Search Results (3,474)

Drought poses a major threat to ecosystem stability in arid regions. In Xinjiang, China, vegetation dynamics are highly sensitive to hydroclimatic variability, yet the evolution of drought and its ecological impacts remain insufficiently quantified. Using meteorological observations from 86 stations (1962–2021), drought dynamics were characterized using the Standardized Precipitation Evapotranspiration Index (SPEI) combined with run theory, while MODIS products (2001–2021) were used to quantify vegetation phenology and productivity. Results indicate that despite a regional warming–wetting trend, more than 97% of Xinjiang exhibits a significant increase in drought frequency and intensity after 1997, with pronounced spatial heterogeneity concentrated in southern Xinjiang. Vegetation phenology shows a significant shift, with spring onset advancing at a rate of −1.9 days decade⁻¹ and growing season length increasing by +3.8 days decade⁻¹. Vegetation productivity derived from MODIS shows strong spatial variability, with GPP and NPP exhibiting consistent increasing trends, particularly in northern Xinjiang. Multi-scale analysis reveals strong scale dependence in drought–vegetation interactions, where short-term drought (SPEI-3 and SPEI-6) exerts the strongest influence on vegetation dynamics, while long-term drought (SPEI-12) primarily controls ecosystem stability and post-drought recovery. Correlation and extreme-event analyses further indicate that seasonal drought and phenological shifts jointly regulate ecosystem productivity by altering water availability and carbon uptake periods. These results highlight a warming–wetting but drought-intensifying regime in Xinjiang and emphasize the dominant role of seasonal drought in regulating vegetation functioning under climate change. Full article

The present study investigates how bed roughness affects the velocity field in a laboratory water channel designed for testing hydrokinetic turbines. The main aim is to evaluate the impact of bed morphology on flow hydrodynamics and, consequently, on the turbines’ operating conditions. Experimental studies were carried out in two hydraulic regimes—smooth channel bed and bed with artificially created irregularities—at flow velocities of 0.3 and 0.4 m/s, with a depth of 180 mm. The results indicate that bed roughness significantly affects the velocity field, leading to increased turbulent fluctuations, the formation of vortex structures, and momentum redistribution. There is also localized velocity acceleration within the measurement region caused by local acceleration between the bed irregularities, which is influenced by the geometry of the water channel. A clear vertical velocity distribution is established, with larger fluctuations being registered in the surface layer, while near the channel bed, the flow is more stable. The results obtained emphasize the importance of bed roughness as a key factor in laboratory modeling and analysis of hydrokinetic turbine performance, with a direct impact on their efficiency and load. Full article

This study addresses the challenge of drought stress in ornamental plants by evaluating the drought response of Cuban oregano (Coleus amboinicus Lour.) and the potential of sea fennel (Crithmum maritimum L.) extracts as biostimulants to mitigate the effects of water deficit. Conducted in a greenhouse under two irrigation regimes, full irrigation (100% water replacement) and deficit irrigation (50%), the research applied foliar treatments of sea fennel extracts prepared via aqueous extraction (WE) and alcoholic extraction (AE) at various concentrations. Drought stress significantly reduced total dry biomass by 48%, leaf number by 33%, and leaf area by 57%, severely impacting both aboveground and root growth. Biostimulant treatments alleviated these negative effects, with alcoholic extracts at 2.5 mL L⁻¹ showing the greatest efficacy by increasing biomass by approximately 60% and restoring leaf area to levels comparable to fully irrigated plants. Aqueous extracts provided moderate improvements. Drought induced an increased root-to-shoot ratio, indicating adaptive biomass allocation, while SPAD values and gas exchange parameters (net photosynthesis and stomatal conductance) declined under stress but improved with biostimulant application, especially with AE treatments. Photosystem II efficiency (Fv/Fm) confirmed stress but showed partial recovery in AE-treated plants. Additionally, WE at 5 mL L⁻¹ enhanced anthocyanin and amino acid accumulation, suggesting metabolic adjustments to drought. Overall, alcoholic sea fennel extracts demonstrated superior potential as sustainable biostimulants to enhance drought tolerance in ornamental plants. Full article

This work examines the nonlinear dynamics of a generalized Korteweg–de Vries–Zakharov–Kuznetsov equation, a model that appears in plasma physics, shallow water flows, and nonlinear wave propagation. By applying a solitary-wave transformation, the governing partial differential equation is reduced to an autonomous dynamical system, enabling a direct study of its phase portraits and equilibrium behavior. Stability of the fixed points is assessed through Jacobian matrices and eigenvalue classification, revealing parameter regimes that admit saddle states, centers, and oscillatory structures. The system’s richer behavior is explored by varying key parameters, with phase-space trajectories exhibiting periodic, quasiperiodic, and irregular wave patterns. To probe the onset of complexity, we employ several diagnostic tools, including time-series evolution, Lyapunov exponents, bifurcation analysis, sensitivity tests, and Poincaré sections, which together indicate transitions to chaotic motion. The resulting dynamics are further captured using a nonlinear autoregressive neural network, which accurately reproduces the observed trajectories. The combination of analytical and computational perspectives provides a clear framework for understanding this generalized equation and offers a practical approach for investigating other nonlinear systems with a similar structure. Full article

Water composition is a key factor influencing brewing performance and beer quality due to its impact on mash chemistry, fermentation kinetics, and fermentation-derived metabolites. This study evaluated the effect of four Albanian spring waters (Bogova, Germenji, Selita, and Lajthiza), each with distinct mineral compositions, on the fermentation behaviour and physicochemical characteristics of Pale Ale beer produced under standardised brewing conditions. All beers were brewed using the same malt formulation, hopping regime, yeast strain, and fermentation parameters, with water source as the sole experimental variable. The produced worts showed only moderate differences in pH, colour, extract, free amino nitrogen (FAN), bitterness, and density, whereas alcoholic fermentation proceeded efficiently in all treatments and was completed within seven days. Final alcohol contents ranged from 5.56 to 5.70% v/v, confirming comparable fermentation performance among treatments. More pronounced differences were observed in acidity-related parameters and fermentation-derived compounds. Volatile acidity ranged from 0.19 to 0.93 g/L, with the highest values in beers produced with Selita and Lajthiza waters. Glycerol concentrations varied from 0.88 to 1.24 g/L, with Germenji beer showing the highest value, whereas acetaldehyde ranged from 3.16 to 6.04 mg/L, with the lowest concentration in Germenji beer. Pearson correlation analysis and exploratory principal component analysis (PCA) identified associations between water mineralisation and selected physicochemical and fermentation-derived beer parameters. Calcium, magnesium, conductivity, and hardness were positively associated with glycerol concentration, whereas bicarbonate concentration was associated with beer pH and acidity-related parameters. The first two principal components explained 87.7% of the total variance. Overall, the results indicate that Albanian spring waters are suitable for Pale Ale production and show that differences in water mineral composition were associated with variations in the physicochemical and fermentation-derived characteristics of the final beers. These findings highlight that brewing water should not be regarded as a neutral processing medium but rather as an important technological factor associated with differences in the physicochemical characteristics of beer, while supporting the valorisation of Albanian spring waters for geographically distinctive craft brewing applications. Full article

Drought is becoming more frequent and severe in many regions, particularly in Mediterranean climates, where water demand is increased by warming and changes in precipitation regimes. A long-term assessment of meteorological drought at the Lisbon climatological station is provided in this study using the Standardized Precipitation Index (SPI) and the Reconnaissance Drought Index (RDI) over the period 1864–2021. Monthly precipitation and temperature data are used to compute SPI and RDI at 3-, 6-, and 12-month time scales, so that short-, mid-, and long-term droughts and their temporal evolution can be characterized. RDI is evaluated with three widely used empirical potential evapotranspiration (PET) formulations—Hargreaves, Thornthwaite, and Blaney–Criddle—in order to examine how PET estimations influence drought classification. Given the absence of a physically based reference PET—such as FAO-56 Penman–Monteith—for this station, the focus is on the internal consistency of the PET methods. Furthermore, the Hargreaves formulation is retained as a representative empirical PET for subsequent SPI–RDI comparison. The results show broadly consistent standardized RDI behavior across PET methods; it is indicated that drought conditions are captured more comprehensively by RDI than by SPI because both precipitation deficits and enhanced evaporative demand are included. At the Lisbon station, the estimated average return periods for short-, mid-, and long-term droughts are 3.79, 7.31, and 7.92 years according to RDI, compared with 3.86, 5.69 and 10.88 years from SPI. Several severe drought episodes are identified, including the years 1907, 1922–1923, 1944–1945, 1976, 1981, 1992–1993, 2005, and 2018. While no formal attribution analysis is performed, the drought characteristics are interpreted in the context of observed long-term warming and documented rainfall variability in Lisbon. The findings provide a single-station benchmark of historical drought behavior, by which local water-resources management can be supported and which can serve as a basis for future multi-station and climate-projection-based studies in Portugal. Full article

Consolidation treatments are essential for the conservation of wall paintings affected by decohesion and disintegration phenomena. In hypogean environments, high relative humidity, limited ventilation and elevated biological risk impose particularly stringent performance requirements. Under these conditions, consolidants must ensure chemical compatibility, effective distribution within water-saturated substrates, long-term stability at high relative humidity and low toxicological impact. Calcium-based nanomaterials, especially nanolime dispersions, are widely employed as reference consolidants. However, their performance is strongly influenced by the dispersing medium, environmental conditions and substrate characteristics. This study addresses the lack of comparative assessments of currently available calcium-based consolidants by testing four products—two alcohol-based nanolimes (Nanorestore Plus^® and CaLoSil^®), one aqueous nanolime dispersion (Nanolaq^®) and a laboratory-formulated aqueous nanocalcite—applied to painted mock-ups. For the first time, the effectiveness of these treatments was investigated under both high relative humidity and water-saturated conditions through a multi-analytical approach. Colorimetric variations, water vapour permeability, water absorption and consolidant distribution within the pictorial layers were evaluated. The results provide a comparative assessment of consolidant performance as a function of the hygrometric regime of the substrate, with differentiated responses under high-humidity conditions and attenuated differences under water-saturated conditions. Overall, the effectiveness of the consolidant appeared to depend significantly on the combined influence of the dispersing medium, the imbibition state of the substrate and its chemical nature, highlighting the need for selection criteria and evaluation protocols based on simulating realistic conservation conditions. Full article

Bigels (BGs) were formulated using gelatin (GA) or gellan gum (GG) hydrogels (HGs) combined with beeswax-structured oleogels (OGs). Carob fruit extracts—an inositol-rich fraction (I-CFE) and a polyphenol-rich fraction (P-CFE)—were incorporated into the HG and OG phases, respectively, to enable dual delivery. The effects of composition on rheological, textural, thermal, color, and stability properties were evaluated at HG/OG ratios of 70/30, 60/40, and 50/50. GG-based BGs formed rigid, coherent, and crystal-reinforced networks, exhibiting the highest oscillatory stiffness and complex viscosity. GA-based BGs developed softer, more deformable, and viscous structures, with mechanical behavior strongly governed by damping and water content. Increasing OG content reinforced GG BGs through beeswax–crystal integration, whereas in GA it increased oscillatory stiffness but weakened the cohesive, viscous, and recoverable characteristics of the protein network. Categorical principal component analysis (CATPCA) revealed two mechanical domains: a GA-associated regime dominated by viscosity, penetration resistance, and loss factor (tan δ), and a GG-associated regime governed by elastic stiffness. Correlations confirmed tan δ_max as a marker of structural fragility in GA, while stiffness parameters dominated GG behavior. Melting points remained within 53–54 °C, and all BGs showed excellent physical stability. Overall, GA and GG provide complementary design spaces, offering a mechanistic basis for the rational design of BGs with controlled structural and functional properties. Full article

The increasing penetration of variable renewable energy sources (RESs) poses significant challenges to power system flexibility and reliability, particularly in systems with high solar generation. At the same time, existing Concentrating Solar Power (CSP) plants in Europe face declining economic viability due to high capital costs and the expiration of incentivized tariff schemes. This study proposes and evaluates a novel approach to repurpose CSP plants as flexible energy assets through the integration of cold thermal energy storage (CTES) within a Thermally Integrated Power-to-Heat-to-Power Energy Storage (TI-PTES) framework. The proposed system combines an ice/water-based cold storage with a CO₂-based refrigeration cycle to enhance the efficiency of the CSP steam cycle by reducing condenser temperatures, while also enabling temporal shifting of electricity consumption. A techno-economic optimization model based on PyPSA is developed to determine the optimal sizing and operation of the storage and refrigeration system under realistic load and electricity price conditions representative of the Spanish market. Results show that the integration of cold storage significantly alters system operation, shifting the chiller from a continuous demand-following mode to an intermittent, high-intensity regime. This leads to a reduction in annual operating expenditures by approximately 32% and an increase in annual profit and net present value (NPV), despite higher capital investment. While hourly net revenue becomes more volatile, with negative values during charging periods, cumulative annual performance improves due to effective temporal optimization. However, the absence of strong electricity price arbitrage and negative price signals limits the revenue potential of the storage system, which primarily acts as a cost-reduction mechanism. The findings demonstrate that cold thermal storage can successfully reposition CSP plants as flexible, value-generating assets in modern electricity systems. The proposed concept offers a promising pathway for extending the operational lifetime of existing CSP infrastructure while supporting higher integration of renewable energy sources. Full article

Micro gas turbines are small-scale systems based on the Brayton cycle and represent a viable solution for distributed generation. However, the main limitation to extending their application range is the cycle efficiency. Numerical and experimental analyses of power plants are important for evaluating the energy performance of different cycle configurations. Another issue is the formation of pollutants, including nitrogen oxide emissions. The humidified gas turbine cycle is one alternative to address these problems. Among wet cycles, the regenerative evaporative cycle offers a means to improve gas turbine efficiency. However, this configuration is less commonly discussed in the literature, which focuses more on steam injection cycles. Therefore, this paper presents an energy, exergetic, and nitrogen oxide formation analysis of an evaporative regenerative cycle for a 30 kW micro gas turbine across the gas turbine load range to define the most suitable operational system regime. The novelty of this study lies in an integrated assessment that simultaneously covers the operation of the micro gas turbine at full and part load under different conditions of water injection into the evaporator. The analyses conducted show that, for the micro turbine operating at full load, the benefits in terms of energy and pollutant formation are positive for all fractions of injected water. However, decreases in cycle performance are reported at power outputs below 19 kW compared with the dry cycle. Although nitrogen oxide formation decreases with increasing water injection, the reduction is less pronounced at lower microturbine power levels. Full article

Rice cultivation is a major source of methane (CH₄) emission in the agricultural sector, with a significantly higher global warming potential than carbon dioxide. Accurate and scalable quantification of CH₄ from rice paddies is essential for carbon accounting. This study presents an automated framework for estimating rice CH₄ emissions from irrigated paddies in the central plain of Thailand, integrating multi-sensor Synthetic Aperture Radar (SAR) observations with the IPCC methodology. The framework combines Sentinel-1 C-band SAR time series for phenological detection, ALOS-2 PALSAR-2 L-band full-polarimetric SAR for water regime classification, and IPCC water-scaling factors corresponding to Continuous Flooding, Single Drainage, or Multiple Drainage regimes. Evaluated across five stratified holdout sets, the phenology detection algorithm achieved planting and harvesting date Mean Absolute Errors of 6.1 ± 1.4 and 8.3 ± 1.7 days, with a 97.0% ± 2.7% operational detection rate. Water regime classification employed rice growth stage-specific Support Vector Machine classifiers with Radial Basis Function kernels (SVM-RBF), achieving per-stage test Balanced Accuracy ranging from 0.59 to 0.89. End-to-end integration using a four-track counterfactual decomposition yielded a full-pipeline mean absolute error of 18.5 ± 4.5 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$ (21.4% of the mean ground-based CH₄ calculation) and a mean bias of 3.5 ± 5.8 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$. Water level classification was confirmed as the dominant algorithmic uncertainty source, while the IPCC Tier 1 emission factor structural range (−32% to +48% of the default) exceeded all algorithmic errors combined. The proposed framework provides a spatially explicit approach for integrating multi-frequency SAR data into IPCC-compliant methane estimation, supporting Monitoring, Reporting, and Verification applications. Full article

Seasonal snowpack and snowmelt are critical regulators of forest ecosystem functioning in temperate, boreal, montane, and alpine regions. Snowpack acts as a temporary water and energy reservoir, while snowmelt determines the seasonal availability of water and influences ecosystem processes during the growing season. Climate change is altering snowfall patterns, snow accumulation, and melt timing, with consequences for forest productivity, resilience, and disturbance dynamics. This review synthesizes current knowledge on snow–forest interactions and identifies major research trends, methodological approaches, and remaining knowledge gaps. The study combines a bibliometric analysis and a qualitative literature review based on publications indexed in the Scopus and Web of Science databases. A total of 695 publications were included in the bibliometric dataset and analyzed to assess temporal trends, geographical patterns, research themes, and the ecological consequences of changing snow dynamics in forests. Representative studies from this dataset were subsequently synthesized to evaluate the influence of snowpack and snowmelt on forest ecosystem functioning, resilience, and sustainability. The reviewed literature shows that snowpack and snowmelt strongly regulate forest water availability, soil thermal conditions, nutrient cycling, vegetation responses, and carbon dynamics. Changes in snow regimes, particularly reduced snow accumulation and earlier melt, can increase the risk of soil freezing, modify moisture conditions, intensify water stress, and affect ecosystem carbon balance. However, the magnitude and direction of these effects depend on forest type, species composition, climate, and landscape characteristics. Forest structure also plays an important role in controlling snow interception, accumulation, persistence, and melt processes. The bibliometric analysis indicates a rapid increase in research interest in snow–forest interactions over the last two decades, with major contributions from the United States, Canada, China, and Northern Europe. Environmental sciences, hydrology, and ecology were the dominant research areas. Despite substantial progress, uncertainties remain regarding long-term ecosystem responses, species-specific vulnerabilities, and the interactions between declining snow cover and other climate-driven disturbances. This review emphasizes that understanding snowpack and snowmelt dynamics is essential for predicting forest ecosystem responses to climate change and for improving sustainable forest management and watershed conservation strategies in snow-dependent regions. Full article

Drought stress significantly constrains broccoli (Brassica oleracea L.) productivity by impairing growth, photosynthesis, and yield. Seed priming with ascorbic acid (AsA) has shown promise in enhancing early seedling performance; however, its effects on head development and yield under water deficit remain limited. This greenhouse pot experiment evaluated four seed treatments: non-primed control, water-primed control, 1 mg L⁻¹ AsA, and 10 mg L⁻¹ AsA under two irrigation regimes: 100% and 50% field capacity. Growth, physiological traits, biochemical responses, and yield were assessed. AsA priming significantly (p < 0.05) enhanced plant height, net photosynthesis, and chlorophyll content under both water regimes. Under 100% FC, water priming significantly increased canopy length, whereas under 50% FC, only AsA priming produced a significant increase relative to the non-primed control (p < 0.05). Biochemical responses further showed that 10 mg L⁻¹ AsA significantly (p < 0.05) increased chlorophyll a and chlorophyll b under 50% FC compared with the non-primed control. Proline accumulation was reduced by 10 mg L⁻¹ AsA, but this reduction was significant (p < 0.05) only under 100% FC. Under 100% FC, 10 mg L⁻¹ AsA significantly (p < 0.05) increased total phenolic content compared with the non-primed control. Total flavonoid content was significantly (p < 0.05) increased by 1 and 10 mg L⁻¹ AsA compared with the control, while both water priming and AsA priming significantly (p < 0.05) increased carotenoid content and reduced H₂O₂ accumulation relative to the non-primed control, irrespective of watering regime. Total yield per plant, measured on a fresh weight basis, significantly (p < 0.05) increased with increasing AsA concentration, with 10 mg L⁻¹ AsA enhancing yield by 37.8% relative to the water-primed control and by 70.5% relative to the non-primed control, independent of water regime. Percentage dry weight was unaffected by AsA treatment. Overall, AsA seed priming potentially enhanced physiological resilience and fresh yield of broccoli under water-limited conditions, indicating its potential as a low-cost strategy for drought mitigation. Full article

A field experiment was conducted at the Agronomy Field Laboratory of Bangladesh Agricultural University to evaluate the effects of arbuscular mycorrhizal fungi (AMF) inoculation and foliar supplementation of nitrogen (N) and phosphorus (P) on the performance of maize (Zea mays L.) under irrigated and rainfed conditions. The experiment followed a randomised complete block design with two levels of AMF (inoculated and non-inoculated) and four foliar treatments (no N and P, N only, P only, and combined N + P). The recommended dose of fertiliser (RDF) was applied as a soil application to all treatments. AMF inoculation significantly increased grain yield by 8.1% under rainfed and 10.0% under irrigated conditions compared with non-inoculated plants. Foliar application of N and P, especially when they were applied together, significantly improved yield components, including cob length, number of grains per cob, and 1000-grain weight. The highest grain yield (9.08 t ha⁻¹ under rainfed and 10.91 t ha⁻¹ under irrigated conditions) was obtained from the combined treatment of AMF inoculation and foliar N + P application. Redundancy analysis (RDA) and linear mixed-effects modelling (LMM) confirmed that water availability was the dominant factor controlling maize productivity, while AMF inoculation exhibited a stronger independent effect than foliar fertilisation. Under rainfed conditions, the treatment responses were reduced, and maize responded better to foliar N application in combination with AMF than combined N + P application. These findings indicate that the integrated use of AMF and foliar nutrient management enhances maize productivity, but optimal combinations depend strongly on moisture regimes. Full article

Accurate monitoring of inundation in rice paddies is essential for optimizing water use efficiency and mitigating methane emissions; yet, detecting water beneath dense rice canopies remains a major challenge. This study proposed a reliable classification approach applied to the Winter–Spring 2025 season in An Giang province, Vietnam, by integrating multi-temporal ALOS-2 PALSAR-2 (L-band) and Sentinel-1 (C-band) SAR data with in situ field surveys. Time-series Sentinel-1 observations were used to estimate rice phenology (rice age), while multi-polarization backscatter from ALOS-2 PALSAR-2 was analyzed to discriminate inundated from non-inundated conditions across different growth stages. Results demonstrated that L-band signals, particularly in VV polarization, penetrated dense vegetation effectively, enabling classification of inundated vs. non-inundated fields with an overall accuracy of 81% and a Kappa coefficient of 0.77. The resulting multi-date inundation maps revealed distinct flooding regimes consistent with local field survey observations. These findings demonstrated the potential of L-band VV SAR data for characterizing sub-canopy inundation conditions under rice canopies. Crucially, the approach provides essential data for greenhouse gas inventories and supports the verification of low-emission water management practices, such as Alternate Wetting and Drying (AWD). Overall, the study demonstrated the value of multi-frequency SAR integration for advancing agricultural monitoring and climate-smart management in rice-growing regions. Full article