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Soil shrinkage characteristic curves are used to describe the shrinkage behavior and hydraulic properties of unsaturated soils. To construct soil shrinkage characteristic curves, a high‐data‐density measurement method is needed that relates water content to soil volume changes. We present a fully automated soil shrinkage measurement setup, based on the simplified evaporation method, to characterize the shrinkage behavior of undisturbed natural expansive clay soils. The high data density creates the opportunity to produce soil shrinkage characteristic curves without the need for a mathematical model. The technique allows for resaturation of the samples after drying, enabling differentiation between reversible and irreversible shrinkage. The setup consists of the commercialized HYPROP2 apparatus combined with optical distance sensors to measure the horizontal and vertical dimensions of the samples, yielding data on the sample volume, weight, and soil water suction. The measurement frequency is once per 10 min, and the measurement period is up to 4 weeks, providing a detailed time series of the drying and shrinkage characteristics. The setup can capture the different shrinkage phases and offers the opportunity to relate the soil shrinkage characteristic curve to soil water suction. The measurement data acquisition rate and accuracy enable detailed interpretation of soil water retention curves for nonrigid soils and are shown to be essential for understanding and quantifying the shrinkage potential of several types of deposits. [ABSTRACT FROM AUTHOR]

The susceptibility of surface soil to drying when rainfall is scarce has prompted evaluation of deeper placement (20 cm) of fertilizers within the profile to where soil moisture is more likely to be stored. However, concerns arise regarding potential chemical challenges to P availability in the subsurface. This study examined differences in chemical conditions between the soil surface (0–10 cm) and subsurface (15–25 cm), and investigated the effect on the diffusion and extractability of banded P. Analysis of surface and subsurface samples from 15 sites revealed substantial differences in characteristics that influence P behavior between depths. The phosphorus buffering index (PBI) was largely explained by concentrations of amorphous Al and Fe (hydr)oxides and CaCO3. The measured diffusion distance of P from monoammonium phosphate (MAP) granules was found to be inversely related to PBI. Consequently, significant differences in diffusion distances were typically observed between soil layers characterized by marked PBI variations. The measured diffusion radii were used to calculate the mean P concentrations of surface-banded and deep-banded MAP in a field scenario, which were replicated in a 4-week laboratory incubation. The resulting lability of applied P was determined through isotopic exchange, and although significantly higher P recoveries were measured from the subsurface at two sites where large pH differences existed between depths, no significant differences were measured between depths at all other sites. Hence, the subsurface is not a more hostile zone for deep-placed P. [ABSTRACT FROM AUTHOR]

This study addresses the problem of 2D soil water movement under ponding radii of 1, 2, and 3 cm. The soil water movement characteristics (shape parameters of the water content profile, ratio of horizontal wetting front to vertical wetting front, relationship between infiltration time and horizontal wetting front, and relationship between infiltration time and cumulative infiltration) under the above three kinds of water ponding radius were analyzed. On the basis of the assumption that the soil wetting body is a semi-ellipse and the analytical solution of the 1D soil water movement equation at any angle, the approximate analytical solution of the 2D soil water movement equation under ponding conditions is optimized. The function relationships between infiltration time, wetting front, and cumulative infiltration are established. We applied the numerical data simulated by HYDRUS-3D to validate the parameters in proposed analytical solutions and evaluated the relationships between the wetting front and hydraulic parameters. The results indicate that as the water ponding radius increases, the wetting body and 2D water content distribution becomes larger. When the water ponding radius was 2 cm, the numerical and analytical solution of 1D soil water distribution showed the best comparison results, and the model error was the smallest. The ratio of wetting fronts was linearly increased with the increase of air-entry suction with R² = 0.9969. [ABSTRACT FROM AUTHOR]

Field capacity is a dubious soil physical property, but its use continues because of its perceived value for representing a soil’s capacity to store water. Appropriate field capacity estimates can be useful for interpreting data from soil moisture sensors, including those in large-scale monitoring networks, but suitable methods for defining field capacity in this context are unclear. Motivated by the desire to determine optimal field capacity values for the Oklahoma Mesonet, our objectives were (1) to develop and apply an automated time series analysis algorithm to estimate volumetric soil water content at field capacity and corresponding matric potential and (2) to compare the resulting water contents to those calculated from traditional matric potential thresholds (−33 and −10 kPa). Across 118 Oklahoma Mesonet sites and three soil depths (5, 25, and 60 cm), a matric potential threshold of −10 kPa underestimated field capacity water content by 0.010–0.014 cm cm−3 (3–4%) on average, and a threshold of −33 kPa underestimated it for every site and depth by 0.055– 0.078 cm cm−3 (16%−22%) on average. Median matric potentials corresponding to field capacity were −7.6 kPa at the 5-cm depth, −7.2 kPa at the 25-cm depth, and −7.3 kPa at the 60-cm depth. The algorithm developed here can be used to estimate field capacity wherever adequate data are available, and for sites where soil water retention properties are known, matric potentials at field capacity can also be estimated. Using a matric potential of −33 kPa as a standard threshold to represent field capacity is not scientifically justified and should be discontinued. [ABSTRACT FROM AUTHOR]

Soil texture can affect soil temperature, soil moisture, the protection of organic material against microbial degradation, and other soil properties. All these factors potentially influence net nitrogen (N) mineralization. The objective of this analysis is to investigate the relationship between soil texture and net N mineralization using different approaches, including a 10-week laboratory incubation of undisturbed soil cores from 47 sites in California, modeling, and a meta-regression analysis of 461 datasets from 20 studies. In the laboratory incubation as well as in the meta-analysis, total soil N increased significantly with increasing clay content. Net N mineralization expressed in mg kg−1 soil did not change significantly with increasing clay content, but significantly decreased when expressed as a proportion of total soil N. These results are most likely explained by physical and chemical protection of organic molecules by clay minerals. Protection in turn led to the observed increase in total soil N over time. Based on the incubation and measured bulk densities, net N mineralization in the top 15 cm of the soil profile was 30% higher in a sandy loam compared to a clay soil. Model simulations indicated that texture-related differences in soil temperature and moisture have only a small effect on net N mineralization in irrigated agricultural fields under Mediterranean conditions. [ABSTRACT FROM AUTHOR]

The two most important abiotic plant stressors that impact plant development and crop yields are water stress and salinity stress. These issues are particularly important in arid and semi‐arid regions. According to a 2019 research paper, “thirty crop species provide 90% of our food, most of which display severe yield losses under moderate salinity.” Moderate salinity is defined as extracted pore‐water salinity in the range of 4–8 dS m−1. Currently, commercially available soil moisture and bulk soil electrical conductivity sensors can estimate in situ soil pore‐water electrical conductivity with suitably calibrated soil moisture and electrical conductivity models for a wide range of soil types and growing media. With knowledge of the pore‐water electrical conductivity it is possible to estimate osmotic tension. Furthermore, there are commercially available dielectric tensiometers that provide soil water tension measurements from the water content of a porous matrix component that is in equilibrium with the water capillary forces in the surrounding soil or growing media. Combining soil moisture and soil water tension measurements enables water retention curves and the hydraulic properties of a soil to be determined. However, the overall ability of a plant to extract water from a soil or substrate is typically dominated by water tension and osmotic tension. Currently, while the technology blocks exist in different commercial offerings, the combination of a water tension and osmotic tension in an integrated sensor does not exist. A key benefit of the porous matrix in a dielectric tensiometer is that electrical measurements include a component of extracted water from the soil or growing media. With the appropriate dielectric characterization of the porous matrix, there should be no need for soil‐specific calibrations. The aim of the paper is to outline the measurement processing that could be implemented into an integrated water tension and osmotic tension sensor. [ABSTRACT FROM AUTHOR]

Proper soil sampling is critical for accurate fertilizer recommendations. Samples collected in extremely wet or dry conditions may compromise the integrity of the sample and influence analytical results. We evaluated the effects of six soil moistures, two sampling depths (0–10 and 0–15 cm), and two soil probes on soil core uniformity and soil test results. Moisture treatments encompassed a range from dry (11.2%–18.5% moisture) to saturated conditions in Captina, Dewitt, Calhoun, and Calloway silt loam soils. Core depth and dry core weight were measured in all soils, and pH and Mehlich‐3 extractable P, K, S, and Zn were assessed for Calhoun and Calloway soils. Soil moisture, probe, or their interaction influenced core depth and weight, while chemical properties were significantly affected only by soil moisture. Sampling very dry or saturated soils compromised the collection of uniform cores mainly for the 0‐ to 15‐cm depth. Soil pH tended to increase with increasing moisture, but the mean values fluctuated only ±0.3 units. Across soils and depths, extractable S consistently decreased by 16%–48% as soil moisture at sampling time increased. Phosphorus was affected by soil moisture for 0–15 cm samples in both soils but showed no clear pattern. Soil moisture at the time of sampling affected soil test K for both soils and sample depths with individual cores varying up to 47 mg kg−1 (i.e., 59–106 mg kg−1). Greater soil test P and K variability occurred for very dry and wet conditions, which often prohibit collecting samples to the proper depth and could impact fertilizer rate recommendations. Core Ideas: Soil moisture and probe type influence sampling reproducibility and soil test results.Very dry or wet soil conditions affect the accuracy and precision of soil sample depth.Soil sample depth and moisture condition at collection time can influence soil test results.Soil test results and fertilizer recommendations are influenced by soil sampling accuracy. [ABSTRACT FROM AUTHOR]

High levels of soil water repellency (SWR) can hinder water infiltration and increase surface soil erosion risk and runoff. Although SWR occurs naturally in many areas, it is often patchy and does not impede water movement. However, fire can increase the connectedness and extent of SWR leading to topsoil loss, nutrient limitations, increased root water stress, and ultimately slower ecosystem recovery. This study examines the naturally hydrophobic soils of Oregon's Deschutes National Forest following the 2020 Green Ridge Fire to (1) examine the relationship between SWR and management‐relevant burn severity classes, (2) quantify an appropriate spatial scale over which to evaluate SWR properties, and (3) determine which environmental factors drive patterns in SWR. We found that the top 1–3 cm of soil became less hydrophobic after fire, while the profile to about 10 cm became more uniformly hydrophobic. This could indicate that surface soil is more prone to post‐fire erosion in burned areas. However, predicting SWR is still challenging. While burn severity and environmental metrics did statistically account for some variation in SWR following fire, the range of SWR spatial autocorrelation was at best a few meters. Due to this fine‐scale variation, future work should focus on determining an efficient post‐fire soil evaluation protocol with adequate density and scale of sampling while also incorporating the influence of environmental factors to inform management decisions. Core Ideas: Naturally occurring hydrophobicity complicates predicting post‐fire hydrology.Fire increased the homogeneity of water repellency in only some burn severities.Variability makes predicting hydrophobicity or scaling up incredibly difficult.The top 1–3 cm of soil across all burn severities may have highest erosion risk. [ABSTRACT FROM AUTHOR]

Excessive tillage reduces soil water storage and increases surface runoff. Cover crops can modify the effect of tillage on soil water dynamics, but limited information is available for the Mississippi River Alluvial Basin. This study was conducted to determine whether soil–water dynamics could be manipulated through conservation production systems affecting surface residue management. Effects of tillage (conventional tillage [CT] vs. no‐tillage [NT]) and cover cropping (no cover crop and Austrian pea [Pisum sativum L.] cover crop [CC]) on soil water balance during the CC season in sorghum (Sorghum bicolor L.) and cotton (Gossypium hirsutum L.) crops were modeled using the root zone water quality model for a site near Stoneville, MS, on "Commerce" silty‐loam soil. Capacitance sensors measured soil volumetric water content to 120 cm during CC growth in 2019 and 2020. Field calibration of sensors reduced root mean square error from 0.05 to 0.03 m3 m−3. Pooled across years, NT increased volumetric water content in the 0–40 and 40–120 soil layers by 8.5% and 6.8%, respectively, compared to CT. Regardless of the CC treatment and cropping system, NT reduced surface runoff by 24.5% over its conventional counterpart, while soil water storage increased from 2.35 to 5.23 cm within the 1.2‐m profile, resulting in a 17% increase in consumptive use of water (evapotranspiration). CC treatments did not impact soil water storage and consumptive water use. The results demonstrate that NT systems can affect water dynamics by increasing infiltration and soil water storage in the humid subtropical region of the United States. Core Ideas: No‐tillage reduced surface runoff and increased soil water storage in alluvial soil.Cover crop reduced runoff from no‐till plots but not from conventional tillage.Cover crop produced substantial biomass with minimal risk of depleting soil water.No‐tillage with cover cropping would improve soil water storage in the Mississippi River Basin. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effects of water salinity and sodicity on the least limiting water range (LLWR) of two clay loam and sandy loam soils. The undisturbed soil samples were subjected to different water qualities, including three levels of sodium adsorption ratio (SAR, 1, 5, and 12) and electrical conductivity (EC, 1, 6, and 10 dS m−1). Our findings indicate that increasing EC at each SAR led to greater soil water retention. This was attributed to salinity affecting pore size distribution toward smaller pores by altering the diffuse double layer and causing soil particle flocculation. With increasing SAR levels at each EC level, soil water content at the wilting point also rose due to structural changes, clay swelling, and dispersion, resulting in more micropores and increased adsorptive surfaces in the soil. Additionally, soil volumetric water content at a 10% air‐filled porosity decreased, while values at a critical penetration resistance of 2 MPa increased with higher bulk density across all treatments. The LLWR showed a negative correlation with bulk density in clay loam soil across all SAR and EC treatments. The LLWR increased with higher water EC but decreased with increasing water SAR. The highest LLWR was observed at SAR = 1 and EC = 10 dS m−1, while the lowest occurred at SAR = 12 and EC = 1 dS m−1. The results revealed that elevated values of SAR in irrigation water reduced soil water accessibility for plants. However, as irrigation water salinity increased, the detrimental effects of SAR diminished. Core Ideas: Increasing salinity at each sodium adsorption ratio (SAR) led to greater soil water retention.The least limiting water range (LLWR) increased with higher salinity but decreased with increasing sodicity.The LLWR of clay loam soil responded more to water quality changes than sandy loam soil.The LLWR of clay loam soil was markedly restricted as bulk density increased. [ABSTRACT FROM AUTHOR]

Soil texture and organic matter are considered overarching factors controlling a diversity of soil processes and properties. However, a more complete understanding of how these factors quantitatively affect other soil properties has been lacking due to either limited scope of land use and management conditions, confounding climate and environmental conditions with management, or narrow range of soil and management conditions. This study evaluated the strength of associations of sand and total soil N concentrations with soil physical, chemical, and biological properties and processes from 310 surface‐soil (0–10‐cm depth) samples (87% Ultisols, 4% Inceptisols, and ≤3% each of Alfisols, Spodosols, Entisols, and Histosols) collected under conventional‐till and no‐till cropland, grassland, and woodland in four physiographic regions of North Carolina. Sand concentration was most strongly associated with dry‐stable mean‐weight diameter (MWD), MWD product, and sieved soil density (|r| > 0.63, p < 0.001). Total soil N concentration was most strongly associated with particulate organic C and N and soil water content at water‐holding capacity (|r| > 0.74, p < 0.001). Soils under unfertilized woodlands deviated the most from general associations, suggesting that organic matter quality could be unique, and requires further investigation. Overall, sand concentration associated more closely with soil physical properties and total soil N concentration associated closely with both soil physical and biogeochemical properties. Soil chemical properties were only weakly associated with either property. This study suggests that soil texture and organic matter would be complementary, additional properties in holistic soil health assessments that already included routine soil chemical analyses. Core Ideas: Soil texture strongly associated with dry‐stable aggregation but weakly associated with water‐stable aggregation.Total soil N strongly associated with particulate organic C and N and soil water content at water‐holding capacity.Sand and total soil N concentrations were strong combined indicators of bulk density, sieved soil density, and cation‐exchange capacity.Sand and total soil N concentrations were unique soil health indicators in addition to routine soil chemical propertiesSieved soil density could be a relatively rapid and inexpensive indicator that combines the influences of soil texture and organic matter. [ABSTRACT FROM AUTHOR]

Using compost as an agricultural amendment offers a means to reduce organic waste, as mandated in the US state of California (SB 1383). Compost can improve soil physical characteristics and soil carbon content by increasing soil organic matter. We examined the effect of compost application (7‐year duration) on soil nitrous oxide (N2O) emissions, inorganic nitrogen (N) pools, soil temperature and water content, bulk density, and total carbon (C) and N content. The orchard was composed of Nonpareil cultivars interplanted with Aldrich and Carmel cultivars, all grafted on Nemaguard peach rootstock [Prunus persica (L.) Bratsch]. Its soil was Oakdale sandy loam (coarse‐loamy, mixed, active, thermic Mollic Haploxeralf). Delivering nutrients through the irrigation system, the orchard was fertigated 14 times with urea ammonium nitrate or calcium ammonium nitrate, using high frequency and low concentration (HFLC) fertigation applications (total 195 kg N ha−1). Soil without compost (No Compost) tended to have higher N2O fluxes (up to 2.75‐fold) than soil with compost (Compost). Cumulative measured N2O emissions (i.e., sum of nine sampling events) from Compost were half that from No Compost. Soil pH, electrical conductivity, total C, and N tended to be greater in Compost, and bulk density tended to be lower in Compost than No Compost. No relationships between N2O emissions and soil temperature, volumetric water content, water‐filled pore space, and inorganic N pools occurred in either treatment. Our findings indicate that long‐term applications of compost in perennial crops, in combination with an HFLC nutrient management program, could reduce losses of N as N2O to the atmosphere. Core Ideas: Compost and high frequency low concentration fertilization reduced cumulative N2O emissions by nearly half.Soils using compost had peak N2O fluxes nearly one‐fifth lower than peak fluxes in soils not receiving compost.Total carbon (C) and nitrogen (N), bulk density, pH, and electrical conductivity (EC) tended to differ between soils receiving compost and those that did not. [ABSTRACT FROM AUTHOR]

In the Lower Mississippi River Basin, farmlands are flooded in late fall and winter by impeding drainage to provide a habitat for migratory birds stopover. A laboratory incubation study was conducted to study the influence of temporary wetting of these soils on carbon (C) and nitrogen (N) mineralization from residue decomposition. Surface soils (0–15 cm) were collected from fields with clay and silty clay loam soils. Both soils were incubated with five crop residues—corn (Zea mays), soybean (Glycine max), cotton (Gossypium hirsutum), sorghum (Sorghum bicolor), and sweet potato (Ipomea batatus)—at 50% and 100% water holding capacity (WHC). Soil carbon dioxide (CO2) efflux was measured during 74 days of incubation. Soil moisture had the largest effect on soil CO2 efflux and most of the enzyme activities followed by residue and soil type. Cumulative soil CO2 efflux was reduced by 46% at 100% WHC compared to 50% WHC. Clay soil had higher cumulative CO2 efflux, aryl sulfatase, aryl phosphatase, and β‐N‐acetyl glucose aminidase activities than silty clay loam soil. Residue type had the largest effect on post‐incubation soil inorganic‐N, remaining biomass, and residue C and residue N. Sweet potato residue had the lowest remaining biomass, significantly lower than cotton, corn, and sorghum, but statistically similar to soybean. After incubation, residue N concentration had a positive association with cumulative CO2 efflux and a negative association with remaining residue biomass percentage. Winter flooding might limit the loss of soil C as CO2 depending on the crops grown and soil type. Core Ideas: Wetting soils to saturation influence residue decomposition and nutrient dynamics due to anoxic conditions.At 100% water holding capacity (WHC), inorganic N concentration increased for clay soil but not for silty clay loam soil.CO2 efflux reduced by 46% at 100% WHC over 50% WHC.CO2 efflux had a positive association with residue N concentration and a negative association with residue C/N ratio. [ABSTRACT FROM AUTHOR]

Decades of intense tillage have created the problem of surface sealing in loam soils across the Mid‐South United States and beyond. These soils exhibit low organic matter, poor aggregate stability, and ultimately low infiltration rates that decrease rainfed crop productivity and increase irrigation water demand. This research quantified the effects of soil management practices on rainfed maize (Zea mays L.) yield, furrow water infiltration, and soil moisture in Commerce very fine sandy loam and silt loam near Stoneville, MS. The six treatments included conventional tillage (CT), cereal rye (CR; Secale cereale L.), furrow diking (FD), no‐till (NT), polyacrylamide (PAM), and subsoiling (SS). No other treatment achieved a significantly higher maize grain yield than the CT control treatment in both years consistently. Single‐ring infiltrometer results indicated no significant differences among CT, CR, PAM, and SS in 2022 and between CT and NT in 2021. Neutron attenuation found that total soil water within the top 1 m was not significantly different among CT, FD, and SS on any of the eight measurement dates throughout the 2022 maize reproductive period. However, soil moisture was numerically lower for FD in the late reproductive stages. These findings suggest that environmental factors and other agronomic operations may counteract conservation practices, limiting their effectiveness at reducing irrigation requirements to mitigate groundwater depletion in the Mississippi River Valley Alluvial Aquifer. Core Ideas: None of the five conservation practices consistently surpassed conventional tillage in rainfed maize yield.The cereal rye, no‐till, polyacrylamide, and subsoiling treatments did not accelerate furrow water infiltration.The furrow diking and subsoiling treatments did not increase total soil water within the top 1 m.Better timing and methods of conservation intervention are needed to enhance Mid‐Southern US water sustainability. [ABSTRACT FROM AUTHOR]

The aim of this work has been to assess the Hilhorst model, used for estimating in‐soil pore water conductivity, against soil properties of percolation threshold and soil particle conductivity. The Hilhorst model has the benefit of requiring a single soil‐specific parameter which makes this model easy to apply from soil permittivity and bulk conductivity measurements. However, the Hilhorst model requires that the bulk conductivity measurement is dominated by pore water conductivity, which is not always the case in many "real‐world" settings. This work examines a mathematical framework derived from combining the Hilhorst and Ewing and Hunt models which allows the Hilhorst soil parameter to be derived for a range of soil particle conductivities (0 to 10 mS m−1) and percolation thresholds (0 to 0.1 m3 m−3). The analysis in this work indicates that the Hilhorst parameter is highly sensitive to both soil properties with respect to the default value of 4.1 that is often employed. This assessment indicates that: (i) soil particle conductivity can result in the Hilhorst model overestimating pore water conductivity, which becomes more significant for lower bulk conductivities, and, (ii) percolation threshold can result in the Hilhorst model underestimating pore water conductivity, which becomes more significant for lower soil moisture contents. The results from this analysis suggest that the application of the Hilhorst model should be considered against the context of soil particle conductivity and percolation threshold for a given soil under test. Core Ideas: The Hilhorst model parameter is sensitive to soil conductivity and percolation threshold of soil.Soil particle conductivity can result in substantial pore water conductivity overestimates from the Hilhorst model.A non‐zero percolation threshold can result in pore water conductivity underestimates from the Hilhorst model.Soil‐specific model calibrations should be performed over the anticipated moisture and conductivity ranges. [ABSTRACT FROM AUTHOR]

Drought is increasingly common due to frequent occurrences of extreme weather events, which further increases soil water repellency (SWR). It could reinforce the effect of SWR on soil functions under conservation tillage systems. However, the relationship between SWR and soil hydrological function is still unclear. We studied the impacts of SWR and soil structure on soil hydrological function. Three treatments were conducted in a long‐term tillage experiment: conventional tillage (CT), reduced tillage (RT), and no‐tillage (NT). Tillage, soil depth, and growth period had significant influences on SWR, soil structure (i.e., penetration resistance [PR], total porosity [TP], and mean weight diameter [MWD]), and soil hydrological functions (i.e., water storage, least limiting water range [LLWR], and plant available water). Compared to CT, NT and RT increased the water repellency index (RI) in 0–20 cm by 13.8%–40.1% and 6.5%–18.2% during the growth period. RI played a prominent role in increasing soil water storage compared to soil TP, PR, MWD, and SOC. PR was the most critical influence on LLWR compared to other variables. A structural equation model revealed that SWR directly affected soil hydrological function, whereas the effect of SWR (0.24) was smaller than that of soil structure (0.67). In addition, soil structure had a direct influence on SWR, indicating that the effect of SWR could be regulated by soil structure. Overall, this study showed a link between SWR and soil hydrological function and provides deeper fundamental insights into the role of SWR on the sustainability of conservation tillage. Core Ideas: No‐tillage (NT) increased soil water repellency (SWR) by 13.8%–40.1% compared to conventional tillage.Soil structure had a stronger influence on soil hydrological function than SWR.The increased soil moisture by NT is more obvious under low rainfall (11 mm) than under high rainfall (30 mm).SWR had a positive relationship with soil organic carbon and mean weight diameter (p < 0.05). [ABSTRACT FROM AUTHOR]

Traditional laboratory methods for measuring soil water retention curves (SWRCs) typically consist of suction tables, pressure cells, and pressure plate apparatus (i.e., traditional methods). However, technological advancement has resulted in newer methods based on precision mini‐tensiometers and dew point water potential meters (i.e., modern methods). This study investigated the discrepancy between SWRCs measured using traditional and modern methods in three soil textures. Our results showed that SWRCs from both traditional and modern methods were similar at the wet end (i.e., matric potentials 0 to −10 kPa) and at the dry end (−500 to −1,500 kPa) of the SWRC, with an average mean absolute difference (MAD) across all three soils of 0.033 and 0.017 cm3 cm−3, respectively. The largest discrepancy between methods was consistently observed at moderate tensions of −33 and −70 kPa for the three soils, with an average MAD of 0.059 cm3 cm−3 for −33 kPa and a MAD of 0.083 cm3 cm−3 for −70 kPa. Plant available water capacity differed by up to 20% between the traditional and modern methods in a clay loam soil. While previous studies have mostly focused on the dry end of the SWRC, our study suggests that additional research comparing traditional and modern methods is required at moderate (−70 and −500 kPa) tension levels. Core Ideas: Traditional methods included tension table, pressure cells, and pressure plates.Modern methods included precision mini‐tensiometers and dew point water potential meter.Mean absolute difference between traditional and modern methods at the dry end of the curve was 0.017 cm3 cm−3.The largest discrepancy between traditional and modern methods was observed at matric potentials of −33 and −70 kPa.Plant available water capacity differed by 20% between methods in a clay loam soil. [ABSTRACT FROM AUTHOR]

The warming climate is rapidly changing the circumpolar region, presenting new opportunities and challenges for agricultural production in South Greenland. The warming climate is projected to increase the frequency of drought periods, but little is known about the soil–water retention (SWR) and the plant available water (PAW) of the agricultural soils in the region. This study aimed to measure the SWR and PAW of Greenlandic agricultural soils and evaluate the effect of organic carbon (OC) and clay (CL) content using pedotransfer functions based on OC and CL. The study included 464 South Greenlandic agricultural soil samples from 20 fields with a wide distribution in clay (0.016–0.184 kg kg−1) and OC contents (0.006–0.254 kg kg−1). Pedotransfer functions were successfully developed for estimating the gravimetric water content (w) at five soil–water potentials (−1500, −100, −30, −10, and −5 kPa) and PAW. The OC content was the primary variable governing the gravimetric water content at each soil–water potential, evidenced by R2 values consistently above 0.80. The effect of OC on the gravimetric water content at −1500 kPa was close to the range reported in the literature, but OC effects were markedly higher between −100 and −5 kPa. Overall, this study highlights a substantial effect of OC on the PAW as a 1% increase in OC increased PAW by more than 4%, which is almost twice the value of a recent meta‐study. Our study highlights the potentially dominating effects of organic matter on soil–water balance and availability in high‐latitude agriculture. Core Ideas: This is the first comprehensive study measuring the soil–water retention (SWR) of Greenlandic agricultural soils.The SWR and plant available water (PAW) were determined for 464 soils originating from 20 agricultural fields.Pedotransfer functions were developed to evaluate the effect of organic carbon (OC) and clay content.OC was the primary variable governing the SWR of these subarctic soils, especially at matric potentials ≥−100 kPa.The impact of OC content on the SWR and PAW was high compared to the literature. [ABSTRACT FROM AUTHOR]

Soil temperature extremes are not uncommon when woody fuels are ignited in prescribed burns or wildfires. Whether this leads to substantial loss of soil organic matter or microbial life is unclear. We created a soil heat gradient by burning four levels of masticated woody fuels (0, 34, 101, and 169 Mg ha−1) to determine if heat thresholds produce abrupt changes in soil C, N, microbial biomass, or fungal hyphae. Twenty‐four burns were conducted with masticated fuels overlaying a clay loam soil equilibrated at either 4 or 25% volumetric soil water content. Maximum temperatures ranged from 40 to 450 °C depending on fuel load and soil moisture content, with heat duration (>60 °C) as great as 22 h. Moist soil quenched temperatures two‐ to threefold compared with dry soil at comparable fuel loads. A slight, gradual decline in total C and N was found with increasing temperature and heat duration, reaching a maximum loss of 14–18% of the total at the highest heat load. Available NH4 increased linearly starting at 150–175 °C and reached a maximum 15‐fold increase relative to unburned soil by 450 °C. Nitrification (30 d post‐fire) was low regardless of treatment and was essentially eliminated at the highest temperatures. Microbial biomass declined curvilinearly with increased heating, approaching 65% loss compared with unburned soil, and was most rapid in moist soil once temperatures exceeded 60–70 °C. Ultimately, we found no evidence of abrupt heat thresholds for these common soil properties. Instead, property changes followed a slightly declining trajectory (soil C, N, NO3, fungal hyphae) or a steady incremental increase (NH4) or decrease (microbial biomass). Core Ideas: Multiple burns and fuel loadings led to a wide range of critical soil temperatures.Soil C and N were generally unaffected at temperatures ranging from 40 to 450 °C.A large incremental increase in plant‐available NH4–N was found as temperatures surpassed 200 °C.Microorganisms declined steadily with increasing temperature.Changes in soil properties were mostly gradual and limited to the thin surface layer. [ABSTRACT FROM AUTHOR]

Rain‐fed rice (Oryza sativa L.)–wheat (Triticum aestivum L.) (RFRW) rotation can be a resource‐saving solution for sustainable cropping systems. However, conventional puddled and flood transplanted rice, repeat tractor compaction, and years of shallow rotary tillage and paddy–dryland rotation had a negative impact on soil physical in the RFRW rotation (e.g., soil consolidation and shrinkage, shallow tillage layer). A 4‐yr field experiment was established to determine if different post‐paddy tillage systems would improve soil physical properties and plant factors. We compared no‐tillage (NT), conventional rotary tillage (RT), and deep tillage (DT) to improve the deteriorated soil structure, soil water, wheat root system, and grain yield. The results indicated that DT increased the average soil water content by 7.25% and 9.98%, increased field capacity by 9.58 and 5.23%, and decreased the soil bulk density by 6.2 and 2.2% at 0‐to‐20‐cm soil depth in 4 yr as compared to NT and RT, respectively. The NT increased the average relative soil moisture and had higher soil bulk density at 0‐to‐20‐cm depth. The DT deepened the root growth and increased the total root point numbers by 21.0 and 22.8% at 0‐to‐40‐cm soil depth in 4 yr, respectively, compared with NT and RT. In 4 yr, the DT significantly achieved higher average grain yield by 5.3 and 13.5%, respectively, compared with NT and RT. Overall, DT after rice was shown to be a promising management approach for improving wheat yields and might enable sustainable intensification of RFRW rotation. Core Ideas: Traditional puddling destroys the soil structure resulting in hardpan and a shallow tillage layer.Post‐paddy tillage is a tool to improve soil physical properties and plant factors for wheat.Deep tillage improves soil physical properties, wheat roots, and grain yield.Deep tillage is a promising management strategy for sustainable rain‐fed rice–wheat rotation. [ABSTRACT FROM AUTHOR]

Understanding the factors controlling nutrient dynamics can help guide forest management plans to promote their long‐term productivity. We used experimental treatments with three levels of biomass removals and two levels of compaction to monitor the impacts to soil biophysical characteristics in an intensively managed forest. Soil temperature, moisture, and respiration observations began 6 mo after treatment installation completion and continued for 2 yr. Compaction had few consistent significant effects on measured variables, and there were negligible differences in volumetric soil water content between whole tree (WT) and bole only (BO) harvesting. Compared with BO, the 10‐cm average and maximum growing season temperatures in WT significantly increased by 1.2 and 2.5 °C, respectively. The effects of WT removals resulted in whole profile (10–100 cm) increases in the average and maximum growing season soil temperatures. The WT removals resulted in an increase of 1.4 times more soil growing degree days (SGDD) at 10 cm and 1.6 times more at 100 cm compared with BO. Despite favorable temperature and moisture conditions, differences in soil respiration could not be explained by biomass or compaction treatments. The uncut reference forest was consistently cooler and drier, but respired more CO2 throughout both years of observation compared with treated areas. The large physical disturbance of forest harvesting on the site likely masked any incremental treatment differences by homogenizing the microbial response in the ensuing 2‐yr study period. Future research should continue to investigate whether these soil biophysical changes influence site productivity or more sensitive indices of soil C dynamics. Core Ideas: Bulk density increased 16–23% but compaction had no influence on soil moisture or soil respiration.As more biomass was removed, average growing season temperatures increased significantly from 10 to 100 cm in depth.At the 100‐cm depth whole tree plus forest floor removals had three times more soil growing degree days.The uncut reference forest was consistently cooler and drier, but respired more CO2 throughout the study period.The intense and temporally recent harvest disturbance obscured differences in soil respiration between treatments. [ABSTRACT FROM AUTHOR]

Winter cover crop (CC) has the potential for improving soil physical condition; however, both improvement and depletion of soil water storage because of CC were reported depending on the soil depth and the rainfall received in a growing season. The present study used sensors to measure the soil moisture content (cm3 cm−3) and soil water potential (–cm) for a no‐till corn (Zea mays L.)–soybean [Glycine max (L.) Merr.] system managed with and without winter CC. The sensors were installed at three soil depths (15, 30, and 45 cm) and the measurements were continued for three cash crop growing seasons (corn, 2017; soybean, 2018; and corn, 2019). The observed soil water potential (–cm) was lower (high tension) for the no cover crop (NCC) system as compared to the CC for the 45‐cm depth in 2017 and 2019, and 15‐ and 30‐cm depth in 2018. The Hydrus‐1D satisfactorily simulated the soil water potential and moisture content values for the CC and NCC systems with a coefficient of determination (R2) ranging from.58 to.93 and.57 to.92, respectively. The CC stored 12, 17, and 7% less soil water in the Ap soil layer (0–18 cm) than NCC for the day of cash crop planting for the years 2017, 2018, and 2019, respectively. However, the water input from rainfall replenished the soil moisture after the establishment of the cash crop and resulted in increased soil water storage in the CC as compared to the NCC in the Ap soil layer for the years 2018 and 2019. The present study, therefore, concluded that the use of winter CC improved soil water status for the following cash crop as compared to a NCC system. Core Ideas: Winter cover crop improved the soil water storage for the following cash crop as compared to the no cover crop.The use of winter cover crop improved the soil water dynamics for three consecutive cash crop growing season.The impact of cover crop on soil water was observed to a deeper soil.Hydrus 1D could simulate the impacts of cover crops on soil water dynamics. [ABSTRACT FROM AUTHOR]

Agricultural system models can help quantify soil water dynamics, crop evapotranspiration, and crop growth with a high temporal resolution to enhance soil and crop management. Simplifying the process of model calibration and validation is an important aspect for crop model use. The objective of this study was to explore the capability of using the Root Zone Water Quality Model (RZWQM2) with soil hydraulic property input parameters (SHPIPs) identified once under a given crop for other crops without recalibrating. A field experiment with soybean [Glycine max (L.) Merr.], corn (Zea mays L.), wheat (Triticum aestivum L.), and fallow soil was conducted from 2015 to 2017. The soil hydraulic property parameter calibration process was evaluated. Four model scenarios of calibrating measured SHPIPs for soybean, corn, wheat, and fallow soil were created. The RZWQM2 simulation results showed high sensitivity to the model inputs of the SHPIPs. Model input parameters of bulk density, field capacity, permanent wilting point, and saturated hydraulic conductivity showed a large effect on model simulations. Model inputs of soil water content θ at field capacity and permanent wilting point showed high impact on water holding capacity and crop development, whereas the model input parameters of saturated hydraulic conductivity and bulk density yielded a high effect on soil water dynamics. All model scenarios presented satisfactory results with regard to soil water dynamics, evapotranspiration, crop growth, and mineral nitrogen, indicating that, for a particular field, RZWQM2 calibrated for one season performs well for other seasons without recalibration. Core Ideas: Representative soil hydraulic measurements are necessary for model simulations.A deviation of model simulations could be due to uncertainty of hydraulic inputs.It is not necessary to re‐calibrate soil hydraulic input parameters for each crop. [ABSTRACT FROM AUTHOR]

This study developed a comprehensive database of soil physical properties to expand the potential applications of soil moisture observations across the Kansas Mesonet environmental monitoring network. The database comprises 14 site‐ and depth‐specific soil hydraulic properties for 40 stations monitoring soil water content. The measured soil hydraulic properties include sand, clay, and silt contents; bulk density; particle density; total porosity; effective saturation; saturated hydraulic conductivity; and water retention at six matric potentials. The soil database spans eight soil textural classes, with silty clay loam, silt loam, and silty clay soils dominating the fine‐textured soils, and sandy loam and sandy clay loam soils comprising the only coarse‐textured soils. All the measured soil hydraulic properties showed low coefficient of variation (CV ≤10%) within soil textural classes, except for the saturated hydraulic conductivity, which varied from a median of 0.520 ± 308 cm d–1 in the clay soils to 47.1 ± 119 cm d–1 in the sandy loam soils. The uncertainty of the Kansas Mesonet soil water content observations was reduced by at least 29% using laboratory sensor calibration equations instead of the factory default sensor equation. Our soil physical property database offers new prospects to use historical and near real‐time in situ soil water content observations across the Kansas Mesonet for diverse agricultural and hydrological applications, including drought monitoring, wildfire preparedness, and estimating potential drainage and groundwater recharge rates. Core Ideas: This study developed a comprehensive soil physical property database for the Kansas Mesonet.The database comprises 14 site‐ and depth‐specific soil hydraulic properties for 40 stations.The soil database is dominated by fine‐textured soils with 92% of the soils having >20% clay content.Laboratory sensor calibration equations reduced the uncertainty of the water content measurements by at least 29%. [ABSTRACT FROM AUTHOR]

Decreasing physical quality of Mollisols in the Argentinean Pampas region is observed due to simplified crop rotations. The main objective of this work was to evaluate the effects of cover cropping management on soil water capture, transport, and storage as compared with different crop rotations with bare fallow in two different and representative Mollisols of the Argentinean Pampas region (one Typic Argiudoll [TA] and one Typic Hapludoll [TH]). Water capture, transport, and storage processes were assessed through soil sorptivity, infiltration tests at different pressures heads, and soil water retention curve determination. In addition, aggregate stability and soil organic carbon (SOC) were determined and the relationship between studied variables and processes was evaluated. It was observed that soybean [Glycine max (L.) Merr.] monocultures jeopardize Mollisols conservation, decreasing water capture and transport and SOC content. The inclusion of cover cropping management increased the soil water transport in the TA and water capture in the TH, as compared with bare fallow rotations. In this sense, our results show that cover cropping could be a suitable management in order to recover degraded soils due to simplified crop rotations in Mollisols from the Argentina Pampas region. Core Ideas: Effects of cover crops on soil hydraulic properties depended on the soil type.Soybean monocultures decreased water capture and transport.Cover crops increased water transport in the Typic Argiudoll.Cover crops increased water capture in the Typic Hapludoll. [ABSTRACT FROM AUTHOR]

The article titled "Biochar and compost amendment impacts on soil water and pore size distribution of a loamy sand soil" has been retracted due to concerns raised by the corresponding author of another article, who claimed to have been omitted as an author and unaware of the submission. An investigation found significant overlap between the two articles, leading to the conclusion that this article is a duplicate publication. Furthermore, the article failed to disclose the university's funding and did not appropriately acknowledge the omitted author. The corresponding author disagreed with the retraction, while a co-author collaborated during the investigation and agreed to the retraction. [Extracted from the article]

Water extractable organic matter (WEOM) is critical for soil fertility because of its role as a readily available C substrate for microbial metabolism. In the semi‐arid Texas High Plains, dryland cropping systems are common because of limited precipitation and irrigation water. Little is known about the long‐term effects of dryland cropping on soil WEOM content and composition, and how these differ from native grassland. The objective of this study was to use soils collected near Amarillo, TX, in 1977 and 2013 to examine the long‐term (72 yr total cropping length) effects of dryland cropping systems [continuous wheat and wheat–fallow rotations] and tillage methods (disk plow, stubble‐mulch tillage, and delayed stubble‐mulch tillage) on WEOM characteristics, compared with native grassland. In cropped plots, water‐extractable organic carbon (WEOC) concentrations, a measure of WEOM content, were depleted regardless of tillage or crop, with reductions up to 13% in 1977 and 60% in 2013, compared with native grassland in 2013. Other parameters of WEOM changed over time, where cropped soils from 2013 had proportionally more WEOM in aromatic, phenolic, and lignin‐like forms, attributed to recently incorporated crop residues. In contrast, WEOM in cropped soils from 1977 and native grassland (2013) contained more functional groups (e.g., aliphatic, aromatic, polysaccharide, phenol, etc.) and humic‐like substances than cropped soils in 2013. This suggests that long‐term dryland cropping led to depletion of stable, humic‐like WEOM. Enhancement of WEOM stocks and long‐term sustainability in the Texas High Plains may require more vigorous conservation systems than currently used. Core Ideas: Long‐term dryland cropping systems depleted soil dissolved organic C concentrations by up to 60% over time.Water‐extractable organic matter in cropped soils was in simple aromatic forms, while grassland dissolved organic C was more humic‐like.Long‐term dryland cropping led to depletion of stable, humic‐like water‐extractable organic matter.Vigorous conservation systems should be adopted to improve water‐extractable organic matter stocks.Soil C sequestration may be difficult in regions where limited water constrain C inputs. [ABSTRACT FROM AUTHOR]

The significant contribution of greenhouse gas (GHG) emissions to global climate change and stratospheric ozone depletion has been calling the attention to assess the effect of agricultural management on them. Although machine learning (ML) methods have been widely used for the quantification of various inherent and dynamic soil properties, the accuracy of these techniques in the prediction of agricultural soil GHG emissions remains unclear. Therefore, this study aims at evaluating the performance of six different ML methods including simple linear regression, Cubist, support vector machines (SVM) with three different kernel functions, and random forest (RF) for the prediction of CO2 and N2O fluxes from plots managed with and without cover cropping. The input parameters include typical meteorological data as well as soil temperature and soil water content. Results show that the daily flux of CO2 is positively correlated with soil temperature and solar radiation and negatively with soil water content, whereas daily N2O flux is positively correlated with soil water content. For plots without cover cropping, Cubist and SVM with polynomial kernel function outperformed in the prediction of the testing dataset with RMSE of 14.18 kg ha–1 d–1 and 11.52 g ha–1 d–1 for daily CO2 and N2O emissions, respectively. Where cover cropping was considered, SVM with radial basis function and Cubist were the best models in the prediction of daily CO2 and N2O fluxes with respective RMSE values of 15.71 kg ha–1 d–1 and 14.12 g ha–1 d–1. Considering the ranking of the models for all scenarios and both GHGs, SVM with nonlinear kernel functions and Cubist method surpassed other ML techniques. [ABSTRACT FROM AUTHOR]

Grazed pasture constitutes a major source of agriculturally derived nitrous oxide (N2O), which is a potent greenhouse gas. Soil texture and structure, soil moisture, and soil-gas diffusivity are considered to be major soil physical drivers controlling pastoral N2O emissions. Research gaps exist regarding their combined roles on N2O emissions dynamics. This study used 2-mm-sieved and repacked soil samples, retrieved at three depths (0, 10, and 15 cm) from three grazed pasture sites in New Zealand, to investigate the combined effects of soil-water characteristic (SWC) and soil-gas diffusivity on N2O emissions. The existing and modified parametric functions were used to numerically characterize and parameterize measured particle size distribution (PSD), SWC, and soil-gas diffusivity. We observed distinct PSDs within the three soils with little variation across depths. Distinct fingerprints were observed for SWC and gas diffusivity in the three pasture soils, suggesting clear effects of soil type on diffusioncontrolled gas emissions. The soil moisture retention above approximately −10 kPa decreased with increasing depth and showed clear soil type effects. Soil-gas diffusivity, on the other hand, showed pronounced depth-wise variation below approximately −1000 kPa. Pore tortuosity was found to be nonlinearly correlated to air-filled pore space as well as the PSD. The measured N2O fluxes peaked around a diffusivity window of 0.005 to 0.01 for all soil types, and the corresponding water-filled pore space ranged from 0.80 to 0.95. The results provide guidance for managing pasture soils to reduce high N2O fluxes through reductions in compaction and excess irrigation such that the critical diffusivity window, where peak N2O emissions occur, is avoided. [ABSTRACT FROM AUTHOR]

Statistical models for soil organic carbon (SOC) differ substantially regarding the degree to which climate variables, such as precipitation and air temperature, influence SOC. These discrepancies contribute to uncertainties regarding the potential feedback effects of climate change on SOC. Soil-climate variables, such as soil moisture and soil temperature, can strongly influence SOC gains and losses, but these variables have not been widely utilized in statistical SOC models.We hypothesized that SOC is more strongly related to soil-climate variables than to climate variables and that using soil-climate variables in statistical SOC models would improve SOC estimates. We tested these hypotheses using >10 years of daily climate and soil-climate data from 67 temperate grassland sites across Oklahoma, USA, along with soil physical properties, and corresponding SOC data at 5-, 25-, and 60-cm depths. Soil moisture was the single most influential predictor variable, as indicated by least absolute shrinkage and selection operator (LASSO) regression analysis. The effects of precipitation and air temperature were insignificant, apart from a weak negative effect of precipitation at 25 cm. Models including soil-climate variables provided more accurate SOC estimates than models excluding soil-climate variables and were statistically superior based on the Akaike information criterion. Future soil moisture conditions, not precipitation or air temperature, may be the key determinant of climate change–SOC feedback effects at these grassland sites and similar sites worldwide. [ABSTRACT FROM AUTHOR]

Soil aggregates are the basic units of soil structure. Dry and wet sieving are two conventional methods used for isolating aggregates. However, different methods can cause variation in the distribution of enzymes and nutrients. For better understanding the influence of water on soil aggregate stability and building the relationship between soil nutrients and the enzyme activity of aggregates, three soil samples with different organic matter (OM) content were selected: Qiyang, Hunan (HN); Hailun, Heilongjiang (HLJ); and Changshu, Jiangsu (JS). In this study, we measured the enzyme activity of invertase (INV), urease (URE), phosphatase (PHO), and arylsulfatase (ARY) together the OM, total N (TN), available N (AN), available P, and available K of dry and wet sieved aggregates. The results showed that wet sieving caused 34.0, 66.8, and 35.1% decreases in the soil mean weight diameter for HN, HLJ, and JS, respectively. The TN content of wet sieved aggregates decreased to various degrees (19.9–47.7%) compared with dry sieving. The activity of INV, PHO, and ARY decreased sharply after wet sieving especially for microaggregates (reached 70% in <0.1-mm particles of JS). Enzyme activities were mainly located in microaggregates under dry isolation but changed to macroaggregates after wet sieving. The geometric mean (GMean) index of <0.1-mm particles were 1.54, 1.01 and 1.36 times higher than that of >2-mm aggregates under dry sieving. Furthermore, the GMean index showed a significant positive relationship with soil OM, TN, and AN under both dry and wet sieving methods. [ABSTRACT FROM AUTHOR]

Nitrogen (N) fertilizer use efficiency can be improved when nonfertilizer N inputs, including N mineralization from soil organic matter, can be quantified accurately. The objectives of this study were (i) to calculate annual N mineralization rates based on a budget for organic N inputs and outputs for soils under annual crops in California's Central Valley and (ii) to compare the results with temperature- and moisture-adjusted N mineralization rates from a laboratory incubation. The organic-N budget included organic N inputs from aboveground crop residues, roots, and root exudates as well as longterm changes in soil organic N. A 10-wk laboratory incubation was performed at 25°C and optimal moisture content with undisturbed soil cores collected pre-plant in spring 2016 and 2017 from 30 field sites. The sites had no recent history of cover crops, manure, or compost applications. Based on the organic- N budget, annual N mineralization rates in the top 30 cm of the profile ranged from 76 to 123 kg ha-1 yr-1. Taking soil moisture and temperature in furrow-irrigated fields into account, approximately half of this amount was mineralized during a cropping season from mid-April to mid-August. Even when corrected for daily temperature and moisture content, N mineralization rates in the incubation study were considerably higher than the rates estimated with the organic-N budget. The organic-N budget provides an estimate of the annual N mineralization rates in these soils. Adjustments for soil properties and crop management will likely improve estimates for individual sites.

In semiarid dryland farming regions, No-till and intensified crop rotations may improve water use. Our objective was to determine water use efficiency (WUE) and precipitation use efficiency (PUE) for spring wheat (Triticum aestivum L.; SW) grown in crop sequences representing different levels of intensification, under minimum (Min-till) or No-till. Root zone (0-122 cm) water at planting (SWP) was 2.76 cm higher for two- and three-phase sequences under Min-till than continuous spring wheat (CSW), and sequences with fallow averaged 2.65 cm higher than those without. Conversely, SWP was unaffected by sequence under No-till, with less effect of fallow. Root zone water at harvest was unaffected by the number of crop phases or fallow under Min-till. However, values for CSW exceeded the two- or three-phase sequences by 1.57 and 2.53 cm under No-till, and sequences without fallow averaged 1.52 cm more than those with fallow. The highest WUE (8.4 kg grain ha-1 mm-1 water) was observed when SW was grown in three-phase sequences compared with 7.7 kg grain ha-1 mm-1 water, for CSW and SW-fallow. Spring wheat under Min-till had higher WUE in sequences with fallow, but no effects of fallow occurred with No-till. The lowest PUE (near 3 kg grain ha-1 mm-1 precipitation) and no effects of tillage were found in sequences with fallow. However, SW in continuously cropped sequences had PUE between 5.5 and 6.4 kg grain ha-1 mm-1 precipitation and was higher under No-till. Both WUE and PUE are affected by intensification but may also be influenced by patterns of weather.

Saline playas in arid and semiarid regions of the world are significant sources of unconsolidated sediments susceptible to aeolian transport. Lake Urmia in Iran, one of the largest saltwater lakes on Earth, has waned to approximately 18% of its original size due to groundwater pumping and surface water diversions. This has led to ecosystem degradation, accelerated desertification and frequent dust storms, causing public health problems. In this paper we introduce a new framework for delineation of dust source zones and estimation of dust occurrence probability based on remotely sensed land surface properties (soil moisture and vegetation cover), soil texture, wind speed, and measured dust frequencies. Observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the Urmia Lake basin were utilized to determine the Normalized Difference Vegetation Index (NDVI) and to estimate surface soil moisture with a recently introduced optical trapezoid model. The soil textures extracted from the SoilGrids database and wind speeds obtained from local weather stations together with the estimated surface soil moisture were found to be highly correlated with dust emission probability. When the surface soil moisture is low, wind speed is the major determinant for dust occurrence. With increasing surface soil moisture, the dust occurrence probability decreases. Soil moisture effects are more pronounced at high wind speeds. While at low wind speeds the dust occurrence probabilities for the investigated soil textures loam, clay loam and sandy clay loam are similar, at higher wind speeds the sandy clay loam texture exhibits the highest susceptibility to dust generation.

There is a need for improved knowledge of the limits to the available water range for root growth in the subsoil. The objective of this study was to recalculate the upper and lower limits of the least limiting water range (LLWR) concept by using respectively the air-filled porosity (εa) at which 0.005 of the relative gas diffusivity (Ds/Do) is reached and readily available water (RAW). The refined upper limit estimates the variation in εa related to pore connectivity and the refined lower limit expresses the boundary at which plants suffer physiological water stress. This study was based on soil sampled in compaction trials on two sandy loam soils. Soil samples were taken from plots with no compaction (Control), and compaction with 78 kN (M8) and 58 kN (M6) wheel loads with multiple wheel passes. The soil cores were analyzed for εa, Ds/Do, bulk density (rb) and penetration resistance (PR). Heavy farm machinery impact of M8 and M6 led to subsoil compaction up to depth of 0.5 to 0.7 m for the soils under study. The subsoil structure was affected by compaction across depths with the decrease in εa (~33-46%) and Ds/Do (~37-61%) and increase in rb (~4-8%) and PR (~40-50%, at -100 hPa at 30-cm depth). The refined LLWR showed a wider water range compared to the original approach. We anticipate that the refined LLWR well reflects the limiting soil physical conditions for root growth for the studied soils, but validation by combined soil physical and plant growth measurements is needed.

Obtaining accurate soil moisture data from sensors in automated monitoring networks is critical as these data are increasingly used for research in soil hydrology, ecohydrology, and related disciplines. One of the earliest such networks is the Oklahoma Mesonet, which monitors soil matric potential using heat dissipation sensors. Various calibration equations have been proposed for those sensors, and there is a need to compare and validate the performance of those equations, especially for matric potentials < .150 kPa. A laboratory experiment was conducted in silt loam soil using a sand-kaolin box and a pressure plate apparatus with matric potentials ranging from 0 to .1500 kPa. The calibration equations included Starks' equation, Flint et al.'s equation, Schneider et al.'s equation, and a new logistic equation. The upper limit of the sensors was -9 kPa, and the sensors remained responsive at -1500 kPa matric potential. The logistic equation produced the lowest root mean squared error (34 kPa), followed by Flint et al.'s equation (192 kPa), Starks' equation (295 kPa), and Schneider et al.'s equation (463 kPa). After recalibration of the coefficients in the three preexisting equations, their performances improved, with all RMSE values . 251 kPa; however, the logistic equation still provided superior accuracy. The logistic equation effectively removed an ~ 0.02 cm3 cm-3 positive bias in soil water content that resulted from use of the original parameterization of Schneider et al.'s equation. This logistic equation is recommended for use with past and future data from the Oklahoma Mesonet's heat dissipation sensors.

Irrigation scheduling based on a real-time and location-specific (RT-LS) model increases irrigation water savings and yield. The RT-LS irrigation scheduling models have been developed as smartphone applications and have been used for crop-specific irrigation requirements. Although many RT-LS irrigation models have been tested and used in several agronomic and horticultural crops in Florida, none of these irrigation-scheduling models has been tested for their impacts on nutrient distribution in Florida’s sandy soils. A two-season (fall 2015 and spring 2016) study was conducted to determine the effects of an RT-LS–based irrigation scheduling on soil water, NO3-–N, and NH4+–N distributions during a tomato cropping season. In both seasons, an RT-LS model for tomato was evaluated at three irrigation application rates (66, 100, and 150% RT-LS–suggested amounts) and compared with a historic evapotranspiration (ET)-based irrigation schedule (Historic ET) currently recommended in Florida. This study suggests that the RT-LS model improves water savings by 20 and 17% for the fall and spring seasons, respectively, compared with the Historic ET irrigation scheduling method. No specific pattern was observed for soil NH4+–N concentration between scheduling methods, but the RT-LS model maintained a higher soil NO3-–N concentration within the crop root zone and hence could reduce NO3-–N leaching potential. In each season, compared with the Historic ET irrigation method, the RT-LS improved both nitrogen recovery and irrigation water use efficiency in the open-field fresh-market tomato production system. Results obtained in this study clearly demonstrate that irrigation applications using the RT-LS irrigation scheduler improved irrigation scheduling accuracy by maintaining nutrients within the tomato root zone and hence could reduce nutrient leaching potential in sandy soil. [ABSTRACT FROM AUTHOR]

A systematic set of flume tests was developed to explore the relation between soil water content and soil detachment capacity for a coarse-grained soil and a fine-grained soil. The experiments included aging treatments (three volumetric water contents of 4.0, 11.5, and 21.7% for the sandy loam soil and 5.0, 10.5, and 17.4% for the silt loam soil, and seven aging durations of 0, 12, 24, 36, 48, 60, and 72 h) and drying treatments (saturated soil samples oven-dried for 0, 12, 24, 36, 48, 60, and 72 h). Results showed that soil detachment capacity for these two soils presented unique patterns as soil water content increased: the fine-grained soil presented an increasing and then a decreasing trend under aging treatments, whereas the coarse-grained soil showed a continuous increasing trend as soil water content increased. Both patterns could be fitted by quadratic equations. The effect of soil water content on soil detachment capacity was mainly reflected by water-stable aggregate content. Higher soil water content results in weaker bonds for fine-grained soil but in less slaking for coarse-grained soil. Lower soil water content leads to less slaking for fine-grained soil but more particle deposition and cementation for coarse-grained soil. Future work will include additional soil textures and focus on soil erodibility and critical shear stress to expand our understanding of soil detachment influenced by soil water content. [ABSTRACT FROM AUTHOR]

Pecan [(Carya illinoinensis (Wangenh.) K. Koch] is an important specialty crop in New Mexico. This research quantifies soil water and soil nitrate-nitrogen (NO3–N) (mg L−1 of soil) variations with depth, root NO3–N (kg ha−1) uptake, and NO3–N (kg ha−1) balance for the 100-cm soil profile during two growing seasons in a flood-irrigated pecan orchard. Nitrate-nitrogen was determined six times during the growing seasons of 2015 and 2016. The HYDRUS-1D model was used to optimize the water flow parameters using measured volumetric soil water content (θ). Model calibration and validation for NO3–N included the optimization of reaction parameters for nitrification and denitrification of each soil layer. The results showed that the model simulated θ well (0.44 ≤ d [index of agreement] ≤ 0.73) at different depths during both calibration (2009) and validation (2010) periods. Generally, HYDRUS-1D simulated soil profile NO3–N concentrations that were correlated with measurements at all depths during both years. Total root NO3–N uptake showed a significant increase of 72% in 2016 compared with 2015. The NO3–N balance showed that ∼40% of applied NO3–N per year was denitrified, which was the main contributor to the NO3–N loss from the soil profile during both years. Nitrate-nitrogen leaching below the soil profile was 32 and 26% of applied NO3–N in 2015 and 2016, respectively. The fertigation rate was much higher than the plant demand during both years, and it should be decreased to reduce NO3–N losses. [ABSTRACT FROM AUTHOR]

Water table data collected for hydric soil and wetland identification studies require supporting analysis of rainfall normality. Water table measurements made after periods when precipitation is within a normal range are believed to represent long-term trends, whereas data collected following periods of abnormally high precipitation represent rare events, potentially resulting in erroneous hydric soil determinations. The USDA-NRCS currently uses two different methods to assess normal precipitation ranges; both have been used to assess hydric soils. This study compared methodologies that identify normal precipitation periods by using: (i) the range defined by the 30th and 70th percentiles observed within a 30-yr period [i.e., the Climate Analysis for Wetlands Tables (WETS) method] and (ii) long-term monthly mean precipitation ± one SD (i.e., the U.S. Soil Taxonomy method). Comparisons were made for 30 geographically diverse locations and soil moisture regimes. The results demonstrated that the U.S. Soil Taxonomy method yielded normal precipitation ranges approximately twice as large as those from the WETS method. As a result, the U.S. Soil Taxonomy method precluded the occurrence of drier than normal conditions in many instances and displayed increased sensitivity to infrequent high rainfall events. Three case studies evaluated the implications of method selection on hydric soil identification, demonstrating that the U.S. Soil Taxonomy method identified normal conditions more frequently than the WETS method. As a result, the adoption of the WETS method, which accounts for the non-normal distribution of precipitation data, as the sole method to determine normal precipitation periods for hydric soil assessment is recommended. [ABSTRACT FROM AUTHOR]

A common approach for measuring N2O emissions is to collect midmorning or early evening gas samples from experiments utilizing the chamber-based flux methodology. However, due to high spatial and temporal variability, N2O estimates based on midmorning or early evening sampling may not provide accurate estimates of total emissions. This study determined the impact of sampling collection timing on the precision and accuracy of N2O emissions estimates. Nitrous oxide emissions, air and soil temperatures, and soil moisture were measured for 21 d following the application of 224 kg urea-N ha-1 on 20 Sept. 2017, 11 Oct. 2017, and 1 May 2018, at six time intervals (0130-0230, 0530-0630, 0930-1030, 1330-1430, 1730-1830, and 2130-2230 h) over a 24-h period. Based on multiple daily measurements, point samples collected between 0930 and 1030 h (midmorning) were inconsistent in their ability to predict N2O emissions. However, samples collected between 2130 and 2230 h (early evening) were similar to average emissions. The number of randomly collected point samples to be within 20% of the mean 80% of the time over a 21-d period ranged from 13 samples for fertilizer applied on 20 Sept. 2017 to 48 samples for fertilizer applied on 11 Oct. 2017. This research indicates that management and climatic variability affect N2O emissions, and that accurate sampling protocols vary across management and climates. To reduce uncertainty, N2O sampling protocol should be tested under conditions likely to occur and [ABSTRACT FROM AUTHOR]

Accurate knowledge of the soil water retention curve (WRC) is essential for various hydrological and plant-physiological studies. Currently, there is a lack of a uniform protocol for measuring the wilting point water content (WP) with the dewpoint method (DP), despite its ecological relevance and frequent use to calculate available water capacity. We present a new protocol for measuring the WP with the dewpoint method. In contrast to existing methods which add or remove specific amounts of water to moist, air-dry, or oven-dry soil, we propose to apply the dewpoint method after the evaporation method in which tensiometers measure the pressure head of the soil. We suggest to stop the evaporation experiment when the air-entry of one tensiometer cup is reached, to slice the soil core into slabs, and to apply the dewpoint method to subsamples of the slabs. We test the method by numerical simulations and laboratory experiments on five soils covering a broad range of texture. We investigate the accuracy, robustness, and practicability of the new method and compare it to the existing protocols for the dewpoint method and the pressure plate technique. We find that the proposed method allows a precise determination of the WP and the WRC across the full moisture range. It is easy to perform, robust, accurate, and does not require any a priori guess about the amount of water to be added or removed. By fitting a retention curve to the measured data, any water content, including the WP, can be obtained with great confidence. [ABSTRACT FROM AUTHOR]

Density-induced soil structural changes may potentially alter both soil total porosity and soil pore size distribution, and thus change the soil's water retention characteristics, gas diffusion and transport properties, and subsequent greenhouse emissions. In this study, we characterized and parameterized water retention, pore size distribution, gas diffusivity and cumulative emissions of nitrous oxide (N2O) and nitrogen (N2) fluxes in a differently compacted silt-loam sampled from a grazed pasture in Lincoln, New Zealand. The soils used for the simulations were subjected to five different density treatments (1.1, 1.2, 1.3. 1.4, 1.5 Mg m-3), subsequently saturated and successively drained to 11 matric potentials at which water retention, gas diffusivity and flux measurements were performed. Results show strong correlations between best-fit soil-water characteristic parameters and the density levels. A recent predictive gas diffusivity model developed for undisturbed soils was modified to better characterize the measured gas diffusivity data in sieved-repacked pasture soils. Further, two exponential and linear parametric models were developed to adequately parameterize the observed fingerprints of cumulative (35-d) N2O and N2 fluxes, respectively. Results clearly distinguished the density- induced changes in pore structure, pore size distribution, gas diffusivity and emission of gas fluxes and hence provide useful implications for pasture management to reduce future emission of greenhouse gases. Results particularly highlighted the importance of ensuring a diffusivity ⩾0.038 to limit extensive emission of N2O and N2 fluxes. The improved parametric models and parameter correlations provide valuable numerical insight to better characterize density-dependent behavior in soil physical properties and functions. [ABSTRACT FROM AUTHOR]

A solution of the quasi-linear flow equation for steady and unsteady infiltration from a horizontal ring-shaped source with evaporation at the surface of a vertically heterogeneous soil is derived. A coupled source-sink approach enables analyzing the effects of geometrical source and sink attributes, potential evaporation rate and soil heterogeneity on wetting patterns and water-uptake rates. Ring emitters significantly smaller than the soil's capillary length behave like a point source and substantially larger rings behave like a line source. For ring source radii comparable to the soil's capillary length, water uptake depends on the ring radius and on the size of the root zone in a complex manner. At the stage of root development toward a ring emitter, water uptake is low, and it increases as the radius of the ring (torus)-shaped root system increases. Deepening a subsurface ring emitter decreases water uptake in the absence of evaporation from the soil surface and increases ater uptake in the presence of evaporation. It is suggested that the evaluated relative water-uptake rate be used as a design criterion for determining the desired radius and depth of the ring emitter with respect to root-zone geometry, soil properties and atmospheric evaporation demand. [ABSTRACT FROM AUTHOR]

Soil physical characteristics are important drivers for soil functions and productivity. Field applications of near-infrared spectroscopy (NIRS) are already deployed for in situ mapping of soil characteristics and therefore, fast and precise in situ measurements of the basic soil physical characteristics are needed at any given water content. Visible-near-infrared spectroscopy (vis-NIRS) is a fast, low-cost technology for determination of basic soil properties. However, the predictive ability of vis-NIRS may be affected by soil-water content. This study was conducted to quantify the effects of six different soil-water contents (full saturation, pF 1, pF 1.5, pF 2.5, pF 3, and air-dry) on the vis-NIRS predictions of six soil physical properties: clay, silt, sand, water content at pF 3, organic carbon (OC), and the clay/OC ratio. The effect of soil-water content on the vis-NIR spectra was also assessed. Seventy soil samples were collected from five sites in Denmark and Germany with clay and OC contents ranging from 0.116 to 0.459 and 0.009 to 0.024 kg kg-1, respectively. The soil rings were saturated and successively drained/dried to obtain different soil-water potentials at which they were measured with vis-NIRS. Partial least squares regression (PLSR) with leave-one-out crossvalidation was used for estimating the soil properties using vis-NIR spectra. Results showed that the effects of water on vis-NIR spectra were dependent on the soil-water retention characteristics. Contents of clay, silt, and sand, and the water content at pF 3 were well predicted at the different soil moisture levels. Predictions of OC and the clay/OC ratio were good at air-dry soil condition, but markedly weaker in wet soils, especially at saturation, at pF 1 and pF 1.5. The results suggest that in situ measurements of spectroscopy are precise when soil-water content is below field capacity. [ABSTRACT FROM AUTHOR]

Accurately estimating soil moisture infiltration information contributes to scientific understanding of the one-dimensional (1D) vertical infiltration process. Because of its simple form, the Green-Ampt (GA) model has been extensively employed to simulate soil infiltration processes. However, the GA model is an implicit solution that must be solved through iterative techniques, and thus is inconvenient. Therefore, based on the two-parameter infiltration equation proposed by Valiantzas, by adding an error term and non-dimensional numerical analysis, this study proposes an approximate explicit Green-Ampt model (EGA model) for estimating cumulative infiltration with a determined power function expression for the error term. A total of 12 typical soils were selected from the USDA soil textural classes, and the 1D vertical soil infiltration process was simulated using Hydrus-1D. The reliability of the proposed EGA model was verified using measured and simulated values. The mean absolute percentage relative error (MAPRE) and percentage of bias (PB) were taken as evaluation indicators to compare the estimated cumulative infiltration with the measured and simulated values. The results revealed that all cumulative infiltration values estimated by the EGA model are in good agreement with those measured in laboratory experiments and simulated using Hydrus-1D; the mean MAPRE and PB values of all treatments were 4.2 and 0.7%, respectively. In addition, the estimated errors of the EGA model were consistent with those of the GA model. Hence, the EGA model can estimate the cumulative infiltration in 1D vertical soil infiltration with high accuracy and is suitable for a variety of soil textures. [ABSTRACT FROM AUTHOR]

Portable X-ray fluorescence (pXRF) has been used in many countries to assess the total elemental composition of soils and has agronomic, pedological, and environmental applications. This technique is still incipient in tropical developing countries like Brazil but has potential to improve and decrease the costs of research. Soil moisture is one of the most important factors influencing pXRF results. This pilot study evaluated how soil moisture affects elemental concentrations of oxides common in Brazilian soils (SiO2, Al2O3, Fe2O3, TiO2, and P2O5) as assessed by pXRF. Undisturbed soil samples were collected from the surface and subsurface horizons of six representative Brazilian soils (representing ~40% of the country) with variable texture, weathering, or leaching status. Soil moisture ranged from complete saturation to oven-dry. During drying, six pXRF measurements were made and oxide contents were recorded. In all soils, the P2O5 content was below the pXRF detection limit, and SiO2 and Al2O3 were strongly influenced by soil water content. As soil moisture increased, SiO2 and Al2O3 contents decreased (described by a power model, y = a – bxc). The TiO2 content was much less affected by soil moisture, whereas Fe2O3 was not significantly affected by soil moisture. Soil texture and weathering status are closely related to variation in the SiO2 and Al2O3 contents determined by the pXRF with soil moisture. These findings are critical to the appropriate application of pXRF in tropical countries featuring oxide-laden soils. For in-field measurement of oxides affected by soil moisture (Si and Al), a practical correction factor was determined. [ABSTRACT FROM AUTHOR]

Peat soils shrink and become very hydrophobic when dried. Both properties may cause inaccuracies when applying laboratory methods for soil hydraulic properties that have been developed and tested for mineral soils. This study aimed to compare different methods for the determination of the water retention of peat soils near permanent wilting point (pF 3.5 to 4.2). Three common methods were tested: two pressure apparatus (ceramic plate [Soilmoisture] vs. membrane [Eijkelkamp]) and a dew-point potentiameter (WP4C, Decagon Devices, Inc.), which is based on the equilibrium of soil water potential with air humidity. We used both field-moist peat samples and samples that had been rewetted after oven-drying. We found that there was no systematic difference between the two pressure apparatus. Low moisture variability among replicates and dew-point potentiameter measurements that indicated a drainage to pF 4.2 support the use of pressure apparatus for the determination of water retention near permanent wilting point. Despite a rewetting time of 2 wk including periodic mixing, rewetted oven-dried samples showed lower soil moistures at pF 3.5 and 4.2 than field-moist ones. This severe and long-lasting hysteresis effect was strongest for less decomposed peat samples. Thus, field-moist samples should be used. This makes the classical dew-point potentiameter measurement protocol, which is based on defined water additions to oven-dried samples, unsuitable for peat samples. [ABSTRACT FROM AUTHOR]

A soil water release curve (SWRC) describes the critical and soil-specific relationship between soil water content and matric potential. In this study, soil moisture and corresponding matric potentials were measured using (1) a new method by HYPROP and WP4 dewpoint potentiometer, and, (2) the traditional method by hanging water column, Tempe cell, and pressure plate. The SWRCs were developed for Fargo silty clay, Glyndon silty loam, and Hecla sandy loam soils by using the van Genuchten model. The goodness of fit between the fitted SWRC and the measured data agreed well with R² between 0.91 and 0.98. The comparison for the fitted SWRCs showed that the SWRCs for Hecla sandy loam soil provided the best agreement while Glyndon silty loam soil had the best match in terms of slope and shape. The SWRCs for Fargo silty clay soil did not provide a good match between the two methods. The difference in water content between the two fitted SWRCs was less than 2% for Glyndon silty loam and Hecla sandy loam soils. However, Fargo silty clay had a 4.5 to 5% difference for 66% of the measurements, possibly due to the different bulk densities caused by shrinkage and swelling nature of the clay soil. Since the best fitted van Genuchten parameters were within the reference range that was acceptable for the same type of soils, the HYPROP and WP4 can be used to develop SWRCs that are comparable to the traditional laboratory methods for the three soils in the Red River Valley. [ABSTRACT FROM AUTHOR]

In this study, we explored four approaches to infer field-saturated hydraulic conductivity (Kfs) from both early-time and steady-state infiltration measurements using an explicit expression for three-dimensional flow. All approaches required an estimate of the soil capillary length, l. Approach 1 estimated Kfs via optimization, in which all other infiltration parameters (9 in total) were known. The remaining approaches constrained l through different interpretations of coefficients generated by linear regression between infiltration and time. Approach 2 utilized these coefficients plus estimated soil water content to simultaneously quantify both l and Kfs. Approach 3 used an analytical expression in which l was estimated based on water retention/unsaturated hydraulic conductivity parameters, while Approach 4 adopted a universal l value of 15 cm. The accuracy of these four approaches were tested using numerical and laboratory infiltration data. Approach 1 had the highest accuracy but also required the most auxiliary data, making it most suitable for laboratory and numerical experiments. Approach 2 was the least consistent, providing negative estimates for l and Kfs under certain conditions. Approach 3 also gave accurate predictions of Kfs, but may be inaccurate in instances where the water retention model parameters are uncertain or do not describe soil hydraulic behaviors well. Approach 4 provided reasonable estimates of Kfs (within a factor of three from the actual value in most cases), while not requiring additional observational data. The optimal approach for interpreting Kfs will thus vary depending on the type and quality of available auxiliary data. [ABSTRACT FROM AUTHOR]