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Eco-friendly, bioactive and edible films from renewable resources are increasingly regarded as viable replacements for petroleum-based packaging. This study investigates the application of Ulva lactuca macroalgae powder (ULP) as an active additive in crab (Portunus segnis) chitosan-based films for natural food packaging. Films with ULP concentrations of 0.5, 1.5, and 2.5% were prepared using a solvent-casting method with glycerol as a plasticizer. Their physicochemical, mechanical, functional, and biological properties were evaluated comprehensively. Fourier-transform infrared spectroscopy revealed intermolecular interactions between ULP’s polyphenolic compounds and the chitosan matrix, enhancing the films’ structural integrities. ULP’s incorporation reduced the moisture content, water solubility, lightness (L*), redness (a*), and whiteness index values while significantly (p < 0.05) increasing the yellowness (b*), total color difference (ΔE), yellowness index (YI), tensile strength (TS), and elongation at break (EB). The antioxidant activity improved in a concentration-dependent manner, as evidenced by the high free-radical scavenging capacity. Moreover, antimicrobial tests showed significant inhibitory effects against pathogenic strains. Biodegradability tests confirmed that the films decomposed entirely within 12 days under soil burial conditions, reinforcing their environmental compatibility. These results highlight the multifunctional potential of chitosan–ULP composite films, combining enhanced mechanical properties, bioactivity, and sustainability. By utilizing renewable and biodegradable materials, this work contributes to reducing waste and promoting resource efficiency, aligning with the principles of a circular economy and environmental preservation. Full article

Volatile and semi-volatile compounds, such as petroleum hydrocarbons and equipment lubricating oils, often contaminate soil due to accidents, posing significant ecological and health risks. Traditional soil remediation methods, such as thermal desorption and bioremediation, are time-consuming and resource-intensive, prompting researchers to explore more efficient alternatives. This study investigates the effectiveness of an in situ reactor for microwave-assisted soil remediation, specifically focusing on the impact of soil type and moisture content on pollutant removal efficiency. The reactor, designed to operate within a modified household microwave oven, provides direct microwave irradiation to the soil surface, enabling precise control of heating conditions. Experiments were conducted using soil samples of varying particle sizes and moisture levels under standardized conditions (1000 W microwave power, 2.45 GHz frequency). The results show that moisture content plays a critical role in pollutant removal efficiency, with an optimal moisture content of 10 wt % enhancing microwave absorption and energy transfer, thus improving pollutant recovery. In comparison with traditional resistive heating, microwave heating achieved a faster temperature rise and higher final temperatures, significantly improving pollutant removal efficiency in a shorter time frame. This study highlights the advantages of microwave heating, including its superior energy efficiency, faster pollutant volatilization, and the potential for optimized soil remediation in real-world applications. These findings provide valuable insights for the development of more sustainable and efficient soil remediation technologies. Full article

The rapid detection of landslide phenomena that may be triggered by extreme rainfall events is a critical point concerning timely response and the implementation of mitigation measures. The main goal of the present study is to identify susceptible areas by estimating changes in the Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Bare Soil Index (BSI), and Synthetic Aperture Radar (SAR) amplitude ratio before and after extreme rainfall events. The developed methodology was utilized in a case study of Storm Daniel, which struck central Greece in September 2023, with a focus on the Mount Pelion region on the Pelion Peninsula. Using Google Earth Engine, we processed satellite imagery to calculate these indices, enabling the assessment of vegetation health, soil moisture, and exposed soil areas, which are key indicators of landslide activity. The methodology integrates these indices with a Weight of Evidence (WofE) model, previously developed to identify regions of high and very high landslide susceptibility based on morphological parameters like slope, aspect, plan and profile curvature, and stream power index. Pre- and post-event imagery was analyzed to detect changes in the indices, and the results were then masked to focus only on high and very high susceptibility areas characterized by the WofE model. The outcomes of the study indicate significant changes in NDVI, NDMI, BSI values, and SAR amplitude ratio within the masked areas, suggesting locations where landslides were likely to have occurred due to the extreme rainfall event. This rapid detection technique provides essential data for emergency services and disaster management teams, enabling them to prioritize areas for immediate response and recovery efforts. Full article

Accurate estimates of biomass C stocks of grasslands are crucial for grassland management and climate change mitigation efforts. Here, we estimated the mean C stocks of grasslands in the Inner Mongolia Autonomous Region (IMAR), China, in 2020 at a 10 m spatial resolution by combining multi-source data, including remote sensing, climate, topography, soil properties, and field surveys. We used the random forest model to estimate the aboveground biomass (AGB) of grasslands, achieving an R² value of 0.83. We established a relationship between belowground biomass (BGB) and AGB using a power function based on field data, which allows us to estimate the BGB of grasslands from our AGB estimate. We estimated the mean AGB across IMAR to be 100.7 g m⁻², with a total value of 1.4 × 10⁸ t. The BGB of grasslands is much higher than AGB, with mean and total values of 526.0 g m⁻² and 7.4 × 10⁸ t, respectively. Consequently, our C stock estimates show that IMAR grasslands store significantly more C in their BGB (332.6 Tg C) compared to AGB (63.7 Tg C). Random forest model analyses suggested that remotely sensed vegetation indices and soil moisture are the most important predictors for estimating the AGB of grasslands in the IMAR. We highlight the important role of BGB for the C store in the Inner Mongolia grasslands. Full article

A variety of drought indices were developed to monitor different types of drought, a significant natural hazard with multidimensional impacts. However, no single drought index can capture all dimensions of drought, necessitating a composite drought index (CDI) that integrates a range of indicators. This study proposes a CDI using principal component analysis (PCA) and a temporal dependence assessment (TDA) applied to time series of drought indices in a spatially distributed approach at the basin level. The indices considered include the Simplified Standardized Precipitation Index (SSPI), Simplified Standardized Precipitation-Evapotranspiration Index (SSPEI), soil moisture (SM), Normalized Difference Vegetation Index (NDVI), and streamflow (SF) from two climatically distinct small-sized basins in Portugal. Lag correlation analyses revealed a high contemporaneous correlation between SSPI and SSPEI (r > 0.8) and weaker but significant lagged correlations with SF (r > 0.5) and SM (r > 0.4). NDVI showed lagged and negligible correlations with the other indices. PCA was iteratively applied to the lag correlation-removed matrix of drought indices for all grid points, repeating the procedure for several SSPI/SSPEI time scales. The first principal component (PC1), capturing the majority of the matrix’s variability, was extracted and represented as the CDI for each grid point. Alternatively, the CDI was computed by combining the first and second PCs, using their variances as contribution weights. As PC1 shows its highest loadings on SSPI and SSPEI, with median loading values above 0.52 in all grid points, the proposed CDI demonstrated the highest agreement with SSPI and SSPEI across all grid cells, followed by SM, SF, and NDVI. Comparing the CDI’s performance with an independent indicator such as PDSI, which is not involved in the CDI’s construction, validated the CDI’s ability to comprehensively monitor drought in the studied basins with different hydroclimatological characteristics. Further validation is suggested by including other drought indicators/variables such as crop yield, soil moisture from different layers, and/or groundwater levels. Full article

Drip irrigation generates structural bodies in soil, forming layered structures with moisture content gradients. There are four typical soil moisture characteristic values in this concentric structure as saturation capacity (θs), field capacity (FC), 60% field capacity (60% FC), and 30% field capacity (30% FC). In this study, we simulated these four soil water characteristic values to conduct an indoor soil incubation experiment under three different incubation conditions: aerobic (O), aerobic with 10 pa acetylene (OC), and anaerobic (AO). The results indicate that in soil with saturated water content, denitrification under aerobic conditions leads to high N₂O emissions; in soil at field holding capacity, nitrification under aerobic conditions dominates low N₂O emissions, which is most conducive to N₂O reduction and greenhouse gas emission mitigation; in soil with 60% of field holding capacity, denitrification under anaerobic conditions leads to high N₂O emissions; and in soil with 30% of field holding capacity, microbial activity decreases, inhibiting nitrification, denitrification, and N₂O emissions. Our research has found that when conducting aerobic drip irrigation in soil at field capacity (FC), denitrification was reduced by 99%, nitrification was increased by 70%, and microbial activity was enhanced by 5%. Therefore, during drip irrigation, the position and flow rate of the dripper should be controlled to reduce soil water saturation areas, maintain soil aeration, control soil moisture content below field holding capacity, promote the nitrification process, reduce N₂O emissions, and improve soil nitrogen use efficiency. Our study elucidates the characteristics of nitrogen transformation and N₂O emissions across various soil moisture contents within the soil water structure under drip irrigation conditions, providing a scientific basis for the formulation of precise irrigation management practices and strategies for efficient soil nitrogen utilization. Full article

The ability to track moisture content using soil moisture sensors in green stormwater infrastructure (GSI) systems allows us to understand the system’s water management capacity and recovery. Soil moisture sensors have been used to quantify infiltration and evapotranspiration in GSI practices both preceding, during, and following storm events. Although useful, soil-specific calibration is often needed for soil moisture sensors, as small measurement variations can result in misinterpretation of the water budget and associated GSI performance. The purpose of this research is to quantify the uncertainties that cause discrepancies between default (factory general) sensor soil moisture measurements versus calibrated sensor soil moisture measurements within a subsurface layer of GSI systems. The study uses time domain reflectometry soil moisture sensors based on the ambient soil’s dielectric properties under different soil setups in the laboratory and field. The default ‘loam’ calibration was compared to soil-specific (loamy sand) calibrations developed based on laboratory and GSI field data. The soil-specific calibration equations used a correlation between dielectric properties (real dielectric: ε_r, and apparent dielectric: K_a) and the volumetric water content from gravimetric samples. A paired t-test was conducted to understand any statistical significance within the datasets. Between laboratory and field calibrations, it was found that field calibration was preferred, as there was less variation in the factory general soil moisture reading compared to gravimetric soil moisture tests. Real dielectric permittivity (ε_r) and apparent permittivity (K_a) were explored as calibration options and were found to have very similar calibrations, with the largest differences at saturation. The ε_r produced a 6% difference while the K_a calibration produced a 3% difference in soil moisture measurement at saturation. K_a was chosen over ε_r as it provided an adequate representation of the soil and is more widely used in soil sensor technology. With the implemented field calibration, the average desaturation time of the GSI was faster by an hour, and the recovery time was quicker by a day. GSI recovery typically takes place within 1–4 days, such that an extension of a day in recovery could result in the conclusion that the system is underperforming, rather than it being the result of a limitation of the soil moisture sensors’ default calibrations. Full article

There are approximately 36.7 million hectares of saline alkali land available in China. To enhance the comprehensive utilization value of coastal saline alkali land and boost crop yields in such areas, it is essential to conduct research on optimizing the operational performance of high-performance soil contact components in light of the soil characteristics of coastal saline alkali land. Discrete element simulation can be employed to investigate the operational mechanisms of various key components. Nevertheless, at present, there is a dearth of discrete element models for the key physical parameters and soil structure of coastal saline alkali land soil. In this article, typical coastal saline alkali field soil was sampled, and the physical properties of the saline alkali soil, including salt content, moisture content, particle size distribution, and particle size, as well as intrinsic parameters such as soil compaction, density, Poisson’s ratio, and shear modulus, were measured. The Hertz Mindlin with Bonding contact model was employed. Physical experiments on soil accumulation angles at different depths were carried out using the cylindrical lifting method. Subsequently, by means of the discrete element method and the BBD experimental design method, a response surface model was established, and an optimization analysis was performed on the optimal parameters for the soil–soil collision recovery coefficient, static friction coefficient, and dynamic friction coefficient at each depth. Test benches for measuring the collision recovery coefficient, static friction coefficient, and rolling friction coefficient of saline alkali soil at -65Mn were set up, calculation formulas for each parameter were derived, and the contact parameters between soil at different depths and 65Mn were obtained. The results of the sliding friction angle test on different depths of saline alkali soil at -65Mn were further verified using the discrete element method, with a maximum error of 3.11%, which falls within the allowable range. This suggests that the calibration results of the discrete element simulation parameters for the interaction between soil and contact components are reliable, providing data and model support for future research on enhancing the operational performance of high-performance contact components. Full article

This study investigates the feasibility of using mineralized collector-drainage water (CDW) for irrigating maize crops on light gray soils in the Syrdarya region of Uzbekistan, an area facing severe water scarcity and soil salinity challenges. The research is particularly novel as it explores maize production in marginalized soils, a subject previously unexamined in this context. The experiment was designed as a three-factor factorial study with three replications, following the guidelines of the Uzbekistan Cotton Scientific Research Institute. Five irrigation treatments (Fresh Water, Fresh Water 70% vs. CDW 30%, Complex Method (Mixing with Specific Rules), CDW 70% vs. Fresh Water 30% (Mixing) and only CDW) were evaluated using an Alternate Furrow Irrigation system, incorporating various mixtures of fresh water and CDW to determine their effects on soil salinity, crop health and yield. The amount of irrigation water required was determined using a soil moisture balance model, with soil samples collected at multiple depths (0–100 cm) to monitor changes in moisture content and salinity. Salinity levels and soil health parameters such as alkalinity, chloride, sulfate and cation/anion balances were measured at different stages of crop growth. Data were collected over three growing seasons (3 years). An analysis of the data revealed that using CDW, even in mixtures with fresh water, can sustain crop production while managing soil salinity. Notably, irrigation methods such as Mixing 70–30 and the Complex Mixing Method effectively reduced freshwater dependency and maintained the crop yield without significantly increasing salinity. The results suggest that CDW could be a viable alternative water source in regions where traditional water resources are limited. The findings have significant implications for improving water use efficiency and agricultural productivity in areas facing similar environmental challenges. This research not only contributes to the broader understanding of sustainable irrigation practices in arid regions but also provides a scientific basis for the wider adoption of CDW in Uzbekistan, potentially enhancing food security and supporting long-term agricultural sustainability in the region. Full article

Field studies were conducted in the North China Plain (NCP) during the 2023–2024 season to investigate the vertical microclimate, yield, and yield-related characteristics of winter wheat during the grain-filling stage under no-till direct seeding and conventional tillage. The aim was to compare the differences in microclimate between the two tillage methods in wheat fields and the impact of microclimate on yield. The results indicated that, compared to conventional tillage, no-till direct seeding reduced the air temperature and increased the relative humidity of the air at 20 cm and 100 cm above the ground during the wheat grain-filling period. The soil moisture content at 20 cm below the ground under no-till direct seeding was higher than under conventional tillage during the early grain-filling stage. Seven days before the wheat harvest, the dry weight per plant and the dry weight per spike were significantly greater under no-till direct seeding than under conventional tillage. Consequently, the thousand-grain weight of no-till direct seeding was significantly higher than that of conventional tillage, with an increase of 7.9%. The number of wheat sterile spikelets under no-till direct seeding was significantly lower than that under conventional tillage. Furthermore, the number of grains per spike was higher than that of conventional tillage. Although the number of harvested spikes under no-till direct seeding was 10.8% lower than under conventional tillage, the increase in thousand-grain weight and the number of grains per spike compensated for the reduced number of harvested spikes. As a result, the grain yield of winter wheat under no-till direct seeding was higher than that of conventional tillage, increasing by 2.7%. Therefore, adopting no-till direct seeding in the NCP is conducive to increasing winter wheat production and efficiency, as well as supporting sustainable agricultural development. Full article

The dramatic changes in precipitation patterns on the Tibetan Plateau affected the carbon-sequestering microbial communities within wetland ecosystems, which were closely related to the responses and adaptation mechanisms of alpine wetland ecosystems to climate change. This study focused on wetland soils subjected to different precipitation gradient treatments and employed high-throughput sequencing technology to analyze the soil cbbM carbon-sequestering microbial communities. The results indicated that Proteobacteria were the dominant microbial community responsible for carbon sequestration in the Wayan Mountain wetland. A 50% increase in precipitation significantly raised the soil moisture content, while a 50% reduction and a 25% increase in precipitation notably enhanced the total soil carbon content. The 25% reduction in precipitation increased the differences in microbial community composition, whereas both the 50% increase and the 50% reduction in precipitation decreased these differences. The soil pH and temperature had the most significant impact on the carbon-sequestering microbial communities. In conclusion, changes in precipitation affect the cbbM carbon sequestration characteristics of soil microbial communities, and a moderate reduction in water input benefited carbon sequestration in wetlands. Full article

The Temperate Highland Peat Swamps on Sandstone (TPHSS) in the Sydney Basin of Australia provide critical ecological and hydrological services but are increasingly threatened by wildfires and human activities such as underground mining. The 2019–2020 wildfires severely impacted these swamps, raising concerns about their resilience and recovery. This study assessed the post-fire recovery of swamps and evaluated the ability of remote sensing techniques to determine recovery patterns. Specifically, it investigated differences in post-fire recovery patterns between swamps where groundwater levels and soil moisture contents were impacted by underground mining and those unimpacted by mining. Two mined and one non-mined swamp were studied. Soil moisture contents were monitored at five sites, and previously performed vegetation field surveys (2016–2022) were utilized. Remote sensing indices, including the Normalized Difference Vegetation Index (NDVI) and Soil Moisture Index (SMI), were calculated and compared with ground data to map post-fire responses. The results showed that hydrological conditions directly affect post-fire recovery, with slower recovery in mined swamps compared to non-mined ones. This study demonstrated that NDVI and SMI indices can effectively determine recovery patterns in terms of vegetation and hydrology. However, evaluating the recovery pattern of specific vegetation species requires more frequent field surveys. Full article

The construction of roads in saline soil areas usually involves using coarse-grained soil as roadbed fill material; studying the water–vapor–salt migration mechanism in coarse-grained saline soil subgrades is crucial for ensuring the stability of highway infrastructure. In order to clarify the influence of fines content and initial moisture on the water–salt migration and to clarify the water–vapor–salt migration patterns in coarse-grained saline soil, a model test of coarse-grained saline soil was conducted to study the response patterns of external water replenishment, final moisture content, final salt content, and liquid level height of coarse-grained saline soil. The results indicated that the water vapor migration amount only causes a change in the final moisture content, albeit not enough to cause salt redistribution. With increasing initial moisture content in coarse-grained saline soil, the migration characteristics of water vapor are weakened, and it imposes a significant inhibitory effect on liquid water migration at the same time. Increasing fines content in coarse-grained soil significantly inhibits water vapor migration, whereas liquid water migration is promoted. Water and salt accumulate in the liquid and vapor coupling migration mode at different heights. Based on the mechanisms of water vapor and salt transport characteristics, this study proposes a novel roadbed structure, which is vital for ensuring the long-term service performance of coarse-grained saline soil roadbeds in saline soil areas. Full article

To reduce the amount of pesticides in the environment, it is necessary to consider the wettability properties of pesticide droplets on the leaf surface to improve the spraying effect. The wettability properties of the droplet on the leaf surface are related not only to the properties of the liquid itself but also to the properties of the leaf surface. It is typically believed that leaf surface properties are difficult to control, and thus research has generally ignored this aspect of pesticide use. However, in the field environment, the structure and properties of the leaf surface can be altered by changing the moisture content of the soil where plants are grown. In this study, the roughness, contact angle, and surface free energy of the leaf surface were measured and calculated under different soil moisture contents to study the changes in the leaf surface wettability properties, with the aim of achieving efficient pesticide spraying by adjusting the soil water content. The results showed that the surface composition and microstructure of leaves were altered by the change in the soil moisture content, and the wettability properties of leaves decreased initially and then increased with a decrease in the soil moisture content. When the amount of soil water was sufficient or seriously insufficient, the wettability properties of the leaves were increased, but a lack of soil water may lead to irreversible damage to the plants. Therefore, before spraying pesticides on the leaf surfaces, the plants should be fully watered to improve the wettability properties of the leaf surface, which is conducive to the deposition and adhesion of pesticide droplets on the leaf surface and improved application effectiveness. The results of this study can provide a useful reference for the theoretical research and practices of precision spraying. Full article

Soil moisture is one of the main factors influencing evapotranspiration (ET) under soil water stress conditions. The TSEB_SM model used soil moisture to constrain soil evaporation. However, the transpiration schemes constrained by soil moisture require greater physical realism and the soil evaporation schemes parameters usually need calibration. In this study, the TSEB_SM model was enhanced by incorporating Jarvis’s canopy resistance which considered the influence of soil moisture on transpiration schemes. We assessed the new model (TSEB_SM+) in the Heihe and Haihe basins of China. The TSEB_SM+ model displayed a consistency to the TSEB in the ET estimation at the A’rou site, but approximately 30% and 35% reductions in RMSEs at the Huazhaizi and Huailai sites. It produced approximately 20% and 10% of the reductions in the ET RMSEs at the Huailai and A’rou sites compared to the TSEB_SM model, but had a similar performance at the Huazhaizi site. Moreover, the TSEB_SM+ model estimated ET in the Heihe River Basin with an RMSE of 0.58 mm·day⁻¹, and it was sensitive to the soil moisture, particularly when the soil moisture was below 30%. In conjunction to soil moisture, the TSEB_SM+ model could potentially be a more effective tool for monitoring the ET. Full article