Soil Moisture Conditions Research Articles

The impacts of cover crop mixes on the penetration resistance model of an Oxisol under no-tillage

Soil penetration resistance is used as an indicator of mechanical resistance to root growth into the soil matrix. However, penetration resistance measured only under wet soil conditions may not identify the effects of cover crops on soil structure. We aimed to determine the impact of individual and mixes of cover crops on soil penetration resistance as a function of water content and bulk density in an Oxisol under no-tillage in southern Brazil. Six treatments of individual and mixed cover crops were tested: (i) black oat; (ii) ryegrass; (iii) forage radish; (iv) wheat; (v) Fibrous-rooted crop mix: with 80 % fibrous-rooted and 20 % tap-rooted plants; and (vi) Tap-rooted crop mix: 40 % fibrous-rooted and 60 % tap-rooted plants. Soil cores were collected from a depth of 0–0.10 and 0.10–0.20 m and soil penetration resistance was evaluated under four soil water matric potentials (−6, −33, −100, and −500 kPa). Soil penetration resistance (Q) data for each treatment were fitted as a function of bulk density (ρ) and water content (θ) [Q=f(ρ, θ)]. The soil penetration resistance model was a non-linear equation (i.e., a double power function, with a negative exponent for water content and a positive exponent for bulk density). Under a given combination of bulk density and water content values, soil penetration resistance was higher after single crops than crop mixes, indicating a crop-mediated soil strengthening process. The cover crop mixes increased the macroporosity, resulting in an adequate soil physical quality for successional crops such as soybean, although no differences were observed for cover crops at soil water matric potentials of −60 hPa and −330 hPa when soil penetration resistance was used as a static measurement. The modelling of the soil resistance to penetration, as a function of soil bulk density and soil water content, showed that cover crops changed soil cohesion and reduced the impact of drying on soil strength when compared to the single cropping systems, indicating that soil penetration resistance should be modelled under a broad range of water contents, instead of only under a specific soil water content, to quantify the impacts of cover crops on soil strength.

A Soil Moisture and Vegetation-Based Susceptibility Mapping Approach to Wildfire Events in Greece

Wildfires in Mediterranean areas are becoming more frequent, and the fire season is extending toward the spring and autumn months. These alarming findings indicate an urgent need to develop fire susceptibility methods capable of identifying areas vulnerable to wildfires. The present work aims to uncover possible soil moisture and vegetation condition precursory signals of the largest and most devastating wildfires in Greece that occurred in 2021, 2022, and 2023. Therefore, the time series of two remotely sensed datasets–MAP L4 Soil Moisture (SM) and Landsat 8 NDVI, which represent vegetation and soil moisture conditions—were examined before five destructive wildfires in Greece during the study period. The results of the analysis highlighted specific properties indicative of fire-susceptible areas. NDVI in all fire-affected areas ranged from 0.13 to 0.35, while mean monthly soil moisture showed negative anomalies in the spring periods preceding fires. Accordingly, fire susceptibility maps were developed, verifying the usefulness of remotely sensed information related to soil moisture and NDVI. This information should be used to enhance fire models and identify areas at risk of wildfires in the near future.

Skillful seasonal prediction of the 2022–23 mega soil drought over the Yangtze River basin by combining dynamical climate prediction and copula analysis

An unprecedented soil moisture drought broke out over the Yangtze River basin (YRB) in the summer of 2022 and lasted until the spring of 2023, caused great economic losses and serious environmental issues. With the rapid onset and long-lasting duration, the mega soil drought challenges the current seasonal prediction capacity. Whether the state-of-the-art climate models provide skillful predictions of the onset, persistence and recovery of the 2022–23 mega soil drought needs to be assessed. Identified by the drought area percentage, here we show that the mega soil drought over the YRB started from July, 2022, reached the peak in August, and diminished in April, 2023. Combined with real-time predictions of monthly precipitation released by three climate models participating in the North American multi-model ensemble (NMME) project, we predict the monthly evolution of the 2022–23 soil drought through a joint distribution between precipitation and soil moisture established by the copula method. The results indicate that the NMME/copula prediction well reproduced the spatiotemporal evolution of the mega soil drought at 1 month lead. Using the climatological prediction that relies on the information of initial soil moisture conditions as the reference forecast, the Brier skill score (BSS) values for NMME multi-model ensemble are 0.26, 0.23 and 0.2 for the forecast lead times increased from 1 to 3 months during the entire soil drought period. Specifically, the BSS is 0.14 at 2 months lead during drought onset stage, and 0.26 at 3 months lead during persistence stage, while it is close to zero at all leads during the recovery stage. Our study implies that climate models have great potential in probabilistic seasonal prediction of the onset and persistency of mega soil drought through combining with the copula method.

Endophytes Alleviate Drought-Derived Oxidative Damage in Achnatherum inebrians Plants Through Increasing Antioxidants and Regulating Host Stress Responses

Endophytes generally increase antioxidant contents of plants subjected to environmental stresses. However, the mechanisms by which endophytes alter the accumulation of antioxidants in plant tissues are not entirely clear. We hypothesized that, in stress situations, endophytes would simultaneously reduce oxidative damage and increase antioxidant contents of plants and that the accumulation of antioxidants would be a consequence of the endophyte ability to regulate the expression of plant antioxidant genes. We investigated the effects of the fungal endophyte Epichloë gansuensis (C.J. Li & Nan) on oxidative damage, antioxidant contents, and expression of representative genes associated with antioxidant pathways in Achnatherum inebrians (Hance) Keng plants subjected to low (15%) and high (60%) soil moisture conditions. Gene expression levels were measured using RNA-seq. As expected, the endophyte reduced the oxidative damage by 17.55% and increased the antioxidant contents by 53.14% (on average) in plants subjected to low soil moisture. In line with the accumulation of antioxidants in plant tissues, the endophyte increased the expression of most plant genes associated with the biosynthesis of antioxidants (e.g., MIOX, crtB, gpx) while it reduced the expression of plant genes related to the metabolization of antioxidants (e.g., GST, PRODH, ALDH). Our findings suggest that endophyte ability of increasing antioxidant contents in plants may reduce the oxidative damage caused by stresses and that the fungal regulation of plant antioxidants would partly explain the accumulation of these compounds in plant tissues.

Farmland mulching and optimized irrigation increase water productivity and seed yield by regulating functional parameters of soybean (Glycine max L.) leaves

In both arid and semi-arid regions, adopting field mulching can effectively optimize soil moisture distribution, enhance crop yields, and improve water productivity. While acknowledging its advantages, field mulching seems insufficient for maintaining high crop productivity due to the increasing frequency of extreme weather. Furthermore, drought often coincides with critical crop growth stages, necessitating the implementation of agricultural irrigation to ensure normal crop growth. Accordingly, we conducted a three-year field experiment from 2021 to 2023 including three typical field mulching methods (no mulching, NM; straw mulching, SM; plastic film mulching, FM) and three supplementary irrigation strategies (irrigated at the branching stage (V4), W1; irrigated at the pod-filling stage (R2), W2; irrigated at both the V4 and R2 stage, W3). Throughout the entire growth period, we monitored soil moisture conditions for each treatment, measured leaf physiological parameters at crucial growth stages, and assessed soybean yields and water productivity (WP). Our findings indicated that, relative to SM and NM, FM maintains optimal soil moisture balance, augments chlorophyll content, and enhances photosynthesis, resulting in an average yield increase of 17.0% and 38.3% over three growing seasons. Additionally, supplementary irrigation also significantly affects the growth and seed yield of soybean. FMW2 achieved the higher seed yield (4307.5 kg ha−1, 3-year averaged), had insignificant difference with the highest seed yield of 4568.6 kg ha−1, both significantly higher than other treatments. Similarly, the leaf area index, chlorophyll content, net photosynthetic rate (Pn) and transpiration rate (Tr) also presented insignificant difference between FMW2 and FMW3, while WUEleaf (Pn/Tr) of FMW2 obviously higher than that of FMW3. As a result, FMW2 achieved the highest WP of 12.2 kg ha−1 mm−1 over the three growing seasons, compared to the three-year average of the other treatments, the increase ranges from 5.6% to 46.7%. In summary, the FMW2 treatment optimized water distribution to meet the water demands of soybeans during the reproductive growth stages, achieving a beneficial balance between soybean seed production and WP by regulating leaf functional parameters. Future research will explore more specific irrigation scheduling techniques (e.g., precision irrigation, deficit irrigation, and sensor-based irrigation management systems) while integrating innovative agricultural film materials (e.g., biodegradable films) to further enhance crop resilience and productivity under evolving climatic conditions.

Features of the Geoinformation Monitoring System Using Microwave and Optical Tools

The article discusses the issues of GIMS-technology that combines the methodology of GIS-technology and simulation modeling, giving it predictive functions when solving problems of environmental monitoring of the environment. The relationships between experimental data, algorithms and models of environmental processes are analyzed to implement effective operational control and diagnostics of the environment. Particular attention is paid to remote microwave sensing sensors, which ensure the implementation of the functions of GIMS-technology when solving specific problems of monitoring natural systems. For example, the use of microwave technology makes it possible to quickly obtain data on the state of soil moisture, and salinity water bodies, assess the possibility of critical hydrological situations and monitor the condition of hydraulic structures in regions with increased hydrological hazard. It is noted that GIMS-technology ensures the restoration of the spatial distribution of geoecosystem characteristics based on the data of route and ground measurements, which are characterized by fragmentation in space and episodicity in time. GIMS-technology makes it possible to overcome situations of irreducible information uncertainty, using the evolutionary modeling technique for this. The use of optical sensors and spectroellipsometry and spectrophotometry technologies makes it possible to calculate indicators of the quality of water resources, assessing the content of chemical elements in water and the presence of pollutant stains on the water surface.

Association Study of SNPs Markers to Traits Linked to Drought Stress Tolerance in Potato

Potato (Solanum tuberosum L.) is the third most important food crop in the world and its production is constantly threatened by periods of drought. In this study, 115 potato genotypes were evaluated among 56 of the andigena group and 59 phureja to observe genetic variation in physiological traits that may be linked to drought tolerance. Eleven attributes were evaluated in genotypes tolerant and susceptible to drought stress. The genotypic variation of the materials was evaluated with a total of 968 SNP-type molecular markers, subjected to two soil moisture conditions. Association analysis was performed using the GWASpoly program to determine possible allelic interactions between genotypes with different ploidy levels. Analyses were corrected using population structure and parentage matrix as fixed cofactors. Significant SNPs were associated with phenotypic characteristics under contrasting water conditions for traits such as days to flowering, relative water content, tuber number and plant height. MYC-type transcription factors were associated with plant height, number of tubers per plant and plant water balance, demonstrating the multifunctionality of these regulatory proteins. While the HOS1 gene could be linked to the reduction of flowering time. These results will be the starting point for future studies for the validation of the markers, so that they can be used in potato drought stress breeding programs.

Screening of Wheat Genotypes for Water Stress Tolerance Using Soil–Water Relationships and Multivariate Statistical Approaches

Drought stress constricts crop production around the world. Employing high-yielding cultivars with drought tolerance might be the ideal professional approach to coping with its detrimental outcomes. As a result, the current study was performed to investigate the sensitivity and tolerance of nine wheat genotypes to drought stress. In a randomized block design experiment, nine wheat genotypes were subjected to four water treatments: 100%, 85%, 70%, and 55% of the available water (AW). Four water regimes in two growing seasons were counted as eight environmental zones. The leaf’s water relations and photosynthetic pigment were estimated, as well as growth and yield parameters. Univariate and multivariate statistical approaches, including the new method of multi-trait genotype–ideotype distance (MGIDI), were used for evaluation. The analysis of variance revealed that genotype, environment, and their interactions had a highly significant effect on all traits. The same trend was shown by the additive main effects and multiplicative interaction (AMMI) analysis of variance for grain yield across the environments. The AMMI biplot study indicated that the G8 genotype is the most stable in terms of water stress. The G7 genotype can withstand droughts up to 55% of the available water, while the G8 and G3 genotypes can withstand droughts up to 70% of the available water. Based on all examined traits, this index was used to identify the stable genotypes G7, G8, and G3, which can therefore be suggested for cultivation during drought conditions. Furthermore, we found a positive correlation between the MGIDI, ANOVA, and tolerance index results, indicating that the same desirable genotypes of G7 and G8 were identified by these procedures as being highly tolerant and stable across a range of soil moisture conditions. Based on MGIDI analysis, we can recommend that the G7 genotype exhibits higher grain yield and yield-related traits with the best drought-tolerant indices.

Tree growth potential and its relationship with soil moisture conditions across a heterogeneous boreal forest landscape

Forest growth varies across landscapes due to the intricate relationships between various environmental drivers and forest management. In this study, we analysed the variation of tree growth potential across a landscape scale and its relation to soil moisture. We hypothesised that soil moisture conditions drive landscape-level variation in site quality and that intermediate soil moisture conditions demonstrate the highest potential forest production. We used an age-independent difference model to estimate site quality in terms of maximum achievable tree height by measuring the relative change in Lorey’s mean height for a five year period across 337 plots within a 68 km2 boreal landscape. We achieved wall-to-wall estimates of site quality by extrapolating the modelled relationship using repeated airborne laser scanning data collected in connection to the field surveys. We found a clear decrease in site quality under the highest soil moisture conditions. However, intermediate soil moisture conditions did not demonstrate clear site quality differences; this is most likely a result of the nature of the modelled soil moisture conditions and limitations connected to the site quality estimation. There was considerable unexplained variation in the modelled site quality both on the plot and landscape levels. We successfully demonstrated that there is a significant relationship between soil moisture conditions and site quality despite limitations associated with a short study period in a low productive region and the precision of airborne laser scanning measurements of mean height.

Influence of cultivation methods on the soil aggregate state in the context of weed development in winter wheat plantations

Weed control in winter wheat crops is an important issue. There is a risk of increasing populations of certain weed species that are resistant to some of herbicides used for winter wheat crops. This could be controlled by a combination of agronomic, mechanical, chemical, and biological methods. After introducing winter wheat into the rotation and improving tillage, the weediness of regular black soils with perennial root and emerged weeds were significantly reduced. The formation of nodal and rudimentary roots had a significant effect on the productivity of winter wheat under different soil moisture conditions. The highest yield of winter wheat was obtained when sown at the optimum time, with higher stem density and ear productivity due to better grain fullness. We studied what effects did the tillage methods have on the aggregate state of the soil in relation to weed development in winter wheat crops, finding that the structural and aggregate composition of the soil played an important role in winter wheat crops, influencing both the development of the crop root system and the water-physical balance of the chernozem, as well as naturally influencing the course of erosion processes in the experimental plots, and having a universal dynamic in terms of adaptation of aggregation and disaggregation processes. Prolonged mechanical stress on soil can cause destruction of its structure. For instance, continuous ploughing or moldboardless tillage with little or no manure application may permanently reduce soil fertility by increasing humus mineralisation. Subsequently, these factors may cause a significant decline in the soil's structural and aggregate composition, resulting in larger amounts of dusty particles smaller than 0.25 mm and cloddy particles larger than 10–12 mm. The soil's structural condition before sowing winter wheat in early September, on average for 2011–2016, indicates increased dispersion of the tilth layer (0–10 cm) in the experimental variants where shallow disc tillage of 10–12 cm was applied. Increase in the number of clods larger than 10 mm in the areas where moldboardless tillage had been applied can be attributed to significant soil drainage. The soil's aggregate state was rated as good, with 8.7% in the 0–10 cm soil layer and 1.7% of clods > 10 mm in the 0–30 cm layer. In 2014–2016, it was rated as satisfactory, with 7.4% and 9.8% of clods > 10 mm, respectively. Shallow disc cultivation resulted in slightly worse indicators: 6.6% and 8.3% of clods > 10 mm in soil layer 0–10 cm and 0–30 cm, respectively, in 2011–2013; and 7.2% and 6.9% of clods > 10 mm, respectively, in 2014–2016. In general, the parameters of optimal structural condition were positive. The tillage method used had a considerable effect on weed growth and development, particularly for those with a root and rhizome structure. It also affected the prevalence and development of pests and diseases in winter wheat. Agrotechnical methods of weed control do not guarantee complete destruction of weeds. Mechanical moldboardless tillage to the depth of 14–16 cm and disc tillage to the depth of 10–12 cm left the fields with 4.1 to 8.8 annual weeds per square meter and 1.3 to 3.3 specimens of harmful root weeds such as Convolvulus arvensis, Lactuca tatarica and Cirsium arvense. Mechanical moldboardless tillage to the depth of 14–16 cm and disc tillage to the depth of 10–12 cm left the fields with 4.1 to 8.8 annual weeds per square meter and 1.3 to 3.3 specimens of harmful root weeds such as Convolvulus arvensis, Lactuca tatarica and Cirsium arvense. Post-harvest residues (4–5 t/ha) can provide almost complete protection against weeds by covering the soil surface. However, pests and diseases may spread more easily due to preservation of fungal spores on the surface of plant residues and preservation of pest larvae in the straw and soil. The distribution of weed seeds in the soil was altered when the rotational tillage of common chernozems in winter wheat cultivation technology had been replaced with energy–saving minimum tillage (shallow flat-cutting disc tillage). This resulted in the concentration of most of the weed seeds (85–90%) in the upper soil layer (0–10 cm).

Combing transfer learning with the OPtical TRApezoid Model (OPTRAM) to diagnosis small-scale field soil moisture from hyperspectral data

Accurate, timely, and continuous soil moisture information is helpful for crop stress diagnosis and irrigation management decision. OPtical TRApezoid Model (OPTRAM) based on optical satellite data has been proven to be an effective method for assessing soil moisture status. However, the applicability of OPTRAM to small-scale field soil moisture assessment remains to be explored. In this study, we propose a strategy for the genetically parameterized OPTRAM and evaluate its applicability on Unmanned Aerial Vehicle (UAV) high-resolution hyspectral data. The results showed that: (1) When OPTRAM was used to genetically parameterized with PROSAIL generated dataset, 46 characteristic narrowband bands (|R|= 0.52–0.78) were determined in the spectral region of near infrared (NIR) (750–850 nm) and SWIR (1060–1080 and 1450–1500 nm); (2) By fine-tuned soil moisture estimation model using transfer learning strategy, the reliable soil moisture estimation was achieved in three crops (R2=0.57–0.64; RMSE=0.008–0.022 m3m−3);(3) Compared to soil moisture estimation model using a single spectral region (NIR or SWIR), the DSWC model that combine NIR and SWIR was more effective for tracking soil moisture; (4) The scale effect was observed when the fine-tuned soil moisture estimation model was applied on the high-resolution UAV images. The model performance was stable in pixel size of 1–7 cm and began to drop at pixel size of 11 cm. The above results advance the application of OPTRAM on small farmland soil moisture assessment and demonstrate the application potential of OPTRAM on narrow-band hyperspectral data. This study provides a new candidate for the use of hyperspectral data to estimate soil moisture, and scientific support for precision agriculture and irrigation scheduling.

Interpretable and explainable hybrid model for daily streamflow prediction based on multi-factor drivers.

Streamflow time series data typically exhibit nonlinear and nonstationary characteristics that complicate precise estimation. Recently, multifactorial machine learning (ML) models have been developed to enhance the performance of streamflow predictions. However, the lack of interpretability within these ML models raises concerns about their inner workings and reliability. This paper introduces an innovative hybrid architecture, the TCN-LSTM-Multihead-Attention model, which combines two layers of temporal convolutional networks (TCN) followed by one layer of long short-term memory (LSTM) units, integrated with a Multihead-Attention mechanism for predicting streamflow with streamflow causation-driven prediction samples (RCDP), employing local and global interpretability studies through Shapley values and partial dependency analysis. The find_peaks method was used to identify peak flow events in the test dataset, validating the model's generality and uncovering the physical causative patterns of streamflow. The results show that (1) compared to the LSTM model with the same hyperparameter settings, the proposed TCN-LSTM-Multihead-Attention hybrid model increased the R2 by 52.9%, 2.5%, 43.1%, and 10.7% respectively at four stations in the test set predictions using RCDP samples. Moreover, comparing the prediction results of the hybrid model under different samples in Hengshan station, the R2 for RCDP increased by 5.06% and 1.22% compared to streamflow autoregressive prediction samples (RAP) and meteorological-soil volumetric water content coupled autoregressive prediction samples (MCSAP) respectively. (2) Historical streamflow data from the preceding 3days predominantly influences predictions due to strong autocorrelation, with flow quantity (Q) typically emerging as the most significant feature alongside precipitation (P), surface soil moisture (SSM), and adjacent station flow data. (3) During periods of low and normal flow, historical data remains the most crucial factor; however, during flood periods, the roles of upstream inflow and precipitation become significantly more pronounced. This model facilitates the identification and quantification of various hydrodynamic impacts on flow predictions, including upstream flood propagation, precipitation, and soil moisture conditions. It also elucidates the model's nonlinear relationships and threshold responses, thereby enhancing the interpretability and reliability of streamflow predictions.

Runoff generation in a semiarid environment: The role of rainstorm intra-event temporal variability and antecedent soil moisture

Rainfall intensity and antecedent soil moisture are key variables affecting the initiation and accumulation of runoff, and therefore, impact on the occurence flood events. We used time series of rainfall intensities characterizing rainstorms with different mean, standard deviation, and skewness to simulate runoff response of a sealed loamy soil profile under various initial soil moisture conditions. We found that shifting from wet to dry initial soil moisture leads to a 300 % increase in ponding time and a 350 % decrease in total runoff. Intense rainfall events catalyze runoff development and runoff occurs earlier with increasing mean, maximum intensity, and variance of rainfall. Higher variance in intra-event storm-intensity temporal distribution yields more runoff. Earlier runoff formation aligned with negatively skewed storm structures, but largest cumulative runoff resulted from storms displaying near-zero skewness values. The combination between rainfall intensification and extended dry periods between storms might reduce potential runoff. These insights improve our understanding of anticipated impacts of climate variations on floods and may also contribute to ecosystem health evaluations, and bolster predictive capabilities of surface processes.

Extreme rainfall and landslides as a response to human-induced climate change: a case study at Baixada Santista, Brazil, 2020

In March 2020, an extreme rainfall in Baixada Santista, Brazil, led to a series of landslides affecting more than 2800 people and resulting losses exceeding USD 43 million. This attribution study compared extreme rainfall in two large ensembles of the UK Met Office Hadley Centre HadGEM3-GA6 model that represented the event with and without the effects of anthropogenic climate change. Antecedent rainfall conditions on two different timescales are considered, namely extreme 60-day rainfall (Rx60day) which relates to the soil moisture conditions and extreme 3-day rainfall (Rx3day) which represents landslide triggering heavy rainfall. In the scenario including both natural and human-induced factors the antecedent 60 day rainfall became 74% more likely, while the short-term trigger was 46% more likely. The anthropogenic contribution to changes in rainfall accounted for 20–42% of the total losses and damages. The greatest economic losses occurred in Guarujá (42%), followed by São Vicente (30%) and Santos (28%). Landslides were responsible for 47% of the homes damaged, 85% of the homes destroyed, all reported injuries, and 51% of the deaths associated with heavy rainfall. Changes in land cover and urbanization showed a pronounced increase in urbanized area in Guarujá (107%), São Vicente (61.7%) and Santos (36.9%) and a reduction in farming area. In recent years, the region has experienced an increase in population growth and a rise in the proportion of irregular and/or precarious housing in high-risk areas. Guarujá has the highest number of such dwellings, accounting for 34.8%. Our estimates suggest that extreme precipitation events are having shorter return periods due to climate change and increased urbanization and population growth is exposing more people to these events. These findings are especially important for decision-makers in the context of disaster risk reduction and mitigation and adaptation to climate change.

Effects of biochar versus film mulching on soil hydrothermal properties and wheat crop performance in semi‐arid loess

AbstractFilm mulching and biochar have been applied as effective measures for increasing crop yields in arid and semi‐arid areas for many years. However, the effects of the temporal and spatial distributions of soil hydrothermal properties on crop yields are still unclear under film mulching and biochar addition. Thus, we conducted a field experiment with winter wheat on the Loess Plateau of China for two years (2020–2022) with three treatments: control, film mulching, and biochar. The results demonstrated that film mulching and biochar addition increased the average soil temperature in the 0–50 cm soil depth throughout the whole growth period and the influence depth exceeded 50 cm. Biochar addition only significantly increased soil temperature in the overwintering stage (p < 0.05). Film mulching increased the maximum and minimum temperatures in the 0–50 cm soil depth at seedling stage. Film mulching and biochar increased average ≥10°C accumulated soil temperature by increasing the ≥10°C accumulated soil temperature in the daytime and nighttime, and the number of days with a daily soil temperature ≥10°C during the whole growth period. Film mulching improved soil water storage in the 0–300 cm soil depth in each growth stage during both years, and also increased the wheat grain yield, aboveground biomass, and water use efficiency. Biochar addition increased the wheat grain yield and aboveground biomass of two years compared with control, but the increases were not significant (p > 0.05). In addition, correlation analysis showed that adequate temperatures in the 0–50 cm soil depth during the seedling and overwintering stages, and suitable soil moisture conditions in the 0–300 cm soil depth before sowing, jointing, and filling stages were important factors for increasing wheat grain yields under film mulching. In summary, film mulching mainly regulated the soil temperature in the 0–50 cm soil depth and moisture conditions in the 0–300 cm soil depth during different growth stages to increase grain yields. Film mulching has more obvious effects on moisture regulation, temperature regulation, and yield increases than biochar addition. Some environmentally friendly measures (such as conservation agriculture) with the same yield improving effect as mulching are also recommended to explore and promote in theLoess Plateau region.

Soil moisture status and foliar nutrition on growth, yield, quality and economics of sunflower (Helianthus annuus L.) in Vertisol of N-E Karnataka

Soil moisture status and foliar nutrition on growth, yield, quality and economics of sunflower (Helianthus annuus L.) in Vertisol of N-E Karnataka

Responses of soil moisture at different topographic positions to rainfall events along a steep subtropical forested hillslope

AbstractUnderstanding the dynamic response of soil moisture to rainfall is crucial for describing hydrological processes at the hillslope scale. However, because of sparse monitoring coupled with the complexity of water movement and steep topography, the findings of rainfall‐related soil moisture dynamics have not always been consistent, indicating a need for systematic investigations of soil moisture dynamics and infiltration patterns following rainfall inputs at multiple topographic positions along a hillslope. This study aimed to examine the nature of these responses by characterizing and quantifying the response amplitude, rate and time for 37 large rainfall events at 25 combinations of topographic positions and soil depths along a steep forested hillslope. Our results showed that soil moisture responses under different rainfall patterns could be attributed to one or the other rainfall characteristics, such as rainfall intensity and amount. However, soil moisture dynamics at different hillslope positions after rainfall varied widely due to the controls of soil properties, topography, and non‐equilibrium flow. Preferential flow was more evident under dry initial soil conditions than under wet initial soil conditions. Findings of this study reveal that the dynamic response patterns of soil moisture to rainfall do not always follow topographic controls, which can improve our understanding of water cycling related to the infiltration process at the hillslope scale, and support water resources management in subtropical mountain ecosystems.

Evaluation of soil moisture, irrigation parameters and post nutrient status influenced in six fallow crops with limited number of irrigations

Evaluation of soil moisture, irrigation parameters and post nutrient status influenced in six fallow crops with limited number of irrigations

On the Sensitivity of the Potential Evapotranspiration of Egypt to Different Initial Conditions of the Soil Moisture Using a High-resolution Regional Climate Model

The present study investigated the sensitivity of the Potential Evapotranspiration (PET) of Egypt to different initial conditions of soil moisture using a high-resolution Regional Climate Model (RegCM4). To address this issue, two 32-year simulations were conducted from 1979 to 2010. The first two years were considered as spin-up. In the first simulation, the RegCM4 was initialized with the satellite product ESACCI (ESA) and the RegCM4 was initialized with version 3 of the Century Reanalysis Product (CEN) in the second simulation. The PET was computed using a calibrated version of the Hargreaves–Samani (HS) equation. In the two simulations, the RegCM4 was configured with the Community Land Model version 4.5 (CLM45). Era-Interim Reanalysis of 1.5 degrees (EIN15) was used to downscale the RegCM4 with 25 km grid spacing. The ERA5-based product (ERA5) was used as the observational dataset. The results showed that switching between ESA and CEN didn’t induce a notable influence on the daily maximum air temperature. Regarding the daily minimum air temperature, the CEN outperforms the ESA concerning the Climate Research Unit (CRU). In comparison with the ERA5 product, the CEN was able to reduce the PET negative bias (0.8 to 1.8 mm day-1) better than the one noted in the ESA (0.8 to 3 mm day-1). On a point scale, the performance of the ESA/CEN varies with the location and month. Such a point was confirmed using different statistical metrics such as mean bias, Pearson correlation coefficient and standard deviation ratio. In conclusion, the CEN can be recommended to initialize the RegCM4 to ensure a reliable estimation of the PET of Egypt either in the present climate or under different future scenarios.

Results of a comparative study of coulter groups of a seeder for strip sowing of grass seeds in the sod

For the effective use of sod seeders SDK in conditions of degraded forage lands, it is necessary to modernize the design of their coulter group to work in conditions of high soil moisture and increased content of plant residues in it. A method of strip sowing is proposed, which is based on the removal of the sowing working elements from under the casing of a milling furrow opener, and a design and technological scheme of the coulter group with a shoe opener mounted on a suspension mechanism in the form of torsion springs. The coulter group includes a mounting bracket on a seeder, a suspension mechanism, shoe openers, rollers, mechanisms for adjusting the position of coulters in the vertical and horizontal planes and the forces of deepening coulters and the pressure of rollers on the soil. Compared to the coulter group of SDK seeders, its weight (19.6 kg) is reduced by 3.8 kg while the total length of the seeder increases by 0.12 m. To assess the efficiency of the modernized coulter group of the sod seeder, experimental studies were carried out in the field, during which the quality indicators of seed placement were determined when using a serial coulter group of SDK seeders and a prototype coulter group. Comparative studies of coulter groups of a sod seeder showed that when sowing Eastern galega, the depth of seed placement complies with agrotechnical requirements and is: for the coulter group of SDK seeder – 19.4...22.4 mm, for the prototype - 18.6...19.5 mm, and for the prototype the value of the standard deviation is almost two times lower. The uniformity of the distribution of seeds over the width of the strip for the coulter group of the SDK seeder is 20.2...26.1 mm, for the prototype – 8.4...10.1 mm.