under various prior information settings in the virtual test. By contrast, the discrete mixing model, MixSIAR was greatly influenced by the prior information and deviated from the true profile. The root mean squared error of the uptake proportions from CrisPy ranged from 3.6% to 7.4%, while MixSIAR exhibited values of 6.3%–15.2%. Furthermore, posterior predictive checking indicated that CrisPy effectively reconstructed the mean and standard deviations of plant water isotopic compositions in both virtual and field‐based tests. MixSIAR, however, underestimated the mean and overestimated the standard deviation of these compositions. These findings collectively support the enhanced accuracy, greater robustness, and reduced uncertainty of CrisPy in comparison to MixSIAR. Therefore, CrisPy provides a powerful tool for partitioning plant water sources. Plain Language Summary: Root water uptake mixing models are essential to study root water uptake patterns. MixSIAR is widely used for this purpose but it requires soil segmentation, which results in limited accuracy and spatial resolution of the root water uptake patterns. In this study, we introduced a novel model named CrisPy. It describes root water uptake in a continuous pattern, instead of dividing the soil profile into segments. The virtual and field tests illustrated CrisPy had fewer errors associated with root water uptake profiles than MixSIAR. Moreover, CrisPy generated plant water isotopic distributions that are closer to observations than that from MixSIAR. These differences illustrate that CrisPy is more accurate than MixSIAR. Key Points: A continuous root water uptake isotope mixing model, named CrisPy, was developedCrisPy is less sensitive to the prior information and more accurate than MixSIARCrisPy is a robust and open‐source tool for plant water partitioning [ABSTRACT FROM AUTHOR]

The analysis of water infiltration channels requires significant time and cost when conducted through laboratory experiments. Alternatively, mathematical modeling followed by numerical method can be employed. The mathematical model of water infiltration in furrow irrigation channels takes the form of a boundary value problem, with the Helmholtz equation serving as the governing equation. The Dual Reciprocity Boundary Element Method (DRBEM) is a numerical method derived from the Boundary Element Method (BEM), utilized for solving partial differential equations encountered in mathematical physics and engineering. This research employs DRBEM to analyze infiltration in trapezoidal irrigation channels with root-water uptake across various homogeneous soil types prevalent in agricultural lands in each District/City of the Yogyakarta Special Region Province. The results demonstrate that DRBEM provides numerical solutions for suction potential, water content, and root water absorption for each soil type. It was found that sandy soil exhibits high water content but has a low rate of root water absorption. On the other hand, clayey soil has low water content but a higher rate of root water uptake. These findings indicate that sandy soil, such as those found in Sleman District and Yogyakarta city, are less efficient in water usage when employing the furrow irrigation system, whereas clayey soil, as found in Gunung Kidul regency, is more effective.

Summary: Investigating plant responses to climate change is key to develop suitable adaptation strategies. However, whether changes in land management can alleviate increasing drought threats to crops in the future is still unclear.We conducted a management × drought experiment with winter wheat (Triticum aestivum L.) to study plant water and vegetative traits in response to drought and management (conventional vs organic farming, with intensive vs conservation tillage). Water traits (root water uptake pattern, stem metaxylem area, leaf water potential, stomatal conductance) and vegetative traits (plant height, leaf area, leaf Chl content) were considered simultaneously to characterise the variability of multiple traits in a trait space, using principal component analysis.Management could not alleviate the drought impacts on plant water traits as it mainly affected vegetative traits, with yields ultimately being affected by both management and drought. Trait spaces were clearly separated between organic and conventional management as well as between drought and control conditions. Moreover, changes in trait space triggered by management and drought were independent from each other.Neither organic management nor conservation tillage eased drought impacts on winter wheat. Thus, our study raised concerns about the effectiveness of these management options as adaptation strategies to climate change. [ABSTRACT FROM AUTHOR]

This study investigates the hazardous effect of salinity on plant growth and soil moisture dynamics in the root zone. Field irrigation experiments on paddy (Oryza sativa L.—basmati variety) with varying levels of salinity of irrigation water (0.5, 5, 10, 15, 20, and 25 dS/m) were performed for studying the effect of salt water stress on crop growth. Throughout the crop's growth period, measurements of leaf area index (LAI), root depth (RD), and soil moisture status in the root zone were recorded. For the analysis, a numerical model was developed to simulate root water uptake (RWU) and soil moisture movement in the root zone, accounting for osmotic pressure developed as a result of the salinity. Nonlinear parameters for the RWU model were estimated based on these observations for each salinity level. By incorporating meteorological data and soil–crop parameters, the model simulated RWU and root zone soil moisture. The results of the irrigation experiments revealed that increased salinity levels in the irrigation water significantly hindered crop development, leading to a decrease in LAI and root depth. The maximum LAI in the growth period decreased markedly, from 5.19 m2m−2 at 0.5 dS/m to 2.01 m2m−2 at 25 dS/m, a decline of approximately 61%. Root depth also exhibited a substantial reduction, declining by up to 36%, from 69.5 cm at 0.5 dS/m to 44.5 cm at 25 dS/m. The simulation outcomes further demonstrated that higher salt concentrations in the irrigation water resulted in reduced root water uptake and decreased soil moisture content in the root zone, ultimately affecting crop yield. The reduction in root water uptake becomes notably pronounced, exhibiting an approximate decrease of 81% when salinity level increases from 0.5 to 25 dS/m. These findings shed light on the hazards posed by salinity in agricultural practices and emphasize the importance of effective management strategies to ensure sustainable crop production in the presence of salinity-induced hazards. Practical Applications: The results of our research yield significant insights with practical applications for real-life conditions. We find that increasing salinity levels in irrigation water have a pronounced adverse effect on paddy crop growth and root water uptake. As salinity levels rise, there is a noticeable effect on crop growth i.e., decrease in leaf area index (LAI), root depth (RD), and root water uptake (RWU), which are crucial parameters for crop development. Furthermore, our findings reveal a clear correlation between increasing salinity and reduced soil moisture content, particularly at the critical depths of 20 and 40 cm below the surface. The practical implications of our research are twofold. First, it underscores the importance of carefully managing salinity levels in irrigation practices to mitigate the negative effects on crop growth and water uptake. Secondly, our study provides valuable insights for crop selection, suggesting that paddy crops may be less suitable under high salinity conditions. These results offer practical guidance for agricultural decision makers, highlighting the need for salinity control measures and informed crop selection to optimize agricultural productivity in regions with saline water environments. [ABSTRACT FROM AUTHOR]

Garlic (Allium sativum L.) is an important crop cultivated in arid and semi-arid climates. To quantify the tolerance of garlic to drought and salinity stresses in terms of parameter values of the stress response function, we conducted pot experiments in a greenhouse for two years. Nine 1/5000a Wagner pots were used for three treatments, namely drought-treated, salinity-treated, and control pots, for estimating the relative transpiration. Daily transpiration rates were observed by weighing pots, and the soil surface of each pot was covered. The soil water contents were measured hourly using two soil moisture probes for drought-treated pots, and two salinity probes for both soil water content and bulk electrical conductivity were monitored for salinity-treated pots. When the ratio of actual to potential transpiration fell below 50%, the root length distributions were obtained by dismantling the pots. The parameter values for both drought-stress and salinity-stress functions were estimated using inverse-analysis and bulk-analysis methods. The parameter values of drought-stress and salinity-stress functions obtained by the simpler and cheaper bulk method gave similar results to the inverse method when the root length distributions were relatively uniform. [ABSTRACT FROM AUTHOR]

Aims: Gradients in water potential of soil and plant system drives the water movement in soil-plant-atmospheric continuum. Here, we demonstrate how root water potential measured directly from the roots upon changes in soil water potential would contribute to the understanding of the drought response in Chrysopogon zizanoides. Methods: Plants of Chrysopogon zizanoides L. were sampled at different soil water status (inducing drought) and growth periods (3-, 4- and 5- months). The roots and leaves of the plants were dissected to measure the root water potential and specific leaf area, respectively. The root water potential was measured in a WP4C dew-point potentiometer. Root diameter corresponding to the roots measured for root water potential was also measured. Results: Our findings showed a logarithmic increase in gradient between soil and root water potential under the induced drought stress, similar to the existing findings of root hydraulic conductance. Specific leaf area significantly decreased with root water potential, indicating the hydraulic continuity between roots and leaves. A new power law correlation between root diameter and root water potential established a trait-based understanding of root water uptake. Conclusion: The aggregation of such root water potential measurements using potentiometer would offer strategies to explore the implications of below-ground plant behaviour in applications such as slope stability and irrigation. [ABSTRACT FROM AUTHOR]

Partitioning soil water balance (SWB) is an effective approach for deciphering the impacts of vegetation change on soil hydrological processes. Growing apple trees on the Loess Plateau, China, leads to a substantial deep soil water deficit, posing a serious threat to the sustainable development of apple production. However, the impact of deep-rooted apple trees on SWB remains poorly understood. In this study, we conducted a "Paired Plot" experiment to achieve this objective by decoupling SWB components using water stable isotopes, tritium, and soil water contents from deep soil cores (up to 25 m) under apple orchards with a stand age gradient of 8–23 years. The results showed that deep soil water storage under apple orchards was notably reduced compared to nearby farmland, showing a stand age-related pattern of deep soil water deficit (R2 = 0.91). By analyzing the changing patterns of SWB components, we found that the main factor driving this deficit is the water uptake process controlled by the deep root system. This process is triggered by the increased transpiration demand of apple trees and short-term water scarcity. These findings have implications for understanding soil water dynamics, sustainable agroforestry management, and soil water resources' protection in this region and other similar water-limited areas. [ABSTRACT FROM AUTHOR]

Plants on the land surface play a vital role in the hydrological water cycle as they transport soil water to the atmosphere through transpiration. Root water uptake (RWU) is considered a crucial step in this process as it is the first stage of transpiration, directly determining the actual transpiration (Ta) of plants. However, accurately measuring RWU or Ta in situ poses significant challenges. Here, we establish an overall approach of combining mathematical models and machine learning algorithms to obtain high-precision (500 m×500 m) regional-scale daily Ta maps for various future climate patterns. The Hydrus-1D and AquaCrop models were employed to calculate the total RWU fluxes across the entire root zone, aiming to achieve Ta at a point scale. A machine learning model was developed using the CatBoost algorithm and environmental covariates extracted from the Google Earth Engine (GEE) platform to upscale these point-scale Ta to the regional scale. Furthermore, a total of 22 CMIP6 Earth System Models (ESMs) were evaluated, and among them, ACCESS-CM2 and ACCESS-ESM1–5 were selected for simulating future climate scenarios. Based on the established machine learning model and selected ESMs, regional-scale Ta maps were generated from 2020 to 2100 for the SSP245 and SSP585 (Shared Socioeconomic Pathways) scenarios. The results indicate that near-surface specific humidity, mean near-surface air temperature, latitude, and surface downwelling shortwave radiation are the critical factors influencing regional-scale Ta. As greenhouse gas emissions intensify and temperatures rise, regional-scale Ta is enhanced, leading to an accelerated transfer of soil water to atmospheric water. Under the SSP245 scenario, Ta increases on average by 0.55–1.16 % every 20 years, with its incremental value ranging from 7.14∙10−4 to 8.65∙10−4 cm day−1, while under the SSP585 scenario, Ta increases more significantly, achieving an average increase of 0.64–1.81 % every 20 years, with its incremental value ranging from 1.595∙10−3 to 2.821∙10−3 cm day−1. This study provides a robust integrated approach to assess the future regional-scale Ta providing valuable insights into the underlying water cycle mechanisms and regional water requirements for future climate scenarios.

In order to ensure sustainability in the agricultural sector and to meet global food needs, a particularly important challenge for our time is to investigate the possibility of increasing agricultural production in areas with extreme hyper-arid environments. Warming air temperatures and sandy soils significantly influence tree root water uptake (RWU) dynamics, making accurate estimation of RWU depth distribution and magnitude crucial for effective resource management, particularly in the context of precision irrigation within agroecosystems. This study employed two non-invasive techniques, namely HYDRUS 1D and electrical resistivity tomography (ERT), to simulate RWU under controlled experimental conditions and under an extreme hyper-arid environment. The results revealed that the highest RWU rates occurred during the morning (08:00–11:00). RWU activity predominantly concentrated in the upper soil profile (0–30 cm), and the soil water content in this area was notably lower compared to the deeper soil layers. With increasing temperature, there was a tendency for the RWU zone to shift to lower depths within the soil profile. The findings of this study could have important implications for farmers, providing valuable insights to implement irrigation water management strategies. [ABSTRACT FROM AUTHOR]

The development of an accurate root water-uptake model is pivotal for evaluating crop evapotranspiration; understanding the combined effect of drought and waterlogging stresses; and optimizing water use efficiency, namely, crop yield [kg/ha] per unit of ET [mm]. Existing models often lack quantitative approaches to depicting crop root water uptake in scenarios of concurrent drought and waterlogging moisture stresses. Addressing this as our objective; we modified the Feddes root water-uptake model by revising the soil water potential response threshold and by introducing a novel method to calculate root water-uptake rates under simultaneous drought and waterlogging stresses. Then, we incorporated a water stress lag effect coefficient, φ W s , that investigated the combined effect of historical drought and waterlogging stress events based on the assumption that the normalized influence weight of each past stress event decreases with an increase in the time interval before simulation as an exponential function of the decay rate. Further, we tested the model parameters and validated the results obtained with the modified model using data from three years (2016–2018) of rice (Oryza sativa, L) trails with pots in Bengbu, China. The modified Feddes model significantly improved precision by 9.6% on average when calculating relative transpiration rates, particularly post-stress recovery, and by 5.8% on average when simulating soil moisture fluctuations during drought periods. The root mean square error of relative transpiration was reduced by 60.8%, and soil water was reduced by 55.1%. By accounting for both the accumulated impact of past moisture stress and current moisture conditions in rice fields, the modified model will be useful in quantifying rice transpiration and rice water use efficiency in drought–waterlogging-prone areas in southern China. [ABSTRACT FROM AUTHOR]

In ecohydrology, water isotopologues are used to assess potential sources of root water uptake by comparing xylem water signatures with source water signatures. Such comparisons are affected by the variability and uncertainty of the isotope signatures of plant water and water sources. The tree‐scale and stand‐scale variabilities of the isotope signatures in stem xylem water are often unknown but are important for sampling design and uncertainty estimation in assessing the sources of tree water uptake. Here, we quantified tree‐scale and stand‐scale variabilities of xylem water isotope signatures in beech, oak and spruce trees in a mature forest on the Swiss plateau. For stem xylem water, sub‐daily replicates and replicates in different cardinal directions showed no systematic differences, but we found systematic differences with sampling height. The observed variability of isotope signatures at different heights along the stem suggests that water residence times within trees need to be considered, along with their effects on the isotope signatures in different compartments (stem, branches, leaves). Further, concerning the hydrogen signatures, we found height‐ and species‐specific offsets (SW‐excess δ2H). Stem xylem water's tree‐scale variability was similar in magnitude to its stand‐scale variability and smaller than the variabilities in branch xylem and bulk soil water around each tree. Xylem water from stem cores close to the ground, therefore, can give a more precise estimate of the isotopic signal of the most recent root water uptake and facilitate more accurate source water attribution. [ABSTRACT FROM AUTHOR]

Cryogenic vacuum distillation (CVD) is a widely used technique for extracting plant water from stems for isotopic analysis, but concerns about potential isotopic biases have emerged. Here, we leverage the Cavitron centrifugation technique to extract xylem water and compare its isotopic signature to that of CVD‐extracted bulk stem water as well as source water. Conducted under field conditions in tropical northern Australia, our study spans seven tree species naturally experiencing a range of water stress levels. Our findings reveal a significant deuterium bias in CVD‐extracted bulk stem water when compared to xylem water (median bias −14.9‰), whereas xylem water closely aligned with source water (median offset −1.9‰). We find substantial variations in deuterium bias among the seven tree species (bias ranging from −19.3‰ to −9.1‰), but intriguingly, CVD‐induced biases were unrelated to environmental factors such as relative stem water content and predawn leaf water potential. These results imply that inter‐specific differences may be driven by anatomical traits rather than tree hydraulic functioning. Additionally, our data highlight the potential to use a site‐specific deuterium offset, based on the isotopic signature of local source water, for correcting CVD‐induced biases. [ABSTRACT FROM AUTHOR]

Whole orchard recycling (WOR) is an emerging practice in perennial cropping systems and is an alternative to open or cogeneration burning. It is an orchard removal practice that incorporates large amounts of woody biomass back into the soil system. In this study, we utilized a soil hydrological model (HYDRUS-1D) to evaluate the seasonal effects of WOR on water movement and nitrogen (N) retention for a newly established almond orchard on a typical sandy loam soil in the Central Valley of California. Soil moisture and N content were monitored across the first five growing seasons from 2018 to 2022. The model was able to track seasonal moisture fluctuation nicely compared to observed data. Additionally, an increase in soil moisture was measured in the WOR treatments in surface soil (i.e., 0- to 15-cm depths) where biomass was incorporated, and N leaching was reduced when compared to the unamended control. Simulations suggest that with WOR, irrigation can be reduced by up to 20 % during the tree establishment stage with minimal effect on root water uptake. This reduction in applied water can increase farm water use efficiency and reduce operational expenses, e.g., cost of water and pumping. Likewise, the reduction in N leaching observed in both predicted results and laboratory analysis can further cut farm capital costs, e.g., fertilization, and lessen orchard environmental impacts. Overall, results from our simulation show a positive effect of WOR on soil ecosystem services and can potentially be a profitable strategy for orchard turnover. The results have important implications in reducing groundwater nitrate contamination in irrigated agriculture in the Central Valley of California and applicable to most parts of Southwestern United States.

This paper highlights the evolution and impact of the SWAP model (Soil – Water – Atmosphere – Plant), which was initiated by R.A. Feddes and colleagues fifty years ago, in 1974. Since then, the SWAP model has played a crucial role in the advancement of agrohydrology. This paper highlights some major advances that have been made, especially focussing on the last fifteen years. The domain of the SWAP model deals with the simulation of the soil water balance in both unsaturated and saturated conditions. The model solves the Richards equation using the water retention and hydraulic conductivity functions as described by the Van Genuchten – Mualem equations. Bimodal extensions of the Van Genuchten - Mualem relationships have been implemented, as well as modifications near saturation and addressing hysteresis. An important sink term in the Richards equation is root water uptake. Crop development plays an important role in a robust simulation of root water uptake. That is why a link has been made with the dynamic crop growth model WOFOST. Instead of using a prescribed crop development, a distinction between potential and actual crop development is calculated by reducing the potential photosynthesis as a result of water or oxygen stress. Since the early days of SWAP, empirical and macroscopic concepts have been used to simulate root water uptake. Recently two process-based concepts of root water uptake and oxygen stress have also been implemented. Another important sink-source term in the Richards equation is the interaction with artificial drains. In SWAP, drainage can be simulated by either using prescribed or simulated drain heads and simulation of controlled drainage with subirrigation is possible. Finally, we briefly elaborate on three studies using SWAP: water stresses in agriculture in the Netherlands, regional water productivity in China, and controlled drainage with subirrigation. We finish discussing promising developments for the near future.

Poplar plantations play an active role in windbreak and sand-fixation and timber production in water-limited areas, but the large-scale plantations are experiencing degradation, characterized by short trees, small size, and dieback. Moreover, the potential impacts of plantation degradation on ecohydrological processes in soil-plant systems remain unclear. We continuously measured soil water content (SWC), hydrogen and oxygen isotopic compositions in the soil water and plant xylem water, carbon isotopic compositions in the leaf, and sap flow velocity of poplar trees under various degraded plantations (no degraded, ND; lightly degraded, LD; severely degraded, SD) during the 2021 growing season (May–September). We also investigated tree root systems at a depth of 0–200 cm. Our results showed that as plantation degradation intensified, the root weight density at different depths decreased and the root proportion of the shallow layer (0–40 cm) increased. Although the SWC of the shallow layer did not change in the degraded plantations, the SWCs at middle layer (40–80 cm) and deep layer (80–200 cm) were higher in the LD and SD plantations than in the ND plantations, which might be related to reduced transpiration of degraded plantations. The Bayesian mixing model showed that all plantations can shift the water source from shallow to deep layers in the process of soil wetting to drying. Evidence from leaf carbon isotopes suggested that degraded plantations increased the sensitivity of intrinsic water-use efficiency to SWC. Our findings demonstrate that the normal growth of poplar plantations is prone to soil desiccation of deep layers due to high transpiration demand in water-limited areas, and degraded poplar plantations alleviate deep soil water depletion due to low transpiration. For rain-fed poplar plantations, proper thinning and measures of reducing soil evaporation may be necessary to avoid water excess consumption from deep soils.

Acute shortage of water resources and high unproductive water losses are the key problems of irrigated agriculture in arid regions. One of the possible solutions is to optimize soil water retention using natural and synthetic polymer water absorbers. Our approach uses the HYDRUS-1D design to optimize the placement of organic water absorbents such as peat and composite hydrogels in the soil profile in the form of water-storing capillary barriers. Field testing of the approach used a water balance greenhouse experiment with the cultivation of butternut squash (butternut squash (Cucurbita moschata (Duchesne, 1786)) under sprinkler irrigation with measurement of the soil moisture profile and unproductive water losses in the form of lysimetric water outflow. In addition, the biodegradation rate of organic water absorbents was studied at the soil surface and at a depth of 20 cm. Organic capillary barriers reduced unproductive water losses by 40–70%, retaining water in the topsoil and increasing evapotranspiration by 70–130% with a corresponding increase in plant biomass and fruit yield. The deepening of organic soil modifiers to the calculated depth not only allowed capillary barriers to form, but also prevented their biodegradation. The best results in soil water retention, plant growth and yield according to the “dose-effect” criterion were obtained for a composite superabsorbent with peat filling of an acrylic polymer matrix. The study showed good compliance between the HYDRUS design and the actual efficiency of capillary barriers as an innovative technology for irrigated agriculture using natural and synthetic water absorbents.

With current observations and future projections of more intense and frequent droughts in the tropics, understanding the impact that extensive dry periods may have on tree and ecosystem-level transpiration and concurrent carbon uptake has become increasingly important. Here, we investigate paired soil and tree water extraction dynamics in an old-growth upland forest in central Amazonia during the 2018 dry season. Tree water use was assessed via radial patterns of sap flow in eight dominant canopy trees, each a different species with a range in diameter, height, and wood density. Paired multi-sensor soil moisture probes used to quantify volumetric water content dynamics and soil water extraction within the upper 100 cm were installed adjacent to six of those trees. To link depth-specific water extraction patterns to root distribution, fine root biomass was assessed through the soil profile to 235 cm. To scale tree water use to the plot level (stand transpiration), basal area was measured for all trees within a 5 m radius around each soil moisture probe. The sensitivity of tree transpiration to reduced precipitation varied by tree, with some increasing and some decreasing in water use during the dry period. Tree-level water use scaled with sapwood area, from 11 to 190 L per day. Stand level water use, based on multiple plots encompassing sap flow and adjacent trees, varied from ∼1.7 to 3.3 mm per day, increasing linearly with plot basal area. Soil water extraction was dependent on root biomass, which was dense at the surface (i.e., 45% in the upper 5 cm) and declined dramatically with depth. As the dry season progressed and the upper soil dried, soil water extraction shifted to deeper levels and model projections suggest that much of the water used during the month-long dry-down could be extracted from the upper 2-3 m. Results indicate variation in rates of soil water extraction across the research area and, temporally, through the soil profile. These results provide key information on whole-tree contributions to transpiration by canopy trees as water availability changes. In addition, information on simultaneous stand level dynamics of soil water extraction that can inform mechanistic models that project tropical forest response to drought.

The Bayesian stable isotope mixing (MixSIAR) model was widely used in water source tracing. However, double isotope and single isotope calculated by the MixSIAR model led to different results in terms of previous studies. The effect of different nitrogen treatments on the water traceability results of wheat crops is still unclear. This study investigated the wheat root water uptake patterns at different nitrogen application gradients, as well as at different isotopes in the MixSIAR model. The results showed the main soil water uptake layer was relative constant at the treatment of 15% nitrogen reduction, and the water source was mainly from 0–10 cm soil layer from jointing to harvest. The main soil water uptake layer significantly varied at the treatment of 30% nitrogen reduction, which yielded the highest. 45% reduction of nitrogen treatment showed the deepest soil water uptake absorption on average with the whole wheat growth period. The consistency of the results between the two single isotope methods was better in the early stage of wheat and worse in the later stage. The inconsistency of root water uptake distribution results between the two single isotope methods might be influenced by the water transport mechanism of wheat stem and sampling errors. The double isotope method had the lowest uncertainty, but it might amplify the error of the sampling process. The uncertainty of the single hydrogen isotope method was less than single oxygen isotope method. This study provided a new evaluation of hydrogen-oxygen stable isotope traceability methods for wheat under different nitrogen treatments, and gave more ideas and insights for subsequent crop water traceability by the MixSIAR method.

The spatiotemporal pattern of root water uptake (RWU) depends on multiple factors, such as plant root biomass, soil water availability, and prevailing weather conditions at the site. The water uptake reduction due to the nonuniformity in soil water contents is often mitigated through compensated root water uptake (CRWU) and hydraulic redistribution (HR). Although previous studies have often considered these two processes independently due to the simplicity and feasibility of analyzing them separately, CRWU and HR can coexist in field conditions. Therefore, this work demonstrates the importance of considering CRWU and HR simultaneously in estimating daily transpiration and RWU distribution for nonuniform soil moisture conditions. For that, we have implemented the mechanistic RWU models developed by de Jong van Lier et al. (denoted below as the DJ model), Couvreur (CR), and Nimah and Hanks (NH) (see the references in the main text) into the widely-used HYDRUS-1D model, in addition to the previously available Jarvis (JF) and Feddes (FD) models. The performance of these models was then compared for varying soil water contents and boundary conditions using experimental data and hypothetical modeling scenarios. Our analysis has shown that these models are beneficial in estimating RWU with varying degrees of accuracy. The DJ and CR models are effective in simultaneously simulating CRWU and HR. NH and JF models can simulate CRWU but cannot simulate HR satisfactorily. Implementing these models into the HYDRUS platform for simultaneously considering CRWU and HR will significantly improve the accuracy of RWU predictions.

Alfalfa is one of the major perennial forage crops in California, vital for the livestock industry, and provides environmental benefits to the ecosystem in the state. Information on subsurface drip irrigation (SDI) practices on alfalfa is limited particularly in areas related to drip tape spacings and installation depths and their impacts on topsoil profile wetting patterns and alfalfa productivity. The objective of this study was to compare three different depths of drip lines: 15, 30, and 45 cm on topsoil profile wetting patterns and identify the optimum depth for achieving sustainable management practices for alfalfa production under SDI. Crop water requirements were determined using Tule Technologies system. Volumetric soil water contents from twelve cuts were simulated using HYDRUS-2D. Initial volumetric soil water contents from Watermark sensors were used in the model and measured volumetric soil water distributions were used for hydraulic conductivity calibration. Simulated results showed that there was no significant difference between root water uptake (RWU) among the various drip depths. RWU was 171.6, 170.0, and 168.2 cm at drip line depths of 15, 30, and 45 cm, respectively. Applied irrigation water during the study period was 195.1 cm while rainfall was 4.1 cm. A 10% reduction in topsoil volumetric soil water content was observed for drip lines at 30 cm depth as compared with 15 cm depth, while a 20% reduction in topsoil volumetric soil water content was observed for drip lines at 45 cm depth as compared with 15 cm depth. Drip lines at 30 cm depth are likely the optimal for RWU and free drainage; however, drip lines at 45 cm depth may allow growers to provide additional irrigation events (without increasing the topsoil volumetric soil water content) closer to the harvest date, potentially resulting in higher yield and water use efficiency.

Water content (WC) is a key variable in plant physiology even during the winter period. To simulate stem WC during the dormant season, a series of experiments were carried out on walnut trees under controlled conditions. In the field, WC was significantly correlated with soil temperature at 50 cm depth (R 2 = 0.526). In the greenhouse, WC remained low as long as soil temperature was kept cold (<+5 °C) and increased after the soil temperature was warmed to +15 °C regardless of the date. Stem dehydration rate was significantly influenced by the WC and evaporative demand. A parsimonious model with functions describing the main experimental results was calibrated and validated with field data from 13 independent winter dynamics in Juglans regia L. orchards. Three functions of water uptake were tested, and these gave equivalent accuracies (root-mean-square error (RMSE) = 0.127–8; predictive root-mean-square error = 0.116). However, only a sigmoid function describing the relationship between the root water uptake and soil temperature gave values in agreement with the experimental results. Finally, the simulated WC provided a similar accuracy in predicting frost hardiness compared with the measured WC (RMSE ca 3 °C) and was excellent in spring (RMSE ca 2 °C). This model may be a relevant tool for predicting the risk of spring frost in walnut trees. Its genericity should be tested in other fruit and forest tree species. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Summary: The effect of root hairs on water uptake remains controversial. In particular, the key root hair and soil parameters that determine their importance have been elusive.We grew maize plants (Zea mays) in microcosms and scanned them using synchrotron‐based X‐ray computed microtomography. By means of image‐based modelling, we investigated the parameters determining the effectiveness of root hairs in root water uptake. We explicitly accounted for rhizosphere features (e.g. root–soil contact and pore structure) and took root hair shrinkage of dehydrated root hairs into consideration.Our model suggests that > 85% of the variance in root water uptake is explained by the hair‐induced increase in root–soil contact. In dry soil conditions, root hair shrinkage reduces the impact of hairs substantially.We conclude that the effectiveness of root hairs on root water uptake is determined by the hair‐induced increase in root–soil contact and root hair shrinkage. Although the latter clearly reduces the effect of hairs on water uptake, our model still indicated facilitation of water uptake by root hairs at soil matric potentials from −1 to −0.1 MPa. Our findings provide new avenues towards a mechanistic understanding of the role of root hairs on water uptake. See also the Commentary on this article by Boursiac & Bauget 240: 2173–2175. [ABSTRACT FROM AUTHOR]

Roadway trees planted as barriers reduce traffic noise and particle pollution in cities. However, tree roots may alter the soil's moisture content, resulting in uneven soil subsidence and maintenance issues for neighbouring structures. This study determined the safe distance between trees and pavement by investigating the effects of transpiration on pore water pressure (PWP) and pavement subsidence under seasonal variations. The root water uptake was simplified in a finite element model using multiple hydraulic head boundaries and validated using field observations. A hypoplastic model was used to model non-linear behaviour and plastic strain accumulation in unsaturated soil. Evergreen trees can reduce PWP by 72% during the dry season and 84% during the wet season, compared to bare soil. The subsidence did not decrease linearly with the distance away from trees under a rigid and impermeable pavement structure. The maximum bending moment was influenced by the distance between trees and pavement with the highest value occurring when trees were located near the pavement (up to five times the bending moments on pavement without trees). Our findings suggest that the pavement is at risk of experiencing structural failure if trees are located within 0.4 times their height away from the pavement. [ABSTRACT FROM AUTHOR]

Non-destructive phenotyping of roots and measurement of root water uptake from different soil layers in the field are vital for improving water management and facilitating the development of drought-resistant crop varieties, but difficult because of their opaqueness. As a result, indirect methods using easy-to-measure variables such as soil water content have been used as alternatives. However, the inherent measurement errors could undermine the robustness and reliability of these methods. This paper proposes a new method to bridge this knowledge gap by using soil water content profiles measured at two time points to calculate root uptake and root-length density. It is based on the Richards' equation by treating root uptake from different soil layers between the two time points as random unknown numbers; their distributions are calculated using the Bayesian framework, solved by the Markov Chain Monte Carlo method. We applied the method to 39 winter wheat lines grown in a silt-clay loam field. Soil water content profile measured at the first time point from each plot served as the initial condition, and water content measured at the second time point was the target to match the model for calculating average root water uptake and root-length density between the two time points. The results show that the measured soil water contents fall within the 95% confidence interval of the calculated soil water contents. The inherent soil water measurement errors lead to uncertainties in the calculated root water uptake for all lines, but such uncertainties decrease with soil depth. Although the soil types and agronomic management were the same for all 39 lines, their root water uptake from different soil layers varies considerably, with some lines more capable of using subsoil water than others. Generally, the calculated and measured root-length densities agree well, albeit the degree of the agreement varies with lines. While this paper focuses on methodology and applies the method to one growth stage spanning one month only, the consistent results for all 39 lines indicates the method is robust and can be applied to other crops cultivated in different conditions. Given the growing interest in improving root traits to enhance water use efficiency, the proposed method has important implications as phenotyping roots and understanding their water uptake from different soil layers in the field is a prerequisite to achieve this crucial target.

Assessing root sources of three uncertainties – parameterization of soil hydraulic characteristics, boundary conditions, and estimation of source/sink terms – is a significant challenge in soil water transport modeling. This study aims to evaluate the uncertainty of three each widely-used parameter estimation methods affecting plot-scale water dynamics. The study employs HYDRUS, a process-based hydrologic model, to incorporate these uncertainties and compare model predictions to measured values in a semiarid Inner Mongolia steppe, China. Soil hydraulic parameters are determined using two direct methods (laboratory-derived approach and evaporation method) and one indirect method (neural network). While each hydraulic parameter method generally simulates soil moisture dynamics, the evaporation method performed better, especially under dry conditions. This suggests that measuring the intensity properties, such as unsaturated hydraulic conductivity, with the evaporation method is crucial for reasonable soil moisture simulation. The study also demonstrates the impact of different applied boundary conditions on simulated soil moisture, specifically the partitioning of reference FAO evapotranspiration via one direct method (soil fraction cover) and two indirect methods (leaf area index and crop height). The partitioning via soil fraction cover reflected a better simulation. Additionally, the study compares the uncertainties of root water uptake function with root growth parameters and constant root depth referenced to grass and pasture, and finds no significant difference among them. Comparing three sources of uncertainty in predicting soil moisture, the study concludes that the input soil hydraulic parameter is more sensitive than evapotranspiration partitioning or representation of root water uptake function. Our study highlights that measuring soil intensity properties can better reflect the effects of land use change, such as compaction, on field water transports.

Study region: Changwu Tableland, Chinese Loess Plateau Study focus: Soil water status and water demand are two important factors to influence root water uptake (RWU) patterns, but the mechanisms involved in deep-rooted plants remain unknown. This study addresses this knowledge gap by investigating diurnal variations in RWU patterns for two different-aged apple orchards (7 vs. 19 years) on the Chinese Loess Plateau (CLP). We achieved this by inputting measured plant and soil information into a physical-based numerical RWU model. New hydrological insights for the region: The results showed that the 19-year-old orchard exhibits distinct characteristics compared to the 7-year-old orchard. Specifically, the 19-year-old orchard had less deep soil water content, resulting in lower matric potential and hydraulic conductance. In contrast to cropland soil water, the cumulative deep soil water (>2 m) deficits were 17.6 and 1108.3 mm in the 7-year-old and 19-year-old orchards, respectively. Despite the 19-year-old orchard having 67% of its fine roots below 5 m soil depth, their contribution ratio to total RWU was only 30–40%, indicating less available deep soil water for the older orchard.Sap flow and leaf water potential had bell-shaped diurnal variations, leading to shifting soil water contributions to RWU in the 7-year-old and 19-year-old orchards. These changes were particularly evident when soil water potential in the root zone was heterogeneous, resulting in contrasting RWU patterns during different water demand periods. Notably, the 7-year-old orchard exhibited less water contribution from deep 2–5 m layer and enriched xylem water isotopes at midday with high water demand, while the 19-year-old orchard had more water contribution from deep 5–21.6 m layer and depleted xylem water isotopes. These contrasting RWU variations shed light on the profound impact of orchard age on deep RWU patterns, especially under the varying water demand conditions after CLP afforestation.

Accurately assessing isotope information on water sources and mixtures is essential for determining root water uptake (RWU) patterns. This study investigates the impact of rooting depth and cryogenic vacuum extraction (CVE) on the isotopic composition of deep soil water and RWU patterns in a 19-year-old apple orchard on China’s Loess Plateau. We used a Bayesian mixing model (MixSIAR) to analyze corrected isotopic data from soil and xylem water samples collected at different depths, ranging from 3 m to 21.6 m. Our findings reveal a progressive decline in the isotopic composition of deep soil water by 0.63‰ m–1, which decreased deep soil water contributions to transpiration by 1–12% at different rooting depths. The xylem and soil water isotopes became more enriched after correction, with xylem water isotopes closer to the soil water isotope line and water isotopes enriched in the shallow soil layer. Consequently, the contributions of shallow soil water to transpiration increased after xylem water isotope correction but decreased after soil water isotope correction. Monthly averages of these ratios decreased by 12.8% or increased by 8.4%, respectively. After correcting for both soil and xylem water isotopes, the average contributions of shallow soil water increased by 7.4% each month, while those of deep soil water were not consistent. Our findings suggest that rooting depth and CVE have a greater impact on seasonal contribution ratios but a comparatively milder influence on seasonal patterns. This delineation is important for accurately quantifying plant water use strategies.

Xylem water isotopic compositions (2H, 18O; δXYLEM) can be used to estimate plant water uptake depths; however, environmental heterogeneity in these measurements may prevent reaching robust conclusions. Bayesian mixing models used to estimate plant water uptake depths often assume that measurements of δXYLEM and candidate water uptake sources are normally and identically distributed. We tested if δXYLEM measured across 30 Eastern hemlock (Tsuga canadensis (L.) Carrière) trees met these assumptions. Bootstrap simulations suggested that the distributions of hemlock δXYLEM data were non‐normal in March, April, June, and July and that between 15 and 26 hemlock δXYLEM samples were required to reject the assumption of normality. In June, July, and August, δXYLEM was significantly predicted by a multivariate linear regression with tree sapwood depth or elevation, rejecting the assumption of independently distributed observations. A comparison of dry season hemlock water uptake depth estimates between a Bayesian mixing model and a process‐based ecohydrological model calibration showed differences, with the Bayesian model estimating a substantially greater proportion of shallow water uptake. These results highlight the need for standardized field sampling protocols for δXYLEM and analytical methods that will lead to more robust estimates of plant water uptake depths. These findings also suggest that water uptake functions conditioned on landscape and tree structural variables could substantially advance the representation of plants in ecohydrological models. [ABSTRACT FROM AUTHOR]

Arbuscular mycorrhizal fungi (AMF) have been presumed to ameliorate crop tolerance to drought. Here, we review the role of AMF in maintaining water supply to plants from drying soils and the underlying biophysical mechanisms. We used a soil–plant hydraulic model to illustrate the impact of several AMF mechanisms on plant responses to edaphic drought. The AMF enhance the soil's capability to transport water and extend the effective root length, thereby attenuating the drop in matric potential at the root surface during soil drying. The synthesized evidence and the corresponding simulations demonstrate that symbiosis with AMF postpones the stress onset limit, which is defined as the disproportionality between transpiration rates and leaf water potentials, during soil drying. The symbiosis can thus help crops survive extended intervals of limited water availability. We also provide our perspective on future research needs and call for reconciling the dynamic changes in soil and root hydraulics in order to better understand the role of AMF in plant water relations in the face of climate changes. [ABSTRACT FROM AUTHOR]

Water scarcity is the primary environmental constraint affecting wheat growth and production and is increasingly exacerbated due to climatic fluctuation, which jeopardizes future food security. Most breeding efforts to improve wheat yields under drought have focused on above-ground traits. Root traits are closely associated with various drought adaptability mechanisms, but the genetic variation underlying these traits remains untapped, even though it holds tremendous potential for improving crop resilience. Here, we examined this potential by re-introducing ancestral alleles from wild emmer wheat (Triticum turgidum ssp. dicoccoides) and studied their impact on root architecture diversity under terminal drought stress. We applied an active sensing electrical resistivity tomography approach to compare a wild emmer introgression line (IL20) and its drought-sensitive recurrent parent (Svevo) under field conditions. IL20 exhibited greater root elongation under drought, which resulted in higher root water uptake from deeper soil layers. This advantage initiated at the pseudo-stem stage and increased during the transition to the reproductive stage. The increased water uptake promoted higher gas exchange rates and enhanced grain yield under drought. Overall, we show that this presumably 'lost' drought-induced mechanism of deeper rooting profile can serve as a breeding target to improve wheat productiveness under changing climate. [ABSTRACT FROM AUTHOR]

The water deficit experienced by crops is a function of atmospheric water demand (vapor pressure deficit) and soil water supply over the whole crop cycle. We summarize typical transpiration response patterns to soil and atmospheric drying and the sensitivity to plant hydraulic traits. We explain the transpiration response patterns using a soil–plant hydraulic framework. In both cases of drying, stomatal closure is triggered by limitations in soil–plant hydraulic conductance. However, traits impacting the transpiration response differ between the two drying processes and act at different time scales. A low plant hydraulic conductance triggers an earlier restriction in transpiration during increasing vapor pressure deficit. During soil drying, the impact of the plant hydraulic conductance is less obvious. It is rather a decrease in the belowground hydraulic conductance (related to soil hydraulic properties and root length density) that is involved in transpiration down-regulation. The transpiration response to increasing vapor pressure deficit has a daily time scale. In the case of soil drying, it acts on a seasonal scale. Varieties that are conservative in water use on a daily scale may not be conservative over longer time scales (e.g. during soil drying). This potential independence of strategies needs to be considered in environment-specific breeding for yield-based drought tolerance. [ABSTRACT FROM AUTHOR]

The new isotope module in HYDRUS‐1D can be used to infer the origin of root water uptake (RWU), a suitable dynamic indicator for agriculture and forest water management. However, evidence shows that the equilibrium fractionation between liquid water and water vapor within the soil is affected not only by soil temperature but also by soil tension. How soil tension affects isotope transport modeling and interpretations of the RWU origin is still unknown. In this study, we evaluated three fractionation scenarios on model performance for a field data set from Langeoog Island: (a) no fractionation (Non_Frac), (b) the soil temperature control on equilibrium fractionation as described by the standard Craig‐Gordon equation (CG_Frac), and (c) CG_Frac plus the soil tension control on equilibrium fractionation (CGT_Frac). The model simulations showed that CGT_Frac led to more depleted isotopic compositions of surface soil water than CG_Frac. The vertical origin of RWU was estimated using the water balance (WB) calculations and the Bayesian mixing model (SIAR). While the former directly used water flow outputs, the latter used as input simulated isotopic compositions (using different fractionation scenarios) of RWU and soil water. Both methods provided similar variation trends with time and depth in different soil layers' contributions to RWU. The contributions of all soil layers interpreted by the CGT_Frac scenario were always between Non_Frac and CG_Frac. The temporal origin of RWU was deduced from particle tracking (PT, releasing one hypothetical particle for individual precipitation event and tracking its movement based on the water balance between particles) and a virtual tracer experiment (VTE, assigning a known isotope composition to individual precipitation event and tracking its movement based on the cumulative isotope flux). Both methods revealed similar variation trends with time in drainage and root zone (RZ) travel times. The interpreted drainage and RZ travel times were generally ranked as Non_Frac > CGT_Frac > CG_Frac. Overall, the factors considered in the standard CG equation dominated isotope fractionation, transport, and interpretations of the RWU origin. Isotope transport‐based methods (SIAR, VTE) were more computationally demanding than water flow‐based methods (WB, PT). Key Points: While factors in the Craig‐Gordon equation dominate evaporation fractionation, soil tension effects deplete isotopic composition of surface soil waterRoot water uptake origin interpreted by considering tension effects is between no fractionation and Craig‐Gordon fractionation scenariosUsing the Bayesian isotope mixing model or the virtual tracer experiment is more demanding than water balance or particle tracking methods [ABSTRACT FROM AUTHOR]

In drylands, poor rains combined with high evaporation rates increase the risks of soil salinization in addition to drought stress. Here, we determined the values of the parameters in the Feddes root water uptake function for sesame (Sesamum indicum L.) under drought and salinity stresses in a pot experiment using "Lebap-55", which has been bred for the drylands of the Aral Sea Basin but is moderately sensitive to salinity stress. We measured the hourly values of the transpiration, soil moisture, and salinity in the upper and lower soil layers in pots, solar radiation, and root distribution. The values were quantified by two methods. The bulk method uses only daily pot weight data, and the average soil water content and salt concentration are back-calculated from the mass balance. The inverse method uses the monitored values of the soil water content and salinity as well as daily weight data and solar radiation. Both methods could successfully estimate all the parameter values for both stresses. The bulk method performed better under drought stress, even without the measured soil water content or root distribution. It also had satisfactory accuracy in estimating the values under salinity stress. Both methods performed better under drought stress than under salinity stress. The parameter values determined here could be used for irrigation scheduling and salinity management using numerical models for the studied crop. [ABSTRACT FROM AUTHOR]

The uncontrolled establishment of weeds in upland cotton (Gossypium hirsutum L.), especially perennial silverleaf nightshade (Solanum elaeagnifolium), reduces lint yield and quality of cotton primarily by competing with cotton to limit essential resources such as water. Quantitative insight into the effects of cotton-silverleaf nightshade interactions on the root water uptake (RWU) in cotton is needed to develop weed management systems, particularly based on the critical periods of competitive water uses. A field experiment was conducted during two consecutive cotton growing seasons (2019–2020) to evaluate root zone soil water dynamics in subsurface drip-irrigated cotton under three treatments: only cotton plants (CP), only silverleaf nightshade plants (SNP), and cotton-silverleaf nightshade plants grown together (CP-SNP). The numerical model HYDRUS (2D/3D) was calibrated and validated using experimental data under the CP, SNP, and CP-SNP systems. The results of numerical simulations suggested that the HYDRUS (2D/3D) provided an effective tool for helping to understand and predict soil water dynamics and RWU under the CP-SNP competitive interactions at different cotton growth stages. Simulations showed that actual RWU (i.e., transpiration) and evapotranspiration rates remained higher under the CP-SNP treatment during two consecutive growing seasons, and RWU and evapotranspiration rates were in the order of CP-SNP > SNP > CP. The temporal variations in cumulative transpiration, evaporation, and drainage fluxes revealed that RWU solely contributed to higher evapotranspiration rates under the CP-SNP system as the magnitudes and patterns of evaporation and drainage fluxes remained similar among all the treatments. The temporal variations in RWU patterns at different cotton growth stages suggested that higher competitive RWU under the CP-SNP system than CP and SNP occurred during cotton’s leaf development and flowering growth stages, indicating critical periods for competitive soil water uses. Weed control measures during these critical periods are essential to minimize competitive water uses under the CP-SNP system in semiarid environments.

An isotope-enabled module of Hydrus-1D was applied to a potted olive tree to trace water parcels originating from 26 irrigation events in a glasshouse experiment. The soil hydraulic parameters were optimized via inverse modelling by minimizing the discrepancies between observed and simulated soil water content and soil water isotope (18O) values at three soil depths. The model's performance was validated with observed sap flow z-scores and xylem water 18O. We quantified the source and transit time of irrigation water by analysing the mass breakthrough curves derived from a virtual tracer injection experiment. On average, 26% of irrigation water was removed by plant transpiration with a mean transit time of 94 hours. Our proof of concept work suggests that transit time may represent a functional indicator for the uptake of irrigation water in agricultural ecosystems. [ABSTRACT FROM AUTHOR]

Moderate soil drying can cause a strong decrease in the soil‐root system conductance. The resulting impact on root water uptake depends on the spatial distribution of the altered conductance relatively to remaining soil water resources, which is largely unknown. Here, we analyzed the vertical distribution of conductance across root systems using a novel, noninvasive sensor technology on pot‐grown faba bean and maize plants. Withholding water for 4 days strongly enhanced the vertical gradient in soil water potential. Therefore, roots in upper and deeper soil layers were affected differently: In drier, upper layers, root conductance decreased by 66%–72%, causing an amplification of the drop in leaf water potential. In wetter, deeper layers, root conductance increased in maize but not in faba bean. The consequently facilitated deep‐water uptake in maize contributed up to 21% of total water uptake at the end of the measurement. Analysis of root length distributions with MRI indicated that the locally increased conductance was mainly caused by an increased intrinsic conductivity and not by additional root growth. Our findings show that plants can partly compensate for a reduced root conductance in upper, drier soil layers by locally increasing root conductivity in wetter layers, thereby improving deep‐water uptake. Summary statement: Soil drying leads to a strong reduction of root conductance in shallow soil layers, which maize partly compensates by facilitating deep water uptake via local increases in root conductivity. [ABSTRACT FROM AUTHOR]

The stability of slopes is greatly influenced by seasonal variations in pore water pressures (pwp) induced by rainfall infiltration and evapotranspiration processes. Despite that, the prediction of the hydrological effects of long-stem planting is often simplified or neglected because it is challenging to address. Its computation requires a proper definition of the plant root water uptake spatial distribution, which depends, in turn, on geometry and spatial root density. A well-suited case study in this field of application has been provided by a soil-filled embankment, close to an important traffic artery in Newcastle (Australia), which experienced shallow instability. The implementation of long-stem planting has been suggested as a remediation intervention. Based on this, an experimental study focusing on the effects of plant roots on the distribution of pwp in the site soil has been performed by means of a large-scale laboratory experiment on a 2-year-old native plant. Suction measurements were recorded within the vegetated soil mass under controlled boundary conditions and used to calibrate two different root spatial distributions in a seepage simulation. One is based on a flexible RWU spatial distribution function, and the other, specific for the plant RWU pattern, is simpler in its formulation and requires the definition of a lower number of parameters. A comparison between their performances in reproducing pwp distribution suggests that the second one is a better alternative. The methodological approach adopted has proven to be suitable for representing the hydraulic behaviour of a vegetated hillslope, to be eventually implemented in a proper stability assessment problem. [ABSTRACT FROM AUTHOR]

In the present study, a numerical model is developed to simulate the soil moisture flow and root water uptake under the limiting conditions in the root zone. The model solves the Richards equation by a mass conservative fully implicit finite difference scheme. The model is applied to two problems, i.e. numerical experiments on wheat grown in silt loam and sandy loam soils with three saline irrigations (with electrical conductivities 0.5, 15, 30 dS/m), and field irrigation experiments on rice crop grown with saline irrigations (with electrical conductivities 0.5, 7.9, 14.7 dS/m) with varying matric and osmotic stress conditions. The results show that the model performs well for both the cases and can be used for simulating root water uptake and scheduling of irrigation events. The model finds application in predicting root zone soil moisture for scheduling irrigation events for optimum crop yield in different agro-climate conditions, where treated waste water is used in conjunction with fresh water. [ABSTRACT FROM AUTHOR]

In water‐limited ecosystems, soil water regulates root water uptake (RWU) strategies. However, RWU responses to soil water changes under different species are not well‐understood. We assessed RWU responses of three revegetation species [shrub (Hippophae rhamnoides Linn.), coniferous forest [Platycladus orientalis (L.) Franco], and broad‐leaved forest (Robinia pseudoacacia L.) during the dry (May to June) and rainy (July to August) seasons in 2020 on the Loess Plateau using stable isotope methods. We sampled soil and xylem for each species at approximately weekly intervals and used the MixSIAR model to quantify RWU contribution with stable water isotopes. The results indicated that soil water in the shallow (0–40 cm) and middle (40–200 cm) soil layers fluctuated more strongly than the deep soil layer (200–300 cm) due to precipitation and evapotranspiration. Before precipitation in the dry season, most of the RWU for H. rhamnoides and R. pseudoacacia (97% and 98%) came from the middle layer under limited soil water. After precipitation in the dry season, the three species had similar RWU responses to soil water changes. After precipitation in the rainy season, the RWU change of H. rhamnoides and R. pseudoacacia with deep soil drying was more sensitive to soil water change than P. orientalis with sufficient deep water on August 3 and 11, while, the RWU of H. rhamnoides was more sensitive to soil water change than R. pseudoacacia on August 11 and 19. Thus, by switching its water‐use strategy, H. rhamnoides adapted better to the soil water environment than P. orientalis and R. pseudoacacia. This finding will help in selecting the optimal revegetation species for water use in a changing climate environment. [ABSTRACT FROM AUTHOR]

The development of an accurate root water-uptake model is pivotal for evaluating crop evapotranspiration; understanding the combined effect of drought and waterlogging stresses; and optimizing water use efficiency, namely, crop yield [kg/ha] per unit of ET [mm]. Existing models often lack quantitative approaches to depicting crop root water uptake in scenarios of concurrent drought and waterlogging moisture stresses. Addressing this as our objective; we modified the Feddes root water-uptake model by revising the soil water potential response threshold and by introducing a novel method to calculate root water-uptake rates under simultaneous drought and waterlogging stresses. Then, we incorporated a water stress lag effect coefficient, φWs, that investigated the combined effect of historical drought and waterlogging stress events based on the assumption that the normalized influence weight of each past stress event decreases with an increase in the time interval before simulation as an exponential function of the decay rate. Further, we tested the model parameters and validated the results obtained with the modified model using data from three years (2016–2018) of rice (Oryza sativa, L) trails with pots in Bengbu, China. The modified Feddes model significantly improved precision by 9.6% on average when calculating relative transpiration rates, particularly post-stress recovery, and by 5.8% on average when simulating soil moisture fluctuations during drought periods. The root mean square error of relative transpiration was reduced by 60.8%, and soil water was reduced by 55.1%. By accounting for both the accumulated impact of past moisture stress and current moisture conditions in rice fields, the modified model will be useful in quantifying rice transpiration and rice water use efficiency in drought–waterlogging-prone areas in southern China.