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This study assessed the performance of different remotely sensed soil moisture products with in situ observations; six profile probes for the water content monitoring were selected, operating during 2016–2021 from the Voineşti Experimental Basin in the Romanian Subcarpathian region. The reliability of satellite observations has been analyzed on both single ground-based observation points and spatialized information, considering near-surface and root-zone soil moisture data. The physics-based index (HCI) and some statistical tests widely used in inter-comparison analyses have been computed. The study of HCI highlighted that the SMAP SP_L4_SM products have shown the best performances considering the near-surface and root-zone data evaluations. The comparison of SWI1km observations with in situ data produced good results for single-point and spatialized soil moisture estimations acquired at different depths over the experimental basin. The SSM1km and SMAP L2_SM_SP products exhibited the lowest performances. The results contribute to the validation of satellite products of surface and root-zone soil moisture in the Subcarpathian region, helping to provide information in an area not monitored by the International Soil Moisture Network. The findings offer valuable insights into evaluating the performance of satellite soil moisture products in the Romanian region. [ABSTRACT FROM AUTHOR]

The simplicity of the so-called triangle method allows estimates of evapotranspiration and soil water content to be made without ancillary data external to the image and with just a few simple algebraic calculations. Drawing on many examples in the literature showing that the pixel distribution in temperature/fractional vegetation cover (NDVI) space closely resembles a right triangle, this paper shows that adoption of a right triangle shape further simplifies the triangle model. Moreover, it allows one to mostly avoid the problem of sparse or low-resolution data. A time dimension can be included showing that trajectories inside the triangle can provide additional information on root zone soil water content. After discussing some of the ambiguities in the triangle method, and the advantageous properties of the right triangle, a proposal is made to illuminate the relationship between thermal/optical measurements and root zone water content within the right triangle framework. [ABSTRACT FROM AUTHOR]

The composition of clay minerals in soils, and more particularly the presence of montmorillonite (as part of the smectite family), is a key factor in soil swell–shrinking as well as off–road vehicle mobility. Detecting these topsoil clay minerals and quantifying the montmorillonite abundance are a challenge since they are usually intimately mixed with other minerals, soil organic carbon and soil moisture content. Imaging spectroscopy coupled with unmixing methods can address these issues, but the quality of the estimation degrades the coarser the spatial resolution is due to pixel heterogeneity. With the advent of UAV-borne and proximal hyperspectral acquisitions, it is now possible to acquire images at a centimeter scale. Thus, the objective of this paper is to evaluate the accuracy and limitations of unmixing methods to retrieve montmorillonite abundance from very-high-resolution hyperspectral images (1.5 cm) acquired from a camera installed on top of a bucket truck over three different agricultural fields, in Loiret department, France. Two automatic endmember detection methods based on the assumption that materials are linearly mixed, namely the Simplex Identification via Split Augmented Lagrangian (SISAL) and the Minimum Volume Constrained Non-negative Matrix Factorization (MVC-NMF), were tested prior to unmixing. Then, two linear unmixing methods, the fully constrained least square method (FCLS) and the multiple endmember spectral mixture analysis (MESMA), and two nonlinear unmixing ones, the generalized bilinear method (GBM) and the multi-linear model (MLM), were performed on the images. In addition, several spectral preprocessings coupled with these unmixing methods were applied in order to improve the performances. Results showed that our selected automatic endmember detection methods were not suitable in this context. However, unmixing methods with endmembers taken from available spectral libraries performed successfully. The nonlinear method, MLM, without prior spectral preprocessing or with the application of the first Savitzky–Golay derivative, gave the best accuracies for montmorillonite abundance estimation using the USGS library (RMSE between 2.2–13.3% and 1.4–19.7%). Furthermore, a significant impact on the abundance estimations at this scale was in majority due to (i) the high variability of the soil composition, (ii) the soil roughness inducing large variations of the illumination conditions and multiple surface scatterings and (iii) multiple volume scatterings coming from the intimate mixture. Finally, these results offer a new opportunity for mapping expansive soils from imaging spectroscopy at very high spatial resolution. [ABSTRACT FROM AUTHOR]

Accurate estimation of soil moisture content (SMC) in the field is a critical aspect of precise irrigation management. The development of unmanned aerial vehicle (UAV) platforms has provided an economically efficient means for field-scale SMC measurements. However, previous studies have mostly focused on single-sensor estimates of SMC. Additionally, the lack of differentiation between various crops and their growth stages has resulted in an unclear understanding of how crop types and growth stages affect the accuracy of SMC estimation at different soil depths. Therefore, the purpose of this paper was to use UAV multimodal remote sensing and a machine learning algorithm to estimate the SMC in agricultural fields and investigate estimation's effectiveness under different scenarios. The results indicated the following: (1) The multispectral remote sensing method provided higher accuracy in SMC estimation compared to thermal infrared remote sensing. Moreover, the integration of multimodal data improved the accuracy of SMC estimation, enhancing the coefficient of determination (R2) by approximately 14% over that achieved through the use of multispectral data alone and 39% over that of thermal infrared data alone. (2) Across the entire growth period, the optimal soil depths of SMC estimation for soybean were 10 cm and 20 cm (average R2 were 0.81 and 0.82, respectively), while for corn, they were 10 cm, 20 cm, and 40 cm (average R2 were 0.59, 0.60, and 0.55, respectively). (3) The SMC estimation model performed better for both crops during the first three growth stages, with accuracy declining in the maturity stage. These results demonstrate that this approach can provide relatively accurate root zone SMC estimates for different crops throughout their main growth periods. Thus, it can be employed for SMC monitoring and precision irrigation system design. [ABSTRACT FROM AUTHOR]

Compound extreme events pose more grave threats to human health, the natural environment, and socioeconomic systems than do individual extreme events. However, the drivers and spatiotemporal change characteristics of compound extreme events under climate transition remain poorly understood, especially in the arid region of Northwest China. This study examined the spatiotemporal change characteristics and driving mechanisms of extreme temperature and precipitation compound events in Northwest China based on data from 86 national meteorological stations and 11 climate models of the Coupled Model Intercomparison Project, Phase 6. The results indicated that (1) the frequency values of heat extremity–dry (1.60/10a) and heat extremity–heavy precipitation (0.60/10a) events increased from 1961 to 2020, and showed a faster uptrend after 1990 than before. (2) Under four shared socioeconomic pathway scenarios, there is also the likelihood of an upward trend in heat extremity–dry and heat extremity–heavy precipitation events in Northwest China by the end of 21 century, especially under SSP585, with probability values of 1.70/10a and 1.00/10a, respectively. (3) A soil moisture deficit leads to decreased evaporation and increased sensible heat by reduction in the soil–atmosphere exchange; the non-adiabatic heating process leads to a higher frequency of hot days. This land–air interaction feedback mechanism is a significant driver of heat extremity–dry events in Northwest China. (4) In the Northwest China region, the warmer trend surpasses the wetter trend, contributing to increased specific humidity, and the vapor pressure deficit may lead to an increasing frequency of extreme precipitation, consequently increasing heat extremity–heavy precipitation events. These results provide new insights for the understanding of compound extreme events, in order to cope with their risks. [ABSTRACT FROM AUTHOR]

With the development of material science and increasing awareness of ecological environmental protection, liquid biodegradable mulch films (LBDMs) have garnered significant public interest. In this research, new LBDMs were developed using hydrophobically modified polymer materials, surfactants, and photosensitive catalysts. Characterization by scanning electron microscopy (SEM) revealed good material compatibility. LBDMs exhibited excellent wettability and degradability, effectively covering soil surfaces and enhancing soil moisture conservation, with a degradation rate of 76.09% after 80 days of burial. The field performance experiment was conducted over two consecutive years, 2021 and 2022, to assess differences in soil temperature and moisture, peanut agronomic traits, pod traits, and yield under four treatments: non-mulching (CK), LBDMs, clear polyethylene mulch films (CPEMs), and black polyethylene mulch films (BPEMs). LBDMs increased soil temperature by 0.56 °C and soil moisture by 19.25%, accelerated the seedling stage by 4-to-6 days, and improved the average emergence rate by 15.91%. Furthermore, LBDMs significantly promoted peanut growth, and it increased yield by 14.34% compared to CK. LBDMs performed comparably to the two types of PE films in maintaining soil conditions and different crop phenotype traits, including plant height, branch number, yield, and quality, and they even outperformed PE films in productivity per plant and 100-kernel weight. These findings suggest that LBDMs are a promising eco-friendly alternative to traditional PE films. [ABSTRACT FROM AUTHOR]

The information of the temporal and spatial distribution of irrigation events is of great significance for protecting the cultivated land quality and coping with climate change. Irrigation information can traditionally be captured using farmland water conservancy construction and field investigation. However, there is a great variation in the time and space of irrigation information from the different regions, due to the various water sources, planting structures, irrigation technology, water transmission, and measurement facilities. At the same time, remote sensing can be expected to timely and accurately monitor the ground surface all day. The previous research focused mainly on the crop growing season without considering the influence of different vegetation coverage on the irrigation remote sensing signals. Therefore, it is very necessary to detect the year-round events of farmland irrigation using remote sensing, particularly for different vegetation coverage. In this study, the farmland irrigation events were detected in the arid areas of northwest China using remote sensing. The research area was taken as Daman Super Station in Ganzhou District, Zhangye City, Gansu Province, China. The comparison was also performed on the conventional, near-infrared band reflectivity with MOD09GA optical remote sensing data, segmented PDI differential threshold model, microwave moisture products, and the combination of PDI differential threshold and microwave moisture products. An optimal scheme was achieved in the remote sensing detection suitable for all-year farmland irrigation events with different vegetation coverage. The performance was finally tested from the space-time dimension. The results show that there was a strong negative linear correlation between the PDI difference threshold and NDVI. Thus, a segmented PDI difference threshold model was constructed in 2016; The highest accuracy of irrigation events was achieved in the microwave moisture products combined with the PDI differential threshold. There was a close relationship between the soil surface water after irrigation and the response of vegetation to the soil water supply. The content of soil water reached saturation after irrigation. But the soil surface water continued to decrease and then returned to the pre-irrigation water content in about three days, due mainly to the evaporation. Furthermore, the microwave data was more sensitive to the surface soil moisture than the vegetation, indicating the dominant soil dielectrics. The high time resolution was realized to timely and effectively capture the occurrence of irrigation events. However, the electromagnetic wave energy was attenuated by crops with the increase in crop coverage. The water status of the soil surface failed to be monitored. Therefore, it was suitable for the case of no crops or low vegetation coverage. Moreover, the time resolution was low in the optical data. The content of soil surface water was captured in time, but it was also sensitive to the vegetation. Plant growth was subjected to water stress before irrigation. Once the soil water supply was sufficient, a significant difference was found in the vegetation water content and leaf structure, indicating the vegetation spectral in the near-infrared and red bands before irrigation. Optical data was used to indirectly monitor the irrigation events using these spectral. In particular, microwave water products were compensated for the irrigation monitoring the vigorous growth of crops or high coverage. The best performance was achieved in dry years, followed by normal years. The regional inversion showed that the distribution map of irrigation times made by microwave moisture products combined with the PDI differential threshold was consistent with the actual situation. The farmland with low irrigation capacity was distributed mainly on the edge of Zhangye Basin, which was far from the river, indicating the greater risk of climate change. Therefore, it was suitable to use microwave moisture products combined with PDI differential threshold in the detection and application of irrigation events in arid areas of northwest China. The findings can provide a theoretical basis for the efficient acquisition of actual irrigation information, cultivated land quality protection, and response to climate change. [ABSTRACT FROM AUTHOR]

Illegal cultivation and reclamation activities are expressly prohibited in the area of reclamation of steep slopes. Large areas of sloping farmland have posed a high risk of soil erosion to reduce land productivity, even seriously threatening food security. However, manual ground surveys have been confined to investigating the illegal cultivation on the steep slopes and the prohibition of reclamation, due mainly to time-consuming and laborious. Meanwhile, the steep slopes are often distributed in dangerous areas, such as mountains and hills, leading to delays in the manual supervision of regional soil and water conservation. Fortunately, remote sensing interpretation and detection can be applied to monitor soil and water conservation in steep slopes, particularly with the rapid development of remote sensing and unmanned aerial vehicle (UAV) technology in recent years. Deep learning has been used to extract sloping farmland in the field of cultivated land identification. However, it is still lacking to consider the terrain slope, which has a great impact on soil erosion. At the same time, the large-scale remote sensing images often contain both concentrated contiguous fields and scattered small and micro fields; There are quite different directions and shapes of the fields, due to the differences in topography and landform, leading to the missed, false detection and low confidence in the detection of convolutional neural networks. The low detection efficiency and high time cost can also be caused by manual visual inspection in the supervision of illegal cultivation areas. In this study, a new model was designed to detect the remote sensing images from the illegal cultivation areas on steep slopes using the improved YOLOv9. The datasets were used from the GF-1 satellite and ALOS PALSAR. Firstly, 12.5 m resolution DEM was calculated to extract the potential slope farmland areas using ALOS data. Then the GF-1 satellite remote sensing images in the potential slope farmland area were utilized as experimental data. The specific procedures and main contribution were as follows :1) The lightweight self-attention mechanism (SimAM) was introduced into the backbone network of YOLOv9 for the richer background and the better discrimination of features; 2) The ultra-lightweight upsampling operator (DySample) was selected to replace the kernel-based dynamic one, in order to reduce the number of network parameters for the high recognition speed and accuracy; 3) The recognition accuracy of YOLO was verified for the illegal tillage areas after the introduction of SimAM and DySample; Finally, the comparison was made on the Faster RCNN, YOLOv5, YOLOv7, and Yolov8 models. Field investigation and remote-sensing image migration experiments were also carried out to verify the effectiveness of the improved model. The results show that the average recognition accuracy of the improved YOLOv9 model was 82.27%, which was better than that of mainstream object detection, such as Faster RCNN, YOLOv7, and YOLOv8. The high reliability and effectiveness were achieved in the improved model. The ablation test showed that the accuracy, recall, mean average accuracy, and F1 score of the improved model increased by 3.62, 3.78, 1.86, and 3.7 percentage points, respectively, compared with the original model. The findings can provide high-quality data support for soil and water conservation, particularly for the decision-making on the regional control of soil erosion, ecological environmental protection, as well as green and low-carbon sustainable production. [ABSTRACT FROM AUTHOR]

Predicting and managing the impacts of flash droughts is difficult owing to their rapid onset and intensification. Flash drought monitoring often relies on assessing changes in root-zone soil moisture. However, the lack of widespread soil moisture measurements means that flash drought assessments often use process-based model data like that from the North American Land Data Assimilation System (NLDAS). Such reliance opens flash drought assessment to model biases, particularly from vegetation processes. Here, we examine the influence of vegetation on NLDAS-simulated flash drought characteristics by comparing two experiments covering 1981–2017: open loop (OL), which uses NLDAS surface meteorological forcing to drive a land surface model using prognostic vegetation, and data assimilation (DA), which instead assimilates near-real-time satellite-derived leaf area index (LAI) into the land surface model. The OL simulation consistently underestimates LAI across the United States, causing relatively high soil moisture values. Both experiments produce similar geographic patterns of flash droughts, but OL produces shorter duration events and regional trends in flash drought occurrence that are sometimes opposite to those in DA. Across the Midwest and Southern United States, flash droughts are 4 weeks (about 70%) longer on average in DA than OL. Moreover, across much of the Great Plains, flash drought occurrence has trended upward according to the DA experiment, opposite to the trend in OL. This sensitivity of flash drought to the representation of vegetation suggests that representing plants with greater fidelity could aid in monitoring flash droughts and improve the prediction of flash drought transitions to more persistent and damaging long-term droughts. Significance Statement: Flash droughts are a subset of droughts with rapid onset and intensification leading to devastating losses to crops. Rapid soil moisture decline is one way to detect flash droughts. Because there is a lack of widespread observational data, we often rely on model outputs of soil moisture. Here, we explore how the representation of vegetation within land surface models influences the U.S. flash drought characteristics covering 1981–2017. We show that the misrepresentation of vegetation status propagates soil moisture biases into flash drought monitoring, impacting our understanding of the onset, magnitude, duration, and trends in flash droughts. Our results suggest that the assimilation of near-real-time vegetation into land surface models could improve the detection, monitoring, and prediction of flash droughts. [ABSTRACT FROM AUTHOR]

Quantitative description of the water retention curve (WRC) of soils remains one of the most pressing problems in hydrophysics due to its importance for computer modeling of the transport of soil water and dissolved substances, as well as for the development of the thermodynamic concept of soil physical properties. A new WRC model is presented as a functional dependence of the thermodynamic potential (pressure) of water and its content in the soil over the entire possible range from conditionally zero water content to the maximum water holding capacity. Unlike well-known empirical analogues, the model is based on fundamental physical mechanisms of water retention, combining the capillary effect and disjoining water pressure (according to Derjaguin). Limitations by porosity (maximum water holding capacity), the height of the limiting capillary rise, and the standard thermodynamic potential of conditionally zero water content at a temperature of 105°C are used to justify the domain of determination of the WRC, its inflection point, and scaling. The analytical expression of the new model as a combination of exponential and hyperbolic functions with the argument of soil water content is easily differentiated and allows to calculate, using the WRC, the differential water capacity, variable phase interface, and pore size distribution with a maximum value of field capacity, and to estimate the specific surface area of the solid phase. Validation of the model using mean statistical WRCs of the main genetic types and textural classes of some soils in Eurasia confirms its good agreement with experimental data with a more adequate description of WRC in the vicinity of conditionally zero soil water content compared to the standard empirical van Genuchten's model with the same number of parameters. The fundamental nature of the new model and its good approximation ability for the entire range of WRC create the prospect of its diverse use for assessing the physical quality of soils and process modeling of water transfer, especially in finely dispersed and highly drying arid soils, where the approximating capabilities of the model exceed the known empirical analogues. [ABSTRACT FROM AUTHOR]

The dynamism of carbon pools and flows in landscapes requires special attention to the methods and tools for measuring all carbon-containing soil components. An important component of the carbon budget in carbonate geosystems is the dissolved inorganic carbon, part of which is carried out by surface and lateral flows into water bodies, which requires attention to assessing the total alkalinity (TA) of soils on calcareous rocks. Analysis of soils and parent rocks in the Polar Urals with a CaCO3 content of 0 to 100% revealed the factors that influence the value of their TA, namely, (a) the method used for preparing soil samples and water extraction (the ratio of soil weight to the volume of distilled water, ms : , and the quality of separation of solid and liquid phases); (b) the moment of recording the acid titration endpoint for extracts; and (c) the presence of organic acids with pKa < 4.4. The latter reduces the content of bicarbonate ion by converting it into carbonic acid, not measurable by titration. This mechanism is confirmed by (a) analysis of the model solutions of sodium bicarbonate and formic (pKa = 3.75), tartaric (pKa1 = 3.04 and pKa2 = 4.37), and malic (pKa1 = 3.46) acids; (b) cation–anion balance of soil water extracts; and (c) a negative shift in the titration TA values (the sum of carbonate and organic alkalinities) relative to the amount of equivalents of dissolved inorganic carbon determined by high-temperature catalytic oxidation at the same ms : ratios in both methods. It is possible to compare the TA of soils measured by different laboratories only strictly performing all experimental conditions. It is recommended to use a centrifuge to separate the solid and liquid phases of carbonate soils and a pH-meter or a titrator to record the endpoint of titration. [ABSTRACT FROM AUTHOR]

The persistence of a soil seed bank influences weed management options. However, for many species, the degree of persistence of a soil seed bank is unknown. We assessed how long seeds remain in the soil for two invasive weeds, Chrysanthemoides monilifera subsp. monilifera (boneseed) and C. monilifera subsp. rotundata (bitou bush), as seeds of these species were predicted to have different longevity in the soil associated with differences in seed coat thickness. Seeds of both subspecies were buried at two depths at two sites in eastern Australia. Seeds were tested for germinability and viability regularly over an 8‐year period. Freshly collected seeds had quite low viability, and there was a rapid decline in viability in the first couple of years after burial, with C. m. rotundata declining faster than C. m. monilifera. Some seeds, however, remained viable in the soil at some sites for up to 8 years, with high site‐to‐site variability. The variability in viability from site to site may be due to the length of time soils remain moist: a combination of rainfall quantity and humidity levels. The low numbers of seeds remaining viable at 8 years indicate progressively lower probabilities of recruitment at sites following weed control but also suggest that monitoring for both subspecies needs to occur for a long period to minimize the risk of reinfestation from the seed bank. [ABSTRACT FROM AUTHOR]

For many drylands, both long‐ and short‐term drought conditions can accentuate landscape heterogeneity at both temporal (e.g., role of seasonal patterns) and spatial (e.g., patchy plant cover) scales. Furthermore, short‐term drought conditions occurring over one season can exacerbate long‐term, multidecadal droughts or aridification, by limiting soil water recharge, decreasing plant growth, and altering biogeochemical cycles. Here, we examine how experimentally altered seasonal precipitation regimes in a mixed shrub grassland on the Colorado Plateau impact soil moisture, vegetation, and carbon and nitrogen cycling. The experiment was conducted from 2015 to 2019, during a regional multidecadal drought event, and consisted of three precipitation treatments, which were implemented with removable drought shelters intercepting ~66% of incoming precipitation including: control (ambient precipitation conditions, no shelter), warm season drought (sheltered April–October), and cool season drought (sheltered November–March). To track changes in vegetation, we measured biomass of the dominant shrub, Ephedra viridis, and estimated perennial plant and ground cover in the spring and the fall. Soil moisture dynamics suggested that warm season experimental drought had longer and more consistent drought legacy effects (occurring two out of the four drought cycles) than either cool season drought or ambient conditions, even during the driest years. We also found that E. viridis biomass remained consistent across treatments, while bunchgrass cover declined by 25% by 2019 across all treatments, with the earliest declines noticeable in the warm season drought plots. Extractable dissolved inorganic nitrogen and microbial biomass nitrogen concentrations appeared sensitive to seasonal drought conditions, with dissolved inorganic nitrogen increasing and microbial biomass nitrogen decreasing with reduced soil volumetric water content. Carbon stocks were not sensitive to drought but were greater under E. viridis patches. Additionally, we found that under E. viridis, there was a negative relationship between dissolved inorganic nitrogen and microbial biomass nitrogen, suggesting that drought‐induced increases in dissolved inorganic nitrogen may be due to declines in nitrogen uptake from microbes and plants alike. This work suggests that perennial grass plant–soil feedbacks are more vulnerable to both short‐term (seasonal) and long‐term (multiyear) drought events than shrubs, which can impact the future trajectory of dryland mixed shrub grassland ecosystems as drought frequency and intensity will likely continue to increase with ongoing climate change. [ABSTRACT FROM AUTHOR]

Mediterranean ecosystems are predicted to undergo longer and more intense summer droughts. The mechanisms underlying the response of herbaceous communities to such drier environments should be investigated to identify the resilience thresholds of Mediterranean rangelands. A 5‐year experiment was conducted in deep and shallow soil rangelands of southern France. A rainout shelter for 75 days in summer imposed drier and warmer conditions. Total soil water content was measured monthly to model available daily soil water. Aboveground net primary production (ANPP), forage quality, and the proportion of graminoids in ANPP were measured in spring and autumn. Plant senescence and plant cover were assessed in summer and spring, respectively. The experimental years were among the driest ever recorded at the site. Therefore, manipulated summer droughts were drier than long‐term ambient conditions. Interactions between treatment, community type, and experimental year were found for most variables. In shallow soil communities, spring plant cover decreased markedly with time. This legacy effect, driven by summer plant mortality and the loss of perennial graminoids, led to an abrupt loss of resilience when the extreme water stress index exceeded 37 mm 10 day−1, characterized by a reduction of spring plant cover below 50% and a decreased ANPP in rainy years. Conversely, the ANPP of deep soil communities remained unaffected by increased summer drought, although the presence of graminoids increased and forage nutritive value decreased. This study highlights the role of the soil water reserve of Mediterranean plant communities in modulating ecosystem responses to chronically intensified summer drought. Communities on deep soils were resilient, but communities on shallow soils showed a progressive, rapid, and intense degradation associated with a loss of resilience capacity. Notably, indexes of extreme stress were a better indicator of tipping points than indexes of integrated annual stress. Considering the role of soil water availability in other herbaceous ecosystems should improve the ability to predict the resilience of plant communities under climate change. [ABSTRACT FROM AUTHOR]

Some taxa of wading birds can locate buried prey by detecting vibratory cues in their foraging substrates while probe‐foraging, using a sensory modality called 'remote‐touch'. As more saturated substrates transmit vibrations better, we predict that these birds can detect prey in wetter substrates more easily. We used sensory assays to test whether substrate water content affects the remote‐touch foraging success rate of Hadeda ibises, Bostrychia hagedash. The birds were more successful at locating prey using vibratory cues than when relying on random direct contact with the beak alone. Their remote‐touch foraging success rate was positively affected by increasing water contents of the soil, but water content had no effect on their direct contact foraging success (indicating this is not an artefact of ease of probing). This may partially explain the link between the range expansion of this species in southern Africa and increased soil irrigation, as it is easier for the birds to detect prey in wetter substrates. Thus, it is likely that the distribution of other remote‐touch foraging birds is affected by substrate water content, and as many of these species are endangered and rely on sensitive wetland habitats, it is vital to understand their sensory requirements for foraging. [ABSTRACT FROM AUTHOR]

Climate change is expected to lead to a drier world, with more frequent and severe droughts, constituting a growing threat to biodiversity, especially in drylands. Positive plant−plant interactions, such as nurse plants facilitating beneficiary communities in their understorey, could mitigate such climate‐induced stress. However, testing the real‐world relevance of nurse facilitation under drought requires accounting for interactions within the diverse beneficiary communities, which may reduce, or amplify the buffering effect of a nurse. Here, we investigated when and how the interactions among nurse plants and beneficiary community members buffered drought effects in a Mediterranean semiarid abandoned cropland. We transplanted sapling beneficiary communities of either one or three species either under a nurse or in open microsites for different soil moisture levels through watering. Net facilitative effects on survival and biomass were only observed when beneficiary communities were species‐diverse and under drought (without watering), meaning that under these conditions, facilitation provided by the nurse had larger positive effects than the negative effects stemming from competition with the nurse and among beneficiary species. Nurses appear to be generating these increases in survival and biomass in drought conditions via two mechanisms commonly associated with watering in open sites: they generate complementarity among the beneficiaries and shift traits to lower stress profiles. Contrasting with watering, which was found to enhance competitive hierarchy, our study shows that nurses appear to alter species dominance, favouring the less competitive species. Our results highlight three mechanisms (complementarity, competitive dominance, and trait plasticity) by which nurse species could mitigate the loss of biodiversity and biomass production due to water stress. Maintaining and supporting nurse species is thus a potentially pivotal approach in the face of projected increase in drought conditions for many drylands across the world. Keywords: biodiversity, dryland, ecosystem functioning, facilitation, functional traits, plant–plant interactions [ABSTRACT FROM AUTHOR]

The Yangtze River basin (YRB) experienced a record-breaking mei-yu season in June–July 2020. This unique long-lasting extreme event and its origin have attracted considerable attention. Previous studies have suggested that the Indian Ocean (IO) SST forcing and soil moisture anomaly over the Indochina Peninsula (ICP) were responsible for this unexpected event. However, the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event, especially their linkage with atmospheric circulation changes, remain unclear. By using observations and numerical simulations, this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020. Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds. The intensification of the warm condition further magnified the land thermal effects, which in turn facilitated the westward extension of the western North Pacific subtropical high (WNPSH) in June–July. The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB, thereby contributing to the 2020 mei-yu. In contrast, the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture. The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model. Their synergistic impacts yield a notable 32% increase in YRB precipitation. Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu. [ABSTRACT FROM AUTHOR]

This paper presents an integrated simulation of future hydrological droughts using different climate scenarios for the Piancó River basin. Streamflow and sediment yield are estimated using the Soil and Water Assessment Tool (SWAT) model, and hydrological droughts are calculated using the Streamflow Drought Index (SDI). The study incorporates two future climate scenarios: RCP 4.5 (optimistic) and RCP 8.5 (pessimistic). The SDI is determined based on a series of simulated future flows to identify drought events within the basin. The results show that the model calibration and validation demonstrated excellent agreement with observed data (R² = 0.83, NSE = 0.82 for calibration and R² = 0.89, NSE = 0.77 for validation). When comparing the scenarios, reductions in flow volume by −75.86% and sediment yield by −86.5% are noted, indicating a significant decrease in sediment contribution to the outlet. Interestingly, the most critical years related to drought events, as determined by the SDI, do not coincide across the pessimistic and optimistic scenarios. [ABSTRACT FROM AUTHOR]

Drought threatens plant growth and related ecosystem services. The emergence of plant drought stress under edaphic drought is well studied, whilst the importance of atmospheric drought only recently gained momentum. Yet, little is known about the interaction and relative contribution of edaphic and atmospheric drought on the emergence of plant drought stress. We conducted a gradient experiment, fully crossing gravimetric water content (GWC: maximum water holding capacity—permanent wilting point) and vapour pressure deficit (VPD: 1−2.25 kPa) using five wheat varieties from three species (Triticum monococcum, T. durum & T. aestivum). We quantified the occurrence of plant drought stress on molecular (abscisic acid), cellular (stomatal conductance), organ (leaf water potential) and stand level (evapotranspiration). Plant drought stress increased with decreasing GWC across all organizational levels. This effect was magnified nonlinearly by VPD after passing a critical threshold of soil water availability. At around 20%GWC (soil matric potential 0.012 MPa), plants lost their ability to regulate leaf water potential via stomata regulation, followed by the emergence of hydraulic dysfunction. The emergence of plant drought stress is characterized by changing relative contributions of soil versus atmosphere and their non‐linear interaction. This highly non‐linear response is likely to abruptly alter plant‐related ecosystem services in a drying world. Summary statement: Plant drought stress emerges from a nonlinear interaction of soil water availability (here estimated based on gravimetric water content, GWC) and atmospheric water demand (vapour pressure deficit, VPD) with the relative contribution of VPD accelerating below a critical threshold of GWC. [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]

This study presents a comprehensive comparison between traditional hydrological models and advanced machine learning (ML) techniques in predicting streamflow dynamics. Traditional models, namely the Soil and Water Assessment Tool (SWAT) and Génie Rural à 4 Paramètres Journalier (GR4J), are juxtaposed against ML models, including Random Forest (RF), Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), and Bidirectional LSTM (BiLSTM). Both SWAT and GR4J demonstrated commendable performance, with GR4J displaying marginally superior predictive accuracy, evidenced by its tighter RMSE values. In the realm of ML, RF exhibited exceptional prowess in integrating diverse climatic features, especially in a scenario integrating comprehensive meteorological data. ANN showcased consistent performance across different input scenarios, emphasising its robustness. LSTM and BiLSTM, tailored for time series data, underscored the importance of precipitation's temporal dynamics in streamflow predictions. A notable revelation is the significance of choosing appropriate input data, with certain scenarios outperforming others based on the amalgamation of meteorological parameters. The flow duration curve (FDC) analysis further highlighted the model capabilities, with RF and BiLSTM excelling in capturing extreme flows, while traditional models resonated more with medium flow regimes. This research offers vital insights for hydrologists and decision-makers, aiding in informed model selection for streamflow predictions. [ABSTRACT FROM AUTHOR]

In drylands, grass germination occurs after a large rainfall event. However, trees influence the water requirements for germination either by decreasing the rate of evaporation from soil surface or by interception rainfall with their canopy. The aim of this work was to evaluate the role of Neltuma flexuosa tree on the germination of Leptochloa crinita and Pappophorum caespitosum grasses in response to precipitation events of different sizes. The experiment was conducted in two locations within the Monte desert, Argentina: a semi‐arid location with an average annual precipitation of 345 mm and an arid location with an average annual precipitation of 156 mm. Six microsites were established under N. flexuosa canopies and six microsites in open areas at both locations. Within each microsite, 35 seeds of each grass species were exposed to precipitation events of varying sizes. This procedure was repeated 14 times across two growing seasons. Germinated seeds were counted in the laboratory. Generalized linear mixed models were then applied to evaluate the effects of accumulated precipitation and the microsite on the grass germination in both locations. Results showed that N. flexuosa did not influence the germination of either grass species in the arid location. However, in the semi‐arid location, N. flexuosa facilitated the germination of P. caespitosum only. Large precipitation events would act as an environmental signal for these perennial grasses, allowing them to germinate in favorable years regardless of the microsite or the location. [ABSTRACT FROM AUTHOR]

The semi-arid agro-pastoral ecotone is a transitional zone from agriculture to animal husbandry, with a fragile ecological environment. Top soil moisture (TSM) is an important factor restricting regional development, and studying its spatiotemporal changes and driving factors are important for ecosystem restoration. In this study, the spatiotemporal changes of TSM from 2003 to 2022 were analyzed based on empirical orthogonal function (EOF) method, and the individual and interactive effects of the influencing factors on the temporal or spatial variation of TSM were explored based on geographical detector model (GDM) method. The results showed that climate factors were the main influencing factors on the global spatial variation of TSM, while topography and soil texture had an impact on the local spatial variation of TSM. The explanatory power of the interaction among influencing factors on TSM was greater than that of individual factors on TSM, especially the combination of climate factors, where the combination of temperature, Pet and SPEI was the strongest explanatory power under each vegetation type. Precipitation and NDVI were the main factors affecting the temporal variation of TSM. This study provides insights into the spatiotemporal variations in TSM and its influencing factors in the semi-arid agro-pastoral ecotone. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is crucial for plant functions like root growth, energy transfer, photosynthesis, and cell division. Yet, its soil efficiency is hindered by high fixation, low solubility, and immobility. Besides, its increased availability and subsequent plant uptake requires availability of sufficient moisture, as increased soil moisture contents higher dissolution of P occurs leading to increased root development, which, ultimately, increase nutrient uptake by plants. We performed a field experiment to check the effect of different P application levels along with different irrigation schemes in improving P uptake efficiency of maize and its related growth and yield attributes. In different treatments, irrigation was provided at recommended levels, skipped at milking and flowering stages to check the impacts of moisture contents on soil P availability. We observed that among different P levels, application of P at 90 kg ha-1 along with recommended irrigation level enhanced different maize traits, such as shoot length (13.4%), root length (51%), shoot fresh and dry weights (35 and 25%), root fresh and dry weights (37 and 42%), SPAD value (17%), chlorophyll 'a and b' (16 and 7%), P use efficiency (255%), harvest index (43%) and carotenoid contents (26%), as compared to control followed by P at 120 kg ha-1. Furthermore, in terms of soil nutrient attributes, P at 90 kg ha-1 along with recommended irrigation level enhanced soil organic matter (17%), active carbon (22%), available P (122%) and extractable potassium (36%), as compared to control. A consecutive decline in all the measured attributes was pragmatic under skipped irrigation systems under all the P application levels. We concluded that P application at 90 kg ha-1 combined with recommended irrigation levels can significantly increase P use efficiency of maize along with increased soil P availability and related growth and yield attributes. [ABSTRACT FROM AUTHOR]

Stem water potential (Ψstem) is a key indicator for assessing plant water status, which is crucial in understanding plant health and productivity. However, existing measurement methods for Ψstem, characterized by destructiveness and intermittency, limit its applicability. Microtensiometers, an emerging plant-based sensor, offer continuous monitoring capabilities and have shown success in certain vine and tree species. In this study, we investigate the efficacy of microtensiometers ability to monitor the Ψstem of cotton (Gossypium hirsutum L.) under three distinct irrigation treatments in Maricopa, Arizona, an extremely hot, arid environment. We analyze the diurnal dynamics of Ψstem across the irrigation regimes and compare these measurements with midday leaf water potentials (Ψleaf) obtained using a dewpoint potentiometer. Our results demonstrate that the microtensiometer-derived Ψstem closely follows known diurnal patterns of Ψleaf, tracking with vapor pressure deficit (VPD) and responding to variations in irrigation levels and soil moisture content. Time cross-correlation analysis reveals an 80-minute lag in Ψstem response to changing VPD under non-water limiting conditions, which shortens under water-limiting conditions. Additionally, we establish a robust linear relationship (R2adj = 0.82) between Ψstem and Ψleaf, with this relationship strengthening as water availability decreases. Notably, we observe mean gradients of 1.2 and 0.06 MPa between soil vs. stem and stem vs. leaf water potentials, respectively. Moreover, Ψstem data proves to be more sensitive in distinguishing between irrigation treatments earlier in the growing season compared to Ψleaf, leaf temperature and leaf gas exchange parameters. These findings highlight the utility of microtensiometers as valuable tools for monitoring water status in smaller-stemmed row crops such as cotton. [ABSTRACT FROM AUTHOR]

This study aimed to explore the inversion method of soil moisture content by using numerical simulation and field detection. The researchers used the early signal amplitude envelope (AEA) method to directly invert soil moisture in the shallow part of the soil, which avoided the transmission error of the Topp formula. The Auto-Regressive Moving Average Model (ARMA) was used to calculate the power spectrum of radar signals, and the BP neural network was used to train the power spectrum of different Gaussian windows, so as to improve the inversion accuracy. According to the study, the average error of soil moisture content inverted by AEA method was 0.45% in the range of 0-0.41 m, while the error of ARMA method in depth range of 0.1-1.0 m was less than 1%. The results showed that the combination of the two methods can effectively invert the soil moisture content within the radar detection range. [ABSTRACT FROM AUTHOR]

For marine soft soil under the periodic wave loading, the pore water content in soil suffering dry-wet cycle for a long time, which affects its microstructure and macroscopic mechanical strength, resulting in insufficient bearing capacity and excessive deformation of soft soil. To reveal the microstructural characteristics and strength attenuation law of marine soft soil under dry-wet cycle condition, electron microscopy scanning and direct shear tests under different times of dry-wet cycles were carried out, and the mathematical equations of pore structure and strength parameters were established based on fractal theory. The research results showed that: (1) The pore structure changed considerably after the first dry-wet cycle, and then changed gently with the increase of dry-wet cycle times, which was reflected by the fractal dimension D value decreases to a constant value gradually. (2) The shear strength of the soil diminishes with an increase in the number of dry-wet cycle times, and the maximum attenuation occurs after the first dry-wet cycle. (3) The relationship between cohesion (c), internal friction angle (φ), and fractal dimension (D) is exponential, with the curve shapes being concave and convex, respectively. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Northwest A & F University - Natural Science Edition is the property of Editorial Department of Journal of Northwest A&F University (Natural Science Edition) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Northwest A & F University - Natural Science Edition is the property of Editorial Department of Journal of Northwest A&F University (Natural Science Edition) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Northwest A & F University - Natural Science Edition is the property of Editorial Department of Journal of Northwest A&F University (Natural Science Edition) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

A potential advancement in agriculture is the use of genetically modified rhizobacteria, which are intended to promote stress tolerance and plant development. These altered bacteria have a number of benefits that can greatly increase agricultural yield. They have been designed to interact favorably with plant roots. These rhizobacteria are essential for maintaining the wellness of plants because they provide more effective absorption of nutrients and improve the plant's resistance to harsh environmental factors like salt and moisture in the soil. In addition to promoting more rapid plant growth, the use of genetically engineered rhizobacteria supports sustainable agriculture as a whole. This strategy is in line with the increasing demand for environmentally fr iendly farming methods that address issues related to worldwide nutrition. Genetically created rhizobacteria are an important tool in contemporary agriculture that can improve resistance to stress and maximize intake of nutrients while maintaining vigorous crop production in the face of environmental changes. [ABSTRACT FROM AUTHOR]

The Western Cape in South Africa is a water-scarce region which will likely receive less rainfall and higher air temperatures under projected climate change scenarios. The integration of trees within agricultural systems provides an effective measure for improving water retention on agricultural land. Studying an established and irrigated agroforestry system (AFS) combining alder (Alnus cordata (Loisel.) Duby) as a linear windbreak with a blackberry (Rubus fructicosus L.) crop, we explore the water use dynamics of the intercrop as influenced by the windbreak element by combining methods from hydrology, soil science and forestry disciplines. Our objective is to explore whether the AFS positively impacts the water balance by combining measurement campaigns to characterise the spatial variability of various key system properties with continuous monitoring. The campaigns encompassed extensive soil sampling to determine soil characteristics (nutrient concentrations, hydraulic conductivity, texture, water retention) in the laboratory as well as terrestrial laser scans of the field site, especially of the windbreaks. The continuous measurements covered meteorological, soil water content and soil water potential observations over a 6-month period (in summer). These were applied to understand soil water dynamics during rainstorms and dry spells, including root water uptake as well as soil water storage. We recorded a total of 13 rainfall events delivering 2.5–117.6 mm of rainfall with maximum intensities of 4.1 to 82.6 mm h -1. Further analyses showed that infiltration is likely dominated by preferential flow, with root water uptake potentially occurring in two depth zones corresponding to different plant communities. While soil water content varied by depth and was influenced by physical and environmental factors, it was generally higher in the intercrop zone than within the windbreak-influenced zone. During dry spells, soil water content did not drop below the water content of the permanent wilting point (<-1500 kPa). Values corresponding to soil water tensions above 1000 kPa were recorded on several occasions; these were mitigated by irrigation and, thus, did not result in water stress. Nutrient distribution and soil physical properties differed near the windbreak in comparison to the blackberry crop, and the carbon sequestration potential is great in comparison to monoculture farming. We could demonstrate positive effects of the windbreak on the water balance and dynamics in the blackberry field site, even though questions remain as to the extent of these benefits and how they compared to disadvantageous aspects brought about by the presence of the trees (e.g. increased water usage). Irrigation did, in fact, shift the AFS from a water-limited regime to an energy-limited one. [ABSTRACT FROM AUTHOR]

The proportion of European ash (Fraxinus excelsior L.) stands decreased rapidly over the last thirty years. The highest declines are recorded in fertile ash-dominated habitats. Thus, a comprehensive understanding of successful ash establishment is needed across broader habitat conditions. Therefore, we aimed to investigate ash natural regeneration in pine-ash forests and adjacent pine-dominated forests without ash in overstory but with ash regeneration. We assessed the effects of soil environment, soil moisture, browsing, ash regeneration density and its health status. The most limiting factors of ash regeneration were low soil moisture, high soil acidity, and the increase of pine proportion. We noted the highest densities only for ash regeneration of up to 0.6 m height growing on moderately acidic soils in pine-ash forests. Our models showed a low number of saplings damaged by ash disease. Instead, we revealed a high proportion of drought-damaged saplings without dieback symptoms. The highest browsing occurred within pine-ash forests with a lower proportion of pine trees in overstory. Despite theoretically unfavourable soil conditions, we state that pine-ash forests can harbour ash regeneration and may allow for its natural and assisted recolonization. In contrast, within pine-dominated forests located in the vicinity of pine-ash stands, the successful regeneration of ash is negligible due to high soil acidification and low moisture. [ABSTRACT FROM AUTHOR]

This study analyzed satellite data from 2000 to 2022 in the Tian Shan ecoregions of northwestern China to investigate relationships between climate, environment, soil conditions, and human activities on constantly changing vegetation fluctuations. The NDVI index outperformed EVI over the period, with peak values of 0.56 and 0.33, respectively. NDVI trends indicated a higher slope of 5.15 compared to 4.91 for EVI. Analysis showed that vegetation area had expanded over time, with the lowest coverage between 2000 and 2005, but then, it spread due to varying degree of human activities' impacts from 0 to 63. Tests revealed significant negative correlations between soil moisture and EVI/NDVI indexes attributed to natural water phenomena causing vegetation stress. Positive correlations were found between EVI/NDVI with actual evapotranspiration and snow, while negative with wind speed and radiation. The study also found a positive correlation between NDVI and measures of human activity, indicating restoration efforts, project implementations, and soil management preventing erosion expanded vegetation. Overall, the study concluded that human activities had a greater influence than climate through water and soil preservation, resulting in more vegetation expansion over time. Indigenous resource concepts also significantly contributed to long-term preservation efforts evidently maintaining and strengthening vegetation in the ecoregions. These findings highlight the efficacy and resilience of human activity in overcoming climatic and environmental challenges. While human factors can potentially harm the environment and renewable resources, long-term planning and preservation efforts, as evident in the Tian Shan ecoregions, have successfully preserved and strengthened the vegetation. [ABSTRACT FROM AUTHOR]

Analysis of studies on the direction of enrichment of dendroflora of artificial plantations showed the promising potential of Pinus pallasiana (L.) for agroforestry in the southern regions of Russia. The aim is to develop a technology for obtaining planting material with a closed root system taking into account the ecological and biological characteristics of coniferous plants. The accelerated technology of obtaining seedlings of P. pallasiana with a closed root system was developed. The location of research in closed ground conditions (greenhouse, area 252 m²) at the Nizhnevolzhskaya station on the selection of woody species -- branch of the Federal Research Center of Agroecology of the Russian Academy of Sciences (Russia, Volgograd region, Kamyshin; coordinates 50.078957, 45.370560). The research period was from December 2020 to September 2022. Substrate composition, optimal timing and frequency of plant feeding with complex fertilizers, including chlorine-free fertilizers, were recommended. Accelerated terms of cultivation and placement of pine plants for adaptation on the hardening site give a positive effect, which is associated with the economical consumption of seeds, and the safety of seedlings at all stages of cultivation. A technique is proposed that allows the root to avoid deformation, which, under conditions of soil moisture deficit, allows to increase the rooting of the plant. [ABSTRACT FROM AUTHOR]

The global extent of salt‐affected agricultural land, 20% of which is deemed gypsiferous, results in billions of dollars of annual economic loss, a serious problem deserving of attention. However, the analysis of gypsiferous saline soils, such as in the irrigated Lower Arkansas River Valley (LARV) of Colorado, can result in an inflated estimation of soil salinity when using the traditional soil saturated paste extract electrical conductivity (ECe), leading to inaccurate crop yield loss predictions and misguided decisions for remediation. Sparingly soluble gypsum (CaSO4·$\cdot$ 2H2O) in these soils dissolves more readily during laboratory preparation of saturated paste extracts because of excess soil water dilution coupled with sample disturbance. We present a pragmatic linear‐regression approach to correct for this phenomenon, calibrated using two adapted methods for correcting ECe on an individual sample basis. The novel approach used electrical conductivity of pore water samples from saline fields to evaluate the accuracy of the correction methods. The approach was applied on soil samples from two surface‐irrigated, saline fields in the LARV, which were mapped using electromagnetic induction data and analysis of covariance linear regression, calibrated for ECe and ECe corrected for excess gypsum dissoultion (ECeg). Average ECeg values are as much as 26% lower than uncorrected ECe in gypsum‐biased portions of the fields. Estimation of corn salinity hazard in these gypsum‐affected areas using ECeg in lieu of ECe in a traditional yield response function generated mean relative yield values that are higher by up to 13 percentage points. We discuss lessons learned and suggest enhancements to the techniques. Core Ideas: In gypsiferous soils, excess gypsum dissolution biases saturated paste extract (SPE) analysis.Electrical conductivity of SPE (ECe) was corrected with selective dilution and equilibrium geochemical modeling.Linear models were used to estimate gypsum‐corrected ECe values over study fields.Gypsum significantly affects assessment of salinity hazard and crop yield impact. [ABSTRACT FROM AUTHOR]

Harvesting or degradation of forest ecosystems directly affects the microclimate, causing changes in air and soil temperatures and soil moisture in the forestlands. The objectives of this study were to investigate the effect of frequent clearcutting of forest cover on some selected soil properties, ambient and soil temperatures, soil moisture, and herbaceous vegetation cover and determine their recovery in a short period in the area subject to frequent clearcutting under the powerline corridors (PLCs). The study was conducted in the research forest of Istanbul University-Cerrahpaşa, Faculty of Forestry. The treatment plots were selected from the clearcut area, and control plots were selected from an untouched oak-hornbeam forestland. Soil temperature and moisture and maximum and minimum ambient temperatures were measured in the treatment and control plots between 2020 and 2021 and topsoil sampled between 2019 and 2021. Data were analyzed using analysis of variance (ANOVA) to test the effects of clearcutting on some selected soil properties in the short term after cutting. Clearcutting caused a significant increase in soil bulk density (BD) and a decrease in the soil total porosity (TP), soil hydraulic conductivity (HC), and saturation capacity (SC). Forest cover removal significantly decreased the soil organic matter (SOM) content by 3%, increased average soil temperature by 2.1 °C, and the difference between maximum and minimum temperatures by 8.8 °C. Additionally, clearcutting reduced the average soil moisture from 36 to 35%. The findings revealed that clearcutting negatively affected some hydro-physical soil properties and soil microclimate conditions that may not recover to their previous states within the next few years. [ABSTRACT FROM AUTHOR]

Root zone soil moisture (RZSM) is crucial for agricultural water management and land surface processes. The 1 km soil water index (SWI) dataset from Copernicus Global Land services, with eight fixed characteristic time lengths (T), requires root zone depth optimization (Topt) and is limited in use due to its low spatial resolution. To estimate RZSM at 100-m resolution, we integrate the depth specificity of SWI and employed random forest (RF) downscaling. Topographic synthetic aperture radar (SAR) and optical datasets were utilized to develop three RF models (RF1: SAR, RF2: optical, RF3: SAR + optical). At the DEMMIN experimental site in northeastern Germany, Topt (in days) varies from 20 to 60 for depths of 10 to 30 cm, increasing to 100 for 40–60 cm. RF3 outperformed other models with 1 km test data. Following residual correction, all high-resolution predictions exhibited strong spatial accuracy (R ≥ 0.94). Both products (1 km and 100 m) agreed well with observed RZSM during summer but overestimated in winter. Mean R between observed RZSM and 1 km (100 m; RF1, RF2, and RF3) SWI ranges from 0.74 (0.67, 0.76, and 0.68) to 0.90 (0.88, 0.81, and 0.82), with the lowest and highest R achieved at 10 cm and 30 cm depths, respectively. The average RMSE using 1 km (100 m; RF1, RF2, and RF3) SWI increased from 2.20 Vol.% (2.28, 2.28, and 2.35) at 30 cm to 3.40 Vol.% (3.50, 3.70, and 3.60) at 60 cm. These negligible accuracy differences underpin the potential of the proposed method to estimate RZSM for precise local applications, e.g., irrigation management. [ABSTRACT FROM AUTHOR]

This study aims to assess the effectiveness of PCB-based capacitive soil moisture sensors for local field conditions. The electrical scheme of designed sensors has been presented in this study. The PCB-based capacitive soil moisture sensors are calibrated using a linear equation developed between analog values of capacitive sensors and soil moisture content measured from the gravimetric method. The performance of the designed soil moisture sensors was assessed at five different locations at varying depths (i.e., 15 cm, 30 cm, and 45 cm). The calibration results indicated a positive correlation between the soil moisture content and measurement frequency of the sensor for wheat crop, with R2 values of 0.72, 0.83, and 0.83 for 15 cm, 30 cm, and 45 cm depths, respectively. Results reveal that 85% of the sensors accurately detected the patterns in soil moisture fluctuations during the cropping period. The designed capacitive sensors demonstrated a maximum relative error of 5.87% for 45 cm depth. However, the relative error remained below 5% for the 15 cm and 30 cm soil depths. For the sugarcane crop, R2 values vary from 0.66 to 0.82, with the highest relative error of 5.22% at a 15 cm depth. These sensors offer a highly cost-effective solution for farmers, with the entire wireless sensor network system including one sensor node, three soil moisture sensors, and one soil temperature sensor, which is priced at approximately $150, making it a practical and affordable option for widespread adoption. [ABSTRACT FROM AUTHOR]

The impact of storage duration on the geotechnical properties of soils is a recurring issue in the field of geotechnical engineering. Due to the lack of previous research addressing this topic, an experimental study was conducted to evaluate the variation of these properties over time. Undisturbed samples of silty and organic soil from Quito, Ecuador, were obtained. These samples were subjected to unconfined compressive strength (UCS) and moisture content (MC) tests at various intervals (1, 3, 7, 14, 21, 28, and 56 days). Results revealed a significant correlation between MC, UCS, and modulus of elasticity (ME). A progressive increase in UCS and ME was observed as MC decreased, with peak values observed to occur between 20 and 30 days. These findings suggest that matric suction plays a predominant role in increasing cohesion and, consequently, UCS. Therefore, it is concluded that the time elapsed between sample extraction and testing is a critical factor influencing the preservation of MC and, hence, the accurate assessment of the soil's mechanical properties. [ABSTRACT FROM AUTHOR]

The mechanism for improving soil with high-performance ester material is not yet clear, especially changes in soil moisture under dry–wet cycling conditions. Soil moisture is closely related to its ecological performance, which also leads to a lack of scientific bases for the application range, climate conditions, and long-term performance evolution evaluation of high-performance ester materials in ecological restoration. Our research revealed an optimal ratio for the amount of high-performance ester materials that can improve soil moisture and ecological performance under multiple dry–wet cycling conditions. Dry–wet cycling experiments and planting tests were conducted to study the soil moisture improvement mechanism and the changes caused by high-performance ester materials. Changes in the soil's moisture, EC, and ecological performance were explored. The results indicate that ester materials can effectively improve soil moisture and EC. Even after multiple dry–wet cycles, ester materials can still play an effective role in improving soil moisture and ecological performance. An optimal ratio for the amount of high-performance ester materials was also found. This research reveals the improvement mechanism for ester materials on soil moisture and ecological performance under dry–wet cycling conditions. Our results provide new data and technical guidance for the improvement of soil moisture and ecological restoration by high-performance ester materials. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) plays a crucial role in land–atmosphere interaction systems, directly influencing evapotranspiration, photosynthesis, and the water dynamics of the soil surface. Invariably, SM is negatively impacted by disturbances such as fires, which are becoming more frequent across semi-arid ecosystems. Different ecological restoration activities have been implemented to mitigate the impacts of disturbance that, when left untreated, can worsen the effects of recurrent droughts and accelerate desertification and land degradation processes. To measure and monitor the dynamics of SM, advanced techniques and tools have been developed that integrate remote sensing and in situ measurement. This review encompasses various themes on the application of remote sensing for measuring and monitoring SM dynamics in semi-arid ecosystems at different scales. We focused our analysis on the western United States region and thus have developed a review on the following topics: (a) the different data sources (e.g., satellite, unmanned aerial vehicles), (b) approaches to measure field-based SM, and (c) algorithms and techniques to model SM at different scales. We summarize these topics by emphasizing repeatable approaches for the transparent estimation of this variable, identifying current data gaps, and highlighting future trends to fulfill the expanding demand for SM monitoring strategies. [ABSTRACT FROM AUTHOR]

Maize is highly susceptible to drought, which affects growth and yield. This study investigated how bacterial volatile organic compounds (BVOCs) affect maize drought tolerance. Drought reduced shoot size but increased root length, an adaptation for accessing deeper soil moisture. BVOCs from strain D12 significantly increased root length and shoot growth under drought conditions. Drought also altered root biochemistry, decreasing enzyme activity, and increased osmolyte levels. BVOCs from strains F11 and FS4-14 further increased osmolyte levels but did not protect membranes from oxidative damage, while BVOCs from strains D12 and D7 strains reduced osmolyte levels and cell damage. In shoots, drought increased the levels of osmolytes and oxidative stress markers. BVOCs from FS4-14 had minimal effects on shoot biochemistry. BVOCs from D12 and F11 partially restored metabolic activity but did not reduce cell damage. BVOCs from D7 reduced metabolic activity and cell damage. These results suggest that BVOCs can modulate the biochemical response of maize to drought, with some strains evidencing the potential to enhance drought tolerance. [ABSTRACT FROM AUTHOR]

By integrating the thermal characteristics from thermal-infrared remote sensing with the physiological and structural information of vegetation revealed by multispectral remote sensing, a more comprehensive assessment of the crop soil-moisture-status response can be achieved. In this study, multispectral and thermal-infrared remote-sensing data, along with soil-moisture-content (SMC) samples (0~20 cm, 20~40 cm, and 40~60 cm soil layers), were collected during the flowering stage of soybean. Data sources included vegetation indices, texture features, texture indices, and thermal-infrared vegetation indices. Spectral parameters with a significant correlation level (p < 0.01) were selected and input into the model as single- and fuse-input variables. Three machine learning methods, eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Genetic Algorithm-optimized Backpropagation Neural Network (GA-BP), were utilized to construct prediction models for soybean SMC based on the fusion of UAV multispectral and thermal-infrared remote-sensing information. The results indicated that among the single-input variables, the vegetation indices (VIs) derived from multispectral sensors had the optimal accuracy for monitoring SMC in different soil layers under soybean cultivation. The prediction accuracy was the lowest when using single-texture information, while the combination of texture feature values into new texture indices significantly improved the performance of estimating SMC. The fusion of vegetation indices (VIs), texture indices (TIs), and thermal-infrared vegetation indices (TVIs) provided a better prediction of soybean SMC. The optimal prediction model for SMC in different soil layers under soybean cultivation was constructed based on the input combination of VIs + TIs + TVIs, and XGBoost was identified as the preferred method for soybean SMC monitoring and modeling, with its R2 = 0.780, RMSE = 0.437%, and MRE = 1.667% in predicting 0~20 cm SMC. In summary, the fusion of UAV multispectral and thermal-infrared remote-sensing information has good application value in predicting SMC in different soil layers under soybean cultivation. This study can provide technical support for precise management of soybean soil moisture status using the UAV platform. [ABSTRACT FROM AUTHOR]

The impact of the intercropping system on the soil–plant–atmosphere continuum (SPAC), encompassing soil evaporation, soil moisture dynamics, and crop transpiration, remains an area of uncertainty. Field experiments were conducted for two years in conjunction with the SIMDualKc (Simulation Dual Crop Coefficient) model to simulate two planting configurations: sole-cropped wolfberry (Lycium barbarum L.) (D) and wolfberry intercropped with alfalfa (Medicago sativa L.) (J). These configurations were subjected to different irrigation levels: full irrigation (W1, 75–85% θfc), mild deficit irrigation (W2, 65–75% θfc), moderate deficit irrigation (W3, 55–65% θfc), and severe deficit irrigation (W4, 45–55% θfc). The findings revealed that the JW1 treatment reduced the annual average soil evaporation by 32% compared with that of DW1. Additionally, mild, moderate, and severe deficit irrigation reduced soil evaporation by 17, 24, and 36%, respectively, compared with full irrigation. The intercropping system exhibited a more efficient canopy structure, resulting in reduced soil evaporation and alleviation of water stress to a certain extent. In terms of temporal dynamics, monocropping resulted in soil moisture levels from 1% to 15% higher than intercropping, with the most significant differences manifesting in the mid to late stages, whereas differences in the early stages were not statistically significant. Spatially, the intercropping system exhibited 7–19% lower soil water contents (SWCs) than sole cropping, primarily within the root water uptake zone within the 0–60 cm soil layer. The intercropping system showed an enhanced water absorption capacity for plant transpiration, resulting in a 29% increase in transpiration compared with sole cropping, thereby achieving water-saving benefits. These findings contribute to our understanding of the agronomic and environmental implications of intercropping wolfberry and alfalfa in arid regions and provide insights into optimizing water and soil resource management for sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

The distribution of vegetation in coastal wetlands is significantly influenced by soil properties. However, the mechanisms of how soil characteristics impact the physiological processes of Tamarix chinensis forests remain underexplored. This study examined changes in the soil physicochemical properties and structural attributes of natural T. chinensis forests in the Yellow River Delta with increasing distance from the shoreline. T. chinensis trees were classified into healthy, intermediate, and dying categories based on growth potential, and dynamic changes in salt ions and non-structural carbohydrates (NSCs) were investigated. Results indicated that increasing distance from the shoreline corresponded to decreased soil salinity and pH, and increased soil moisture. T. chinensis mortality rate decreased, while tree height and ground diameter increased with distance. Soil salt content was positively correlated with T. chinensis mortality, but negatively correlated with tree height and ground diameter. Trees with lower growth potential had higher Na+ but lower K+ and K+/Na+ ratio. Soil salt content was positively correlated with root and stem Na+, while soil moisture was positively correlated with leaf NSCs. These findings suggest that soil salt content and moisture significantly influence T. chinensis ion absorption and NSC accumulation, with sodium toxicity being a key factor in the spatial distribution of T. chinensis forests. [ABSTRACT FROM AUTHOR]

The soil water retention curve (SWRC) is a vital soil property used to evaluate the soil's water holding capacity, a critical factor in various applications such as determining soil water availability for plants, soil conservation and management, climate change adaptation, and mitigation of flood risks. Estimating SWRC directly in the field and laboratory is a time-consuming and laborious process and requires numerous instruments and measurements at a specific location. In this context, various estimation approaches have been developed, including pedotransfer functions (PTFs), over the past three decades to estimate soil water retention and its associated properties. Despite the efficiencies, PTFs and semi-physical approach-based models often have several limitations, particularly in the dry range of the SWRC. PTFs-based modeling has become a key research topic due to readily available soil data and cost-effective methods for deriving essential soil parameters, which enable more efficient decision-making in sustainable land-use management. Therefore, advancement and adjustment are necessary for reliable estimations of the SWRC from readily available data. This article reviews the evaluation of the current and past PTFs for estimating the SWRC. This study aims to evaluate PTF techniques and semi-physical approaches based on soil texture, bulk density, porosity, and other related factors. Additionally, it also assesses the performance and limitations of various common semi-physical models proposed and developed by Arya and Paris, Haverkamp and Parlange, the Modified Kovács model by Aubertin et al., Chang and Cheng, Meskini-Vishkaee et al., Vidler et al., and Zhai et al. This assessment will be effective for researchers in this field and provide valuable insight into the importance of new PTFs for modeling SWRC. [ABSTRACT FROM AUTHOR]

Soil salinization is a critical issue impacting agriculture, particularly in arid and semi-arid regions. The objective of this study was to evaluate the effects of different drip irrigation and fertilization treatments on soil water and salt dynamics, maize water use efficiency, and crop yield in the saline–alkali soils of northern Ningxia, China. Over three years, four irrigation treatments were tested: CK (flood irrigation, 810 mm), W1 (low-volume drip irrigation, 360 mm), W2 (medium-volume drip irrigation, 450 mm), and W3 (high-volume drip irrigation, 540 mm). The results demonstrate that treatments W2 and W3 significantly increased soil moisture content at depths of 0–20 cm and 60–100 cm compared to CK, facilitating uniform salt leaching in the 0–40 cm soil layer. However, in the 40–100 cm layer, decreased porosity and upward moisture movement hindered salt migration, resulting in subsurface salt accumulation. Furthermore, drip irrigation combined with fertilization significantly reduced phosphorus fixation and nitrogen leaching, enhancing nutrient availability. This led to a reduction in underground leakage and surface evaporation by up to 39.63%, while water use efficiency improved by 18.97% to 55.13%. By the third year, grain yields under drip irrigation treatments increased significantly compared to CK, with W3 showing the highest gains (up to 21.90%). This study highlights the potential of integrating drip irrigation and fertilization as an effective strategy for managing saline–alkali soils, improving water use, and increasing crop productivity, providing valuable insights for sustainable agricultural practices. [ABSTRACT FROM AUTHOR]

In order to study the influence of fissure morphology on soil moisture-content changes under different fissure types, this study established HYDRUS 2.0 numerical models of stepped fissures and planar fissures with different fissure widths and depths based on the experimental condition parameters obtained from physical simulation tests. Then, we simulated the spatial and temporal variation rules of soil moisture around the fissures. The results showed a high level of agreement between the HYDRUS numerical simulations and actual measurements, indicating that the model accurately reflects the movement of soil moisture near fissures. The study found that ground fissures affected the spatial distribution of soil moisture, leading to an increased rate of moisture loss in the deep soil near the fissure walls. Moreover, larger fissures had greater horizontal and vertical effects on soil moisture. The soil moisture content is lower closer to the fissure walls. As the soil depth increased, the influence of the fissures gradually diminished. For planar fissure with a depth of 50 cm, the soil moisture content was 30.6%, 17.8%, and 8.4% lower at depths of 10, 30, and 50 cm, respectively, compared to a fissure with a depth of 10 cm. For a stepped fissure with a depth of 50 cm, the soil moisture content was 29.2%, 20.9%, and 13.9% lower at depths of 10, 30, and 50 cm, respectively, compared to a fissure with a depth of 10 cm. Under the same conditions of fissure width and depth, stepped fissures exhibit faster moisture loss, and the larger the fissure, the more significant the additional moisture loss compared to planar fissures. [ABSTRACT FROM AUTHOR]