Volumetric Soil Water Content Research Articles

Soil CO2 efflux fluctuates in three different annual seasons in a semideciduous tropical forest in Yucatan, Mexico

Tropical forest soils store a third of the global terrestrial carbon and control carbon dioxide (CO2) terrestrial effluxes to the atmosphere produced by root and microbial respiration. Soil CO2 efflux varies in time and space and is known to be strongly influenced by soil temperature and water content. However, little is known about the influence of seasonality on soil CO2 efflux, especially in tropical dry forests. This study evaluated soil CO2 efflux, soil temperature, and soil volumetric water content in a semideciduous tropical forest of the Yucatan Peninsula under two sites (flat areas close to and far from hills), and three seasons: dry, wet, and early dry (a transition between the rainy and dry seasons) throughout a year. Additionally, six 24-h periods of soil CO2 efflux were measured within these three seasons. The mean annual soil CO2 efflux was 4±2.2 μmol CO2 m-2 s-1, like the mean soil CO2 efflux during the early dry season. In all seasons, soil CO2 efflux increased linearly with soil moisture, which explained 45% of the spatial-temporal variation of soil CO2 efflux. Soil CO2 efflux was higher close to than far from hills in some months. The daily variation of soil CO2 efflux was less important than its spatial and seasonal variation likely due to small diel variations in temperature. Transition seasons are common in many tropical dry forests, and they should be taken into consideration to have a better understanding of the annual soil CO2 efflux, especially under future climate-change scenarios.

Permafrost, active layer, and meteorological data (2010–2020) at the Mahan Mountain relict permafrost site of northeastern Qinghai–Tibet Plateau

Abstract. Relict permafrost presents an ideal opportunity to understand the impacts of climatic warming on the ground thermal regime since it is characterized by a mean annual ground temperature close to 0 ∘C and relatively thin permafrost. The long-term and continuous observations of permafrost thermal state and climate background are of great importance to reveal the links between the energy balance on hourly to annual timescales, to evaluate the variations in permafrost thermal state over multiannual periods and to validate the remote sensing dataset. We present 11 years of meteorological and soil data from the Mahan Mountain relict permafrost site of northeastern Qinghai–Tibet Plateau. The meteorological data comprise air and land surface temperature, relative humidity, wind speed and direction, shortwave and longwave downwards and upwards radiation, water vapor pressure, and precipitation on a half-hour timescale. The active layer data include daily soil temperature and soil volumetric water content at five different depths. The permafrost data consist of the ground temperature at 20 different depths up to 28.4 m. The high-quality and long-term datasets are expected to serve as accurate forcing data in land surface models and evaluate remote-sensing products for a broader geoscientific community. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Cryos.tpdc.271838, Wu and Xie, 2021).

Optimizing Irrigation Strategies to Improve Water Use Efficiency of Cotton in Northwest China Using RZWQM2

Irrigated cotton (Gossypium hirsutum L.) is produced mainly in Northwest China, where groundwater is heavily used. To alleviate water scarcity and increase regional economic benefits, a four-year (2016–2019) field experiment was conducted in Qira Oasis, Xingjiang Province, to evaluate irrigation water use efficiency (IWUE) in cotton production using the Root Zone Water Quality Model (RZWQM2), that was calibrated and validated using volumetric soil water content (θ), soil temperature (Tsoil°) and plant transpiration (T), along with cotton growth and yield data collected from full and deficit irrigation experimental plots managed with a newly developed Decision Support System for Irrigation Scheduling (DSSIS). In the validation phase, RZWQM2 adequately simulated (S) topsoil θ and Tsoil°, as well as cotton growth (average index of agreement (IOA) > 0.76). Relative root mean squared error (RRMSE) and percent bias (PBIAS) of cotton seed yield were 8% and 2.5%, respectively, during calibration, and 20% and −10.3% during validation. The cotton crop’s (M) T was well S (−18% < PBIAS < 14% and IOA > 0.95) for both full and deficit irrigation fields. The validated RZWQM2 model was subsequently run with seven irrigation scenarios with 850 to 350 mm water (Irr850, Irr750, Irr700, Irr650, Irr550, Irr450, and Irr350) and long-term (1990–2019) weather data to determine the best IWUE. Simulation results showed that the Irr650 treatment generated the greatest cotton seed yield (4.09 Mg ha−1) and net income (US $3165 ha−1), while the Irr550 treatment achieved the greatest IWUE (6.53 kg ha−1 mm−1) and net water production (0.94 $ m−3). These results provided farmers guidelines to adopt deficit irrigation strategies.

Time-Lag Effect of Vegetation Response to Volumetric Soil Water Content: A Case Study of Guangdong Province, Southern China

The content of soil water affects the physiological activities of vegetation, and the type of vegetation also affects the soil water balance. It is of great significance to study the response of vegetation to soil moisture change, which is helpful for understanding the vulnerability of vegetation for regional and environmental protections. The response of vegetation to soil moisture in Guangdong Province from mid-October 2015 to the end of March 2017 was studied by using cloudy region drought index (CRDI) as the drought index and volumetric soil water content (VSWC) as the soil moisture index to measure the level of water stress on vegetation. Taking the peak and valley positions of CRDI and VSWC as characteristic points, the lag time of vegetation to volumetric soil water content was obtained by judging the difference between the peak and valley positions of the two indexes. The results indicate that the response of vegetation to volumetric soil water content in Guangdong lagged 3.33 periods (9–35 days) on average. When VSWC is sufficient, there is no obvious difference in time-lag between different types of vegetation. However, when VSWC is relatively insufficient, grass shows the fastest response to the change of volumetric soil water content. Both longitude and soil moisture affect the lag time of vegetation. Under the same conditions, the higher the soil humidity is, the longer the lag time is, and the longer the delay time is with the greater longitude. CRDI can reflect the time-lag effect between vegetation and VSWC in Guangdong, indicating it is a sensitive and applicable index for characterizing the time-lag phenomena of vegetation to soil moisture.

Prediction of Soil Water Content and Electrical Conductivity Using Random Forest Methods with UAV Multispectral and Ground-Coupled Geophysical Data

The volumetric water content (VWC) of soil is a critical parameter in agriculture, as VWC strongly influences crop yield, provides nutrients to plants, and maintains the microbes that are needed for the biological health of the soil. Measuring VWC is difficult, as it is spatially and temporally heterogeneous, and most agricultural producers use point measurements that cannot fully capture this parameter. Electrical conductivity (EC) is another soil parameter that is useful in agriculture, since it can be used to indicate soil salinity, soil texture, and plant nutrient availability. Soil EC is also very heterogeneous; measuring EC using conventional soil sampling techniques is very time consuming and often fails to capture the variability in EC at a site. In contrast to the point-based methods used to measure VWC and EC, multispectral data acquired with unmanned aerial vehicles (UAV) can cover large areas with high resolution. In agriculture, multispectral data are often used to calculate vegetation indices (VIs). In this research UAV-acquired VIs and raw multispectral data were used to predict soil VWC and EC. High-resolution geophysical methods were used to acquire more than 41,000 measurements of VWC and 8000 measurements of EC in 18 traverses across a field that contained 56 experimental plots. The plots varied by crop type (corn, soybeans, and alfalfa) and drainage (no drainage, moderate drainage, high drainage). Machine learning was performed using the random forest method to predict VWC and EC using VIs and multispectral data. Prediction accuracy was determined for several scenarios that assumed different levels of knowledge about crop type or drainage. Results showed that multispectral data improved prediction of VWC and EC, and the best predictions occurred when both the crop type and degree of drainage were known, but drainage was a more important input than crop type. Predictions were most accurate in drier soil, which may be due to the lower overall variability of VWC and EC under these conditions. An analysis of which multispectral data were most important showed that NDRE, VARI, and blue band data improved predictions the most. The final conclusions of this study are that inexpensive UAV-based multispectral data can be used to improve estimation of heterogenous soil properties, such as VWC and EC in active agricultural fields. In this study, the best estimates of these properties were obtained when the agriculture parameters in a field were fairly homogeneous (one crop type and the same type of drainage throughout the field), although improvements were observed even when these conditions were not met. The multispectral data that were most useful for prediction were those that penetrated deeper into the soil canopy or were sensitive to bare soil.

Bio‐tillage improves soil physical properties and maize growth in a compacted Vertisol by cover crops

AbstractBio‐tillage has recently been proposed as a measure to alleviate soil compaction through biopores created by cover crop roots. The objective of this study was to determine the effect of different cover crops on soil physical properties and the succeeding maize (Zea mays L.) growth in compacted soil. Four treatments, including no cover crop as a control (Con), alfalfa (Medicago sativa L.), oilseed rape (Brassica napus L.), and radish and hairy vetch mixture (Raphanus sativus L. and Vicia villosa Roth), were carried out under both compacted and noncompacted soil conditions. Soil physical properties, such as the volumetric soil water content (SWC), bulk density, saturated hydraulic conductivity (Ks) and air permeability at water potential of −60 hPa (Ka60), and maize root characteristics and yield were measured. The cover crops did not affect the soil bulk density but significantly decreased the SWC in both the compacted and noncompacted soils relative to the Con treatment. The alfalfa treatment presented significantly higher Ks in the noncompacted soil and Ka60 in both the compacted and noncompacted soils than the Con treatment in the soil layer depth of 20–50 cm. The three cover crop treatments improved the maize root biomass density (173.2% for 2018 and 35.6% for 2019) and root length density (50.9% for 2018 and 51.8% for 2019) relative to the Con treatment in the soil layer depth of 10–70 cm in 2018 and soil layer depth of 10–50 cm in 2019 in the compacted soil rather than in the noncompacted soil. Compared with the Con treatment, the radish mixed with hairy vetch treatment in 2018 and the oilseed rape treatment in 2019 significantly enhanced the maize yield in the compacted soil. Our results suggest that alfalfa is the best crop for improving air permeability; however, the oilseed rape and mixture of radish and hairy vetch lead to better maize growth in the compacted soil. Bio‐tillage using cover crops is effective in alleviating soil compaction.

Supplemental irrigation increases grain yield, water productivity, and nitrogen utilization efficiency by improving nitrogen nutrition status in winter wheat

Supplemental irrigation (SI) is considered as one of the effective water management practices for improving grain yield and nitrogen utilization efficiency (NUtE) in winter wheat (Triticum aestivum L.). However, whether SI increases grain yield and NUtE by improving the N status in winter wheat is unclear. Based on a two-year field experiment (2017–2018, 2018–2019), we studied the effects of different levels of SI (i.e., no SI (J0), volumetric soil water content at100% field capacity at 20 cm (J20), and volumetric soil water content at 100% field capacity at 40 cm (J40)) and winter wheat cultivars (i.e., large spike-type Shannong23 (SN23) and multi spike-type Shannong29 (SN29)) on grain yield, NUtE and N status in winter wheat of the North China Plain. Our results indicated that, grain yield had a significant positive correlation with the amount of photosynthetic N (PN) at anthesis. With an increase in the N accumulation in shoots at anthesis (NAA), the amount of PN increased first and then remained stable, whereas the amount of reserve N (RN) increased continuously. Compared with SN29, SN23 allocated more N to PN and storage RN and less to structural N (SN) and accumulation RN at anthesis and had higher NUtE. Supplemental irrigation at jointing stage significantly increased the amount of NAA and pre-anthesis N redistributed to grains, and its contribution to grains, while the highest grain yield, NUtE, and water productivity (WP) were reached in J20 and not J40. WP was positively related to the amount of NAA and was also affected by the N nutrition index (NNI) at anthesis. The NNI of winter wheat under J20 treatment is optimal (approximated 1). In J40, with the higher irrigation amount, actual crop evapotranspiration (ETc act), the amounts of NAA and RN, and the NNI at anthesis increased further, but the amounts of PN and grain yield were not affected, which explained the reductions in NUtE and WP. Overall, moderate SI increased winter wheat grain yield and NUtE by improving N nutrition status as indicated by the NNI. And the NNI at anthesis is an important indicator to help manage irrigation and improve grain yield, NUtE, and WP in winter wheat on the North China Plain.

Soil–atmosphere interaction in earth structures

The soil–atmosphere interaction was investigated through laboratory testing, field monitoring and numerical monitoring. In the laboratory, the soil water evaporation mechanisms were studied using an environmental chamber equipped with a large number of sensors for controlling both the air parameters and soil parameters. Both sand and clay were considered. In case of sand, a dry layer could be formed during evaporation in the near surface zone where the suction corresponded to the residual volumetric water content. The evaporative surface was situated at a depth where the soil temperature was the lowest. In case of clay, soil cracking occurred, changing the evaporative surface from one-dimensional to three-dimensional nature. The suctionbased evaporation model was adapted to take these phenomena into account by adopting a function of dry layer evolution in the case of sand and by adopting a surface crack ratio and a retative humidity ratio in the case of clay. In the field, the volumetric water content, and the suction as well as the runoff were monitored for an embankment constructed with lime/cement treated soils. It appeared that using precipitation data only did not allow a correct description of the variations of volumetric water content and suction inside the soils, the consideration of water evaporation being essential. It was possible to use a correlation between precipiration and runoff. The hydraulic conductivity was found to be a key parameter controlling the variations of volumetric water content and suction. For the numerical modelling, a fully coupled thermohydraulic model was developed, allowing analyzing the changes in temperature, volumetric water content and suction of soil, with the upper boundary conditions at the interface between soil and atmosphere determined using meteorological data. Comparison between simulations and measurements showed the performance of such numerical approach.

Irrigation scheduling using continuously monitored data of soil volumetric water content

Irrigation scheduling using continuously monitored data of soil volumetric water content

Demonstrating the Potential of a Low-Cost Soil Moisture Sensor Network.

Soil moisture is a key parameter of the climate system as it relates to plant transpiration and photosynthesis and impacts land–atmosphere interactions. Recent developments have seen an increasing number of electromagnetic sensors available commercially (EM) for soil volumetric water content (θ). Their use is constantly expanding, and they are becoming increasingly used for agricultural, ecological, and geotechnical applications and climate research, providing decision support and high-resolution data for models and machine-learning algorithms. In this study, a soil moisture sensor network consisting of 10 Sense Cap capacitance-based sensors is evaluated. Analytical performance of the sensors was determined based on laboratory and field measurements with dielectric permittivity (ε) standards and soil media substrates. Sensor response normalisation to standards of known ε was found to reduce intersensor variability and provide robust estimates of θ in soil samples with known θ. Cross-comparison with a time-domain reflectometry (TDR) instrument carried out in two soil media demonstrates good agreement between the two probes throughout the tested range. The data communication performance of the network was evaluated in terms of packet drop rate at different ranges and sampling frequencies. It was noticed that the drop rate increased with distance from the gateway, while sampling frequency had no effect. Sources of errors associated with probe installation were identified and recommendations are provided for sensor deployment. The off-the-shelf all-in-one solution provided by Sense Cap is low cost, user friendly and suitable for implementation at temporal and spatial scales once the identified shortcomings are addressed. The evaluation presented aims to aid stakeholders and users involved in soil and land management practices including crop production, soil conservation, carbon sequestration and pollutants transport.

Strawberry Growth under Current and Future Rainfall Scenarios

Globally, the changing and interacting effects of temperature and precipitation are anticipated to influence the fitness of specialty crops. Strawberry (Fragaria x ananassa) is an important crop in the Northeastern United States. In this study, four plausible precipitation scenarios were developed to be representative of current and future growing season precipitation patterns. Using a precipitation simulator, we tested these scenarios on potted-day-neutral strawberries. This study generated four primary results. (1) Though some treatments received different amounts of precipitation, little difference was observed in soil volumetric water content or temperature. Treatments designed to simulate future conditions were more likely to have higher nitrate-in-leachate (N-leachate) concentrations than those designed to simulate current conditions. (2) Neither total precipitation nor seasonable distribution were associated with foliar or root disease pressure. (3) While there was a slightly higher chance that photosynthesis would be higher in drier conditions, little difference was observed in the effects on chlorophyll concentration and no water stress was detected in any treatment. (4) Leaf biomass was likely more affected by total rather than seasonal distribution of precipitation, but the interaction between changing rainfall distribution and seasonal totals is likely to be an important driver of root biomass development in the future.

Quantification of Ecosystem-Scale Methane Sinks Observed in a Tropical Rainforest in Hainan, China

Tropical rainforest ecosystems are important when considering the global methane (CH4) budget and in climate change mitigation. However, there is a lack of direct and year-round observations of ecosystem-scale CH4 fluxes from tropical rainforest ecosystems. In this study, we examined the temporal variations in CH4 flux at the ecosystem scale and its annual budget and environmental controlling factors in a tropical rainforest of Hainan Island, China, using 3 years of continuous eddy covariance measurements from 2016 to 2018. Our results show that CH4 uptake generally occurred in this tropical rainforest, where strong CH4 uptake occurred in the daytime, and a weak CH4 uptake occurred at night with a mean daily CH4 flux of −4.5 nmol m−2 s−1. In this rainforest, the mean annual budget of CH4 for the 3 years was −1260 mg CH4 m−2 year−1. Furthermore, the daily averaged CH4 flux was not distinctly different between the dry season and wet season. Sixty-nine percent of the total variance in the daily CH4 flux could be explained by the artificial neural network (ANN) model, with a combination of air temperature (Tair), latent heat flux (LE), soil volumetric water content (VWC), atmospheric pressure (Pa), and soil temperature at −10 cm (Tsoil), although the linear correlation between the daily CH4 flux and any of these individual variables was relatively low. This indicates that CH4 uptake in tropical rainforests is controlled by multiple environmental factors and that their relationships are nonlinear. Our findings also suggest that tropical rainforests in China acted as a CH4 sink during 2016–2018, helping to counteract global warming.

Biochar in manure can suppress water stress of sugar beet (Beta vulgaris) and increase sucrose content in tubers

Increased soil drought events threaten the yields of sugar beet (Beta vulgaris L.) and other staples of arable production in central Europe. In this study we evaluated soil moisture and nutrients as impacted by a two and five % (wt) addition of biochar, manure and their blend to a loamy-sand Regosol. Cyclical soil drought was achieved by the controlled reduction of watering by 75% in pot experiments. Ongoing soil moisture and nutrient measurements were taken, and physiological parameters of sugar beet plants were analysed three weeks after the induced drought. At the end of the experiment (16 weeks) plants were harvested and their mass assessed, as well as their nutrient, pigment and sugar contents. In contrast to the addition of manure, soil volumetric water contents were two to three times greater after biochar amendment, compared to the control soil. Porewater analysis revealed that nutrient leaching (e.g., NO3−, K+) from manure addition to soil was reduced when biochar was blended in (by ≤86% compared to manure alone). Crop analysis showed that leaf gas exchanges were moderated during drought following soil amendment, and leaf and tuber yields were increased furthest when combined biochar-manure blends were applied (> 2-times compared to the control). Perhaps most importantly, the advantageous soil conditions induced by the combined biochar and manure addition also resulted in significantly increased sugar contents in plants (2.4-times) pointing to immediate practical applications of these results in the field.

Soil water and stable isotopes in the unsaturated zone profile – field observations and analysis

In this review, we provide research data emphasizing the role of groundwater table and hydrometeorological parameters variation on soil water fluctuations in the unsaturated soil profile. We focused on soil water content, air temperature, precipitation and groundwater table observations. The ThetaProbe Soil Water Sensors basing on changes in the apparent dielectric constant were used for soil volumetric water content measurements. The sensors were installed at the different depths of the unsaturated zone profile under natural atmospheric conditions. The observations lasted more than five years (14 November 2013 – 31 December 2018). Groundwater table data was obtained using Diver data loggers, which continuously recorded water pressure and temperature. For more detailed investigations of water and mass transport at the Maišiagala radioactive waste repository site water, stable isotopes as environmental tracers were used as well.

Vegetation cover, gross photosynthesis and remotely sensed vegetation indices in different aged sub-arctic volcanic islands in the Vestmannaeyjar archipelago

Surtsey and the older islands in the Vestmannaeyjar archepelago offer a unique possibility to study how subArctic ecosystems develop from unvegetated mineral volcanic substrate to grasslands with thick Brown Andosol soils. The present study was carried out on 24 study plots distributed across six different ecoystems on Surtsey, Heimaey and Elliðaey islands and involved field measurements of soil volumetric water content (VWC), vascular plant cover (VPC) and instantanious rate of gross primary production (GPP). Remote sensing was also used to determine the vegetation indices of normalized difference vegetation index (NDVI), photochemical reflectance index (PRI) and chlorophyll/carotenoid index (CCI) of each plot and find their relationships to the measured VPC and GPP. Nýjahraun on Heimaey and the area not affected by seabirds on Surtsey were not significantly different in any measured variable. During their initial 48-58 years of primary succession, they had reached ca. 3% (VPC) to 12-13% (GPP, VWC) of the measured variables in the 5900-year-old Lyngfellisdalur on Heimaey, which has negligible seabird nutrient inputs. However, the measured VPC and GPP had reached similar levels in only 58 years in the seabird-affected parts of Surtsey as measured on the 5900-year-old seabird-affected Elliðaey. This shows how seabirds can greatly speed up ecosystem development by oceanic nutrient inputs into terrestrial ecosystems. Significant relationships were found between NDVI and VPC and between CCI and GPP, which may become important tools to track ecosystem development in space and time on the islands.

Effects of the Soil Moisture Content on the Superoxide Anion and Proline Contents in Soybean Leaves

Background: As an important source of feed protein, soybean is involved in the processing industry, food industry and other fields. Therefore, in recent years, the demand for soybean has increased and soybean planting areas have also increased. However, frequent droughts have a serious impact on soybean yield. Methods: During the flowering period, the soybean plants were subjected to drought treatments of different degrees (0-7 days without water). The superoxide anion and proline contents in the leaves were determined. Then, fitting curves were drawn between the soil moisture content and the superoxide anion and proline contents. Result: The effects of different soil moisture contents on the superoxide anion and proline contents in soybean leaves and the correlation between these contents were analyzed. According to the fitting curves, with a decrease in the volumetric water content of soil, the superoxide anion and proline contents in soybean leaves increased. The superoxide anion contents in drought-tolerant cultivars were significantly lower than those in drought-sensitive cultivars and the proline contents were significantly higher in drought-tolerant cultivars than those in drought-sensitive cultivars. The superoxide anion content in soybean leaves was positively correlated with the proline content in the soil volumetric water content range of 31.5% to 14.5%.

Intensification of water storage deficit in topsoil but not deep soil in a semi-humid forest after excluding precipitation for two years

Deep-rooted forest trees can potentially utilize moisture in deep soil to tolerate periods when growth is water limited. Black locust (R. pseudoacacia) is a deep-rooted forest species but the benefits of deep roots for water uptake under drought conditions are unclear. In this study, we assessed the effects of drought on water storage and the hydrological properties of soil at different depths. We performed a precipitation manipulation experiment continuously from June 2015 to November 2016 using mature R. pseudoacacia in the Loess Plateau region of China. The soil volumetric water contents were measured in the 0–4 m soil layer, as well as the soil hydrological properties comprising the soil bulk density (BD), total porosity, saturated hydraulic conductivity (Ks), and aggregate-associated organic carbon (OC) concentration in the 0–20 cm soil layer. The results showed that soil water storage deficit mainly occurred in the 0–1 m soil layer rather than in the 1–4 m layer after excluding precipitation for two years. Compared with the control, excluding precipitation for two years decreased the soil water storage in the 0–1 m soil layer by 18%. Precipitation exclusion also significantly decreased the soil Ks by 28% and total porosity by 17%, but increased BD by 20% in the 0–10 cm soil layer. In addition, precipitation exclusion significantly decreased the total soil OC concentration and macro- and micro-associated OC concentrations. Our results indicate that excluding precipitation for two years could potentially degrade the water conditions in the topsoil layer but not the deeper soil. These findings provide insights into water management and sustainability in semi-humid afforestation areas of the Loess Plateau region in China.

Highly Sensitive Differential Microwave Sensor for Soil Moisture Measurement

This paper presents a highly sensitive differential soil moisture sensor (DSMS) using a microstrip line loaded with triangular two-turn resonator (T2-SR) and complementary of the rectangular two-turn spiral resonator (CR2-SR), simultaneously. Volumetric Water Content (VWC) or permittivity sensing is conducted by loading the T2-SR side with dielectric samples. Two transmission notches are observed for identical loads relating to T2-SR and CR2-SR. The CR2-SR notch at 4.39 GHz is used as a reference for differential permittivity measurement method. Further, the resonance frequency of T2-SR is measured relative to the reference value. Based on this frequency difference, the permittivity of soil is calculated which is related to the soil VWC. Triangular two-turn resonator (T2-SR) resonance frequency changes from 4 to 2.38 GHz when VWC varies 0% to 30%. The sensor’s operation principle is described through circuit model analysis and simulations. To validate the differential sensing concept, prototype of the designed 3-cell DSMS is fabricated and measured. The proposed sensor exhibits frequency shift of 110 MHz for 1% change at the highest soil moisture content (30%) for sandy-type soil. This work proves the differential microwave sensing concept for precision agriculture.

Large‐scale detection and quantification of harmful soil compaction in a post‐mining landscape using multi‐configuration electromagnetic induction

AbstractFast and accurate large‐scale localization and quantification of harmfully compacted soils in recultivated post‐mining landscapes are of particular importance for mining companies and the following farmers. The use of heavy machinery during recultivation imposes soil stress and can cause irreversible subsoil compaction limiting crop growth in the long term. To overcome or guide classical point‐scale methods to determine compaction, fast methods covering large areas are required. In our study, a recultivated field of the Garzweiler mine in North Rhine‐Westphalia, Germany, with known variability in crop performance was intensively studied using non‐invasive electromagnetic induction (EMI) and electrode‐based electrical resistivity tomography (ERT). Additionally, soil bulk density, volumetric soil water content and soil textures were analysed along two transects covering different compaction levels. The results showed that the measured EMI apparent electrical conductivity (ECa) along the transects was highly correlated (R2 > .7 for different dates and depths below 0.3 m) to subsoil bulk density. Finally, the correlations established along the transects were used to predict harmful subsoil compaction within the field, whereby a spatial probabilistic map of zones of harmful compaction was developed. In general, the results revealed the feasibility of using the EMI derived ECa to predict harmful compaction. They can be the basis for quick monitoring of the recultivation process and implementation of necessary melioration to return a well‐structured soil with good water and nutrient accessibility, and rooting depths for increased crop yields to the farmers.

The Effects of Rainfall, Soil Type and Slope on the Processes and Mechanisms of Rainfall-Induced Shallow Landslides

Landslides are a serious geohazard worldwide, causing many casualties and considerable economic losses every year. Rainfall-induced shallow landslides commonly occur in mountainous regions. Many factors affect an area’s susceptibility, such as rainfall, the soil, and the slope. In this paper, the effects of rainfall intensity, rainfall pattern, slope gradient, and soil type on landslide susceptibility are studied. Variables including soil volumetric water content, matrix suction, pore water pressure, and the total stress throughout the rainfall were measured. The results show that, under the experimental conditions of this paper, no landslides occurred on a 5° slope. On a 15° slope, when the rainfall intensity was equal to or less than 80 mm/h with a 1 h duration, landslides also did not happen. With a rainfall intensity of 120 mm/h, the rainfall pattern in which the intensity gradually diminishes could not induce landslides. Compared with fine soils, coarser soils with gravels were found to be prone to landslides. As the volumetric water content rose, the matrix suction declined from the time that the level of infiltration reached the position of the matrix. The pore water pressure and the total stress both changed drastically either immediately before or after the landslide. In addition, the sediment yield depended on the above factors. Steeper slopes, stronger rainfall, and coarser soils were all found to increase the amount of sediment yield.