Soil Moisture Research Articles

Accuracy of remote soil moisture sensing using Sentinel‐1A satellite

AbstractSeveral studies have demonstrated the water conservation potential of soil moisture sensor‐based irrigation scheduling on turfgrass areas; however, research is lacking on the accuracy of satellite‐based moisture measurements. A field study was conducted in 2023 to investigate the accuracy of moisture values based on electromagnetic pulses emitted from the synthetic aperture radar mounted on Sentinel‐1A. The estimates based on satellite remote sensing were compared to measurements collected on fairways 2 and 7 of Sunset Golf Course (Las Campanas, NM) by a ground‐penetrating capacitance sensor (Toro Precision Sense 6000 [PS 6000]) during June and July 2023. The relationship between values estimated using Sentinel‐1A and readings from PS 6000 was significant but weak (R2 ranging from 0.01 to 0.045) on fairway 2 on all sampling dates. On fairway 7, the association was significant only on two of four sampling dates, reaching R2 values of 0.015 and 0.021. The relationship was significantly negative (slope −0.37; R2 = 0.037) for fairway 2 on one sampling date. Generally, the satellite‐derived soil moisture data underestimated soil moisture variability when compared to PS 6000 measurements and indicated a greater moisture uniformity than actually present. Results of our study indicate that Sentinel‐1A satellite data appear to be impractical for the purpose of determining soil moisture in turfgrass areas. More studies are needed to improve the accuracy of measurements and to determine if different mathematical models should be used to estimate soil moisture based on reflectance values on turf areas.

Conservation strategies for Vatica lanceifolia (Roxb.) Blume: habitat distribution modelling and reintroduction in northeastern India

Vatica lanceifolia (Roxb.) Blume is a Critically Endangered species and native to the northeastern India, faces significant conservation challenges. Habitat distribution modelling approach was adopted to determine the potential region and suitable habitat for reintroduction of this species in order to improve its conservation status. The model incorporated six key variables: normalized difference vegetation index (NDVI), elevation, slope, stress index, soil type, and soil moisture based on weighted overlay modelling approach. The study identified prospective locations for species reintroduction in the lower altitudes (175–470 m) and moderate slope of 10–30 degrees with excessively drained loamy soils within its present home range. NDVI exhibited a crucial role with intermediate magnitudes of 0.2–0.43 along with soil moisture of moderate range of 30–60 % respectively. The physiological impact in the study site was assessed in terms of stress index, which exhibited values of 0.2–0.31. These values indicate a moderate magnitude of stress, highlighting the fragile state of the ecosystem supporting the species. The model delineated the study area into three habitat zones, highly suitable (51%), moderately suitable (46%), and least suitable (3%) for reintroducing V. lanceifolia. This study provides comprehensive scientific evidence to enhance biodiversity conservation initiatives and optimize management strategies.

Source analysis of nitrogen pollution in basin by export coefficient modeling and microbial source tracking with mutual verification

Nitrogen pollution in rivers has long been a significant ecological and environmental concern, and research on nitrogen pollution source tracking serves as the foundation for pollution control, playing a crucial role in quantifying different pollution sources and formulating effective mitigation strategies. This study proposes a technical framework for pollution source resolution based on the export coefficient model and microbial source tracking model. Initially, key environmental factors and their spatiotemporal characteristics were analyzed to preliminarily identify potential nitrogen pollution sources, including wastewater treatment plants, stainless steel plants, electroplating factories, chemical plants, pig farms, poultry farms, rice fields, vegetable farms, and tea plantations. Subsequently, hydrochemical and microbial metagenomic analyses were conducted to further refine the identification of nitrogen pollution sources. NMDS analysis revealed significant differences in microbial community structures among different pollution sources, facilitating effective discrimination. Additionally, co-occurrence network analysis was employed to construct microbial fingerprint maps specific to each pollution source. Finally, a Bayesian community-wide non-culture microbial source tracking method (SourceTracker) was used for quantitative pollution source apportionment. The export coefficient model estimated that point-source nitrogen loads were primarily derived from domestic wastewater, whereas non-point source nitrogen loads predominantly originated from rural domestic wastewater and agricultural cultivation. By integrating the microbial source tracking model, the primary sources of nitrogen pollution were accurately identified. During the dry season, domestic wastewater (47.3%) was the dominant contributor, including wastewater treatment plants, rural domestic sewage, stainless steel plants, and electroplating factories, with fecal and agricultural sources mainly stemming from pig farms and rice fields. In contrast, during the wet season, agricultural cultivation (20.5%) and natural soil (27.8%) were the predominant contributors, encompassing rice fields, vegetable farms, and tea plantations. This source-tracking approach provides a valuable tool for guiding precise regional pollution control and is particularly applicable in complex pollution environments.

Physiological, biochemical and elemental responses of grafted grapevines under drought stress: insights into tolerance mechanisms

The selection of appropriate grapevine grafts and optimizing irrigation practices for enhancing water use efficiency are critical for viticulture production in the arid regions of UAE, apart from mitigating the effects of changing environmental conditions. Extremely high arid temperatures leading to depleted soil moisture status limit grape production in the country. In order to streamline the production, it is imperative to focus on specific objectives of screening drought-tolerant grafts utilizing several laboratory analytical tools and irrigation management. Five grapevine cultivar-rootstock combinations were evaluated in an open field experiment under induced drought conditions by regulating irrigation at 100%, 75% and 50% field capacity (FC) in an arid region. The net photosynthetic rate increased in Flame Seedless Ramsey (V1), Thompson Seedless Ramsey (V2), and Crimson Seedless R110 (V3) at 50% FC. Stomatal conductance was reduced in V1, V3, Crimson Seedless Ramsey (V4) and Thompson Seedless x P1103 (V5) at 50% FC. Intercellular CO2 and transpiration rates were significantly reduced at 50% FC. Water use efficiency, calculated as Pn/gs ratio to relate photosynthesis to stomatal closure, was elevated in all the grafts at 75% FC and 50% FC compared to the control (100% FC). The relative water content (RWC) showed a declining trend in all the grafts with reduced water supply. Nevertheless, the V1 and V4 grafts exhibited the highest RWC at an FC of 50%. The V2 graft produced the highest total dry mass and fresh biomass compared to other grafts. The Chl a content decreased, but the Chl b content increased at 50% FC in V2. Lutein significantly decreased for V1, while V3 showed an increase at 50% FC. The N, P and K contents in all the grafts, except V3, showed an increasing trend at 50% FC. The scanning electron microscopy observations point to the strong responses of stomatal behaviour upon changes in irrigation, thus facilitating the drought tolerance of the grafts. The findings emphasize the importance of selecting drought-tolerant grapevine grafts, and our study results could serve as guideposts for developing sustainable viticulture in arid regions, providing valuable insights for future research and practical applications in grape production.Graphical

AI-Driven IOT System for Smart Plant Health Optimization

Smart Plant Communicator is an innovative educational project for primary and nursery school children that brings plants to life through interactive technology. Using sensors for soil moisture, temperature, humidity, light and the system monitors plant conditions and translates data into spoken responses. Children can converse with their plants, learning about care needs in a fun, engaging way. The project transforms plant care into an exciting adventure, fostering environmental awareness and responsibility. Integrating with smart home devices, it ensures consistent care even when children are away. By combining cutting edge technology with hands-on learning, Smart Talking Plants creates an emotional connection between children and nature.This unique approach introduces young learners to concepts of sensors, data processing, and AI while cultivating a deep appreciation for plant life. Key Words: IoT, AI, Smart Agriculture, Plant Health Monitoring, Environmental Sensing, TinyML.

Tundra recovery post-fire in the Yukon–Kuskokwim Delta, Alaska

Abstract The extent of wildfires in tundra ecosystems has dramatically increased since the turn of the 21st century due to climate change and the resulting amplified Arctic warming. We simultaneously studied the recovery of vegetation, subsurface soil moisture, and active layer thickness (ALT) post-fire in the permafrost-underlain uplands of the Yukon–Kuskokwim Delta in southwestern Alaska to understand the interaction between these factors and their potential implications. We used a space-for-time substitution methodology with 2017 Landsat 8 imagery and synthetic aperture radar products, along with 2016 field data, to analyze tundra recovery trajectories in areas burned from 1953 to 2017. We found that spectral indices describing vegetation greenness and surface albedo in burned areas approached the unburned baseline within a decade post-fire, but ecological succession takes decades. ALT was higher in burned areas compared to unburned areas initially after the fire but negatively correlated with soil moisture. Soil moisture was significantly higher in burned areas than in unburned areas. Water table depth (WTD) was 10 cm shallower in burned areas, consistent with 10 cm of the surface organic layer burned off during fire. Soil moisture and WTD did not recover in the 46 years covered by this study and appear linked to the long recovery time of the organic layer.

Exploration of Tianmu-1 and CYGNSS to Estimate Soil Moisture with GNSS-R in Southwest China

Abstract The Tianmu-1 satellites (TM-1) is China's first commercial BDS/Global Navigation Satellite System (GNSS) remote sensing and detection constellation that is compatible with the four major navigation systems, namely BDS, GPS, GLONASS, and Galileo. It could conduct three-dimensional and integrated operational detection of the global ocean, atmosphere, and ionosphere around the clock. The Cyclone Global Navigation Satellite System (CYGNSS) is an Earth System Science Pathfinder mission of the National Aeronautics and Space Administration (NASA) in the United States. This mission represents the first frequent space-based measurements of surface wind speeds in the inner cores of tropical cyclones. Comprising eight microsatellites, it is capable of providing near-seamless coverage of the Earth. This paper utilizes the observation reflection data of the TM-1 and CYGNSS in 2023. It respectively studies the capabilities of these two satellite constellations in estimating soil moisture (SM, 0 - 5 cm). This research opens broader prospects for obtaining high-precision SM products using satellite-based GNSS reflection data. Using Global Navigation Satellite System-reflectometry (GNSS-R) signal data in conjunction with the Normalized Difference Vegetation Index (NDVI), precipitation, Digital Elevation Model (DEM), slope, and geographic coordinates, the SM data from the Soil Moisture Active Passive (SMAP) satellite serves as the benchmark for developing a model based on the Random Forest (RF) method, facilitating SM value estimation in the Sichuan-Tibet transportation corridor. Research results indicate that the generated SM Pearson correlation coefficient (R) is 0.806, with a root mean square error (RMSE) of 0.054 cm³/cm³. Based on this, the extrapolated monthly SM values were obtained, with the maximum RMSE of the monthly retrieval results not exceeding 0.065 cm³/cm³, and the absolute value of the bias not exceeding 0.037 cm³/cm³. Utilizing the CYGNSS, the R soil moisture in the study area is 0.765, with an RMSE of 0.066 cm³/cm³. The extrapolated monthly SM values indicate that the maximum RMSE for the monthly retrieval results does not exceed 0.088 cm³/cm³, while the absolute value of the bias remains within 0.068 cm³/cm³.

Comparative Analysis of the Effects of Different Mulching Materials on Microclimate and Fruit Quality in Apricot Orchards

The ‘Diaoganxing’ is the experimental material, with natural grass cover as the control, to compare the effects of 5 different mulching materials. The aim was to identify the most effective mulching type for improving orchard microenvironments and fruit quality. The results demonstrated that waterproof, breathable film and reflective film significantly enhanced orchard microenvironments and fruit quality (p ≤ 0.05). Specifically, the waterproof, breathable film effectively regulated soil temperature and moisture, reducing soil temperature by 4.60% and increasing soil moisture by 17.09% in the 0–60 cm soil layer. Meanwhile, the reflective film optimized light distribution in the mid-lower canopy, increasing light intensity by 161.04–208.71% and reflectance by 2.6–3.3 times. In terms of fruit quality, the reflective film accelerated ripening by 10 d, increased carotenoid content by 15.34%, and achieved a peel color index (CCI) of 6.23. On the other hand, the waterproof breathable film advanced maturation by 7 d and significantly improved vitamin C, soluble sugar, and soluble solids content by 23.26%, 30.77%, and 12.76%, respectively. This study provides a scientific basis for the efficient and high-quality production of apricots in southern Xinjiang through the use of mulching practices.

Evaluation of intercropping legumes and green manuring on soil properties in maize field

A field experiment was conducted at Lamjung campus, Sundarbazar from March to July of the year 2023 to find out the effect of different legumes and green manuring on the improvement of soil moisture. The experiment was set up in a Randomized Complete Block Design (RCBD) with five treatments which are maize, Maize + Cowpea, Maize + French bean, Maize + Soybean and Maize + Green manuring and 4 replications. It was observed that the use of green manuring was better than the control treatment in increasing moisture content by more than 2.34 times (p<0.05). The control treated plots had higher bulk density which also meant that there was less moisture in the soil. The use of green manuring was seen to decrease the soil temperature by about 1.17 times as compared to the control. As compared to the control system, green manuring enhanced the organic carbon content by more than 2.21 times that of the control. Maize plant growth with the help of green manuring was excellent, ear length was about 20.72 cm and diameter was 3.22 cm and 2.25 % nitrogen content was found in the green manuring treatment and it is a requirement for cell division and elongation. These results indicate that green manuring notably improves maize productivity by substantially increasing soil moisture retention, maintaining soil temperature, and raising organic carbon content of soil. Therefore, green manuring is a sustainable and successful agricultural technique that improves soil qualities and crop yields, according to the study's findings.

Water usage of old-growth oak at elevated CO2 in the FACE (Free-Air CO2 Enrichment) of climate change

Abstract. Predicting how increased atmospheric CO2 levels will affect water usage by whole, mature trees remains a challenge. The present study investigates diurnal (i.e. daylight) water usage of oaks within an old-growth forest during an experimental treatment season (April–October, inclusive). Over the years 2017–2021, inclusive (years 1–5 of the experiment), we collected individual tree data from 18 oaks (Quercus robur L.) within a large-scale manipulative experiment at the Birmingham Institute of Forest Research (BIFoR) Free-Air CO2 Enrichment (FACE) temperate forest in central England, UK. Diurnal tree water usage per day (TWU, L d−1) across the leaf-on seasons was derived from these data. Equal tree numbers were monitored in each treatment: FACE infrastructure arrays (+150 µ mol mol−1) of elevated CO2 (eCO2), FACE infrastructure control ambient CO2 (aCO2) arrays, and control “ghost” (no-treatment, no-infrastructure) arrays. TWU was linearly proportional to tree stem radius, Rb (∼ 3.1 L d−1 mm−1; 274 mm ≤ Rb ≤ 465 mm). Rb was also a very good proxy for projected canopy area, Ac (m2), which was linearly proportional to Rb (∼ 617 m2 m−1). Applying the stem-to-canopy relation implied a mean July water usage of ∼ 5 L d−1 m−2 of projected oak canopy in the BIFoR FACE forest. We normalised TWU by individual tree Rb to derive TWUn (L d−1 mm−1). We report whole-season treatment effects, differing year on year, alongside July-only results. In the 2019 and 2021 seasons, after correction for repeated measures, there was a 13 %–16 %, reduction in eCO2 TWUn compared to aCO2 TWUn, with a marginal 4 % reduction in 2020, but these model results were not statistically significant. Control trees exhibited a significant 27 % increase in aCO2 TWUn compared to ghost TWUn in the whole season in 2019, with lesser, nonsignificant fixed effects in 2020 and 2021. Several factors may have contributed: the installation or operation of FACE infrastructure; array-specific differences in soil moisture, slope, or soil respiration; or the mix of subdominant tree species present. Our results showing normalised per-tree water savings under eCO2 align with sap flow results from other FACE experiments and greatly extend the duration of observations for oak, elucidating seasonal patterns and interannual differences. Our tree-centred viewpoint complements leaf-level and ground-based measurements to extend our understanding of plant water usage in an old-growth oak forest.

Effect of maize-soybean intercropping on soil respiration

Adopting appropriate cropping systems is an effective way to reduce greenhouse gas (GHG) emission, meanwhile GHG emission from farmland is a hot topic recently. In recent years, maize–soybean intercropping has been promoted in many regions in China. To explore the effects of maize-soybean intercropping on soil CO2 emission and carbon balance, we established three planting methods, namely, maize monoculture (M), soybean monoculture (S), and maize-soybean intercropping (MS). Results showed that the cumulative emissions of soil CO2 were M (21231 kg·hm-2) > S (19715 kg·hm-2) > MS (17321 kg·hm-2). The two-factor composite model of soil temperature and moisture content could explain the variation in soil CO2 emission rate well, which reached 58.36–68.54%. Correlation analysis showed that the soil CO2 emission rate was significantly correlated with peroxidase activity (P＜0.01). The soil carbon balance was favorable under different treatments, serving as a sink for atmospheric carbon. The soil carbon sequestration potential of M and MS treatments was significantly higher than that of S treatment (P<0.05), with increases of 37.11 and 34.02%, respectively. These results indicated that M and MS treatments had strong carbon sequestration potential . M treatment exhibited superior soil carbon balance compared with MS and S treatments, with increases of 29.80 and 359.31%, respectively. Therefore, maize treatment was a better planting method compared with soybean and maize-soybean treatments. Bangladesh J. Bot. 54(1): 113-122, 2025 (March)

Facilitation by Baccharis sarothroides (desert broom) during revegetation of a hard rock mine in Southern Arizona, USA.

Post mining revegetation efforts are often faced with challenges associated with poor soil conditions and sparse vegetation. Revegetation in arid regions faces further challenges due to scant and infrequent rainfall during the initial phases of plant establishment. Early successional plants may provide utility for targeted management to enhance remediation outcomes as these species have high dispersal capabilities and rapid growth rates, enabling them to successfully dominate landscapes very quickly after degradation. This research aims to test whether the native Baccharis sarothroides Gray (desert broom), a common early successional species, facilitates the growth of native plant communities on a copper mine in Southern Arizona. Fifty B. sarothroides individuals of varying sizes were randomly selected on a mine tailings waste pile and the plant communities growing both under their canopies as well as in exposed areas were characterized. Soil chemical composition and abiotic conditions were also assessed. We found higher plant density, cover, diversity, and species richness under B. sarothroides canopies in comparison to the exposed areas, however, the height of the individual had no effect. Baccharis sarothroides provides some alleviation from abiotic stresses by creating a cooler understory with higher soil moisture levels and lower soil temperature. Baccharis sarothroides demonstrates value for increasing revegetation success on copper mine tailings storage facilities.

Empirical Models for Estimating Draught and Vertical Reaction Forces of a Duckfoot Tool in Compacted Soil: Effects of Moisture Content, Depth, Width, and Speed

This paper presents the development of empirical mathematical models of draught force, Fx, and vertical force, Fy, acting on duckfoots attached to the tines with different stiffness and working in various soil conditions. The models consider technical variables such as stiffness, k, tool depth-to-width ratio, d/w, tool movement speed, v, and soil moisture content, MC, which have not been thoroughly analysed in the literature. The correlation coefficients for predicting Fx and Fy values were 0.4996 and 0.6227, respectively. Statistical analysis confirmed the significant effect of these parameters on the forces acting on the tools, with the variables d/w and v having the most critical impact on Fx and Fy. The SLSQP (sequential least squares programming) optimisation method was used to determine the optimal values of technical variables. The maximum value of Fx was 438.55 N, and the minimum was 98.98 N, with variable values at the edges of the studied ranges. Similarly, Fy values of 135.25 N and −84.55 N, respectively, were obtained. The optimisation results showed good fitness with experimental results, and the negative relative errors (from −1.72% do −4.81%), indicating overestimating, confirmed the accuracy of the model’s predictions. The justification of the research results allowed us to conclude that there is no basis for rejecting the explanatory hypotheses. The developed models have a generalisable value in the analysed ranges, and further research should focus on creating more universal, theoretical models of soil–tool interactions.

Responses of soil health to seasonal change under different land cover types in a sub-tropical preserve ecosystem.

In subtropical preserve ecosystems, natural factors combined with anthropogenic activities have led to significant seasonal changes, including distinct dry and rainy seasons. These changes can potentially impact soil health indicators, which are keystone properties that control ecosystem services across terrestrial landscapes. Few studies have evaluated the impact of seasonal changes on soil health within non-agronomic landscapes, such as preserves. As part of this study, we collected topsoil samples (0-15 cm) from twenty-three land cover types within a 109 km² preserve in central Florida during two different seasons (dry and wet) to advance the understanding of how soil health responds to seasonal changes and to explore the environmental factors controlling soil health within non-agronomic landscapes. Ten soil indicators were analyzed and incorporated into the total dataset (TDS). From the TDS, a minimum dataset was derived using Principal Component Analysis, which was then used to calculate the Soil Health Index (SHI) for soil health assessment. Our findings showed that changes in soil indicators, their relationships, and the SHI across seasons depend on land cover type. Based on soil health classification grades, soil health status either improved, declined, or remained constant between seasons, depending on land cover type. The regression analysis of eight selected environmental factors, such as soil profile moisture (SPM), surface soil wetness (SSW), precipitation (P), soil temperature (T), elevation (El), slope gradient (S), global horizontal irradiance (GHI) and surface albedo (ALB), showed that only slope gradient significantly explains variations in SHI during wet season, whereas other environmental factors do not show significant explanatory power for SHI variations in either dry or wet season. These findings highlight the dominant influence of slope gradient on soil health within non-agronomic landscapes, while indicating that other evaluated environmental factors may have limited relevance in this context. Furthermore, the non-significant findings among soil indicators across seasons may be attributed to the study's small sample size (i.e., three replications), a limitation stemming from constrained funding. This highlights the importance of future research incorporating larger sample size to validate the findings of this study.

Soil moisture and microbiome explain greenhouse gas exchange in global peatlands

Earth’s climate is tightly connected to carbon and nitrogen exchange between the atmosphere and ecosystems. Wet peatland ecosystems take up carbon dioxide in plants and accumulate organic carbon in soil but release methane. Man-made drainage releases carbon dioxide and nitrous oxide from peat soils. Carbon and nitrous gas exchange and their relationships with environmental conditions are poorly understood. Here, we show that open peatlands in both their wet and dry extremes are greenhouse gas sinks while peat carbon/nitrogen ratios are high and prokaryotic (bacterial and archaeal) abundances are low. Conversely, peatlands with moderate soil moisture levels emit carbon dioxide and nitrous oxide, while prokaryotic abundances are high. The results challenge the current assumption of a uniform effect of drainage on greenhouse gas emissions and show that the peat microbiome of greenhouse-gas sources differs fundamentally from sinks.

Aqueous compost extracts with stabilized biofertilizing microbiota promote plant root growth and drought resilience.

Aqueous compost extracts with stabilized biofertilizing microbiota promote plant root growth and drought resilience.

Development and Application of a Solar-Powered Timer Pump for Irrigation Purpose

frequent power outages and expensive electricity bills in developing countries have driven the development of alternative solutions to electricity from the grid to power pumps for irrigation purposes. In line with this, the study aims to design, construct, fabricate and test a solar powdered timer pump for irrigation that successfully mitigates the concerns of unreliable power supply, inefficient water management, over-irrigation, and raised operational expenses in agricultural activities. The system was developed by designing the various components through design calculations of the pump, solar panel, inverter, charge controller, microcontroller, moisture sensor, sprinkler, and various pipe connections. After designing, the fully assembled system was tested under controlled field conditions. The system was programmed to activate the pump at predetermined times and operate in short cycles typically 4-second intervals until the soil moisture sensor indicated that the desired moisture level had been reached. The soil moisture levels varied from 0 to 150 cl and the corresponding pumping duration was determined. The results revealed that when the level of moisture in the soil was high (1400%) compared to when 10 cl of water was added, there was a 100% reduction in the pumping duration to 0 s. As the percentage amount of water increased from 10 cl, there was a corresponding percentage increase in the duration of pumping. However, at a very high percentage increase of about 1150%, the corresponding level of percentage increase in pumping duration was reduced due to high levels of moisture content in the soil. This study demonstrates that the integration of solar energy with automated control systems can successfully resolve the issues associated with traditional irrigation methods.

The effect of a climatic compound drought and heatwave event on the dune-building grass Elytrigia juncea

Abstract Background and aims Coastal dunes provide vital ecosystem services, including flood protection and freshwater storage. These ecosystems are shaped by clonally-growing dune grasses that trap sediment as patch size increases, enabling the grasses to avoid stress from seawater flooding and freshwater scarcity. However, it remains poorly understood how increasing climate extremes will impact the establishment and survival dynamics of this vegetation. This study investigated the effects of an experimental climatic compound drought and heatwave (CDHW) on Elytrigia juncea in an embryonic dune field. Methods Over a four-week field experiment, we examined two plant-patch sizes (0.014 m2 vs. 1.953 m2) and two climatic treatments (ambient vs. CDHW), monitoring plant response and soil moisture. We hypothesized that larger patches would better resist the CDHW due to their enhanced freshwater storage within larger dune bodies. Results Contrary to our expectations, E. juncea exhibited a positive response to CDHW, with longer shoots in both patch sizes. Initial soil moisture profiles remained similar across patch sizes throughout the experiment. Moreover, soil moisture profiles indicated a substantial freshwater source within reach of roots in all plots, explaining the absence of drought stress. Conclusion Our findings suggest that pioneer dune grasses can be highly resistant to climatic CDHW when roots can reach fresh groundwater, a condition which can occur when a thin freshwater lens is present in proximity to larger dune complexes. For establishing dune grasses, it is not merely dune formation on a local scale but rather on a landscape scale that is crucial for coping with extreme climatic events.

100-m-resolution surface soil moisture data during the thawing season on the Qinghai‒Tibet Plateau

The characteristics of the spatial distribution of surface soil moisture (SM) on the Qinghai‒Tibet Plateau (QTP) on a fine scale are unclear due to the lack of high-spatial-resolution SM datasets. To improve this situation, we first supplemented 659 SM datasets in areas on the QTP containing sparse monitoring stations from 2021–2022 and integrated published SM datasets. Based on Sentinel-1&2 and measured SM data, we developed an SM retrieval algorithm for the ascending and descending orbits. Then, 100-m-resolution SM spatial data were generated for the thawing season of 2017–2023 in the SAR signal-applicable area on the QTP. As validated by the measured data, the correlation coefficients of the retrieval results for the ascending and descending orbits were 0.72 and 0.69, respectively, and the bias reached 0.07 m³/m³ and an RMSE of 0.07 m³/m³ for both. These SM datasets exhibit notable promise for improving our understanding and analysis of the ecology and hydrology of different environments on the QTP.

Assessing 16 Years of Tillage Dynamics on Soil Physical Properties, Crop Root Growth and Yield in an Endocalcic Chernozem Soil in Hungary

The conservation tillage method is a more holistic method introduced in Hungary two decades ago. Its environmental benefits in agriculture were widely studied and documented. The impact of conservation tillage on soil compaction and penetration resistance remains debated, necessitating further research to clarify its long-term effects in different soil types and cropping systems. The present study evaluates the impact on soil penetration resistance following 16 years of implementation of six distinct tillage practices. The study was conducted at Józsefmajor Experimental and Training Farm (JM) of the Hungarian University of Agriculture and Life Sciences near Hatvan. The study employed a randomized complete block design (RCBD) to evaluate six distinct tillage methods. These methods encompassed disking (D) at 12–14 cm depth, shallow cultivation (SC) at 18–20 cm depth, no-tilling (NT), deep cultivation (DC) at 22–25 cm depth, loosening (L) at 40–45 cm depth, and plowing (P) at 28–30 cm depth. In this study, soil compaction was assessed by measuring soil penetration resistance (SPR) at different depths (0–50 cm) and periods of the cropping year. Disking and NT significantly increased SPR between 10 and 20 cm, likely due to increased soil densification and reduced porosity in the absence of deep soil disturbance. While under sunflower cropping season significantly higher SPR was measured. In March 2021, the SPR at D and NT differed significantly from other measurement dates (September, October, November, and April). Regarding the difference between the depths, SPR increased with increasing depths in all treatment plots. The study findings revealed that NT and D tillage methods significantly increased soil penetration resistance in both cropping years, whereas L and P reduced SPR and enhanced the soil moisture storage potential of the soil particularly for the sunflower cropping period. The significance of the Spearman correlations observed suggested that SPR could be a valuable indicator of root growth potential under certain tillage conditions. Based on our results, we recommend the adoption of occasional deep soil loosening for reduced tillage systems (SC, D, DC, and NT) for both wheat and sunflower. This will create a compact-free zone for greater crop root proliferation, nutrient access, and SMC storage.