Search

Nitrate leaching from farmland pollutes the surrounding environment, such as groundwater, causing health hazards to inhabitants. To mitigate the leaching, biochar can be applied. The effect of biochar application differs depending on the application depth; however, the effect of the application depth remains unclear. To evaluate the effect, we conducted a pipe experiment with no plant using bagasse biochar with four treatments: no biochar application, surface application (0−5 cm), plow layer application (0−30 cm), and subsurface application (25−30 cm). The results showed that surface and plow layer applications reduced nitrate leaching, whereas subsurface application did not affect leaching. This difference was due to changes in the soil water movement and water budget. Surface application reduced evaporation, inducing increases in both drainage and the amount of water in the pipe. The increased amount of water might contribute to an increase in the amount of nitrogen in the pipe, reducing the leaching. Plow layer application increased evaporation, leading to decreased drainage and nitrate leaching. Subsurface application did not affect drainage and nitrate leaching; however, the change in the volumetric water content at a depth of 10 cm was the most significant among the treatments. Our study indicated that, although the same amount of biochar was applied, the effect of biochar application differs depending on the application depth. [ABSTRACT FROM AUTHOR]

AbstractIn the present study, persistence and degradation of tembotrione, a triketone herbicide, was studied in loamy soil collected from maize field. Effects of organic amendments, moistures and temperatures on tembotrione dissipation were evaluated. Soil samples were processed according to the modified QuEChERS involving dichloromethane solvent and MgSO4 without PSA. Analysis using LC-MS/MS showed >95% recoveries of tembotrione its two metabolites TCMBA and M5 from fortified soils. Tembotrione residues dissipated with time and 85.55 to 98.53% dissipation was found on 90th day under different treatments. Tembotrione dissipation increased with temperature and moisture content of the soil. Among organic amendments, highest dissipation was observed in vermicompost amended soil. Minimum and maximum half-lives of tembotrione were recorded under 35 °C (15.7 days) and air-dry (33 days) conditions, respectively. Residues of tembotrione declined with time while that of TCMBA increased steadily up to 10-45th day in different treatments and declined thereafter. Residues of M5 were not detected in our experiments. Tembotrione persistence was negatively correlated with the organic carbon (%), moisture regimes, and temperature. A good correlation between soil microbial biomass carbon and degradation was found. A two-way ANOVA indicated significant differences between the treatments at 95% confidence level (p < 0.05). [ABSTRACT FROM AUTHOR]

Water infiltration in unsaturated soil is significantly affected by multi-stage characteristics that depend on the movement of the wetting front. We modified the Green-Ampt model to accurately capture these multi-stage characteristics during infiltration. The proposed model divides the water-infiltrated unsaturated soil into three zones, while the infiltration process itself is divided into three stages, with the quarter-elliptic wetting front curve being defined. The proposed model, together with other Green-Ampt based models, is analysed and compared with experimental investigations conducted in this study, as well as with published results from the literature. The results demonstrate the proposed modified model successfully describes the measured infiltration time for soil columns with different heights. Additionally, a parametric sensitivity analysis of the proposed model reveals the water infiltration process is mainly controlled by the hydraulic conductivity in the infiltrated zone and the suction head between the wetting front zone and the unpenetrated zone. [ABSTRACT FROM AUTHOR]

The global validation for SMAP (Soil Moisture Active Passive) Level-4 surface soil moisture using well-established core validation sites does not comprehensively account for all landscapes on earth's surface due to the diverse nature of their intrinsic characteristics. Due to the inhibitive cost of implementing a standard validation site, this study presents an alternative sampling approach suitable for localized validation of SMAP data in non-complex terrains. It involves clustering a large heterogeneous study area to smaller units of non-complex terrains where landscape-defining characteristics are largely homogeneous, thus permitting the computation of areal soil moisture as a simple arithmetic mean of near-linear point measurements. This allows optimization of limited resources (a hand-held moisture sensor with site-specific calibrations) to balance the need for spatial representativeness of samples in the sampling unit and the need for temporal proximity of sampled measurements to the aggregation time of the satellite product being validated. For ease of movement, transect sampling is implemented along access roads that run across the sampling units to allow sufficient measurement replications within a reasonably short time. Validations with four different landscapes in Kenya show a good agreement between in situ measurements and SMAP with R2 of 0.76, 0.72, 0.80, and 0.82, and biases of −0.0246, +0.0113, 0.0004, and + 0.0035 m3 m−3, respectively for Mawego, Kuresoi, Sotik and Kapsuser sites. These results only marginally differ from those obtained with a spatially distributed sampling method, indicating the potential of the proposed sampling design for time and cost effectiveness in validations at non-complex terrains. An analysis of the temporal variability of SMAP soil moisture in the watershed is also presented, with an assessment of its significance in the selection of sampling sites for validation. Particularly, the concept of temporal stability of soil moisture as a basis for clustering validation sites is evaluated. [ABSTRACT FROM AUTHOR]

This research investigated the green gram crop by employing a time series of Sentinel-1A Single Look Complex (SLC) and Sentinel-2 datasets, which corresponded to different phenological growth stages of the crop. Field campaigns were conducted on the acquisition dates of Sentinel-1A datasets for the entire crop cycle to estimate crop height and soil moisture. In line with these observations, temporal variations in 10 salient Synthetic Aperture Radar (SAR) parameters, obtained from Sentinel-1A datasets, are systematically analysed, which elucidated the importance of dual-polarized SAR parameters in the diverse phenological growth stages of the crop. Moreover, the Normalized Difference Vegetation Index (NDVI) values from Sentinel-2 datasets, estimated at various green gram growth stages, are categorized into initial (NDVI $ \le $ ≤ 0.5), intermediate (0.5 $ \lt $ < NDVI $ \lt $ < 0.8), and maximum growth of the crop (NDVI $ \ge $ ≥ 0.8), which are then aligned with corresponding SAR and ground-measured parameters. The inversion model development and sensitivity analysis were carried out to correlate ground-measured parameters with SAR parameters across various growth stages based on the categorization of NDVI values as well as for the entire growing season of the crop. Backscattering intensities are found to have good sensitivity to crop height at its intermediate growth (r $ \ge $ ≥ 0.75). Among vegetation indices, the Polarimetric Radar Vegetation Index (PRVI) showed significant sensitivity to crop height in its intermediate growth stage (r $ \approx $ ≈ 0.77). H-A-Alpha decomposition parameters displayed notable sensitivity to soil moisture in the initial and maximum growth stages of green gram. This study demonstrates the effectiveness of Sentinel-1 dual-polarized SAR parameters in monitoring green gram phenological growth stages. The parameters show substantial sensitivity to both green gram height and soil moisture. [ABSTRACT FROM AUTHOR]

Freeze-thaw effects can significantly alter the volume of expansive soil due to the water-phase change and soil expansion. The montmorillonite content was an important factor influencing the expansibility of expansive soil. This paper investigated the micropore structure characteristics of expansive soil under freeze-thaw cycles with various montmorillonite contents. In addition, the micropore evolution of expansive soils and relationship between the unfrozen water content and temperature were also examined via X-ray diffraction (XRD) and nuclear magnetic resonance (NMR). The results indicated that: (1) the montmorillonite content affected the pore size distribution of expansive soil, and with increasing montmorillonite content, the relaxation time (T2) distribution curves changed from single-peak into double-peaks; (2) after multiple freeze-thaw cycles, the macropores in expansive soil increased and mesopore pores decreased; (3) considering the freezing point and capillary adsorption, the soil freezing characteristic curve (SFCC) could be divided into four stages, namely, unfrozen water, free water, freezing-capillary water, freezing-hydroscopic water; (4) the montmorillonite content only affected the unfrozen water content from 0°C to −5°C, while at temperatures lower than −5°C, the effect of the montmorillonite content on the unfrozen water content was negligible. [ABSTRACT FROM AUTHOR]

In India, ∼30% of total land is degraded due to pollution, salinization, and nutrient loss. Change in soil-quality at urban waste-dumping site prior and after cow-dung amendment was compared with control agriculture soil. The soil at waste-dumping site had elevated pH, EC, temperature and lowered OC and NPK concentrations when compared to control. Polymetallic pollution of Cr, Cd, Pb, and Ni beyond permissible limits was obtained. Cow-dung amendment restored soil physicochemical properties at the waste-dumping site, with increasing soil moisture, CEC and OC; however, a slight change in soil bulk-density and heavy-metal concentration post-amendment was noted. The seven natural colonizers present at the waste-dumping site accumulated more metals in roots than shoots. Datura innoxia had maximum bioaccumulation of Cr, Calotropis procera of Cd and Ni and Parthenium hysterophorus of Pb in roots. All these plants had Bioacccumulation factor (BAfroot )>1 and translocation factor (Tf) <1 for Cd and serve as its phytostabilizer except Calotropis procera which had BAfroot >1 and Tf >1 and is identified as a phytoextractor for Cd. Cow-dung amendment alone appeared to be insufficient and additionally the revegetation of natural colonizers is recommended for effective reduction in heavy metal load and improving overall soil health at wasteland. Such eco-restoration may also minimize risks to biodiversity in India. Novelty statement: The novelty of the work lies in revegetation of natural colonizers at polluted wasteland to reduce heavy metal load and improve overall soil health. Calotropis procera, Datura innoxia, Parthenium hysterophorus, and S. nigrum showed maximum bioaccumulation of Cr, Cd, Pb, and Ni. The work confirms C. procera as non-edible, fast growing natural colonizer as potential phytoextractor for Cd and taken into consideration to effectively restore heavy metals polluted wasteland. [ABSTRACT FROM AUTHOR]

To separate the contributions of climate change and human activities to alterations in flow for the Ahar Chay watershed in Iran, change points of the normalized difference vegetation index (NDVI) and evapotranspiration (ET) were distinguished before and after significant alterations. The Budyko model and Soil and Water Assessment Tool (SWAT) were used to find the reduction in runoff. New Penman-Monteith-Leuning (PML) ET data was used to consider plant types. Results revealed an increase in NDVI coinciding with the change point in 1998, as well as ET in 1999. The significance of the Sattarkhan Dam became evident when distinguishing the impacts upstream versus downstream of the dam. Results also indicated that climate change contributed significantly to upstream flow reduction (83.5%), whereas downstream reductions were primarily linked to human-related impacts (59.7–82.5%). Assuming no dam interception, 2007 became the change point, signifying a 37.5% reduction in average flow from before to after this point due to the increased vegetation cover. [ABSTRACT FROM AUTHOR]

The soil moisture (SM) balance is affected by afforestation. In this study, the CiteSpace software was used to review the literature on the impact of afforestation on SM, and we further present research findings on the Loess Plateau (LP) as follows: (1) the spatio-temporal heterogeneity of SM varies depending on the research scale; (2) the presence of a dried soil layer significantly hinders deep SM recharge; (3) the accumulation of net primary productivity (NPP) may be occurring at the expense of SM. The following research topics are discussed: (1) the recharge and consumption of deep SM in LP; (2) the green water footprint and its shortage of non-crop greenery for evaluating SM allocation and use; (3) the development of inclusive models encompassing different spatial scales to assess the limits of soil water carrying capacity for vegetation (SWCCV). [ABSTRACT FROM AUTHOR]

Accurate and timely monitoring of drought conditions in grape-producing regions is crucial for achieving healthy growth of grapes. Current soil moisture (SM) products are primarily available at coarse resolutions (e.g. several to tens of kilometres), constraining its applications at fine scales. Here, we trained a weighted stacking ensemble model including three tree-based models (categorical boosting, random forest, and gradient boosting decision tree), using seven forcing parameters related to spectral reflectance (SR), land surface temperature (LST), and evapotranspiration (ET), in conjunction with the digital elevation model (DEM) feature. The weighted stacking ensemble model exhibited an average R2 of 0.86 and an average RMSE of 0.021 m3/m3 in simulating SM in the vegetive stage and the mid-ripening stage of grape. Then we generated high spatiotemporal downscaled SM (HSM) data at a grape growing area at high spatiotemporal resolutions (30 m, 8-day) from 2009 to 2018. Our HSM dataset demonstrated strong spatial, seasonal and interannual dynamics that align with 500 m SM dataset derived from single MODIS data, and the HSM dataset shows more details in SM distribution. Additionally, the SM time series in the HSM is consistently correlated with drought events, offering intricate spatiotemporal information for drought monitoring. The application of downscaled SM results identified a concentration of drought events in the eastern foothills of the Helan Mountains, particularly severe drought conditions were observed in the Hongsipu production area. Drought occurrences in the Hongsipu production area ranged from 90% to 91% during May and June, decreasing to 73% and 41% in July and August, respectively. These findings significantly contribute to enhancing high spatiotemporal SM monitoring capabilities, offering valuable guidance for timely water management in grape-growing regions. [ABSTRACT FROM AUTHOR]

This study assessed the spatio-temporal variation of the degree of curing (DoC) in the Golden Gate Highlands National Park (GGHNP) from 2016 to 2020. The estimation of the degree of grass curing was carried out with the high spatial resolution fused remotely sensed data of MODIS and Sentinel-2 employing Index-then-Blend (IB) data fusion methods on Google Earth Engine (GEE) to compute Grassland Curing Index (GCI) using soil and vegetation moisture content indices-based grassland curing algorithm. Grassland curing indices were computed on Google Earth Engine and converted into Grassland Curing Maps (GCMs), which were then synthesized into fire danger maps. The study showed that all selected indices have the highest DoC in the month of September, with the minor time variation observed in MODIS and Sentinel 2-derived GCI estimated using Shortwave Infrared Water Stress (GCI_SIWSI) in the months of August and March, respectively. The analysis further revealed that GCI_SIWSI (44%) derived from Sentinel-2 data yielded the highest area of extremely high fire danger, followed by GCI estimated using Normalized Difference Moisture Index (GCI_NDMI) (25%) derived from fused data, MODIS-derived GCI_SIWSI and fused-derived GCI estimated using Global Vegetation Monitoring Index (GCI_GVMI) (both 16%). The GCI_SIWSI derived from Sentinel-2 data also showed that more than 95% of the entire landmass of the study area was within a high to extremely high fire danger zone, making the park's vegetation susceptible to fire. Among all the four selected indices correlated against fire point, only SIWSI revealed a positive relationship across MODIS, Sentinel-2 and Fused data. It is also evident from the study that GCMs derived from Fused data outperformed MODIS and Sentinel-2 with the highest R2 and F values of 0.65 and 380, respectively. These results indicate that GCI derived from fused remotely sensed data is a promising GCI for accurately assessing the DoC over mountainous grassland environments. The study paved the way for increasing the spatial resolution for estimating the DoC for fire and fuel management of parks and other fire agencies within mountainous grassland environments. [ABSTRACT FROM AUTHOR]

Advancements in global satellite missions have revolutionized the assessment of Surface Soil Moisture (SSM) at global to local scales. However, spatio-temporal data discontinuities in specific regions remain a challenge. This study proposes a Machine Learning (ML)-based framework to extend the Soil Moisture Ocean Salinity (SMOS) SSM product both in the spatial and temporal domains, over Canada. In the first phase of the proposed framework, ML models based on Random Forest (RF) and Convolutional Neural Networks (CNN) are trained and validated with SMOS SSM as target and SSM-relevant climatic variables and geophysical variables, obtained from fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data (ERA5), for the 2011–2020 period, as predictors. Developed models, when tested on unseen data for the years 2021–2022, suggest slightly better performance of the RF model compared to CNN, with root mean square error (RMSE) of 0.033 and 0.056 respectively; prediction biases mostly noted for regions with large inter-annual variability. The spatial filling of SSM for grid cells that were excluded during the training process, with similar land types as those in the SMOS training data, yields reasonable performance, with RF (RMSE = 0.013) performing better than CNN (RMSE = 0.064). In the second phase, the RF model is selected to extend the SMOS dataset for the 2008–2010 period. The temporal correlation between extended SMOS and ASCAT (Advanced Scatterometer) SSM demonstrates a reasonable association, with correlation coefficient exceeding 0.6. Additionally, spatial correlation analysis reveals similar patterns between the two datasets, with smaller values for the summer season owing to the importance of local processes on SSM during this period. However, extending SMOS SSM spatially for surface types that were not included in the training process such as peatlands, remains a challenge warranting additional studies. The developed framework is robust and can address spatio-temporal discontinuities in other SSM products. [ABSTRACT FROM AUTHOR]

This study assessed the small-scale hydropower potential (SHP) of the Gidabo River catchment. The Soil and Water Assessment Tool (SWAT) hydrological model was used to estimate the streamflow in the river networks. The model was calibrated and validated at Messa and Apposto gauging stations, and the results for the coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) revealed that the observed and simulated streamflow results agree fairly well at the calibration and validation locations. Thus, the simulated streamflow at the sub-catchment outlets was used to determine design discharge at 50%, 75%, and 95% flow dependability. The potential assessment was conducted under a scenario of 500, 1000 and 2000 m horizontal intervals along the stream networks. The study revealed that the river catchment has the potential to develop run-of-river-type plants at different locations with 50%, 75%, and 95% dependability, though it varies from place to place. [ABSTRACT FROM AUTHOR]

In Highway Embankments (HE) constructed on Expansive Yazoo Clay Soil (EYCS), in situ moisture and matric suction variations are environmentally driven variables that can significantly impact the safety of the constructed slope. The collected moisture content and suction data are localized and have low spatial resolution on embankments with point borehole monitoring systems with sensor instrumentation. On the other hand, Electrical Resistivity Imaging (ERI) allows high spatial resolution monitoring and is a proven method of mapping the subsurface geologic setting. Multiple studies have proven a correlation between resistivity and soil moisture. The comparison between resistivity and matric suction, on the other hand, has been rarely attempted, much less for EYCS through field-based investigation. The objective of the current study is to compare the field-sensor-based matric suction and soil moisture data with resistivity data. This localized comparison informed the capability of the ERI data to extrapolate the moisture content and suction parameters globally or to other areas of the slope where the instrumentation isn't available. Comparing ERI, matric suction, and volumetric soil moisture content is critical to embankments reliable predictive models. This study's findings can improve performance monitoring requirements for susceptible HE. [ABSTRACT FROM AUTHOR]

Karal soils mainly composed of swelling clays are considered as one of the main causes of degradation in civil engineering structures in Cameroon. Thus, a better knowledge on Karal-type soil behavior is required to adapt soil treatment for road construction and foundation dimensioning. The physicochemical, mineralogical and geotechnical characterization of ten soils collected in North and Far North Cameroon allowed to classify Karal among plastic soils. As expected, the optimum water contents and maximum dry densities of dynamically compacted Karal reflected the particle size distribution and the mineralogical soil composition with various amounts of swelling clay (montmorillonite) and quartz associated to sand and silt fractions. Then the swelling/shrinkage properties of compacted specimens evaluated by free swelling test and volume shrinkage test were correlated to soil characteristics to propose a suitable classification for Karal-type soils. Not only swelling but also shrinkage properties were assessed and combined to define a new parameter called the total amplitude of swelling and shrinkage deformation, allowing the exclusion of the soil initial water content when evaluating soil deformation. After comparison of usual indirect methods to classify swelling soils, a predictive method of clay-rich soils deformation under moisture variation for Karal was proposed and discussed. [ABSTRACT FROM AUTHOR]

Soil moisture variation plays a key role in maintaining the engineering properties of soils. One of the main factors that impact the soil moisture content is the temperature, which has a strong impact to change the initial or design moisture and results in significant soil volume changes. This study aims to investigate the effects of temperature on the performance of enzymatically stabilised soils. The enzyme used in this study is Eko-soil and the soil used is clayey silt of low plasticity (ML). The mechanical behaviour was first assessed through the unconfined compression strength and weight measurements based on samples exposed to a series of operational temperatures. X-ray μCT tomography images were then used to assess the microstructure. Porosity, size and geometrical shape of the pores were analysed at elevated temperatures. Results revealed that the enzyme is effective in maintaining the initial pore structure under the tested temperature range. [ABSTRACT FROM AUTHOR]

The rapid advancements in Agriculture 4.0 have led to the development of the continuous monitoring of the soil parameters and recommend crops based on soil fertility to improve crop yield. Accordingly, the soil parameters, such as pH, nitrogen, phosphorous, potassium, and soil moisture are exploited for irrigation control, followed by the crop recommendation of the agricultural field. The smart irrigation control is performed utilizing the Interactive guide optimizer-Deep Convolutional Neural Network (Interactive guide optimizer-DCNN), which supports the decision-making regarding the soil nutrients. Specifically, the Interactive guide optimizer-DCNN classifier is designed to replace the standard ADAM algorithm through the modeled interactive guide optimizer, which exhibits alertness and guiding characters from the nature-inspired dog and cat population. In addition, the data is down-sampled to reduce redundancy and preserve important information to improve computing performance. The designed model attains an accuracy of 93.11 % in predicting the minerals, pH value, and soil moisture thereby, exhibiting a higher recommendation accuracy of 97.12% when the model training is fixed at 90%. Further, the developed model attained the F-score, specificity, sensitivity, and accuracy values of 90.30%, 92.12%, 89.56%, and 86.36% with k-fold 10 in predicting the minerals that revealed the efficacy of the model. [ABSTRACT FROM AUTHOR]

This paper proposes a new concept of single-direction water-blocking for waterproof membranes in silt subgrades to meet the demands of inhibiting capillary rising and allowing subgrade water downward through the waterproof membrane. Furthermore, a new approach to determine the total pore area in water-repellent soil is proposed using a contact angle test. The relationship between the water repellence of the waterproof membrane and the consumption of Sodium Methyl Silicate per unit Area (SMSA) is obtained for different levels of compactness. When SMSA consumption is less than 4 g/m2, the water repellence of the waterproof membrane is extremely poor, whereas, in the range of 4–10 g/m2, its water repellence is greatly enhanced. When the SMSA consumption is more than 10 g/m2, the water repellence becomes stable. The total pore area of the waterproof membrane decreases when the SMSA consumption is increased. [ABSTRACT FROM AUTHOR]

Exploring the impact of different monitoring angles from unmanned aerial vehicle (UAV) on the monitoring accuracy of soil moisture content (SMC) is crucial for precision irrigation. To this end, experiment was conducted to monitor the SMC of winter wheat at different growth stages under different irrigation treatments in Yangling, Shaanxi, China. At a solar zenith angle of 45°, multispectral remote sensing data from a UAV were collected at thirteen different monitoring zenith angles. Simultaneously, the SMC in the wheat root zone was measured. From the UAV multispectral images, spectral reflectance was extracted for the construction of vegetation indices. Then the correlation between the vegetation indices and the measured SMC was analyzed. With the vegetation indices as input variables, SMC monitoring models were constructed using Extreme Learning Machine (ELM), Random Forest (RF), and Back Propagation Neural Network (BPNN). The study also examined the effect of specific angles (hotspot and dark spot angles) on the estimation accuracy of the SMC at the nadir angle. The results indicated that different monitoring angles significantly impact the SMC estimation accuracy. Band reflectance and vegetation indices exhibited significant peak values and angular effects at the monitoring zenith angle of 45°. The models achieved the optimal inversion accuracy at the hotspot angle (at a monitoring zenith angle of 45° in the solar principal plane), and the accuracy was ranked as follows: BPNN (R2 = 0.71; RMSE = 1.69) > ELM (R2 = 0.52; RMSE = 1.94) > RF (R2 = 0.48; RMSE = 2.10). By eliminating shadows at the nadir angle through the threshold of dark spot, inversion accuracy similar to the hotspot direction is achieved. This study provides a basis for appropriate selection of UAV flight angles for the monitoring of SMC in the root zone of winter wheat. [ABSTRACT FROM AUTHOR]

Phosphorus fertilizer is commonly applied to soils in crop production as diammonium phosphate (DAP). To decrease ammonium addition to the environment, triple super phosphate (TSP) is being considered as a DAP replacement. This study was undertaken to compare the response of maize plants to soil fertilization with TSP vs. DAP under well-watered conditions, under soil-drying conditions, and root hydraulic conductance. It was found for well-watered conditions in a controlled environment that there was no difference in plant growth between DAP to TSP treatments. In soil dry-down experiments, however, the initiation of the decrease in transpiration rate was unexpectedly quite different between DAP and TSP treatments. The soil water content threshold for initiation of decrease in transpiration rate with DAP treatment (average fraction transpirable soil water for two experiments = 0.285) was consistent with common observations, but the threshold associated with TSP treatment occurred at an unusually high soil water content (average fraction transpirable soil water for two experiments = 0.545). The higher threshold with TSP resulted in an extended period of soil water use, i.e. soil water conservation. Soil water conservation resulting from the TSP treatment was associated with a 27% greater shoot mass accumulation following a 4-wk re-watering period after the water-deficit treatment than measured with the DAP treatment. The high threshold for decrease in transpiration resulting from TSP was consistent with measured lower root hydraulic conductance as compared to DAP treatment. The unexpected discovery of TSP-induced initiation of transpiration rate decrease at high soil water content is consistent with greater crop drought resilience. [ABSTRACT FROM AUTHOR]

Continuous time-series spectral data are important for inversion of crop or soil information. UAV remote sensing is usually selected under clear and windless weather conditions, but it is not possible to have such weather every day, which results in the UAV not collecting continuous daily spectral information. To explore this issue, we focused on summer maize with four irrigation levels as the research subject. A UAV platform with a multispectral sensor was used to acquire measured spectra of the maize canopy. The solar zenith angle was calculated and substituted into the Ambrals kernel-driven model to obtain simulated spectral data for the maize canopy, and the time-series UAV spectral data were complemented. Then, four vegetation indices (VIs) were established using simulated and measured spectral data, respectively, and the accuracy of the simulated VIs was evaluated. Finally, the simulated and measured VIs were used to monitor and evaluate variations in soil surface moisture content, respectively, and provide irrigation warning. The results demonstrated that Ambrals kernel-driven model can be used to simulate the reflectance of maize canopy collected by UAV. The simulated reflectance can complement time-series UAV spectral data and be used to establish VIs, among which Structure Intensive Pigment Index (SIPI) was established with the highest accuracy (R = 0.729). The VIs established by simulated reflectance can be used to monitor soil surface moisture content, and the monitoring effect is similar to the measured data (R2 = 0.642, RMSE = 0.42). It can evaluate the soil moisture a few days after irrigation and ensure the continuity and timeliness of soil moisture data, so as to improve the crop irrigation system and carry out irrigation warning. These results have certain reference for the supplementation of time-series spectral data and farmland irrigation using UAV multispectral remote sensing. [ABSTRACT FROM AUTHOR]

With the requirement of a macroscopic approach to understanding the relationship between water resources and hydrological phenomena, such as severe droughts under climate change, this study investigates South Korea's long-term terrestrial water storage (TWS) using GRACE satellite data. A detailed analysis of water balance in TWS, based on the GLDAS model outputs in Google Earth Engine, reveals the following results: (1) TWS anomaly shows an average decrease of −33.5 mm year−1 from 2003 to 2016; (2) spatial shifts in TWS anomaly (−1.176 to −0.424 cm) unveil regional water storage dynamics, indicating negative temporal slope changes per grid cell (−0.393 to −0.225); (3) contributions of precipitation to TWS are not always straightforward, due to runoff inefficiencies affecting water storage and groundwater; (4) accessible water, integrating surface water and groundwater linked only to the shallow layer's soil moisture, constrains deep groundwater accounting, emphasizing the need for local groundwater surveys in further research. [ABSTRACT FROM AUTHOR]

Slope monitoring has become mandatory in opencast mines. Despite various slope monitoring systems, Wireless Sensor Network is faster and more efficient. It is essential to test the sensors before installation in the field to assess their effectiveness and suitability for a particular slope condition. The significant factors affecting the slope's stability are soil moisture and vibration intensity. This study aims to analyze the functions and performance of sensors used in the advanced real-time wireless slope monitoring system. The sensors were validated by comparing the results from the lab experiment with existing methodologies like the Gravimetric method and Geophone method, then installed in a slope model of clay built on a laboratory scale to analyze their performance. The results are drawn and discussed in conclusion. [ABSTRACT FROM AUTHOR]

The use of carbonaceous materials such as biochar has been considered an innovative solution in agriculture, especially to mitigate dry events caused by climate change. Biochar can improve water holding capacity, physical and chemical properties of soil, and increase the productivity of agricultural systems. However, underlying physiological mechanisms remain poorly understood. Mineral supplementation with potassium nitrate (KNO3) via foliar application is another promising strategy in agricultural management under irrigation deficit. Thus, we investigated the combined effects of biochar and foliar application of KNO3 on growth, yield, and physiology of tomato plants under different irrigation regimes. Results did not indicate a synergistic effect of biochar and foliar application of KNO3. Biochar application alleviated tomato plant stress under deficit irrigation, with plants showing better functioning of photosynthetic apparatus, higher yield, and better fruit quality, as well as increased water use efficiency. Coffee husk biochar (K-rich feedstock) fully met the tomato plant's demand for K and partially met the demand for some other elements (P, Mg, Fe, Zn, Mn, and Cu). Although positive effects of KNO3 application was verified for some physiological and fruit quality components, overall, foliar application of KNO3 did not improve tomato yield. It is concluded that biochar soil amendment can be a promising practice to increase yield and quality of tomato fruits under deficit irrigation. Therefore, biochar-based fertilizer can be an alternative K source that also provides stable carbon to soil and helps to mitigate stress caused by prolonged drought. [ABSTRACT FROM AUTHOR]

The restoration of native vegetation like pines helps mitigate soil erosion, but the effects of pine needle litter on runoff, erosion, and hydrology in karst hillslopes are unclear. This study investigated these factors during the rainy season from June to August 2021 under six treatments (flat, gentle, and steep slopes with and without pine needle coverings). The results showed that pine needle litter significantly increased the soil water content, particularly on steeper slopes, by improving the water-holding capacity. It also substantially reduced runoff (by 23.8%) and soil erosion (by 92.5%). The critical rainfall threshold for generating runoff did not occur in the pine needle covering treatment, whereas it was 19.3 ± 8.8 mm in the bare soil treatment under wet conditions. These findings highlight the efficacy of pine needle cover in reducing runoff and erosion in karst areas, promoting it as a sustainable method for restoring degraded soil. [ABSTRACT FROM AUTHOR]

Forestry plantations have been expanded to meet the increasing demand for tree products, impacting evapotranspiration rates and hydrology. We explore how three Eucalyptus spp. respond to environmental resources using productivity and water use efficiency as indicators. Environmental variables, tree transpiration, soil physical properties, soil water content, and plant productivity were monitored. Eucalyptus saligna was the most productive, with higher volume, basal area and average annual increment compared to E. benthamii and E. dunnii. Transpiration of E. saligna (1249 mm year−1) was also higher than that of E. benthamii (928 mm year−1) and E. dunnii (733 mm year−1). The highest water use efficiency was evident for E. dunnii. Soil water rarely limited plant growth. Nevertheless, annual transpiration for E. saligna exceeded annual rainfall. Eucalyptus species with high water use should be avoided in areas of limited water availability, while species with low water use can provide productivity without depleting water resources. [ABSTRACT FROM AUTHOR]

Reliable drought monitoring is a prerequisite for minimizing potential agricultural losses. Soil moisture is a key variable for monitoring agricultural drought assessment. This study conducted in the Bundelkhand region of Uttar Pradesh uses a macroscale variable infiltration capacity (VIC) hydrological model to simulate soil moisture and calculate soil moisture deficit index (SMDI) for agricultural drought assessment for the Rabi crop growing season, 1998–2016. Crop yield was linked with SMDI and other covariates using a random forest machine learning-based regression technique. The results show that the VIC model effectively simulated root zone soil moisture when compared with the reference data. Major droughts were identified in the years 2000–01, 2007–08, and 2015–16 in the study region. The RF-based crop yield prediction accuracy improved when irrigational factors were added. The study provides a noteworthy reference for drought assessment and prevention, water resource management, and ensuring food security. [ABSTRACT FROM AUTHOR]

Glyphosate (Gly) and its formulations are broad-spectrum herbicides globally used for pre- and post-emergent weed control. Glyphosate has been applied to terrestrial and aquatic ecosystems. Critics have claimed that Gly-treated plants have altered mineral nutrition and increased susceptibility to plant pathogens because of Gly ability to chelate divalent metal cations. Still, the complete resistance of Gly indicates that chelation of metal cations does not play a role in herbicidal efficacy or have a substantial impact on mineral nutrition. Due to its extensive and inadequate use, this herbicide has been frequently detected in soil (2 mg kg−1, European Union) and in stream water (328 µg L−1, USA), mostly in surface (7.6 µg L−1, USA) and groundwater (2.5 µg L−1, Denmark). International Agency for Research on Cancer (IARC) already classified Gly as a category 2 A carcinogen in 2016. Therefore, it is necessary to find the best degradation techniques to remediate soil and aquatic environments polluted with Gly. This review elucidates the effects of Gly on humans, soil microbiota, plants, algae, and water. This review develops deeper insight toward the advances in Gly biodegradation using microbial communities. This review provides a thorough understanding of Gly interaction with mineral elements and its limitations by interfering with the plants biochemical and morphological attributes. Glyphosate (Gly) contamination in water, soil, and crops is an eminent threat globally. Various advanced and integrated approaches have been reported to remediate Gly contamination from the water-soil-crop system. This review elucidates the effects of Gly on human health, soil microbial communities, plants, algae, and water. This review develops deeper insight into the advances in Gly biodegradation using microbial communities, particularly soil microbiota. This review provides a brief understanding of Gly interaction with mineral elements and its limitations in interfering with the plants biochemical and morphological attributes. [ABSTRACT FROM AUTHOR]

Climate change scenarios of precipitation and temperature were divided into three time windows of 30 years each from 2011 to 2099. The new version of Soil and Water Assessment Tool (QSWAT v2.6.1) was used to simulate the hydrological response and it was first calibrated and validated using observed data as an input for assessing the hydrological responses. The results showed that the QSWAT calibration and validation reveals a good agreement (R²=0.77) during calibration and validation. Whereas nash and Sutcliffe simulation efficiency (NSE) was found to be 0.76 during calibration and 0.73 during validation. Based on changes of precipitation, maximum and minimum temperature, the monthly flow volume did not show systematic trends i.e. increases non-rainy months and decreases in the wet-months. Thus, the hydrology of Megech River is highly vulnerable to climate change which causes water stress for domestic use and environmental flow. [ABSTRACT FROM AUTHOR]

Drought is a disaster that seriously constrains economic development and endangers human life. This paper explores the potential of Global Navigation Satellite System Reflectometry (GNSS-R) for drought monitoring, using Cyclone Global Navigation Satellite System (CYGNSS) data to monitor drought in Jiangxi and Hunan Provinces, China, in 2022. This study applies the Random Undersampling Boosting (RUSBoost) algorithm to detect waterbodies and linear regression to retrieve soil moisture (SM). Result shows that drought in September was heaviest, with the area of Poyang Lake in Jiangxi and Dongting Lake in Hunan decreasing by 70.2% and 76.9%, respectively, compared to that in June. The variation in retrieved SM shows that the Poyang Lake Plain and Jitai Basin in Jiangxi and the Dongting Lake, Yuanjiang River, and Xiangjiang River basins in Hunan suffered from the most serious drought. The variation in retrievals shows high consistency with various reference datasets, including Soil Moisture Active Passive (SMAP) SM data and vegetation condition index (VCI). The correlation coefficient between retrieved SM and VCI is 0.93 in Jiangxi and 0.94 in Hunan. [ABSTRACT FROM AUTHOR]

Despite the unique hydrological properties exhibited by frozen soil, its characteristics are often oversimplified in most distributed hydrological models, resulting in major errors in material cycle predictions in cold climate regions. This study aims to modify the Soil and Water Assessment Tool (SWAT), a semi-distributed hydrological model that originally assumes no water movement in frozen soil layers, by incorporating the dynamic change of soil permeability based on the degree of soil freezing, and to understand the effect of water movement in frozen soil on watershed hydrology. SWAT with frozen soil permeability (SWAT-FSP) was developed by adding two modules to the original SWAT: a heat conduction equation that considers the phase change of ice and liquid water and a frozen-soil percolation model that considers dynamic decrease in soil permeability due to soil freezing. The original SWAT and SWAT-FSP were set up in the Tokoro River watershed in northern Japan. The river flow and soil water dynamics during the snowmelt period (March–May) simulated using the original SWAT and SWAT-FSP were compared. The modified model significantly alters the soil water dynamics simulation to generate earlier soil water drainage and reduces the soil water content during the snowmelt period in years featuring weak soil freezing. Consequently, the SWAT-FSP estimated an earlier increase in river flow at the beginning of the snowmelt period and a smaller river flow in the middle of the snowmelt period as compared with the original SWAT. The modified model improved the overall performance in river flow simulation for the snowmelt period (March–May) of 2012–2019. The Nash-Sutcliffe efficiency obtained during the calibration period by the original SWAT was 0.602, and during the validation period it was 0.367. For the SWAT-FSP, it was 0.659 during calibration, and 0.639 during validation. Meanwhile, the SWAT-FSP showed unsatisfactory performance in 2014 and 2015, with underestimated snow water equivalent, indicating that improvements in the snowmelt/accumulation module may further enhance its accuracy. Our results showed that the dynamic change of soil permeability governed by the degree of soil freezing is an important factor affecting the water cycle of cold climate watersheds with seasonally frozen soil. [ABSTRACT FROM AUTHOR]

In this paper, we will conclude the results of Bufeng-1 (BF-1) A/B data processing, calibration workflow, and validation of the calibrated sea surface winds, land surface soil moisture, and sea surface height measurements. Since 2019, the BF-1 mission has operated in-orbit for over 4 years. The Earth reflected delay Doppler maps (DDMs) are continuously collected to perform global sea surface and land observations. At the same time, the intermediate frequency (IF) raw data are also obtained for 12 seconds every pass in diagnostic mode. To begin with, a brief description of the spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) technique will be provided in the introduction. Next, we will present the overview of Chinese BF-1 mission and the data specifications used in our research. In the next section, the BF-1 mission-related spaceborne power calibration and validation are presented to show the support to power DDM observable production for sea surface and land surface applications. Then, the status of Chinese Beidou System (BDS) Equivalent Isotropic Radiated Power (EIRP) acquisition programme is then introduced. Furthermore, the latest sea surface height (SSH) measurements results including two modes (group delay and carrier phase) and wind speed derivation based on machine learning (ML) method will be spatial-temporal aligned and validated with auxiliary datasets including Denmark Technology University (DTU) mean sea surface (MSS) products and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 reanalysis. The previous published results of sea surface winds retrieval under Hurricane conditions and soil moisture retrieval are also reviewed for the BF-1 mission applications. Finally, the conclusion of BF-1 derived results will be discussed to draw out ongoing/future works. [ABSTRACT FROM AUTHOR]

The two vegetation transfer parameters of $\tau $ τ (Vegetation Optical Depth,VOD) and $\omega $ ω (Omega) could vary significantly across microwave channels in terms of frequencies, polarizations, and incidence angles, and their channel-dependent characteristics have not yet been fully investigated. In this study, we investigate the channel dependence of vegetation effects on microwave emissions from soils using a higher-order vegetation radiative transfer model of Tor Vergata. Corn was selected as the subject of investigation, and a corn growth model was developed utilizing field data collected from the multifrequency and multi-angular ground-based microwave radiation experiment from the Soil Moisture Experiment in the Luan River (SMELR). Upon compilation of the simulation dataset of microwave emissions of the corn field, the effective scattering albedo across different channels were calculated using the Tor Vergata model. Results show that vertical polarization of the vegetation optical depth is more affected by incidence angle changes, while horizontal polarization exhibits lower variations in vegetation optical depth due to incidence angle adjustments. The channel dependence of vegetation optical depth can be described as the polarization dependence parameter (${C_P}$ C P ) and the frequency dependence parameter (${C_f}$ C f ). These two parameters enable the calculation of vegetation optical depth at any channel under three adjacent frequencies (L-band, C-band and X-band). The effective scattering albedo of vegetation does not vary significantly with vegetation height or angle. It primarily depends on frequency and polarization, showing an overall increasing trend with increasing frequency. The effective scattering albedo with vertical polarization is slightly higher than that with horizontal polarization at higher frequencies, while both are lower in the L-band. This investigation is helpful for understanding the vegetation effects on microwave emissions from soils, ultimately advancing the accuracy of large-scale soil moisture retrieval in vegetated areas. [ABSTRACT FROM AUTHOR]

Calibration and regionalization are two key tasks in hydrological modelling, and the availability of increased data and computing resources has enhanced our ability to complete these tasks. This paper addresses both tasks, i.e. (i) it proposes novel model structure-based calibration strategies with the goal to improve estimation of high streamflows, and (ii) it explores the association of soil hydraulic properties with optimal parameters to estimate streamflows in ungauged catchments. Both tasks are demonstrated by employing a conceptual hydrological model, Sacramento Soil Moisture Accounting (SAC-SMA), on multiple catchments in the Narmada River Basin. The initial calibrated model exhibited good model performance, with high flows being underestimated. Seven calibration strategies via revising parameter space are explored, and improvement in high flow performance is observed at nine out of 12 catchments. Estimated streamflows based on soil hydraulic parameters demonstrate regionalization potential. The results indicate successful application of the proposed methods which are transferable to other basins. [ABSTRACT FROM AUTHOR]

This study comparatively evaluates the skill of the (un)coupled Weather Research and Forecasting (WRF) – WRF-Hydro system supported with satellite-based soil moisture initiation in long-term simulations of hydrometeorological variables under humid and semi-arid climate conditions. Prior to the coupling, the WRF-Hydro model is calibrated using streamflow data at different data scales (i.e. hourly and daily) to discuss the influences of the changing temporal resolution of the reference dataset on the optimum parameter values. According to the results, fully coupled models correct the location and magnitude of the occurrence of hourly extreme precipitation. Changing the initial soil moisture data source affects the terrestrial water cycle elements in the semi-arid region (i.e. Mediterranean (MED)) more than in the humid area (i.e. Eastern Black Sea (EBS)), especially in spring and summer. The initiation of the coupled model with satellite-based soil moisture improves the streamflow outputs after a reasonable spin-up period for the MED region. [ABSTRACT FROM AUTHOR]

The agriculture sector has been acknowledged as the backbone of the economy of many countries. Specifically, phytoremediation can help to increase the GDP of a country by decontaminating the soil that is unavailable for cultivation. Very few research advancements have been reported on soil moisture transport, drying, and biomass valorization. Hence, the present paper highlights the importance of soil moisture transport by highlighting its impact on heavy metal sequestration along with the valorization of biomass. The objective of the present work is to provide a critical overview of the literature about moisture transport, and heavy metals (HMs) leaching in contaminated soils which is unsuitable for agricultural purposes, and simulating its responses using various available artificial intelligence techniques. Furthermore, insights have been made on various approaches to decontaminate soil that can be used for the cultivation of various crops along with other agricultural practices and thereby it can contribute to food safety and security as well as mitigating the global food crisis from waste to wealth conversion. Valorization of biomass in the field of phytoremediation of contaminated soils. Role of drying in the field of phytoremediation, biomass management, and food safety. Benefits, and limitations of AI focusing on ML and DL simulation in phytoremediation. Scope and application of AI based simulation model in phytoremediation and agriculture. Graphical representation to depict the role of drying and AI based simulation in phytoremediation [ABSTRACT FROM AUTHOR]

In this paper, the current field modulation is described using a solution of the wave action equation. Using an integrated equation model (IEM), a current field modulated scattering model is established. The sea surface backscattering coefficient decreases with increasing current speed. At high wind speeds, the change of backscattering coefficient under 1 m $ \cdot $ ⋅ s−1 current field modulation is about 1 dB. An increase of 60° in the angle between wind and current direction leads to a decrease of 1.5 dB in the modulation coefficient. Finally, the model is verified using satellite data. [ABSTRACT FROM AUTHOR]

Excessive soil moisture (ESM) is a critical factor limiting the productivity of buckwheat (Fagopyrum esculentum Moench) because ESM inhibits its germination. This study investigated the effects of pericarp and seed respiration on reduced buckwheat germination caused by submergence. Seeds were submerged prior to germination testing under aerobic conditions. The effects of days of submergence treatment and pericarp removal on germination percentage were significant. The germination percentage in the 3-day submergence treatment was low in seeds with pericarp (P+) but was significantly improved in seeds without pericarp (P−). Pericarp removal also improved the germination percentage of non-submerged seeds. Pericarp thickness and pericarp/seed dry weight ratio (PWR) were not significantly correlated with the germination percentage in 3-day submerged P+. However, both were significantly negatively correlated with the germination percentage in 1-day submerged P+. Seed respiration rate in water, measured on seeds not submerged before measurement, was significantly higher in P− than in P+; that of P− increased with time, while that of P+ showed a decreasing trend with time beyond the first 24 h. Seed respiration rate during the first 24 h was significantly negatively correlated with germination percentage in 3-day submerged P+. A negative influence of pericarp thickness and PWR on the seed respiration rate of P+ during the first 24 h was suggested. Suppressed seed respiration by the pericarp is probably a cause of inhibited buckwheat germination under ESM conditions. [ABSTRACT FROM AUTHOR]

The selection of the sowing date is one of the most important decisions in soybean production. It is important for farmers to know the expected seed yield when developing a sowing plan. The objective of this study was to quantitatively reveal the decreased seed yield ratio during late sowing in southwestern Japan under irrigated conditions. Total above ground dry matter and distribution were measured from July to August sowing in 2018 and 2019 in Fukuyama, Hiroshima, Japan. The harvest index in the August sowing did not decrease compared to the July sowing under irrigated conditions. The decrease in yield was related to the total aboveground dry matter rather than to the harvest index. The decrease in total aboveground dry matter was related to the total amount of solar radiation intercepted rather than to radiation use efficiency. A significant regression equation was obtained for the relative yield, which was calculated from the maximum seed yield observed from early to mid-July. When seeds were sown after mid-July, our result showed that the seed yield will decrease by 0.60% per day for Sachiyutaka A1 and by 0.64% for Akimaro, even under conditions of 100% seedling establishment and controlled soil water conditions. This regression equation can be used in fields as an indicator of seed yield where irrigation is possible. [ABSTRACT FROM AUTHOR]

To explore field microclimate changes under maize/ginger intercropping and select a reasonable field configuration, this study used the major ginger variety 'Zhugen' from Southwest China as the experimental material. Two maize plant types; tall (Zhenghong 311) and short (Zhenghong 6), with 2, 3, and 4 m row spacings, shading treatment (ST), and a control (pure) without shading (CK) were used for the study. The effects of the maize plant type and row spacing on soil temperature, humidity, canopy temperature, light transmittance, plant growth, and intercropped ginger yield were investigated. Soil moisture, ginger canopy humidity, and shading rate in the maize/ginger intercropping mode were significantly higher than those in the non-shading treatment. Conversely, the soil and ginger canopy temperatures of the maize/ginger intercropping mode were significantly lower than those of the non-shading treatment. As a result, plant height, stem diameter, branch number, and ginger yield were significantly higher under the intercropping mode than the non-shading treatment. Although maize/ginger intercropping improves ginger growth and yield, these parameters are dependent on maize plant type and row spacing. The ginger yield was significantly higher when intercropped with the tall maize ZH 311 than with short maize ZH 6. The yield improved with decreasing row spacing and was the highest at a row spacing of 2 m. At the aforementioned field configurations, the soil and canopy humidity were the highest whereas the soil and canopy temperatures were the lowest, thereby giving best results on parameters like plant height, stem diameter, branch number, and yield. [ABSTRACT FROM AUTHOR]

There is an increasing need for accessible methods to monitor soil health. Our primary objective was to evaluate an accessible, do-it-yourself method for measuring the maximum water holding capacity – we call this the funnel, filter paper, and drainage (MWHCFFPD) method. First, we compared MWHCFFPD to the water desorption method via pressure cells (WHCPC), routinely used for generating soil water retention curves, using 10 soils from a wide range of textures (4–55% clay). Second, we tested the sensitivity of the MWHCFFPD to methodological variations likely encountered by citizen scientists. The two methods were quite comparable in precision, with mean coefficient of variances of 3.5% and 4.4% for the FFPD and water desorption method, respectively. The MWHCFFPD and WHCPC methods were comparable, with MWHCFFPD best correlating to WHCPC at −2.45 kPa (R2 = 0.98). The MWHCFFPD method is somewhat sensitive to some methodological modifications, most notably variation in water source, but with standardized protocols could be scientifically robust. Overall, MWHCFFPD can be used as a simple and affordable test of sieved soil structure and organic matter, and thus has potential to expand soil health monitoring. [ABSTRACT FROM AUTHOR]

In Ethiopia, watershed management interventions have been implemented since the 1980s to curb land degradation and improve soil moisture potential. Thus, this study was aimed at evaluating the impacts of watershed management interventions on the soil moisture potential, soil texture, and bulk density of the study area. A quasi-experimental research design was employed for this analysis. A total of 99 soil samples were collected for soil moisture, soil texture, and soil bulk density laboratory analysis at a depth of 0–20 cm. Moreover, a one-way ANOVA was used to evaluate the mean variances of soil moisture, soil texture, and bulk density attributes among each treatment group in the study area. Univariate analysis was also applied to evaluate the overall effects by following the General Linear Model (GLM). The results of the study showed that a statistically significant difference (P≤ 0.05) was observed in soil moisture status between the treated (physical and bio-physical) and untreated (controlled) farmlands in each cycle of soil moisture status. At each time of observation, bio-physical types of watershed management interventions had a high moisture status (43.6%), followed by physical types (38.63%) of watershed management interventions, while low amounts of soil moisture (30.16%) were observed in untreated (control) parts of the watershed. The correlation between soil texture and soil moisture content indicates that soil with a high moisture content has a fine soil texture. Whereas soil with a low moisture content has a coarser texture. Both soil moisture and soil bulk density were also significantly affected due to watershed management interventions in the study area (P ≤ 0.05). Therefore, the findings revealed that watershed management increased soil moisture potential and decreased the soil bulk density of the watershed. There is also a strong negative correlation between soil moisture and soil bulk density [r = −0.81, n = 27, p<0.005]. [ABSTRACT FROM AUTHOR]

Retrieving surface soil moisture on a local scale using Synthetic Aperture Radar (SAR) data and Deep Learning (DL) models necessitates a substantial volume of data, which may not be available in all scenarios. In this study, the application of transfer learning was introduced as a novel approach to address the scarcity of training samples for DL models in the context of soil moisture retrieval. The proposed DL model was initially trained using International Soil Moisture Network (ISMN) data, followed by a fine-tuned process on a local scale using field trip data from an agricultural area in Karaj, Iran. The proposed DL model was compared against Random Forest Regressor (RFR), Support Vector Regression (SVR), and Multi-Layer Perceptron (MLP) based on Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R2 indicators. All models underwent hyperparameter-tunning, and their performance was evaluated using 8-fold cross-validation (CV) and various combinations of inputs. The proposed DL model outperformed other models on a local scale achieving an RMSE, MAE, and R2 of 2.42 vol%, 1.66 vol%, and 0.90, respectively. The MLP model also exhibited good performance with an RMSE, MAE, and R2 of 2.84 vol%, 2.04 vol%, and 0.88 compared to the RFR with 2.83 vol%, 2.20 vol%, and 0.86, respectively. Additionally, the SVR yielded an RMSE, MAE, and R2 of 3.71 vol%, 3.05 vol%, and 0.78. However, the RMSE, MAE, and R2 of the MLP and the proposed DL model without using transfer learning deteriorated by around 18%, 32%, and 34%, respectively. [ABSTRACT FROM AUTHOR]

The present investigation reports the development and characterization of a clay-polymer composite loaded with urea and Trichoderma harzianum (UTCPC) to enhance soil moisture and nitrogen availability and manage wilt-nematode complex in lentil grown in residual moisture after rainfed rice. The Fourier transform infrared (FT-IR) spectroscopy and scanning electron microscopy (SEM) characterization proved successful synthesis of UTCPC. The bentonite clay (8% w w−1) and Th concentration (10% w w−1) were optimized based on the maximum spore count of the UTCPC and viability of the Th spores at one month of storage at room temperature. The incubation and pot culture experiments were laid out in a completely randomized design (CRD) with six N levels replicated thrice in combinations with UTCPC. Under incubation experiment, the treatment of 100% N through farmyard manure (FYM) along with UTCPC application (T3) resulted in the highest soil moisture (18.5%) and lowest nitrate (NO3-N) content (42%) at 6 and 10 days after incubation, respectively, suggesting its sustained moisture-retaining and slow nitrate (NO3-N) release properties of the UTCPC. Under pot experiment, the treatment T3 expressed the highest soil moisture (28.8%) and NO3-N (17.6 kg ha−1) content even at 60 days after sowing. The disease severity index of all the treatments comprising UTCPC with or without nutrient application was significantly lower than the untreated soil. The lowest population of Fusarium spp. (13.8%) and Meloidogyne spp. (8%) were observed in T3. Therefore, UTCPC can be considered as an eco-friendly agri-input in enhancing moisture retention and sustaining nutrient release to the soil as well as providing biocontrol agents to manage Fusarium-Meloidogyne complex in lentil. [ABSTRACT FROM AUTHOR]

Porosity is a significant property of soil, yet an elusive parameter to retrieve from remote sensing data. Here, an empirical relationship between soil water contents and infrared emissivity is employed for porosity mapping. The assumption is that by deriving the soil water content at saturation point, soil porosity could be indirectly measured. Through time series analysis of daytime ASTER thermal data acquired during the wet seasons, a porosity map was generated over a test site in the Qom area (Iran) and qualitatively verified using field observations. The approach was shown to yield reasonable results over exposed soil and lithologic outcrops. This approach can potentially provide an effective tool for topsoil porosity mapping at local to regional scales. [ABSTRACT FROM AUTHOR]

Relationships between soil water saturation (SWS) and the accumulation of arsenic (As), cadmium (Cd), and lead (Pb) in soils and aboveground biomass of Populus tremula and Salix caprea were explored. SWS was computed with the hydrological model ParFlow/CLM and compared to data from field observations. Plant and soil samples collected at the main pollution sources contained the highest concentrations of As, Cd, and Pb. S. caprea contained higher concentrations of As, Cd, and Pb than P. tremula. In both species, metal(loid) concentrations in leaves were significantly higher than in branches. At strongly mining-affected locations, metalloid concentration in the trees largely reflected the pollution levels in the soil. In remote study locations, the soil–plant transfer of Cd and Pb was affected by water saturation: element accumulation increased significantly with soil moisture. Results demonstrate that coupling field observations with hydrological modelling is a promising approach for estimating element accumulation. [ABSTRACT FROM AUTHOR]

Management practices and soil environmental variables influence microbiological properties and may cause inaccuracies in the interpretation of the results of these bioindicators. This study evaluated the sensitivity of seven microbiological properties to soil management and environmental variables of a Rhodic Ferralsol from a subtropical region of Brazil. The experimental area was cultivated with crotalaria and corn, followed by a fallow period. Samples were collected monthly for a year to determine soil enzyme activities and heterotrophic bacteria and fungi counts. Soil respiration was evaluated directly in the field. Total hydrolytic activity, cellulases, proteases, dehydrogenases and soil respiration were sensitive to management. Moreover, soil respiration was sensitive to fluctuations in soil temperature (r = 0.75) and pre-sampling precipitation (r = 0.54). Dehydrogenase activity was sensitive to soil moisture (r = 0.72) and total microorganisms (r = 0.61). The bacterial (5.69 ± 0.37 log10 CFU g soil−1) and fungal (3.99 ± 0.42 log10 CFU g soil−1) counts showed low sensitivity to soil management and environmental variables. The seven microbiological properties evaluated responded differently to the management and environmental variables. This information must be considered when using soil quality bioindicators to avoid errors in interpreting results. [ABSTRACT FROM AUTHOR]

This article investigated the possibility of remotely sensing the soil moisture profile in thawed soil from multi-angular dual-polarized brightness temperature (TB) observations at P-band frequencies of 750 MHz and 409 MHz using a modified Burke model. Moreover, it was found that an excellent agreement (coefficient of determination R2 = 0.999 and root-mean-square error (RMSE) no more than RMSE = 0.6 K) could be achieved between the Njoku coherent brightness temperature model and the modified Burke model by introducing a reflectivity from the air-soil interface that takes into account the phases of the multiple re-reflected waves in the underlying layers. Based on the modified Burke model, the depths from which apparent moisture and temperature could be retrieved in a dielectrically-inhomogeneous, non-isothermal soil were investigated, being approximately ten times less than the depth for which apparent soil temperature could be retrieved. In general, the thickness of the emitting layer depends on the TB look angle and polarization, along with the moisture and temperature profiles of the soil. It was also shown that due to the effect of the Brewster angle, the H-polarization of TB was twice as sensitive (4 K/1%) to changes in volumetric soil moisture than V-polarization (1.9 K/1%). Based on multi-angular (10°-50°) observations of TB at H- and V-polarizations, a method of moisture profile retrieval in the top 5–15 cm soil (depending on surface moisture) was proposed using an exponential fitting function, the parameters of which are found in the course of solving the inverse problem. A decrease in the sensing frequency from 750 MHz to 409 MHz makes it possible to increase the accuracy of soil moisture profiles retrieval by a factor of two, being from RMSE = 1.6% (R2 = 0.946) to RMSE = 0.85% (R2 = 0.982) in the top 15 cm layer of soil. The conducted investigation shows the promise of using P-band observations of TB for soil moisture profile retrieval. [ABSTRACT FROM AUTHOR]

A field experiment was conducted to investigate the optimum lateral spacing and irrigation frequency of a subsurface drip irrigation system for broccoli crop grown in the semi-arid region of Haryana (India). The effects on soil water dynamics, growth parameters (i.e. plant height, leaf length, no. of leaves/plant, curd weight and curd diameter), irrigation water use efficiency (IWUE), fertilize use efficiency (FUE) and yield response of broccoli were assessed under two lateral spacings (45 cm and 60 cm) and four irrigation frequencies (daily, and after one, two & three days) in the years of 2019–20 and 2020–21. The results show that soil moisture content was higher near the dripper, and it decreased with increasing radial distance from the drippers. Further, the moisture content was high at 45 cm lateral spacing as compared to 60 cm lateral spacing. The effects of selected treatments on growth and yield parameters were found significant and maximum broccoli yield (147. 41 q ha−1) was found at 45 cm lateral spacing with alternate days of irrigation. The highest IWUE and FUE of 9.93 kg/m3 and 30.68 kg/kg, respectively, were also found at alternate days irrigation with 45 cm lateral spacing. It may be concluded from the present study that alternate days irrigation with 45 cm lateral spacing is the best choice to obtain the maximum yield of broccoli grown in winter season in the semi-arid region of India. [ABSTRACT FROM AUTHOR]

Uncertainty exists as to the role of placement conditions of filtered tailings on water retention behaviour. In this study, we measured 12 drying and 12 wetting soil water characteristic curves on two filtered tailings with various initial gravimetric water contents and dry densities. Filtered tailings at ≥90% standard Proctor maximum dry density maintained higher degrees of saturation under suctions between 15 and 600 kPa, when compared to loosely placed (80% compaction) filtered tailings. Similarly, filtered tailings compacted wet of optimum maintained higher saturations under suctions between 15 and 600 kPa compared with filtered tailings compacted at optimum water content. [ABSTRACT FROM AUTHOR]