Soil Water Content Measurement Using Polymer Optical Fibre Bragg Gratings

Measuring soil water content is crucially important and can affect soil strength which is a key parameter in analysis, design and monitoring of geo-structures. In this study, an optical fibre Bragg grating (FBG) sensor inscribed in Polymer Optical Fibre (POF) was developed and for the first time its ability to measure soil water content was investigated. The sensitivity of the sensor to different values of gravimetric soil water content under different compaction conditions of loose and normal compaction was tested. The effect of soil temperature on the sensor’s performance was considered. To assess the sensor’s implementation, accuracy and reliability, a commercial soil water content probe (SM150), which measures volumetric soil water content was employed. The results indicate that the developed sensor when calibrated correctly, is able to provide detailed data on any minor variation of soil water content (e.g. 0.5%) with high precision. The outcomes of this study define an additional capability of the POFBG sensors which is significantly important for long-term performance monitoring of geo-structures.

Accurate Measurements of Forest Soil Water Content Using FDR Sensors Require Empirical In Situ (Re)Calibration

Monitoring volumetric soil water content (θv) is the key for assessing water availability and nutrient fluxes. This study evaluated the empirical accuracy of θv measurements using standard and in situ calibrated frequency domain reflectometers (FDR) with gravimetric water content and bulk density measurements of 1512 samples gathered from 15 profiles across 5 ICP Forests level II intensive monitoring plots. The predicted θv, calibrated with standard functions, predominantly underestimated the real water content. The measurement error exceeded the threshold of 0.03 m3 m−3 in 93% of all soil layers. Layer specific calibration removed bias and reduced the overall prediction error with a factor up to 2.8. A simple linear regression often provided the best calibration model; temperature correction was helpful in specific cases. To adequately remove bias in our study plots, a calibration dataset of up to 24 monthly observations was required for topsoils (whereas 12 observations sufficed for subsoils). Based on estimated precision errors, 3 sensors per soil layer proved to be sufficient, while up to 16 sensors are needed to meet the required accuracy in organic topsoils. Validating FDR sensor outputs using in situ gravimetric measurements is essential for quality control and assurance of long term θv monitoring and for improving site specific instrumentalization.

Rainfall Determines Shallow Soil Seepage in a Piedmont Summer Pasture of Alpine Meadow on the Northeastern Qinghai—Tibetan Plateau

Soil seepage is an important component used for quantifying hydrological processes that remains unclear in high-altitude alpine meadows. Shallow soil seepage was continuously measured using an auto-logged micro-lysimeter (diameter = 30 cm, depth = 30 cm) from July 2018 to June 2019 in a piedmont summer pasture of alpine meadow on the Northeastern Qinghai–Tibetan Plateau. The results showed that all the shallow soil seepage events occurred during the non-frozen period from April to September and that the cumulative amount was 106.8 mm, representing about 1/5 of the annual precipitation. The maximum and minimum monthly soil seepage were 30.7 mm in September and 1.0 mm in April, respectively. The boosted regression trees (BRT) model’s area under the curve averaged 0.92 and revealed that the daily half-hour rainfall frequency, volumetric soil water content, and air temperature played significant roles in the daily soil seepage probability, with the cumulative relative contribution of 68%. The stepwise linear regression analysis showed that the rainfall amount accounted for 59% of the variation in the daily amount of soil seepage. The monthly soil seepage was found to be significantly correlated with the monthly rainfall frequency (r = 0.86, p = 0.005). Our results highlighted that rainfall, including its amount and frequency, was the key determinant of the probability and amount of shallow soil seepage in the piedmont summer pasture of alpine meadows. These findings will be helpful for improving predictions of the water budgets of piedmont alpine meadows.

A Novel Lithium Foil Cosmic-Ray Neutron Detector for Measuring Field-Scale Soil Moisture

During the past decade, cosmic-ray neutron sensing technology has enabled researchers to reveal soil moisture spatial patterns and to estimate landscape-average soil moisture for hydrological and agricultural applications. However, reliance on rare materials such as helium-3 increases the cost of cosmic-ray neutron probes (CRNPs) and limits the adoption of this unique technology beyond the realm of academic research. In this study, we evaluated a novel lower cost CRNP based on moderated ultra-thin lithium-6 foil (Li foil system) technology against a commercially-available CRNP based on BF3 (boron trifluoride, BF-3 system). The study was conducted in a cropped field located in the Konza Prairie Biological Station near Manhattan, Kansas, USA (325 m a.s.l.) from 10 April 2020 to 18 June 2020. During this period the mean atmospheric pressure was 977 kPa, the mean air relative humidity was 70%, and the average volumetric soil water content was 0.277 m3 m−3. Raw fast neutron counts were corrected for atmospheric pressure, atmospheric water vapor, and incoming neutron flux. Calibration of the CRNPs was conducted using four intensive field surveys (n > 120), in combination with continuous observations from an existing array of in situ soil moisture sensors. The time series of uncorrected neutron counts of the Li foil system was highly correlated (r2 = 0.91) to that of the BF-3 system. The Li foil system had an average of 2,250 corrected neutron counts per hour with an uncertainty of 2.25%, values that are specific to the instrument size, detector configuration, and atmospheric conditions. The estimated volumetric water content from the Li foil system had a mean absolute difference of 0.022 m3 m−3 compared to the value from the array of in situ sensors. The new Li foil detector offers a promising lower cost alternative to existing cosmic-ray neutron detection devices used for hectometer-scale soil moisture monitoring.

Soil Mehlich-3 extractable elements as affected by the addition of biochars to a clay soil co-amended with or without a compost

Biochar has potential to sequester carbon and mitigate greenhouse gas emissions, and it may also contribute nutrients for plant growth in temperate climates. Nutrient availability in biochar-amended soil was assessed in a 338-d incubation study. The clay soil prepared with 4% w/w (dry basis) compost or without compost, then amended with wood-based biochar made at different pyrolysis temperatures (maple bark [Acer saccharum] at 400°C [M400], 550°C [M550] and 700°C [M700]) on a dry-rate basis of 5% (w/w). After moistening the soil mixture to 44% volumetric soil water content (equivalent to 70% water-filled pore space), soil mixtures were incubated in the dark at 22°C. Soil was sampled at days 9, 16, 23, 44, 86, 23 170 and 338 of the incubation. Biochar amendment increased the Mehlich-3 P, K, Ca, Mg and Cu concentrations, and reduced the Mehlich-3 Al and Fe concentrations at each sampling date, and M400 had the most significant effect on Mehlich-3 extractable nutrient concentrations. Compost addition also increased the amounts of extractable nutrients. These results suggested that M400 and carbon-rich compost promoted microbial growth and mineralization in amended soil. In addition, soil mixed with compost and amended with biochar had more Mehlich-3 extractable K than when compost or biochar were applied alone, probably due to greater growth and activity of soil K-solubilizing microorganisms. Overall, our study indicated that co-application of wood-based biochar and compost could improve soil fertility in temperate regions by increasing the availability of most plant macronutrients and micronutrients.

Rootstock Affects Scion Nutrition and Fruit Quality during Establishment and Early Production of ‘Honeycrisp’ Apple

‘Honeycrisp’ apple is susceptible to bitter pit, which is associated with fruit mineral nutrient composition. Rootstock genotypes can affect nutrient acquisition, distribution, and fruit yields, which all affect fruit nutrient composition and bitter pit susceptibility. However, the changes of these traits among different rootstock genotypes in response to abiotic stress under semiarid conditions are relatively unknown. The objective of this study was to evaluate the influence of different rootstocks and irrigation on nutrient uptake and partitioning with ‘Honeycrisp’ apple grown in an irrigated, semiarid environment. ‘Honeycrisp’ apple trees were grafted on four different rootstocks, Geneva 41 (‘G.41’), Geneva 890 (‘G.890’), M.9-T337 (‘M.9’), and Budagovsky 9 (‘B.9’), and these were planted at high density (3000 trees/ha). Irrigation was applied as either a water-limited treatment where volumetric soil water content was maintained near 50% field capacity (FC) and a well-watered control where soil water content was maintained near 100% FC. ‘G.890’, the most vigorous rootstock, had lower nitrogen and higher potassium content in leaves, while ‘B.9’, the least vigorous rootstock, had lower potassium and higher nitrogen content. Rootstock genotype did not affect calcium uptake. Interestingly, water-limited conditions increased the nutrient content in root and stems but not in leaves. Water-limited trees partitioned more nitrogen and calcium to roots, while well-watered trees in the control partitioned more nutrients to the stems. Fruit size was the largest for ‘G.890’ and smallest for ‘B.9’. Both ‘G.41’ and ‘G.890’ had higher bitter pit incidence, which was associated with higher potassium content in leaves and fruit. These results suggest that rootstock-induced vigor and irrigation can both contribute to nutrient imbalances in leaves and fruit that could affect the development of physiological disorders in ‘Honeycrisp’ apple.

Improved Delivery of Remedial Agents Using Surface Foam Spraying with Vertical Holes into Unsaturated Diesel-Contaminated Soil for Total Petroleum Hydrocarbon Removal

Surface foam spraying technologies, employing natural infiltration processes, have recently been suggested to not disturb or mix contaminated soils. However, effective delivery of reactive remedial agents to the bottom area of a contaminated region using only natural infiltration processes can be a challenge. This study aimed to improve the delivery of remedial agents such as oxidants, microorganisms, and nutrients to all depths of 30 cm thick unsaturated diesel-contaminated soil using small vertical soil holes. Three vertical holes, occupying 0.8% of the total soil volume and 3% of the soil surface area, were made inside the 17.3 kg soil column. Persulfate oxidation foam and subsequent bioaugmentation foam spraying were applied for remediation of contaminated soil. Foam spraying with vertical soil holes improved the uniformity of distribution of remedial agents throughout the soil, as evidenced by the uniform pH, higher volumetric soil water content, and a microbial population of >107 CFU/g. Therefore, the total petroleum hydrocarbon (TPH) removal efficiency (88–90%) from bottom soils was enhanced compared to soil columns without holes (72–73%) and the control test (5–9%). The kinetic study revealed that relatively similar TPH biodegradation rates (0.054–0.057 d−1) can be obtained for all soil depths by using this new and simple approach.

Sensitivity of Northern Highbush Blueberry Cultivars to Soil Water Deficits during Various Stages of Fruit Development

In many regions, water limitations are increasing because of frequent and persistent droughts and competition for water resources. As a result, growers in these regions, including those producing blueberries, must limit irrigation during drier years. To identify the most critical periods for irrigation, we evaluated the effects of soil water deficits during various stages of fruit development on different cultivars of northern highbush blueberry (Vaccinium corymbosum L.). The study was conducted for 2 years in western Oregon and included two early season cultivars, ‘Earliblue’ and ‘Duke’, a midseason cultivar, ‘Bluecrop’, and two late-season cultivars, ‘Elliott’ and ‘Aurora’. Volumetric soil water content and stem water potentials declined within 1 to 2 weeks with no rain or irrigation in each cultivar and were lowest during the later stages of fruit development. Water deficits reduced berry weight by 10% to 15% in ‘Earliblue’ and ‘Elliott’ when irrigation was withheld in the second year during early or late stages of fruit development and by 6% to 9% in ‘Aurora’ when irrigation was withheld in either year during the final stages of fruit development. However, water deficits only reduced yield significantly in ‘Aurora’, which produced 0.8 to 0.9 kg/plant fewer fruit per year when irrigation was withheld during fruit coloring. In many cases, water deficits also reduced fruit firmness and increased the concentration of soluble solids in the berries, but they had inconsistent effects on titratable acidity and sugar-to-acid ratios. As a rule, water deficits were most detrimental during later stages of fruit development, particularly in midseason and late-season cultivars, which ripened in July and August during the warmest and driest months of the year.

Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor

Low-cost, accurate soil water sensors combined with wireless communication in an internet of things (IoT) framework can be harnessed to enhance the benefits of precision irrigation. However, the accuracy of low-cost sensors (e.g., based on resistivity or capacitance) can be affected by many factors, including salinity, temperature, and soil structure. Recent developments in wireless sensor networks offer new possibilities for field-scale monitoring of soil water content (SWC) at high spatiotemporal scales, but to install many sensors in the network, the cost of the sensors must be low, and the mechanism of operation needs to be robust, simple, and consume low energy for the technology to be practically relevant. This study evaluated the performance of a resistivity–capacitance-based wireless sensor (Sensoterra BV, 1018LE Amsterdam, Netherlands) under different salinity levels, temperature, and soil types in a laboratory. The sensors were evaluated in glass beads, Oso Flaco sand, Columbia loam, and Yolo clay loam soils. A nonlinear relationship was exhibited between the sensor measured resistance (Ω) and volumetric soil water content (θ). The Ω–θ relationship differed by soil type and was affected by soil solution salinity. The sensor was extremely sensitive at higher water contents with high uncertainty, and insensitive at low soil water content accompanied by low uncertainty. The soil solution salinity effects on the Ω–θ relationship were found to be reduced from sand to sandy loam to clay loam. In clay soils, surface electrical conductivity (ECs) of soil particles had a more dominant effect on sensor performance compared to the effect of solution electrical conductivity (ECw). The effect of temperature on sensor performance was minimal, but sensor-to-sensor variability was substantial. The relationship between bulk electrical conductivity (ECb) and volumetric soil water content was also characterized in this study. The results of this study reveal that if the sensor is properly calibrated, this low-cost wireless soil water sensor has the potential of improving soil water monitoring for precision irrigation and other applications at high spatiotemporal scales, due to the ease of integration into IoT frameworks.

Development and Validation of a New Calibration Model for Diviner 2000® Probe Based on Soil Physical Attributes

This study aimed to develop a new model, valid for soil with and without expandable characters, to estimate volumetric soil water content (θ) from readings of scaled frequency (SF) acquired with the Diviner 2000® sensor. The analysis was carried out on six soils collected in western Sicily, sieved at 5 mm, and repacked to obtain the maximum and minimum bulk density (ρb). During an air-drying process SF values, the corresponding gravimetric soil water content (U) and ρb were monitored. In shrinking/swelling clay soils, due to the contraction process, the variation of dielectric permittivity was affected by the combination of the mutual proportions between the water volumes and the air present in the soil. Thus, to account for the changes of ρb with U, the proposed model assumed θ as the dependent variable being SF and ρb the independent variables; then the model’s parameters were estimated based on the sand and clay fractions. The model validation was finally carried out based on data acquired in undisturbed monoliths sampled in the same areas. The estimated θ, θestim, was generally close to the corresponding measured, θmeas, with Root Mean Square Errors (RMSE) generally lower than 0.049 cm3 cm−3, quite low Mean Bias Errors (MBE), ranging between −0.028 and 0.045 cm3 cm−3, and always positive Nash-Sutcliffe Efficiency index (NSE), confirming the good performance of the model.