Aims
Perennial crops with more extensive and deep root systems could access deep stored water and build resilience to water shortage. In the context of human nutrition, perennial grain crops are very ...interesting. However, it is still questionable whether they are effective in using subsoil water. We compared intermediate wheatgrass (Kernza®)
Thinopyrum intermedium
, a perennial grain crop, to alfalfa
Medicago sativa
, a forage crop, for subsoil root growth and water uptake. Alfalfa was chosen because of its deep root system and agronomical interest as a companion crop.
Methods
Using TDR sensors, deuterium tracer labelling, minirhizotrons and the Hydrus-1D model we characterised the root distribution and water uptake patterns of these two perennial crops during two cropping seasons under field conditions down to 2.5 m soil depth.
Results
Both crops grew roots down to 2.0 m depth that were active in water uptake but alfalfa was deeper rooted than intermediate wheatgrass. All experimental methods concluded that alfalfa used more water from below 1.0 m depth than intermediate wheatgrass. However, simulations predicted that intermediate wheatgrass used more than 20 mm of water after anthesis from below 1 m soil depth. Simulations confirmed the advantage of deep roots in accessing deep soil water under drought.
Conclusions
In regions with high groundwater recharge, growing deep-rooted perennial crops have great potential to exploit deep soil water that is often left unused. However, the road to a profitable perennial grain crop is still long and breeding intermediate wheatgrass (Kernza®) cultivars for increased root growth at depth seems to be a worthy investment for the development of more drought tolerant cultivars.
The determination of field capacity (FC), irrigation thresholds, and irrigation amounts is characterized by site-specific soil hydraulic properties (SHPs). This study, conducted in two zones (zone 1 ...and zone 2) delineated based on soil, topography, and historical crop yield in Alabama (USA), focused on determining zone-specific FC using negligible drainage flux qfc criterion. The HYDRUS-1D model was used to optimize zone-specific SHPs using measured soil matric potential (h). The zone-specific FCs were determined using optimized and raw SHPs at 0.01 cm/day as qfc. The results showed that the optimized FC at qfc was at −39 kPa in zone 1 and raw FC was at −15 kPa. However, in zone 2, optimized FC was at −25 kPa and raw FC was at −59 kPa. To validate that optimized values are more accurate than raw values, a relationship between accumulated crop evapotranspiration (ETc) and required irrigation amount was determined using optimized parameters (SHPs and FC) and showed a stronger correlation in both zones than using raw parameters (SHPs and FC). At flux-based FC, the optimized irrigation thresholds and amounts in zone 1 were −88 kPa and 20 mm, and raw irrigation threshold and amount were −58 kPa and 33 mm, respectively. In zone 2, the optimized irrigation thresholds and amounts were −45 kPa and 18 mm, and raw irrigation threshold and amount were −116 kPa and 14 mm, respectively. Therefore, using raw and benchmark FC can result in inefficient irrigation strategies. The proposed novel method of optimizing zone-specific FC and irrigation thresholds can help with adopting timely best irrigation management schemes in respective zones.
•Soil hydraulic properties (SHPs) were optimized using in-situ soil matric potentials (h) with inverse numerical modeling.•Field capacities (FC) were optimized at a negligible drainage flux criterion of 0.01 cm/day using raw and optimized SHPs.•h at optimized FC yielded the best irrigation recommendation relationships with accumulated crop evapotranspiration.•h at FCs were optimized to −39 kPa and −25 kPa, respectively, in zone 1 and zone 2.•Irrigation thresholds were optimized to −88 kPa and −45 kPa, respectively, in zone 1 and zone 2.
Assessing the impact of a land-use change (LUC) or change in land-use management on nonpoint source-driven groundwater quality in heterogeneous aquifers requires complex analysis. Stochastic methods ...have been used to account for prediction uncertainty but at high computational cost, which significantly limits the application of these approaches. As an efficient alternative, this study evaluates the application of a meta-analytical solution for evaluating the change in contaminant breakthrough curves at extraction wells in response to LUC. The solution uses the concentration percentiles from a reference stochastic simulation of water flow and solute transport in a groundwater system, assuming a reference land-use distribution pattern. Reference land-use controls the spatially variable rates of both, recharge and contaminant mass loading. The effect of a LUC is evaluated by scaling the ratio between the reference and the new (post-LUC) average input concentrations. The validity of the proposed meta-analysis tool is tested by comparing the results of the meta-analytical solution with those from a full stochastic simulation of the post-LUC scenario. Simulation results show that the accuracy of the meta-analytical solution is best when the regional average recharge rates for both pre- and post-LUC remain approximately unchanged, for any change in contaminant mass loading. Results also indicate that changes in spatial variability and pattern of the recharge rate do not significantly impact the flow field, travel times, and resulting concentrations, if the magnitude of local recharge remains about the same. Lastly, the results show large variability among wells of (and—for an individual well—uncertainty about) the time lag between the time of LUC and the time of consequential effective change in concentrations across wells in the affected region, captured here using statistical metrics.
Evaporation from bare soil is an important hydrological process and part of the water and energy balance of terrestrial systems. Modeling bare‐soil evaporation is challenging, mainly due to nonlinear ...couplings among liquid water, water vapor, and heat fluxes. Model concepts of varying complexity have been proposed for predicting evaporative water and energy fluxes. Our aim was to test a standard model of coupled water, vapor, and heat flow in the soil using data from laboratory evaporation experiments under different boundary conditions. We conducted evaporation experiments with a sand and a silt loam soil and with three different atmospheric boundary conditions: (i) wind, (ii) wind and short‐wave radiation, and (iii) wind and intermittent short‐wave radiation. The packed soil columns were closed at the bottom (no water flux) and instrumented with temperature sensors, tensiometers, and relative humidity probes. We simulated the evaporation experiments with a coupled water, vapor, and heat flow model, which solves the surface energy balance and predicts the evaporation rate. The evaporation dynamics were predicted very well, in particular the onset of stage‐two evaporation and the evaporation rates during the stage. A continuous slow decrease of the measured evaporation rate during stage‐one could not be described with a constant aerodynamic resistance. Adding established soil resistance parametrizations to the model significantly degraded model performance. The use of a boundary‐layer resistance, which takes into account the effect of point sources of moisture, improved the prediction of evaporation rates for the sandy soil, but not for the silt loam.
Core Ideas
Evaporation experiments under different atmospheric conditions were modeled with coupled water‐vapor‐heat flow.
Model predicted evaporation dynamics well, but slightly falling rates during stage‐one could not be modeled.
Parameterization of soil hydraulic properties accounts for sorbed water and film flow.
Unjustified empirical soil resistance parameterizations degraded model performance.
Use of a boundary‐layer resistance described the decrease during stage‐one for sand, but not for loam.
Core Ideas
Evaporation experiments under different atmospheric conditions were modeled with coupled water‐vapor‐heat flow.
Model predicted evaporation dynamics well, but slightly falling rates during stage‐one could not be modeled.
Parameterization of soil hydraulic properties accounts for sorbed water and film flow.
Unjustified empirical soil resistance parameterizations degraded model performance.
Use of a boundary‐layer resistance described the decrease during stage‐one for sand, but not for loam.
Core Ideas
Water flow and solute transport models described solute leaching during slurry injection.
Intermittent flow increased leaching of injected slurry compounds compared with steady flow.
Mass ...exchange of slurry compounds during interruptions occurred from im‐ to mobile pore regions.
Mass exchange between pore regions should be included in larger scale model predictions.
Animal slurry application to agricultural land can be a threat to the quality of groundwater and nearby surface water bodies by percolation of solutes from slurry sources. We hypothesized that local‐scale processes, such as mass exchange between preferential flow paths and matrix pore regions, can play a substantial role in relation to slurry application and nutrient leaching. To improve understanding of these mass exchange mechanisms, soil column leaching data of nonreactive slurry components after injection of dairy slurry were analyzed under different initial and boundary conditions with single‐ and double‐porosity model approaches. The data set was from nine intact soil columns (20‐cm i.d., 20‐cm height) of the plow layer of arable loamy topsoil that were percolated under unsaturated steady‐flow conditions with a suction of 5 cm applied at the bottom. Both single‐ and double‐porosity water flow and mobile–immobile solute transport models could describe these experimental breakthrough curves. Rainfall interruptions mimicking more natural conditions and variably saturated intermittent flow led to higher leaching of injected slurry compounds than steady‐flow conditions. These observations could be explained by an increased mass exchange of dissolved injected slurry components from the immobile to the mobile pore water regions during interruptions. The results suggest that column tests under steady‐flow conditions could lead to false predictions of solute leaching after slurry injection in structured soils. Furthermore, local‐scale processes, such as mass exchange between pore regions, should be included in larger scale model predictions of nutrient losses from agricultural fields.
Background
Bracken fern (
Pteridium aquilinum
) produces several toxic glycosides, of which ptaquiloside (PTA) is the most well documented. PTA is released from bracken to soil and leaches to surface ...water and to groundwater. This study presents the first comprehensive monitoring study of bracken biomass, PTA content in the biomass, release by precipitation and concentrations in soil solution at 50 cm depth. Laboratory experiments were carried out to estimate the degradation kinetics of PTA in different soil horizons and moisture contents.
Results
The PTA concentration in bracken was highest at the earliest development stages of the plant, i.e., May, declining through the growing season until negligible contents at senescence. The maximum seasonal PTA content in the canopy peaked in early summer, with values up to 1600 mg m
−2
. Results show that on average 0.2% of the PTA present in the canopy is washed per mm of incident rain, resulting in up to 13.1 mg PTA m
−2
being washed off during single rain events. Once in the soil, PTA dissipates rapidly showing a half-lives ranging from 3.3 to 73 h with observed degradation rates showing a tenfold decrease with soil depths increasing from top soil to 25 cm soil depth. Concentrations of PTA in soil solution were positively correlated with the content of PTA in the canopy, with maximum pore water concentrations up to 4,820 ng L
−1
during a pulse event taking place in July 2019.
Conclusions
The production of PTA in bracken was found to be proportional to biomass growth, while the mass of PTA being released is a function of volume and intensity of precipitation, as well as the bracken development stage. Leaching of PTA takes place in the form of pulses linked to precipitation events, with concentrations in the soil solution exceeding levels which are known to pose a risk to human health.
Crop model intercomparison studies have mostly focused on the assessment of predictive capabilities for crop development using weather and basic soil data from the same location. Still challenging is ...the model performance when considering complex interrelations between soil and crop dynamics under a changing climate. The objective of this study was to test the agronomic crop and environmental flux‐related performance of a set of crop models. The aim was to predict weighing lysimeter‐based crop (i.e., agronomic) and water‐related flux or state data (i.e., environmental) obtained for the same soil monoliths that were taken from their original environment and translocated to regions with different climatic conditions, after model calibration at the original site. Eleven models were deployed in the study. The lysimeter data (2014–2018) were from the Dedelow (Dd), Bad Lauchstädt (BL), and Selhausen (Se) sites of the TERENO (TERrestrial ENvironmental Observatories) SOILCan network. Soil monoliths from Dd were transferred to the drier and warmer BL site and the wetter and warmer Se site, which allowed a comparison of similar soil and crop under varying climatic conditions. The model parameters were calibrated using an identical set of crop‐ and soil‐related data from Dd. Environmental fluxes and crop growth of Dd soil were predicted for conditions at BL and Se sites using the calibrated models. The comparison of predicted and measured data of Dd lysimeters at BL and Se revealed differences among models. At site BL, the crop models predicted agronomic and environmental components similarly well. Model performance values indicate that the environmental components at site Se were better predicted than agronomic ones. The multi‐model mean was for most observations the better predictor compared with those of individual models. For Se site conditions, crop models failed to predict site‐specific crop development indicating that climatic conditions (i.e., heat stress) were outside the range of variation in the data sets considered for model calibration. For improving predictive ability of crop models (i.e., productivity and fluxes), more attention should be paid to soil‐related data (i.e., water fluxes and system states) when simulating soil–crop–climate interrelations in changing climatic conditions.
Core Ideas
We demonstrate the use of high precision weighable lysimeter for full model calibration and validation.
Lysimeter data from translocated soils represent effects of changing climatic conditions.
We compare calibration with blind forward simulations (fixed soil and calibrated crop parameter).
We compare individual crop model predictions with multi‐model mean.
We test the predictive ability of crop models and multi‐model mean.
Abstract Evaporation of soil water depends not only on climatic conditions, soil surface roughness, soil texture, and soil hydraulic properties but also on the soils’ macrostructure. Evaporation is ...characterized by water losses over time for a defined soil volume, where soils are assumed to be homogeneous in texture and structure. In this technical note, we investigated the potential and limitations of 3D modeling of evaporation processes on 250 cm 3 soil cores with structural features ≥480 µm determined by X‐ray computed tomography. For this, we used isothermal Richards equation as the main governing equation, accounting also for isothermal vapor flow. We simulated two evaporation experiments with same soil texture but contrasting macrostructures, that is, the spatial arrangement of voxels classified as soil matrix and air‐filled voids, of a ploughed and non‐ploughed grassland soil with HYDRUS 3D. In both simulations, we fixed the potential evaporation rates to the experimental rates and evaluated simulation results with measured matric potential data at two depths (1.25 cm and 3.75 cm) continuously recorded at 10 min intervals. We could show that the simulations of bare soil evaporation were able to predict the tensiometer dynamics and water losses for the full experimental time of 7 days. The simulation provided unique spatial information of water content and flow velocities as a function of time, which are important when studying the effect of air‐filled macropores, macro‐connectivity of soil matrix, and water dynamics on soil evaporation.
Core Ideas The authors present a methodology to conduct 3D simulations with HYDRUS Suite for real soil systems based on X‐ray µCT images. The authors present 3D simulation of bare soil evaporation on structured soils. The authors evaluate the simulations using mass loss and tensiometer measurements. The authors present quantification and visualization of the effects of soil structure on soil water dynamics.
Agroecosystem models need to reliably simulate all biophysical processes that control crop growth, particularly the soil water fluxes and nutrient dynamics. As a result of the erosion history, ...truncated and colluvial soil profiles coexist in arable fields. The erosion‐affected field‐scale soil spatial heterogeneity may limit agroecosystem model predictions. The objective was to identify the variation in the importance of soil properties and soil profile modifications in agroecosystem models for both agronomic and environmental performance. Four lysimeters with different soil types were used that cover the range of soil variability in an erosion‐affected hummocky agricultural landscape. Twelve models were calibrated on crop phenological stages, and model performance was tested against observed grain yield, aboveground biomass, leaf area index, actual evapotranspiration, drainage, and soil water content. Despite considering identical input data, the predictive capability among models was highly diverse. Neither a single crop model nor the multi‐model mean was able to capture the observed differences between the four soil profiles in agronomic and environmental variables. The model's sensitivity to soil‐related parameters was apparently limited and dependent on model structure and parameterization. Information on phenology alone seemed insufficient to calibrate crop models. The results demonstrated model‐specific differences in the impact of soil variability and suggested that soil matters in predictive agroecosystem models. Soil processes need to receive greater attention in field‐scale agroecosystem modeling; high‐precision weighable lysimeters can provide valuable data for improving the description of soil–vegetation–atmosphere process in the tested models.
This review provides an overview on various phenomena, hypothesized causes, and modeling approaches that describe "dynamic nonequilibrium" (DNE) of water flow in soils. Dynamic nonequilibrium is ...characterized from observations on the macroscale by an apparent flow-rate dependence of hydraulic properties or by local nonequilibrium between water content and pressure head under monotonic imbibition or drainage histories, i.e., not affected by traditional hysteresis. The literature indicates that key processes causing DNE are pore-scale phenomena such as relaxation of air-water-interface distributions, limited air-phase permeability, dynamic contact angles, and time-dependent wettability changes. Furthermore, entrapment of water and pore water blockage, air-entry effects, and temperature effects might be involved. These processes act at different pressure head regions and on different time scales, which makes effective modeling of the combined phenomena challenging. On larger scales, heterogeneity of soil properties can contribute to DNE observations. We conclude that there is an urgent need for precision measurements that are designed to quantify dynamic effects.
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