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Plant water uptake and plant and soil water status are important for the soil water balance and plant growth. They depend on atmospheric water demand and the accessibility of soil water to plant roots, which is in turn related to the hydraulic properties of the root system and the soil around root segments. We present a simulation model that describes water flow in the soil–plant system mechanistically considering both root and soil hydraulic properties. We developed an approach to upscale three‐dimensional (3D) flow in the soil toward root segments of a 3D root architecture to a model that considers one‐dimensional flow between horizontal soil layers and radial flow to root segments in that layer. The upscaled model couples upscaled linear flow equations in the root system with an analytical solution of the nonlinear radial flow equation between the soil and roots. The upscaled model avoids simplifying assumptions about root hydraulic properties and water potential drops near roots made in, respectively, soil‐ and root‐centered models. Xylem water potentials and soil–root interface potentials are explicitly simulated and show, respectively, large variations with depth and large deviations from bulk soil water potentials under dry soil conditions. Accounting for hydraulic gradients in the soil around root segments led to an earlier but slower reduction of transpiration during a drought period and a better plant water status with higher nighttime plant water potentials. Core Ideas: Root water uptake depends on root and soil hydraulic properties.Water uptake at root element scale was upscaled to the root system scale.The upscaled model can be implemented in one‐dimensional soil water flow models.Low conductance of dry soil prevents low nighttime plant water potentials. [ABSTRACT FROM AUTHOR]

This comment challenges Gao et al. (2023)'s perspective rejecting the role of soil processes in hydrology. We argue that the authors present a false dichotomy between soil-centric and ecosystem-centric views. These two views of hydrology are complementary and reflect on the inherent multiscale complexity of hydrology where soil processes dominate at certain scales but other processes may become important at catchment scale. We recognize the need for a new scale aware framework that reconciles the interplay between soil processes at small scales with emergent behaviors driven by vegetation, topography and climate at large scales. [ABSTRACT FROM AUTHOR]

Land surface modelling runs with CLM5 over Africa at 3 km resolution were carried out and we assessed the impact of different sources of soil information and different upscaling strategies of the soil information, also in combination with different atmospheric forcings and different temporal resolutions of those atmospheric forcings. FAO and SoilGrids250m were used as soil information. SoilGrids information at 250 m resolution was upscaled to the 3 km grid scale by three different methods: (i) random selection of one of the small SoilGrids250m grid cells contained in the model grid cell; (ii) arithmetic averaging of SoilGrids soil texture values and (iii) selection of the dominant soil texture. These different soil model inputs were combined with different atmospheric forcings model inputs, which provide inputs at different temporal resolutions: CRUNCEPv7 (6-hourly input resolution), GSWPv3 (3-hourly) and WFDE5 (hourly). We found that varying the source of soil texture information (FAO or SoilGrids250m) influences model water balance outputs more than the upscaling methodology of the soil texture maps. However, for high temporal resolution of atmospheric forcings (WFDE5) the different soil texture upscaling methods result in large differences in simulated evapotranspiration, surface runoff and subsurface runoff at the local and regional scales related to the higher resolution representation of rainfall intensity in the model. The upscaling methodology of fine scale soil texture information influences land surface model simulation results, but only clearly in combination with high temporal resolution atmospheric forcings. [ABSTRACT FROM AUTHOR]

Multiannual data (2016–2018) from 12 weighed lysimeters (four soil types with textures ranging from sandy loam to silt loam, three replicates) of the TERENO SOILCan network were used to evaluate if evaporation (E) rates could be predicted from weather data using the FAO Penman–Monteith (PM) method combined with soil water flow simulations using the Richards equation. Soil hydraulic properties (SHPs) were estimated either from soil texture using the ROSETTA pedotransfer functions, from in situ measured water retention curves, or from soil surface water contents using inverse modeling. In all years, E was water limited and the measured evaporation rates (Em) surprisingly did not vary significantly among the four different soil types. When SHPs derived from pedotransfer functions were used, simulated evaporation rates of the finer textured soils overestimated the measured ones considerably. Better agreement was obtained when simulations were based on in situ measured or inversely estimated SHPs. The SHPs estimated from pedotransfer functions represented unrealistically large characteristic lengths of evaporation (Lc), and Lc was found to be a useful characteristic to constrain estimates of SHPs. Also, when soil evaporation was water limited and Em rates were below Epot (PM evaporation scaled by an empirical coefficient), the diurnal dynamics of Em followed those of Epot. The Richards equation that considers only isothermal liquid water flow did not reproduce these dynamics caused by temperature dependent vapor transport in the soil. [ABSTRACT FROM AUTHOR]

Modeling soil hydraulic properties requires an effective representation of capillary and noncapillary storage and conductivity. This is made possible by using physically comprehensive yet flexible soil hydraulic property models. Such a model (Brunswick [BW] model) was introduced by Weber et al. (2019, https://doi.org/10.1029/2018WR024584), and it overcomes some core deficiencies present in the widely used van Genuchten‐Mualem (VGM) model. We first compared the performance of the BW model to that of the VGM model in its ability to describe water retention and hydraulic conductivity data on a set of measurements of 402 soil samples with textures covering the entire range of classes. Second, we developed a simple transfer function to predict BW parameters based on VGM parameters. Combined with our new function, any existing pedotransfer function for the prediction of the VGM parameters can be extended to predict BW model parameters. Based on information criteria, the smaller variance of the residuals, and a 40% reduction in mean absolute error in the hydraulic conductivity over all samples, the BW model clearly outperforms VGM. This is possible as the BW model explicitly accounts for hydraulic properties of dry soils. With the new pedotransfer function developed in this study, better descriptions of water retention and hydraulic conductivities are possible. We are convinced that this will strengthen the utility of the new model and enable improved field‐scale simulations, climate change impact assessments on water, energy and nutrient fluxes, as well as crop productivity in agroecosystems by soil‐crop and land‐surface modeling. The models and the pedotransfer function are included in an R package spsh (https://cran.r‐project.org/package=spsh). [ABSTRACT FROM AUTHOR]

The relatively poor simulation of the below-ground processes is a severe drawback for many ecosystem models, especially when predicting responses to climate change and management. For a meaningful estimation of ecosystem production and the cycling of water, energy, nutrients and carbon, the integration of soil processes and the exchanges at the surface is crucial. It is increasingly recognized that soil biota play an important role in soil organic carbon and nutrient cycling, shaping soil structure and hydrological properties through their activity, and in water and nutrient uptake by plants through mycorrhizal processes. In this article, we review the main soil biological actors (microbiota, fauna and roots) and their effects on soil functioning. We review to what extent they have been included in soil models and propose which of them could be included in ecosystem models. We show that the model representation of the soil food web, the impact of soil ecosystem engineers on soil structure and the related effects on hydrology and soil organic matter (SOM) stabilization are key issues in improving ecosystem-scale soil representation in models. Finally, we describe a new core model concept (KEYLINK) that integrates insights from SOM models, structural models and food web models to simulate the living soil at an ecosystem scale. [ABSTRACT FROM AUTHOR]

Background and aims: Although modelling of water and nutrient uptake by root systems has advanced considerably in recent years, steep local gradients of nutrient concentration near the root-soil interface in the rhizosphere are still a central challenge for accurate simulation of water and nutrient uptake at the root system scale. Conventionally, mesh refinement is used to resolve these gradients. However, it results in excessive computational costs. The object of the study is to present a multiscale approach which resolves the steep gradient of nutrient concentrations at rhizosphere scale and simulates nutrient and water fluxes within the entire root zone at macroscale scale in a computationally efficient way. Methods: We developed a 3D water and nutrient transport model of the root-soil system with explicit consideration of the 3D root architecture. To capture the nutrient gradients at root surfaces, 1D axisymmetric soil models at rhizosphere scale were constructed and coupled to the coarse 3D root-system-scale simulations using a mass conservative approach. The multiscale model was investigated under different scenarios for water and potassium (K+) uptake of a single root, multiple roots, and whole 3D architecture of a Zea mays L. root system in conditions of dynamic soil water and different soil buffer capacity of K+. Results: The steep gradients of K+ concentrations were efficiently resolved in the multiscale simulations thanks to the 1D model at the rhizosphere scale. In comparison with the refinement method, the multiscale model achieved a significant accuracy of K+ uptake prediction with a relative error below 5%. Meanwhile, the simulation at macroscale with coarse mesh could overestimate the K+ uptake in one order of magnitude. Moreover, the computational cost of multiscale simulations was decreased considerably by using coarse soil mesh. Conclusions: The newly developed model can describe the effect of the drying and nutrient transport in the root zone on nutrient uptake. It also allows to simulate processes in larger and complex root systems because of the considerable reduction in computational cost. [ABSTRACT FROM AUTHOR]

Background and Aims Root architecture development determines the sites in soil where roots provide input of carbon and take up water and solutes. However, root architecture is difficult to determine experimentally when grown in opaque soil. Thus, root architecture models have been widely used and been further developed into functional--structural models that simulate the fate of water and solutes in the soil--root system. The root architecture model CRootBox presented here is a flexible framework to model root architecture and its interactions with static and dynamic soil environments. Methods CRootBox is a C++-based root architecture model with Python binding, so that CRootBox can be included via a shared library into any Python code. Output formats include VTP, DGF, RSML and a plain text file containing coordinates of root nodes. Furthermore, a database of published root architecture parameters was created. The capabilities of CRootBox for the unconfined growth of single root systems, as well as the different parameter sets, are highlighted in a freely available web application. Key results The capabilities of CRootBox are demonstrated through five different cases: (1) free growth of individual root systems; (2) growth of root systems in containers as a way to mimic experimental setups; (3) fieldscale simulation; (4) root growth as affected by heterogeneous, static soil conditions; and (5) coupling CRootBox with code from the book Soil physics with Python to dynamically compute water flow in soil, root water uptake and water flow inside roots. Conclusions CRootBox is a fast and flexible functional--structural root model that is based on state-of-the-art computational science methods. Its aim is to facilitate modelling of root responses to environmental conditions as well as the impact of roots on soil. In the future, this approach will be extended to the above-ground part of the plant. [ABSTRACT FROM AUTHOR]

Animal manure application as organic fertilizer does not only sustain agricultural productivity and increase soil organic carbon ( SOC) stocks, but also affects soil nitrogen cycling and nitrous oxide (N2O) emissions. However, given that the sign and magnitude of manure effects on soil N2O emissions is uncertain, the net climatic impact of manure application in arable land is unknown. Here, we performed a global meta-analysis using field experimental data published in peer-reviewed journals prior to December 2015. In this meta-analysis, we quantified the responses of N2O emissions to manure application relative to synthetic N fertilizer application from individual studies and analyzed manure characteristics, experimental duration, climate, and soil properties as explanatory factors. Manure application significantly increased N2O emissions by an average 32.7% (95% confidence interval: 5.1-58.2%) compared to application of synthetic N fertilizer alone. The significant stimulation of N2O emissions occurred following cattle and poultry manure applications, subsurface manure application, and raw manure application. Furthermore, the significant stimulatory effects on N2O emissions were also observed for warm temperate climate, acid soils ( pH < 6.5), and soil texture classes of sandy loam and clay loam. Average direct N2O emission factors ( EFs) of 1.87% and 0.24% were estimated for upland soils and rice paddy soils receiving manure application, respectively. Although manure application increased SOC stocks, our study suggested that the benefit of increasing SOC stocks as GHG sinks could be largely offset by stimulation of soil N2O emissions and aggravated by CH4 emissions if, particularly for rice paddy soils, the stimulation of CH4 emissions by manure application was taken into account. [ABSTRACT FROM AUTHOR]

The article investigates the long-term sorption and sequestration of veterinary antibiotic radiolabeled sulfadiazine (SDZ) using two agricultural soils. A modified two-stage model with irreversible sorption combined with global parameter optimization was able to demonstrate the sequestration dynamics. This was demonstrated with sterilized samples in which no transformation of the parent compound was noted. This also indicates that transformation was primarily biologically driven. The sorption and sequestration of SDZ were allegedly soil-specific and dominated by kinetics.

The article presents a study which examines the association on environmental risks because of using fluoroquinolone antibiotics in animal husbandry and human therapeutics. Difloxacin was administered to pigs and used the contaminated manure to soil, and examined the sequestration and dissipation of difloxacin in soil in the presence and absence of plants. The effect of antibiotic on nitrogen turnover in soil (potential denitrification and nitrification) is also examined. The study shows that difloxacin was very persistent and hardly (bio) accessible under all conditions studied.

Focuses on the improvements and refinements of the Predicted Environmental Concentrations model with regard to the description of volatilization from bare soil. Measurement of volatilization rates of pesticides; Enhancement of the spatiotemporal discretization at the soil surface; Description of temperature dependence of Henry's law constants.

A critical review of implicit assumptions behind typical one-dimensional root water uptake and stress models is performed. Plantscale mathematical expressions for stress and uptake functions obeying Darcy flow equations in three-dimensional systems are proposed. The process description of plant transpiration and soil water uptake in macroscopic root water uptake models is often based on simplifying assumptions that no longer reflect, or even contradict, the current status of knowledge in plant biology. The sink term in the Richards equation for root water uptake generally comprises four terms: (i) a root resistance function, (ii) a soil resistance function, (iii) a stress function, and (iv) a compensation function. Here we propose to use a detailed three-dimensional model, which integrates current knowledge of soil and root water flow equations, to deduct a one-dimensional effective behavior at the plant scale and to propose improvements for the four functions used in the macroscopic sink term. We show that (i) root hydraulic resistance may be well defined by the root length density but only for homogeneous lateral conductances and no limiting xylem conductance--in other cases a new function depending on the root hydraulic architecture should be used; (ii) soil resistance cannot be neglected, in particular in the rhizosphere where specific processes may occur that alter the soil hydraulic properties and therefore affect uptake; (iii) stress and compensation are two different processes, which should not be linked explicitly; (iv) there is a need for a clear definition of compensatory root water uptake independent of water stress; (v) stress functions should be defined as a maximal actual transpiration in function of an integrated root--soil interface water head rather than in terms of local bulk water heads; and (vi) nonlinearity in the stress function is expected to arise if root hydraulic resistances depend on soil matric head or when it is defined as a function of the bulk soil water head. [ABSTRACT FROM AUTHOR]

Temporal mapping of the three-dimensional spatial distribution of solute transport in soils is needed for an improved understanding of the underlying processes. Numerous studies have confirmed that Brilliant Blue imaging provides spatially highly resolved information on solute transport in soils. A drawback of the method, however, is its destructive character, which prevents three-dimensional mapping of the temporal evolution of Brilliant Blue plumes or fronts. In this study, we determined that the negative ionic charge of the Brilliant Blue molecule for moderately acid and basic environments provides an electrical conductivity contrast that can be detected by means of time domain reflectometry (TDR) and electrical resistivity tomography (ERT). Time-lapse ERT supplies three-dimensional spatiotemporally resolved image data through minimally invasive measurements but with limited spatial resolution. A joint application of Brilliant Blue imaging and (time-lapse) ERT offers potential benefits such as ERT image validation by dye staining, spatiotemporally resolved Brilliant Blue displacement studies, and improved ERT inversion regularization based on Brilliant Blue image-derived solute plume or front characteristics. This study illustrates the efforts needed to quantitatively relate Brilliant Blue concentration and electrical conductivity as well as the potential and limitations of noninvasive smoothness-constrained ERT for solute imaging in soils. [ABSTRACT FROM AUTHOR]

One-dimensional transport models that predict field-scale averaged solute fluxes are often used to estimate the risk of nonpoint source groundwater contamination by widespread surface-applied chemicals. However, within-field variability of soil hydraulic properties leads to lateral variation in local solute fluxes. When this smaller scale variability is characterized in a geostatistical sense, stochastic three-dimensional flow and transport equations can be used to predict field-scale averaged transport in terms of geostatistical parameters. We discuss the use of stochastic equations for the parameterization of equivalent one-dimensional models predicting averaged solute fluxes. First, we consider the equivalent one-dimensional convection dispersion model and the equivalent dispersivity, which characterizes the spreading of laterally averaged concentrations or solute fluxes. Second, we discuss the parameterization of a stream tube model to predict local transport variables (i.e., distributions of local concentrations and local arrival times) These local transport variables are shown to be important for predicting nonlinear local transport processes and useful for inversely inferring the spatial structure of soil properties. Stochastic flow and transport equations reveal a dependency of equivalent model parameters on transport distance and flow rate, which reflects the importance of smaller scale heterogeneities on field-scale transport. Approximate solutions of stochastic flow and transport equations are obtained for steady-state and uniform flow. The effect of transient flow conditions on transport is discussed. Throughout the paper we refer to experimental and numerical data that confirm or contradict results from stochastic flow and transport equations. [ABSTRACT FROM AUTHOR]

• Physicochemical soil properties nonlinearly explain the history of LUC in China. • An explainable machine-learning method provides both local and global explanations. • A new perspective on LUC change with reliance on soil properties as drivers. • Toward knowledge gap-filling regarding soil properties in explaining LUC history. Enhancing our comprehension of soil processes and their impact on Earth requires precise quantification of human-induced soil alterations, particularly those related to land use/cover (LUC) histories. Thoroughly validated LUC and soil maps specific to China, and an explainable machine-learning approach were applied to reveal how soil physicochemical properties, independently or in combination, explain LUC histories in the last sixty years. Validation using historical data showed that the proposed machine-learning models can adequately simulate the pattern of LUC histories. Nonlinear mappings of various soil properties in explaining LUC histories were demonstrated and critical thresholds for changes in the explanatory capacities of each soil property to specific LUC histories were identified. Specifically, physical soil properties, except for soil pH, particularly soil thickness, clay content, bulk density, and coarse fragments, play significant roles in explaining the historical trajectories of forests, croplands, and pasture/rangelands than chemical soil properties. Predicted LUC changes suggest more intensive dynamics that are characterized by expansions in forest and pasture/rangeland areas, coupled with a reduction in cropland areas. Overall, improving understanding of the bidirectional links between soil and LUC changes is a crucial and imperative step towards refining the representation of soils in Earth system models. [ABSTRACT FROM AUTHOR]

Saturated soil column experiments were conducted to investigate the transport, retention, and release behavior of a low concentration (1 mg L −1 ) of functionalized 14 C-labeled multi-walled carbon nanotubes (MWCNTs) in a natural soil under various solution chemistries. Breakthrough curves (BTCs) for MWCNTS exhibited greater amounts of retardation and retention with increasing solution ionic strength (IS) or in the presence of Ca 2+ in comparison to K + , and retention profiles (RPs) for MWCNTs were hyper-exponential in shape. These BTCs and RPs were well described using the advection-dispersion equation with a term for time- and depth-dependent retention. Fitted values of the retention rate coefficient and the maximum retained concentration of MWCNTs were higher with increasing IS and in the presence of Ca 2+ in comparison to K + . Significant amounts of MWCNT and soil colloid release was observed with a reduction of IS due to expansion of the electrical double layer, especially following cation exchange (when K + displaced Ca 2+ ) that reduced the zeta potential of MWCNTs and the soil. Analysis of MWCNT concentrations in different soil size fractions revealed that >23.6% of the retained MWCNT mass was associated with water-dispersible colloids (WDCs), even though this fraction was only a minor portion of the total soil mass (2.38%). More MWCNTs were retained on the WDC fraction in the presence of Ca 2+ than K + . These findings indicated that some of the released MWCNTs by IS reduction and cation exchange were associated with the released clay fraction, and suggests the potential for facilitated transport of MWCNT by WDCs. [ABSTRACT FROM AUTHOR]

• Novel workflow for coupled full waveform inversion (CFWI) was proposed. • CFWI outperforms coupled inversion of travel times to invert hydraulic properties. • A range of challenges remain for the application of CFWI to real GPR data. Coupled inversion is a promising technique for determining soil hydraulic properties from time-lapse geophysical measurements. In this inversion approach, a hydrological model is coupled with ground penetrating radar (GPR) forward modelling to avoid interpretation errors from data processing. In this study, a workflow for coupled GPR full-waveform inversion (CFWI) is proposed that combines the benefits of coupled inversion and full-waveform inversion (FWI) to estimate soil hydraulic properties from time-lapse horizontal borehole GPR measurements. In particular, a synthetic modelling study is presented that compares the performance of coupled inversion of full waveforms and first arrival time data from zero-offset profile (ZOP) borehole measurements obtained during an infiltration event for estimating hydraulic parameters and the thickness of the first layer for a 2-layer soil profile. It was found that the thickness of the first layer could be more accurately estimated by CFWI because of the additional information contained in reflected and refracted waves from the air–soil layer boundary. Furthermore, the hydraulic parameters estimated by the coupled inversion of GPR travel times slightly deviated from true values and showed a relatively large uncertainty, whereas the results of CFWI precisely matched the known water retention and hydraulic conductivity functions. Despite these promising results, several challenges should be solved before CFWI can be applied to experimental GPR data. First, conducting CFWI needs accurate conceptual setups for the hydro(geo-)logical model. Furthermore, a robust approach should be developed to accurately estimate an effective source wavelet from the experimental ZOP data, and a more sophisticated hydrological modelling approach has to be considered to better estimate the distribution of soil electrical conductivity during the infiltration event. Finally, the accuracy and efficiency of current GPR modelling methods may need to be improved. [ABSTRACT FROM AUTHOR]

• Sequential inversion of GPR data cannot provide accurate hydraulic parameters. • Coupled inversion of GPR data provides reliable field-scale hydraulic parameters. • Parameters obtained from coupled inversion and TDR measurements were consistent. Horizontal borehole ground penetrating radar (GPR) measurements can provide valuable information on soil water content (SWC) dynamics in the vadose zone, and hence show potential to estimate soil hydraulic properties. In this study, the performance of both sequential and coupled inversion workflows to obtain soil hydraulic properties from time-lapse horizontal borehole GPR data obtained during an infiltration experiment were compared using a synthetic modelling study and the analysis of actual field data. The sequential inversion using the vadose zone flow model HYDRUS-1D directly relied on SWC profiles determined from the travel time of GPR direct waves using the straight-wave approximation. The synthetic modelling study showed that sequential inversion did not provide accurate estimates of the soil hydraulic parameters due to interpretation errors in the estimated SWC near the infiltration front and the ground surface. In contrast, the coupled inversion approach, which combined HYDRUS-1D with a forward model of GPR wave propagation (gprMax3D) and GPR travel time information, provided accurate estimates of the hydraulic properties in the synthetic modelling study. The application of the coupled inversion approach to measured borehole GPR data also resulted in plausible estimates of the soil hydraulic parameters. It was concluded that coupled inversion should be preferred over sequential inversion of time-lapse horizontal borehole GPR data in the presence of strong SWC gradients that occur during infiltration events. [ABSTRACT FROM AUTHOR]

The International Soil Modeling Consortium (ISMC) was established in 2016 with the aim to integrate and advance soil systems modeling, data collection, and observational capabilities. ISMC is a community effort. It follows a bottom-up approach, is based on scientific principles, voluntary contributions, and open to anybody who wants to become a member of the consortium (https://soil-modeling.org/). Its activities are organized into three science panels, organized around a broad workflow from data collection and observation (DO-LINK) to model development and intercomparison (Soil-MIP) to engagement with different scientific communities (CROSS-Connect). ISMC has an executive board and a scientific advisory board that guides ISMC in pursuing its objectives. The mission of the Soil-MIP science panel is to foster the further development of soil models that can predict soil functions and their changes due to soil use and land management, as well as climate change and pollution. A number of model intercomparison studies were recently initiated, focusing on specific processes like soil hydraulic properties, soil thermal properties and related soil heat fluxes, root growth and root water uptake, soil evaporation, soil freezing, infiltration and runoff processes, and coupling between preferential flow in soils and groundwater. From these comparisons, lessons can be learned about how process controls at small scales propagate to larger scales and how this leads to effective process representations at larger scales. The mission of DO-Link is to assist with the development of a global soil data meta-repository that is openly available for soil system research. Data and data requirements are as diverse as the various disciplines developing and applying soil models. The soil data meta-repository will be a resource to analyze past and recent model- and data requirements for continuous standardization and harmonization of soil data. The CROSS-connect science panel identifies soil related knowledge gaps between science communities, and shares this knowledge with other ISMC science panels to push forward development of new tools to better translate soil processes into functions for assessing sustainability and ecosystem services. CROSS-connect develops an exchange platform with other international partners like AgMip/MACSUR, GEWEX, ISCN (International Soil Carbon Network), GSBI (Global Soil Biodiversity initiative) and CSDMS (Community Surface Dynamics Modeling System). In this presentation, we will highlight the most recent developments and activities that are currently underway as well as future projects that are under preparation. [ABSTRACT FROM AUTHOR]