Soil Moisture Variability Research Articles

Effects of woodchip biochar on temperature sensitivity of greenhouse gas emissions in amended soils within a mountain vineyard

The utilization of biochar as a soil amendment holds promise for long-term carbon sequestration due to its elevated carbon content and persistent chemical structure. This characteristic has positioned biochar as a proposed nature-based solution for climate change mitigation. Nevertheless, the impact of biochar on soil greenhouse gas (GHG) emissions remains a subject of ongoing debate. In the present investigation, we evaluated the influence of conifer wood biochar on the fluxes of three GHGs, namely carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4), in a vineyard soil subjected to biochar-alone treatments (at rates of 25 and 50 t ha−1) and in combination with green waste compost (at a rate of 45 t ha−1). The experimental field was situated in northern Italy and was organized in a randomized block design. Soil GHG fluxes were monitored for two and a half years. Monthly flux measurements were conducted using a high-resolution multi-gas analyzer for 24 hours. Fluxes were, therefore, correlated with soil temperature to assess the influence of treatments on the sensitivity of GHG emissions to this pivotal environmental parameter. The findings demonstrated diminished temperature sensitivity in the initial experimental year across all GHG fluxes in soils amended with biochar and biochar-compost combination, in contrast to treatments lacking biochar (i.e., control and compost-alone treatments). Notably, the attenuation was most pronounced for N2O emissions, suggesting a potential role of biochar in mitigating the release of this gas. However, this effect did not persist in the second and third years of the experiment. Overall, biochar significantly contributed to a reduction in N2O fluxes and an increase in CO2 fluxes, but the effect was limited and temporary. Furthermore, biochar had no impact on CH4 fluxes. The discerned fluctuation in the impact of biochar over time can be attributed to the processes of biochar aging and/or the interannual variability in soil moisture.

Correlation between Soil Moisture Change and Geological Disasters in E’bian Area (Sichuan, China)

E’bian Yi Autonomous County is a mineral-rich area located in a complex geological structure zone. The region experiences frequent geological disasters due to concentrated rainfall, steep terrain, and uneven vegetation cover. In particular, during the rainy season, large amounts of rainwater rapidly accumulate, increasing soil moisture and slope pressure, making landslides and debris flows more likely. Additionally, human activities such as mining, road construction, and building can alter the original geological structure, exacerbating the risk of geological disasters. According to publicly available data from the Leshan government, various types of geological disasters occurred in 2019, 2020, 2022, and 2023, resulting in economic losses and casualties. Although some studies have focused on geological disaster issues in E’bian, these studies are often limited to specific areas or types of disasters and lack comprehensive spatial and temporal analysis. Furthermore, due to constraints in technology, funding, and manpower, geophysical exploration, field geological exploration, and environmental ecological investigations have been challenging to carry out comprehensively, leading to insufficient and unsystematic data collection. To provide data support and monitoring for regional territorial spatial planning and geological disaster prevention and control, this paper proposes a new method to study the correlation between soil moisture changes and geological disasters. Six high-resolution Landsat remote sensing images were used as the main data sources to process the image band data, and terrain factors were extracted and classified using a digital elevation model (DEM). Meanwhile, a Normalized Difference Vegetation Index–Land Surface Temperature (NDVI-LST) feature space was constructed. The Temperature Vegetation Drought Index (TVDI) was calculated to analyze the variation trend and influencing factors of soil moisture in the study area. The research results showed that the variation in soil moisture in the study area was relatively stable, and the overall soil moisture content was high (0.18 < TVDI < 0.33). However, due to the large variation in topographic relief, it could provide power and be a source basis for geological disasters such as landslide and collapse, so the inversion value of TVDI was small. The minimum and maximum values of the correlation coefficient (R2) were 0.60 and 0.72, respectively, indicating that the surface water content was relatively large, which was in good agreement with the calculated results of vegetation coverage and conducive to the restoration of ecological stability. In general, based on the characteristics of remote sensing technology and the division of soil moisture critical values, the promoting and hindering effects of soil moisture on geological hazards can be accurately described, and the research results can provide effective guidance for the prevention and control of geological hazards in this region.

Subsurface Drainage and Nitrogen Fertilizer Management Affect Fertilizer Fate in Claypan Soils

Sustainable nitrogen (N) fertilizer management practices in the Midwest U.S. strive to optimize crop production while minimizing N gas emission losses and nitrate-N (NO3-N) losses in subsurface drainage water. A replicated site in upstate Missouri from 2018 to 2020 investigated the influence of different N fertilizer management practices on nutrient concentrations in drainage water, nitrous oxide (N2O) emissions, and ammonia (NH3) volatilization losses in a corn (Zea mays, 2018, 2020)–soybean (Glyince max, 2019) rotation. Four N treatments applied to corn included fall anhydrous ammonia with nitrapyrin (fall AA + NI), spring anhydrous ammonia (spring AA), top dressed SuperU and ESN as a 25:75% granular blend (TD urea), and non-treated control (NTC). All treatments were applied to subsurface-drained (SD) and non-drained (ND) replicated plots, except TD urea, which was only applied with SD. Across the years, NO3-N concentration in subsurface drainage water was similar for fall AA + NI and spring AA treatments. The NO3-N concentration in subsurface drainage water was statistically (p < 0.0001) lower with TD urea (9.1 mg L−1) and NTC (8.9 mg L−1) compared to fall AA + NI (14.6 mg L−1) and spring AA (13.8 mg L−1) in corn growing years. During corn years (2018 and 2020), cumulative N2O emissions were significantly (p < 0.05) higher with spring AA compared to other fertilizer treatments with SD and ND. Reduced corn growth and plant N uptake in 2018 caused greater N2O loss with TD urea and spring AA compared to the NTC and fall AA + NI in 2019. Cumulative NH3 volatilization was ranked as TD urea > spring AA > fall AA + NI. Due to seasonal variability in soil moisture and temperature, gas losses were higher in 2018 compared to 2020. There were no environmental benefits to applying AA in the spring compared to AA + NI in the fall on claypan soils. Fall AA with a nitrification inhibitor is a viable alternative to spring AA, which maintains flexible N application timings for farmers.

Consistency of landscape compositional effects on microclimate, arthropods and plant performance across different years and regions

ContextReinforcement of agrobiodiversity in peri-urban areas requires a landscape lens. Relationships between land use composition and indicators of ecosystem services can depend on weather conditions and differ between regions.ObjectivesIn this study we present new empirical data on relationships between landscape composition and indicators of regulating and provisioning agroecosystem services. Furthermore, we check if these data are consistent between two different ecoregions and different years.MethodsWe apply an innovative methodology in a research landscape in the province of Antwerp (Flanders, Belgium) in 2021 with 1 m²-garden as phytometers along a landscape compositional gradient. Landscape composition at different scales is used as explanatory variable for microclimate variation, arthropod activity, leaf herbivory and crop yield in the 1 m²-gardens. Results are compared to an identical experiment in another ecoregion in East Flanders in 2018, 2019.ResultsWe found that the proportion of built-up areas is negatively related to local agroecosystem functioning. High-value herbaceous vegetation (e.g. extensive grasslands) promotes the activity of predators and high green vegetation buffers soil moisture and temperature variation, during dry and warm periods. Comparison between cases indicates that there is more consistency in the response of predatory invertebrates to the landscape composition than in the response of pollinators. The buffering effect of high green vegetation in the landscape increases when temperature and drought extremes occur.ConclusionsThe extent of high green vegetation can be enhanced at landscape level to maximise their ability to buffer extreme weather conditions. In peri-urban areas we should avoid further urban sprawl into the rural matrix and promote high-value herbaceous vegetation.

Seasonal Fluctuations in Plant-Parasitic Nematode Vertical Distributions and Their Interactions with Edaphic Factors in Vegetable Fields of South Georgia, U.S.A.

Plant-parasitic nematodes (PPNs) can be found deep in the soil profile, compounding nematode management decisions and detection. This study aimed to understand how seasonal fluctuations in edaphic factors are associated with the vertical distribution of PPNs in south Georgia's vegetable cropping systems. Five-core composite soil samples were taken monthly (March 2020 to February 2022) at three random locations in six vegetable fields. Fields represented three cropping systems (vegetable plasticulture, bare ground cucumber, and plastic bed watermelon rotation) and two regions (north and south) sampled from five 15-cm strata (0 to 15, 15 to 30, 30 to 45, 45 to 60, and 60 to 75 cm). Only soil temperatures and precipitation had seasonal fluctuations; the other edaphic factors were vertically stratified. Latitude and stratum had the strongest associations with nematode composition, showing a clear separation between the north and south regions. Variations in soil texture, porosity, moisture, and PPN vertical distribution suggested that the illuvial zone in the north region was the main factor in the differences observed between regions and strata. Seasonal fluctuations in vertical distribution were found among Meloidogyne incognita and Nanidorus spp. Higher abundances of deep-dwelling PPNs were limited to the south region in the winter for deep-dwelling M. incognita and summer and winter for Nanidorus spp., probably due to the illuvial zone barrier in the north region. Because most root-knot nematodes dwell at ≤30 cm during the summer, fumigant/nematicide applications are recommended during this season to minimize the risk of deep-dwelling escapees.

Surface Soil Moisture Estimation from Time Series of RADARSAT Constellation Mission Compact Polarimetric Data for the Identification of Water-Saturated Areas

Soil moisture is one of the main factors affecting microwave radar backscatter from the ground. While there are other factors that affect backscatter levels (for instance, surface roughness, vegetation, and incident angle), relative variations in soil moisture can be estimated using space-based, medium resolution, multi-temporal synthetic aperture radar (SAR). Understanding the distribution and identification of water-saturated areas using SAR soil moisture can be important for wetland mapping. The SAR soil moisture retrieval algorithm provides a relative assessment and requires calibration over wet and dry periods. In this work, relative soil moisture indicators are derived from a time series of the RADARSAT Constellation Mission (RCM) SAR compact polarimetric (CP) data over reclaimed areas of an oil sands mine in Alberta, Canada. An evaluation of the soil moisture product is performed using in situ measurements showing agreement from June to September. The surface scattering component of m-chi CP decomposition and the RL SAR products demonstrated a good agreement with the field data (low RMSE values and a perfect alignment with field-identified wetlands).

Assessment of Global Antibiotic Exposure Risk for Crops: Incorporating Soil Adsorption via Machine Learning.

The overuse and misuse of antibiotics could significantly increase their accumulation in soils. Consequently, antibiotics possibly enter food chain through crop uptake, posing a threat to global food security. Assessing the exposure risks of antibiotics for crops is crucial for addressing this global issue. In this study, we assessed global antibiotic exposure risk for crops, incorporating a machine learning adsorption model based on 4893 data sets from nine antibiotics. The optimized machine learning adsorption model, using the eXtreme Gradient Boosting algorithm and the class-specific modeling strategy, demonstrated relatively good performance. Notably, we introduced unsaturated soil conditions and considered spatiotemporal variations in soil moisture and temperature for the first time in such a risk assessment. Global distributions of antibiotic exposure risk for crops were predicted for March, June, September, and December. The results indicate that soil moisture significantly influences the exposure risk assessment. Relatively high exposure risk for crops was observed during months with colder local temperatures: generally June for the Southern Hemisphere and December for the Northern Hemisphere. The resulting map highlights high-risk agricultural regions, including southern Canada, western Russia, and southern Australia.

Sex-specific phosphorus (P)-use and -acquisition in dioecious Populus euphratica as affected by soil moisture levels

Abstract Dioecious plants show sexual dimorphism in their phosphorus (P) availability responses. However, the understanding of sex-specific strategies for P utilization and acquisition under varying soil moisture levels remains unclear. Here, we assessed a range of root functional traits, soil P properties, total foliar P concentration ([P]), and leaf chemical P fractions – inorganic P ([Pi]), metabolite P ([PM]), lipid P ([PL]), nucleic acid P ([PN]), and residual P ([PR]) – as well as other leaf functional traits in female and male trees under different soil moisture levels (25% for high and 7% for low). Our results showed that females had larger specific root length (SRL) under well-watered conditions, resulting in greater root foraging capacity. This led to a 36.33% decrease in soil active inorganic P in the rhizosphere and a 66.86% increase in total foliar [P], along with all five foliar chemical P fractions ([Pi], [PM], [PL], [PN], and [PR]) compared to males. However, males exhibited significantly higher photosynthetic P utilization efficiency (PPUE) than females. Especially under low soil moisture levels, males exhibited a significant reduction in soil active organic P, coupled with a large increase in the exudation of soil phosphatases and carboxylates. Furthermore, the proportion of metabolite P in total foliar [P] was 41.96% higher in males than in females. Mantel and Spearman correlation analyses revealed distinct coordination and trade-offs between foliar P fraction allocation and below-ground P acquisition strategies between the two sexes. Leveraging these sex-specific strategies could enhance the resilience of dioecious populations in forest plantations facing climate-induced variability.

Natural forming of vegetation cover on black coal mining dumps in the environs of Kopeysk (Chelyabinsk Oblast)

The article considers the current forming of vegetation and biotopes as a result of natural overgrowth of territories disturbed during black coal mining in the environs of Kopeysk town (Chelyabinsk Oblast). The 88 species of vascular plants were detected on the waste banks and spaces between them, the 7 species of vascular plants are woody species. It has been established that in the process of natural overgrowth of dumps, forest and meadow plant communities are actively formed from pioneer ruderal and halophytic communities. By methods of multidimensional statistics, 15 phytocoenochores have been determined and the discriminate of which is d identified by the tree species, which are forming the forest canopy. The identified plant communities are characterized by specific regimes of the fundamental abiotic factors of biotopes and make up a series of biotopic and coenotic substitution, forming a sylvant (forest) and pratant (meadow) successional series. It has been shown that in the process of natural overgrowth, the formation of forest (primarily birch) and meadow coenoses proceeds in parallel, and the invasive species Acer negundo L. plays an active role in sylvatization. It has been established that the leading hand in the formation of the coenotic structure of communities belongs to soil mineralization, acidity, aeration and variability of soil moisture. The obtained data on biotopes and successional series can be used in the development of the biological stage of landfill revegetation after coal mining impacts with the formation of woody or grass plant communities.

Responses of Soil Moisture to Gully Land Consolidation in Asian Areas with Monsoon Climate

Groundwater resources are essential for sustaining ecosystems and human activities, especially under the pressures of climate change. This study employed Electrical Resistivity Tomography (ERT) to assess the impact of Gully Land Consolidation (GLC) engineering on the groundwater hydrological field of small watersheds in the China Loess Plateau (CLP). Results revealed ample subsurface water storage in backfilled areas, primarily migrating along the original river path owing to topographical limitations. Although the distribution patterns of soil moisture in each backfilling block varied slightly, the boundaries of soil moisture content and variation mainly appeared at depths of 8 m and 20 m underground. Significant moisture variation occurred across the 0–20 m underground layers, suggesting the 8–20 m layer could function as a groundwater collection zone in the study area. Human activities could disturb groundwater, altering migration pathways from the original river path. An optimized “Drainage–Conveyance–Barrier” system is proposed to enhance GLC sustainability, involving upstream groundwater level control, midstream soil moisture management, and downstream hydrological connectivity improvement. These findings carry substantial implications for guiding the planning and execution of GLC engineering initiatives. The novelty of this study lies in its application of ERT to provide a detailed spatial and temporal understanding of soil moisture dynamics in the GLC areas. Future research should focus on factors such as soil types and topographical changes for a comprehensive assessment of GLC’s impact on small watershed groundwater hydrology.

Spatiotemporal dynamics and similarity in soil moisture in shallow soils on karst slopes

Understanding the spatiotemporal dynamics and similarity of soil moisture on shallow slopes is important for inferring soil hydrological processes and for vegetation restoration. In karst areas, the spatial distribution patterns and dynamic changes in shallow soil moisture are particularly complex; however, whether there is spatiotemporal similarity in shallow soil moisture on karst slopes has not been fully determined. This work investigated the spatiotemporal dynamic variations in shallow soil moisture in three types of karst slope plots (abandoned land, peanut and Zanthoxylum bungeanum). Wavelet coherence analysis was used to evaluate the spatiotemporal similarity and factors influencing shallow soil moisture under different vegetation types and slope positions. The results indicate that the alternation between dry and wet conditions and spatiotemporal heterogeneity were significant in the shallow soils of slopes. Comparatively, the dry-wet cycle in the shallow soil of abandoned land occurred faster than that in the shallow soil, and the shallow soil for planting vegetation had a better water holding capacity. The terrain and slope position controlled the distribution and dynamic variations in soil moisture on shallow slopes. Compared with those in the middle and upper slopes, the soil moisture in the bottom slopes was greater, and the coefficient of variation was lower. The average coherence between the soil moisture in the different plots was greater than 0.90, and the significant area was greater than 93.0%. The coherence and significant area in the rainy season were significantly greater than those in the dry season. Due to the influence of vegetation types and meteorological conditions, the drought interval after rainfall events led to a decrease in the spatiotemporal similarity of soil moisture. This study indicates that shallow soil moisture in karst slopes exhibits temporal stability and dynamic similarity. The alternation of dry-wet conditions controls the similarity of shallow soil moisture on the slope.

Contributions of Soil Moisture and Vegetation on Surface-Air Temperature Difference during the Rapid Warming Period

The difference (DIF) between land surface temperature (Ts) and near surface air temperature (Ta) is the key indicator of the energy budget of the land surface, which has a more complex process than the individual Ts or Ta. However, the spatiotemporal variations and influencing factors of DIF remain incomplete. The contribution of vegetation and soil moisture (SM) as key driving factors to DIF is not yet clear. Here, we analyzed the spatiotemporal variation patterns of DIF in China from 2011 to 2023 using in situ Ts and Ta data. A convergent cross-mapping method was employed to explore the causal relationship between SM, NDVI and DIF, and subsequently calculated the contribution of NDVI and SM variations to DIF under different climatic backgrounds. The results indicate that during the study period, DIF values were all above 0 °C and showed a significant increasing trend with a national mean slope of 0.02 °C/a. In general, vegetation and SM have a driving effect on DIF, with vegetation contributing more to DIF (0.11) than SM (0.08) under different surface properties. The background values of SM and temperature have a significant effect on the spatial and temporal distribution of DIF, as well as the correlation of vegetation and soil moisture to DIF. The study outcomes contribute to a better understanding of the coupling relationship between the land surface and atmosphere, which are also crucial for addressing climate change and ecological environmental management.

Uncertainty analysis on long-term runoff projection from the Budyko framework and a conceptual hydrological model

ABSTRACT Runoff projections are subject to uncertainties related to model structure and parameters. This study aims to analyze uncertainties in long-term runoff estimations from an empirical (Budyko framework) and a conceptual hydrological model (MHD-INPE). Results indicate that both MHD-INPE and Budyko estimations tend to overestimate long-term runoff during years of recurring droughts. Pareto front solutions in MHD-INPE exhibited small uncertainties in long-term runoff estimations regarding parameter calibration (bias between 5 and 7%); differences were observed in low (bellow 5% variation) and high (bellow 10% variation) daily runoff. Related to model structure uncertainties, both models follow similar patterns and performance for a qualitative analysis. Budyko's future projections tend to exceed MHD-INPE's during high precipitation estimates, where at 2000 mm yearly precipitation the estimated runoff from Budyko tends to be 100 mm greater than the hydrological model. Under arid conditions Budyko tends to estimate smaller runoff than MHD-INPE due to variations in soil moisture and water storage not properly represented in Budyko's parameter. Although uncertainties were identified related to model complexity and calibrated parameters, higher uncertainties were identified as related to the climate models. Therefore, the Budyko method is a viable alternative for first-order analysis of long-term impacts.

A Cross-Resolution Surface Net Radiative Inversion Based on Transfer Learning Methods

Net radiation (Rn) is a key component of the Earth’s energy balance. With the rise of deep learning technology, remote sensing technology has made significant progress in the acquisition of large-scale surface parameters. However, the generally low spatial resolution of net radiation data and the relative scarcity of surface flux site data at home and abroad limit the potential of deep learning methods in constructing high spatial resolution net radiation models. To address this challenge, this study proposes an innovative approach of a multi-scale transfer learning framework, which assumes that composite models at different spatial scales are similar in structure and parameters, thus enabling the training of accurate high-resolution models using fewer samples. In this study, the Heihe River Basin was taken as the study area and the Rn products of the Global Land Surface Satellite (GLASS) were selected as the target for coarse model training. Based on the dense convolutional network (DenseNet) architecture, 25 deep learning models were constructed to learn the spatial and temporal distribution patterns of GLASS Rn products by combining multi-source data, and a 5 km coarse resolution net radiation model was trained. Subsequently, the parameters of the pre-trained coarse-resolution model were fine-tuned with a small amount of measured ground station data to achieve the transfer from the 5 km coarse-resolution model to the 1 km high-resolution model, and a daily high-resolution net radiation model with 1 km resolution for the Heihe River Basin was finally constructed. The results showed that the bias, R2, and RMSE of the high-resolution net radiation model obtained by transfer learning were 0.184 W/m2, 0.924, and 24.29 W/m2, respectively, which was better than those of the GLASS Rn products. The predicted values were highly correlated with the measured values at the stations and the fitted curves were closer to the measured values at the stations than those of the GLASS Rn products, which further demonstrated that the transfer learning method could capture the soil moisture and temporal variation of net radiation. Finally, the model was used to generate 1 km daily net radiation products for the Heihe River Basin in 2020. This study provides new perspectives and methods for future large-scale and long-time-series estimations of surface net radiation.

How Much Does Land–Atmosphere Coupling Influence Summertime Temperature Variability in the Western United States?

Abstract Interannual fluctuations in average summertime temperatures across the western United States are captured by a leading empirical orthogonal function that explains over 50% of the total observed variance. In this paper, we explain the origins of this pattern of interannual temperature variability by examining soil moisture–temperature coupling that acts across seasons in observations and climate models. We find that a characteristic pattern of coupled temperature–soil moisture climate variability accounts for 34% of the total observed variance in summertime temperature across the region. This pattern is reproduced in state-of-the-art global climate models, where experiments that eliminate soil moisture variability reduce summertime average temperature variance by a factor of 3 on average. We use an idealized model of the coupled atmospheric boundary layer and underlying land surface to demonstrate that feedbacks between soil moisture, boundary layer relative humidity, and precipitation can explain the observed relations between springtime soil moisture and summertime temperature. Our results suggest that antecedent soil moisture conditions and subsequent land–atmosphere interactions play an important role in interannual summertime temperature variability in the western United States; soil moisture variations cause distal temperature anomalies and impart predictability at time scales longer than one season. Our results indicate that 40% of the observed warming trend across the western United States since 1981 has been driven by wintertime precipitation trends in the U.S. southwest. Significance Statement Year-to-year fluctuations in summertime temperatures have a large impact on drought, wildfire, and extreme heat across the Western United States. We find strong evidence that soil moisture deficits in the preceding spring may be the primary driver of higher-than-average summer temperatures in this region. Our results suggest that memory in the water cycle may lead to greater predictability in the climate system from season to season and that trends in southwest precipitation have exerted a considerable influence on observed warming over the past 40 years.

Variable soil moisture responses to rainfall events in fields under different management practices

AbstractSoil moisture response to rainfall is a key factor that dictates how well a landscape can support crop growth as well as its susceptibility to water runoff and leaching, however, few studies have investigated how agricultural management impacts this important soil function. This study compares two common agricultural soil treatments (cover crops and soil compaction) and their soil moisture response to rainfall in comparison to a control. In a humid temperate climate during March to November, individual rainfall events were delineated over two growing seasons and corresponding soil moisture responses were identified using in situ soil moisture sensors at four soil depths (20, 30, 40, and 60 cm). Results suggest that hydrological responses differed with both event type and management treatment. Not all rainfall events triggered a response: those that triggered responses at shallower soil depths were typically characterized by higher total event rainfall, and higher maximum and average rainfall intensity. In contrast, rainfall events triggering responses at deeper soil depths were characterized by longer event duration as well as higher 10‐day antecedent rainfall (AR). Soil moisture responses for the cover crop treatment were characterized by relatively lower initial and peak soil moisture at shallower depths but higher values at 60 cm depth, whereas soil moisture responses for the control and compacted soil treatments demonstrated the opposite. Matrix flow was most often generated for rainfall events with high magnitude and was not preferentially associated with any particular soil treatment. However, specific conditions were needed to generate vertical preferential flow, namely high total event rainfall for both horizons, or high AR for preferential flow in the Ap horizon, or high rainfall intensity for preferential flow in the Bt horizon. Our findings demonstrate the potential for detailed event‐based soil water process analysis using high‐frequency, multi‐depth soil moisture data.

Effect of Raised Flat Bed and Ridge Planting on Wheat Crop Growth and Yield under Varying Soil Moisture Depletions

Crop yields remain significantly low in underdeveloped countries, such as Pakistan, primarily due to the prevalent use of traditional farming methods by most farmers. Resource-saving strategies, like ridge and raised flat bed systems, could boost water use efficiency and production per acre. However, further research is needed to investigate the effectiveness of these methods, along with different levels of soil moisture depletion (SMD), on wheat development in the climatic conditions of Sindh Province. Thus, field trials were undertaken at Sindh Agriculture University’s Tandojam for two years (2022 and 2023) during the wheat growing seasons. The experiment included six treatments, viz., T1 (raised flat bed method under 40% depletion), T2 (ridge method under 40% depletion), T3 (raised flat bed method under 50% depletion), T4 (ridge method under 50% depletion), T5 (raised flat bed method under 60% depletion), and T6 (ridge method under 60% depletion). The bed planter was employed to make raised flat beds, and the ridges were prepared using a ridge planter. Wheat variety (TJ-83) was sown. Under all treatments, the plant population, plant height, and seed index were statistically significant (p < 0.05), although spike length, grain spikes−1, and grain weight spikes−1 were non-significant at different SMD levels. To compute water saving through the ridge and raised flat methods, the recommended delta value for wheat crops under the traditional method was used as a benchmark. Both irrigation technologies conserve water compared to traditional irrigation methods. The T5 treatment conserved the most water, followed by T6. Under a 60% depletion level, the ridge approach produced the highest yield of 2175 kg ha−1, compared to 601 kg ha−1 with the raised flat bed method. The best crop water productivity (CWP) of 1.34 kg m−3 was achieved under T6, whereas raised flat beds attained the lowest CWP of 0.27 kg m−3 under T1. In terms of wheat grain production and CWP, the ridge furrow method outperformed the raised flat bed furrow method. Based on the results, it is recommended that farmers should use the ridge furrow method and allow a 60% depletion of soil moisture to obtain a high yield of wheat crops.

Determining friction properties of ABS plastic in contact with loamy soil

The paper explores the feasibility of substituting steel working bodies with polymer ones in soil-cultivating units. (Research purpose) The research aims to investigate how the friction parameters of acrylonitrile butadiene styrene (ABS plastic) are affected by variations in absolute soil moisture and speed of the unit during the interaction of its working body with loamy soil. (Materials and methods) A laboratory unit was developed to examine the friction characteristics of the polymer in contact with loamy soil. The study measures the friction and adhesion properties by altering the absolute moisture of loamy soil. (Results and discussion) Graphs were constructed to illustrate the relationship between of the friction parameters of acrylonitrile butadiene styrene (ABS plastic) on absolute soil moisture. It was determined that at absolute soil moistures of 18, 20 and 26 percent, the friction coefficients of acrylonitrile butadiene styrene are 0.45, 0.5 and 0.6, respectively. The adhesion values were recorded at 100, 145 and 700 pascals for absolute soil moistures of 18, 20 and 28 percent, respectively. A decrease in both friction and adhesion was observed when the soil moisture reached between 26% and 28%. (Conclusions) The friction properties of acrylonitrile butadiene styrene (ABS plastic) are lower than those of steel, yet significantly higher than those of fluoroplastic. Further research in this area is expected to significantly increase the effi ciency of selecting materials for the manufacturing of working parts in soil-cultivating units, while also reducing energy costs.

Improved soil moisture estimation and detection of irrigation signal by incorporating SMAP soil moisture into the Indian Land Data Assimilation System (ILDAS)

Land surface models have facilitated the estimation of soil moisture over a range of spatiotemporal scales. However, limitations in model parameterization and under-representation of anthropogenic processes restrict their ability to estimate local-scale soil moisture variability, especially over irrigated areas. Assimilation of satellite-based soil moisture retrievals into land surface models can be a viable approach to overcome these constraints, specially over highly irrigated countries such as India, where such applications are rare. Additionally, large-scale validation of modeled soil moisture has been limited over India till now due to lack of a representative station network. By assimilating Soil Moisture Active Passive (SMAP)-based estimates into the state-of-the-art Indian Land Data Assimilation System (ILDAS) and combining with a new soil moisture station network of more than 200 stations, this study demonstrates improved soil moisture estimations and capture of irrigation signals over the region. The Noah-MP land surface model is forced by multiple local and global meteorological datasets and Ensemble Kalman Filter (EnKF) is used for assimilation of soil moisture. Comparison of open-loop and data assimilated soil moisture against station soil moisture data shows relative spatial mean improvement of 0.0178 in correlation and 0.0029 m3/m3 in RMSE. Further statistical comparison with in-situ data has also shown better results over most of the stations, as evident from improved correlations and reduced unbiased RMSE after assimilation. Finally, the climatology of soil moisture over the different irrigation fractions reveals that data assimilated outputs over irrigated grid cells tend to have higher soil moisture during dry winter season, demonstrating the ability to capture irrigation signals. These findings quantify the value of data assimilation in improving soil moisture estimates and the ability to capture unmodeled processes such as irrigation, which lays the science groundwork for upcoming space missions such as NASA ISRO Synthetic Aperture Radar (NISAR).

Soil respiration response to reductions in maize plant density and increased row spacing (Southeast pampas, Argentina)

Previous studies have recognized the influence of crop cover and agricultural management on variables (soil temperature, soil moisture, and root biomass) that influence soil respiration. However, despite the influence of plant density and row spacing on these variables in the maize crop (Zea mays L.), their impact on soil respiration has received little attention. Thus, the aims of this study were (i) to investigate whether reducing plant density and row spacing influences soil respiration, and (ii) to identify the controlling variables (soil temperature and soil moisture) underlying this response. We conducted field experiments in Balcarce, Argentina, over two seasons. Treatments included (i) maize crops at high plant density (≈8 plants m−2) and narrow rows (0.52 cm, HDN), and (ii) maize crops at low plant density (≈6.5 plants m−2) and wide row spacing (0.70 cm; LDW). Leaf area index (LAI), soil CO2 fluxes, soil superficial temperature, and moisture (characterized by the water-filled pore space, WFPS) were assessed throughout the growing season. Grain yield and cumulative soil CO2 emissions were determined at the final harvest. Major findings relevant to understanding the influence of reducing plant density and wider row spacing on instant CO2 fluxes include: (i) LAI reductions were related to higher superficial soil moisture, which was consistent at LAI ≥ 3; suggesting higher decreases in water uptake than increases in soil evaporation, and in turn (ii) increments in soil moisture were associated with higher CO2 fluxes. While lower plant density and wider row spacing had notable short-term effects on WFPS and soil respiration fluxes, they did not significantly affect cumulative soil respiration throughout the growing season. However, the combination of this practice with low-yield potential genotypes that exhibit low stability to changes in resource availability can increase CO2 emissions per unit of grain yield. These findings contribute to a better understanding of the impacts of management practices on soil respiration and, consequently, on carbon cycling within agricultural ecosystems.