Search Results (19,331)

High-precision hyperspectral remote sensing reflectance measurement of water bodies serves as the fundamental technical basis for accurately retrieving spatiotemporal distribution characteristics of water quality parameters, providing critical data support for dynamic monitoring of aquatic ecosystems and pollution source tracing. To address the critical issue of water surface glint interference significantly affecting measurement accuracy in aquatic remote sensing, this study innovatively developed a novel sensor system based on multi-field-of-view Kohler-polarization technology. The system incorporates three Kohler illumination lenses with exceptional surface uniformity exceeding 98.2%, effectively eliminating measurement errors caused by water surface brightness inhomogeneity. By integrating three core technologies—multi-field polarization measurement, skylight blocking, and high-precision radiometric calibration—into a single spectral measurement unit, the system achieves radiation measurement accuracy better than 3%, overcoming the limitations of traditional single-method glint suppression approaches. A glint removal efficiency (GRE) calculation model was established based on a skylight-blocked approach (SBA) and dual-band power function fitting to systematically evaluate glint suppression performance. Experimental results show that the system achieves GRE values of 93.1%, 84.9%, and 78.1% at ±3°, ±7°, and ±12° field-of-view angles, respectively, demonstrating that the ±3° configuration provides a 9.2% performance improvement over the ±7° configuration. Comparative analysis with dual-band power-law fitting reveals a GRE difference of 2.1% (93.1% vs. 95.2%) at ±3° field-of-view, while maintaining excellent consistency (ΔGRE < 3.2%) and goodness-of-fit (R² > 0.96) across all configurations. Shipborne experiments verified the system’s advantages in glint suppression (9.2%~15% improvement) and data reliability. This research provides crucial technical support for developing an integrated water remote sensing reflectance monitoring system combining in situ measurements, UAV platforms, and satellite observations, significantly enhancing the accuracy and reliability of ocean color remote sensing data. Full article

Tea (Camellia sinensis) is the second most popular beverage in the United States (water is the first), but there is essentially no commercial production due to limited knowledge regarding cultivars and propagation. The objective of this study was to determine the best time of year to collect tea cuttings, the section of the shoot to collect cuttings, and the number of nodes per cutting for successful propagation while optimizing resource efficiency. To address this objective, two experiments were conducted in western Washington, USA, using cv. Minto Pacific. The first experiment (Expt. 1) evaluated the time of year (September through February) for cutting collection and the role of shoot section on successful propagation. The second experiment (Expt. 2) tested one-, two-, and three-node cuttings on the success rate of propagation. In Expt. 1, 5 months after the cutting collection, the survival of tea cuttings collected from late September through early February was 97% in year 1 and 86% in year 2. Survival was similar for all the shoot sections 5 months after collection in year 1 (94%), and in year 2, the top shoot section had the greatest survival (93%). Overall, the plant height, number of new leaves, plant health rating, root number, and root length in the summer following collection were greatest for cuttings collected in early September through late October. Also, overall, the mid-section of the shoot had the greatest plant height, number of new leaves, plant health rating, and root length the summer following collection. In Expt. 2, the survival of all the cuttings was 100% in year 1 and 87% in year 2 at 5 months after cutting collection. The plant height, root number and root length the summer after collection were similar for all the treatments in both years. The results from these two experiments indicate late October may be the optimum time for tea-cutting collection in this temperate climate region, to optimize use of greenhouse facilities, and single-node cuttings maximize the number of cuttings without a reduction in size of the rooted plants. Full article

Water use strategies reflect the ability of plants to adapt to drought caused by climate change. However, how these strategies change with stand development and seasonal drought is not fully understood. This study used stable isotope techniques (δD, δ¹⁸O, and δ¹³C) combined with the MixSIAR model to quantify the seasonal changes in water use sources and water use efficiency (WUE) of Eucalyptus urophylla S.T.Blake × E. grandis (E. urophylla × E. grandis) at four stand ages (2-, 4-, 9- and 14-year-old) and to identify their influencing factors. Our results showed that the young (2-year-old) and middle-aged (4-year-old) stands primarily relied on shallow soil water throughout the growing season due to the limitations of a shallow root system. In contrast, the mature (9-year-old) and overmature (14-year-old) stands, influenced by the synergistic effects of larger and deeper root systems and relative extractable water (REW), exhibited more flexibility in water use, mainly relying on shallow soil water in wet months, but shifting to using middle and deep soil layer water in dry months, and quickly returning to mainly using shallow soil water in the episodic wet month of the dry season. The WUE of E. urophylla × E. grandis was affected by the combined effect of air temperature (T), vapor pressure deficit (VPD), and REW. WUE was consistent across the stand ages in the wet season but decreased significantly with stand age in the dry season. This suggests that mature and overmature stands depend more on shifting their water source, while young and middle-aged stands rely more on enhanced WUE to cope with seasonal drought stress, resulting in young and middle-aged stands being more vulnerable to drought stress. These findings offer valuable insights for managing water resources in eucalyptus plantations, particularly as drought frequency and intensity continue to rise. Full article

Carboxymethyl chitosan (CMCS) exhibits excellent film-forming capability but suffers from limited water resistance. To enhance hydrophobicity and antimicrobial properties, citrus essential oil was emulsified directly with citrus pectin and dispersed into the CMCS matrix. This study investigated the effects of varying emulsion concentrations (0, 1, 3, 5, and 7 wt%) on film performance. FT-IR, XRD, and SEM analyses confirmed uniform emulsion distribution within the CMCS matrix with favorable compatibility. Increased emulsion loading improved water resistance, antioxidant activity, and antimicrobial efficacy of the CMCS-based films, with the 3% emulsion concentration achieving optimal mechanical strength (TS: 4.09 MPa, EAB: 144.47%) and water vapor permeability (1.30 × 10⁻¹⁰ g·m·(Pa·s·m²)⁻¹). Applied to grape preservation, the films significantly delayed quality deterioration of grapes. Furthermore, by modulating the activity of enzymes involved in anthocyanin metabolism, the films could effectively extend the shelf life of grapes by suppressing the oxidative degradation of anthocyanins. Full article

The application of urease inhibitors (UIs) and optimizing nitrogen (N) split application ratio (NSR) can both minimize ammonia (NH₃) volatilization and increase rice yield. However, few studies have analyzed the combined effects of these two practices with straw returning on rice yield and NH₃ volatilization. In this study, based on a field experiment involving rice yield, aboveground dry matter (ADM), crop N uptake (N_upt), and NH₃ volatilization from 2018 to 2019 in Sichuan Basin, China, the WHCNS (soil water heat carbon nitrogen simulator) model was used to simulate the effects of straw returning, UI, and NSR on rice growth and NH₃ volatilization. The results showed that the WHCNS model performed well in simulating rice growth and NH₃ volatilization. With straw return amount exceeding 4 t ha⁻¹, rice yield increased slowly or stabilized, while N_upt and NH₃ volatilization continued to increase. Increasing the panicle fertilizer (PF) proportion enhanced N_upt during the PF stage, thereby promoting yield improvement. The NSR₃ (a 1:1:3 ratio of base fertilizer, tiller fertilizer, and PF) achieved the highest yield, exceeding that of 2:1:2 by 0.29, 0.23, and 0.08 t ha⁻¹ at straw return amounts of 2, 3, and 4 t ha⁻¹, respectively. However, the effects of UI on N_upt and yield enhancement were limited. Furthermore, optimized NSR and the application of UI reduced NH₃ volatilization during the basal or tiller fertilizer stages, leading to an average decrease of 5.5% and 8.5% in total NH₃ volatilization, respectively. Meanwhile, the increase in straw return amount reduced the NH₃ volatilization reduction effects of both practices. Overall, the combination of NSR₃ and UI with the straw return amount of 3 t ha⁻¹ was the optimal practice for balancing food security and environmental benefits in purple soil area. Full article

Tree root intrusion can cause failures of underground sewer pipes and thus represent a major water asset management issue. If tree root intrusion is not detected early, this may lead to the interruption of wastewater services and high costs of repair to the pipeline. The objectives of this review are to assess the existing maintenance strategies, explore suitable strategies for Australia and similar settings around the world, and identify possible factors and predictive tools. Maintenance strategies can be divided into two categories: reactive and proactive approaches. The current reactive approaches are (1) mechanical techniques to clean the root mass in pipe networks and (2) chemical techniques to remove the root mass and control future growth. The literature suggests that the reactive approaches often provide only partial solutions. The proactive approaches, guided by a predictive model of tree root intrusion and its related factors, showed the potential to improve maintenance and limit the risk of the damage from re-occurring. Predictive models could help to evaluate the risk of planting trees in different conditions and minimise the damage of tree root intrusion after further multifactor investigations. Full article

The integration of smart sensor networks and Internet of Things (IoT) technologies has emerged as a key strategy for enhancing productivity and sustainability in agriculture and aquaculture under increasing climate and resource pressures. This review consolidates empirical findings on the performance of sensor-driven systems in optimizing the management of water, nutrients, and energy. Studies have demonstrated that IoT-based irrigation systems can reduce water use by up to 50% without compromising yields, while precision nutrient monitoring enables a 20–40% reduction in fertilizer inputs. In aquaculture, real-time monitoring and automated interventions have improved feed conversion ratios, reduced mortality by up to 40%, and increased yields by 15–50%. The integration of artificial intelligence (AI) into IoT frameworks further enhances predictive capabilities and operational responsiveness. Despite these benefits, widespread adoption remains constrained by high infrastructure costs, limited sensor robustness, and fragmented policy support. This paper provides a comprehensive evaluation of current technologies, adoption barriers, and strategic directions for advancing scalable, sustainable, and data-driven food production systems. Full article

Countries worldwide have implemented regulations on the green coverage ratio of new buildings to address the urban heat island effect. For example, Taipei City mandates that the green coverage rate of new buildings must be between 40% and 70%, while Singapore requires a green coverage rate of 100% or higher. Consequently, building greening is now a regulatory requirement rather than a preference. This study focuses on developing an indoor light-emitting-diode (LED) hydroponic inverted planting system to utilize ceiling space for expanding green areas in buildings. The light source of this system is suitable for both plant growth and daily lighting, thereby reducing electricity costs. The watertight planting unit does not require replenishment of the nutrient solution during a planting cycle for small plants, which can reduce water consumption and prevent indoor humidity. The modular structure allows various combinations, enabling interior designers to create interior ceiling scapes. Additionally, it is possible to grow aromatic plants and edible vegetables, facilitating the creation of indoor farms. Consequently, this system is suitable for high-rise residential buildings, office buildings, underground shopping malls, and indoor areas with limited or no natural light. It is also applicable to hospitals, clinics, wards, and care centers, where indoor plants alleviate psychological stress and enhance mental and physical health. Full article

Enhanced or engineered geothermal systems (EGSs), or non-hydrothermal resources, are highly notable among sustainable energy resources because of their abundance and cleanness. The EGS concept has received worldwide attention and undergone intensive studies in the last decade in the US and around the world. In comparison, hydrothermal reservoir resources, the ‘low-hanging fruit’ of geothermal energy, are very limited in amount or availability, while EGSs are extensive and have great potential to supply the entire world with the needed energy almost permanently. The EGS, in essence, is an engineered subsurface heat mining concept, where water or another suitable heat exchange fluid is injected into hot formations to extract heat from the hot dry rock (HDR). Specifically, the EGS relies on the principle that injected water, or another working fluid, penetrates deep into reservoirs through fractures or high-permeability channels to absorb large quantities of thermal energy by contact with the host hot rock. Finally, the heated fluid is produced through production wells for electricity generation or other usages. Heat mining from fractured EGS reservoirs is subject to complex interactions within the reservoir rock, involving high-temperature heat exchange, multi-phase flow, rock deformation, and chemical reactions under thermal-hydrological-mechanical (THM) processes or thermal-hydrological-mechanical-chemical (THMC) interactions. In this paper, we will present a THM model and reservoir simulator and its application for simulation of hydrothermal geothermal systems and EGS reservoirs as well as a methodology of coupling thermal, hydrological, and mechanical processes. A numerical approach, based on discretizing the thermo-poro-elastic Navier equation using an integral finite difference method, is discussed. This method provides a rigorous, accurate, and efficient fully coupled methodology for the three (THM) strongly interacted processes. Several programs based on this methodology are demonstrated in the simulation cases of geothermal reservoirs, including fracture aperture enhancement, thermal stress impact, and tracer transport in a field-scale reservoir. Results are displayed to show geomechanics’ impact on fluid and heat flow in geothermal reservoirs. Full article

Drought is a complex and interconnected natural phenomenon, involving multiple drought types that mutually influence each other. To capture this complexity, various composite drought indices have been developed using diverse methodologies. Traditionally, Principal Component Analysis (PCA) has served as the primary method for extracting index weights, predominantly capturing linear relationships among variables. This study proposes an innovative approach by employing Independent Component Analysis (ICA) to develop an ICA-based Composite Drought Index (ICDI), capable of addressing both linear and nonlinear interdependencies. Three drought indices—representing meteorological, hydrological, and agricultural droughts—were integrated. Specifically, the Standardized Precipitation Index (SPI) was adopted as the meteorological drought indicator, whereas the Standardized Reservoir Supply Index (SRSI) was utilized to represent both hydrological (SRSI(H)) and agricultural (SRSI(A)) droughts. The ICDI was derived by extracting optimal weights for each drought index through ICA, leveraging the optimization of non-Gaussianity. Furthermore, constraints (referred to as ICDI-C) were introduced to ensure all index weights were positive and normalized to unity. These constraints prevented negative weight assignments, thereby enhancing the physical interpretability and ensuring that no single drought index disproportionately dominated the composite. To rigorously assess the performance of ICDI, a PCA-based Composite Drought Index (PCDI) was developed for comparative analysis. The evaluation was carried out through three distinct performance metrics: difference, model, and alarm performance. The difference performance, calculated by subtracting composite index values from individual drought indices, indicated that PCDI and ICDI-C outperformed ICDI, exhibiting comparable overall performance. Notably, ICDI-C demonstrated a superior preservation of SRSI(H) values, yielding difference values closest to zero. Model performance metrics (Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and correlation) highlighted ICDI’s comparatively inferior performance, characterized by lower correlations and higher RMSE and MAE. Conversely, PCDI and ICDI-C exhibited similar performance across these metrics, though ICDI-C showed notably higher correlation with SRSI(H). Alarm performance evaluation (False Alarm Ratio (FAR), Probability of Detection (POD), and Accuracy (ACC)) further confirmed ICDI’s weakest reliability, with notably high FAR (up to 0.82), low POD (down to 0.13), and low ACC (down to 0.46). PCDI and ICDI-C demonstrated similar results, although PCDI slightly outperformed ICDI-C as meteorological and agricultural drought indicators, whereas ICDI-C excelled notably in hydrological drought detection (SRSI(H)). The results underscore that ICDI-C is particularly adept at capturing hydrological drought characteristics, rendering it especially valuable for water resource management—a critical consideration given the significance of hydrological indices such as SRSI(H) in reservoir management contexts. However, ICDI and ICDI-C exhibited limitations in accurately capturing meteorological (SPI(6)) and agricultural droughts (SRSI(A)) relative to PCDI. Thus, while the ICA-based composite drought index presents a promising alternative, further refinement and testing are recommended to broaden its applicability across diverse drought conditions and management contexts. Full article

Streamflow in the Upper Williamson Basin of the Klamath Watershed is groundwater dominated with year-to-year fluctuations in both volume and duration, including multi-year periods with no streamflow. The relationship between precipitation, groundwater, and streamflow is difficult to characterize because of the limited number of monitoring wells, large data gaps, and a unique geologic structure that controls flow. To understand why surface flow has ceased entirely, we use the Groundwater Data Mapper Tool to impute gaps in the well data using machine learning and open-source Earth observation data and then compute changes in groundwater storage over time. Our research confirms that groundwater storage is correlated to streamflow and finds that there is a control groundwater storage below which flow does not occur. Furthermore, we find that groundwater storage is correlated to rainfall with a three- to four-year delay. This lag and the geologic structural control mean that even with several years of above-average precipitation, live flow may take years to resume. This insight allows water managers to understand and adjust for this highly irregular streamflow for better management decisions. Full article

Membrane filtration, including reverse osmosis filtration, is widely applied in water treatment worldwide, offering solutions to a broad range of separation challenges. However, due to the porous structure of membranes, they are prone to fouling, which reduces their efficiency and can eventually render the membranes incapable of functioning. In such cases, a systemic intervention becomes necessary, highlighting the importance of accurately predicting the expected fouling time. Various approaches for estimating fouling processes and times are well documented in the literature. However, a common limitation of these methods is that they typically assume constant and well-defined operating parameters over time. Under such stable conditions, the process can be described deterministically, and the fouling time can be predicted using straightforward extrapolation techniques. However, in industrial practice, process conditions often fluctuate due to multiple influencing factors, making fouling time a variable quantity. Therefore, it can be more appropriately treated as a random variable characterized by a mean value and standard deviation. Rather than predicting a precise fouling time, it is more relevant to define a probabilistic interval within which the fouling is expected to occur with a specified confidence level (e.g., 95%). The associated maintenance scheduling can then be optimized based on economic criteria. The probability-based model presented herein defines this interval based on operational measurements, thereby providing users with a time window during which maintenance should be planned. From this point forward, the exact timing of interventions becomes a matter of technical feasibility and economic optimization. Full article

Toxic cyanobacterial blooms are prevalent in surface waters. Depending on several conditions, these blooms produce cyanotoxins. Human exposure to these toxins can occur through multiple routes, including contaminated crops through irrigation with contaminated water. Analytical methods have been developed for cyanotoxin quantification to investigate these exposures. Yet, proper comparisons between different labs via proficiency tests or interlaboratory comparison tests, as well as method quality assurance, are impossible. Developing reference materials for cyanotoxins in plants would help resolve these problems. Therefore, a novel liquid hydroculture setup was optimized to grow and contaminate strawberries. During fruit ripening, these plants were exposed to growth medium contaminated with pure microcystin-LR or freeze-dried cyanobacterial biomass containing different microcystin congeners. Afterwards, fruits, greens, and roots were harvested. Validated UHPLC-MS/MS methods were used to quantify the microcystin congeners in the growth medium and the plants. Furthermore, both contamination conditions resulted in the accumulation of toxin(s) in the roots and the greens. Yet in the contamination models, no toxin(s) accumulated in the fruits. Therefore, this contamination approach, combined with strawberries as a berry plant model, is only suitable for reference material production for limited matrices. Our cultivation model to produce reference material could be evaluated for other berry producers. Full article

Nutrients function as essential biological substrates for coastal phytoplankton growth and serve as pivotal indicators in marine environmental monitoring. The intensification of land-based nutrient sources inputs has exacerbated eutrophication in Chinese coastal water, while mechanistic understanding of differential self-purification processes among distinct land-based source nutrients (river source, domestic source, aquaculture source, and industrial source) remains limited, constraining accurate assessment of bay’s self-purification capacity. This study conducted incubation experiments in Tieshan Bay (TSB) during Summer (June 2023) and winter (January 2024), systematically analyzing the self-purification process of nutrients and associated environmental drivers. Distinct source-specific patterns emerged: river inputs exhibited maximal dissolved inorganic nitrogen (DIN) 1.390 ± 0.74 mg/L, whereas industrial discharges showed peak dissolved inorganic phosphorus (DIP) 4.88 ± 1.45 mg/L. Chlorophyll a (Chl-a) concentrations varied markedly across sources, ranging from 34.97 ± 23.37 μg/L (domestic source) to 86.63 ± 77.08 μg/L (river source). First-order kinetics demonstrated significant source differentiation (p < 0.05). River-derived DIN exhibited the highest attenuation coefficient (−0.3244 ± 0.17 d⁻¹), contrasting with industrial-sourced DIP showing maximum depletion (−0.4332 ± 0.20 d⁻¹). Correlation analysis indicated that summer was significantly associated with the impacts of three key control factors pH, dissolved oxygen, and turbidity on nutrient dynamics (p < 0.05), whereas winter exhibited a stronger dependence on salinity. These parameters collectively may modulate microbial degradation pathways and particulate matter adsorption capacities. These findings establish quantitative thresholds for coastal nutrient buffering mechanisms, highlighting the necessity for source-specific eutrophication mitigation frameworks. The differential self-purification efficiencies underscore the importance of calibrating pollution control strategies according to both anthropogenic discharge characteristics and regional hydrochemical resilience, which is of key importance for ensuring the traceability and control of land-based sources of pollution into the sea and the scientific utilization of the self-purification capacity of the bay water body. Full article

Background: Food safety remains a global concern due to biological and chemical contaminants, including adulterants, pathogens, antibiotic residues, and pesticides. Traditional detection methods are accurate but limited by time requirements, complex sample preparation, high costs, and poor field applicability. Surface-Enhanced Raman Spectroscopy (SERS) offers non-destructive analysis with low detection limits and high specificity, yet conventional SERS substrates face challenges with reproducibility, nanoparticle aggregation, and sensitivity in food matrices. Hydrogels have emerged as supporting materials for SERS due to their water content, tunable porosity, flexibility, and ability to entrap plasmonic nanostructures. Scope and Approach: This review examines recent advances in hydrogel-integrated SERS platforms for food safety applications. The three-dimensional structure of hydrogels enables homogeneous distribution of metal nanoparticles, prevents aggregation, and offers analyte enrichment. We analyze material design, functionalization strategies, and how hydrogel properties—crosslinking density, porosity, surface charge, and nanoparticle distribution—influence SERS performance in food matrices. Key Findings and Conclusions: Hydrogel-integrated SERS platforms demonstrate superior performance in detecting various food contaminants—including pesticides, adulterants, and additives—in real food matrices, often achieving detection limits in the nanomolar to picomolar range, depending on the analyte and substrate design. Current limitations include storage stability concerns, batch-to-batch variability, and regulatory acceptance hurdles. Future research directions should focus on multiplex detection capabilities, integration with smart sensing technologies, and industrial scalability to facilitate practical deployment in global food safety monitoring across diverse supply chains. Full article