Search Results (1,486)

Farmland soil water-soluble organic carbon (WSOC), serving as a labile carbon substrate for microbial utilization, demonstrates pronounced sensitivity to land-use modifications and agricultural management practices. This study systematically investigated the impacts of long-term straw incorporation frequencies—including annual (S-1), biennial (S-2), and triennial (S-3) return patterns—on WSOC distribution across 0–20 cm and 20–40 cm soil profiles. Through the integration of three-dimensional excitation–emission matrix (EEM) fluorescence spectroscopy with parallel factor analysis (PARAFAC), we elucidated structural characteristics and humification dynamics associated with different incorporation regimes. The results showed a depth-dependent WSOC distribution pattern with higher concentrations in surface soils (0–20 cm: 261.2–368.9 mg/kg) compared to subsurface layers (20-40 cm: 261.8–294 mg/kg). Straw incorporation significantly increased WSOC content in the 0–20 cm of 16.9%~21.7% and 20–40 cm soil layers of 6.2%~12.3%. Biennial return had the lowest WSOC/SOC ratio, indicating enhanced stability of the soil organic carbon pool. Spectral indices—including the fluorescence index (FI, 1.59~1.69), biological index (BIX, 0.90~0.95), and humification index (HIX, 0.64~0.74)—collectively indicated that WSOC predominantly consisted of microbially processed organic matter with a low degree of humification. PARAFAC modeling resolved two fluorescent components: C1 (humic acid-like substances, 47.4–50.4%), C2 (soluble microbial metabolites, 49.6–52.6%). This systematic investigation provides mechanistic insights into how straw management temporality regulates both quantity and quality of labile carbon pools in agricultural ecosystems. Full article

Microplastic pollution in freshwater systems represents a growing environmental concern, yet the dynamics of microplastic distributions in smaller tributaries like canals/creeks remain understudied. This case study presents an investigation of microplastic contamination in a canal system in upstate New York, USA, examining land use and rainfall that influence microplastic abundance, distribution, and characteristics. Water and sediment samples were collected bi-weekly (June–August 2023) from sites representing runoff from diverse land-use types: agricultural areas, residential zones, academic buildings, and parking lots. The study reveals significant land-use dependent variations in contamination, with mean concentrations of 17 ± 7 items/L in the water column, while suspended sediment and bedload reached 540 ± 230 items/kg and 370 ± 80 items/kg, respectively. Upstream water column exhibited the highest loads (27 ± 2 items/L), driven by cumulative agricultural and commercial inputs, while downstream declines highlighted vegetation-mediated sedimentation. Land-use patterns strongly influenced contamination profiles, with parking lots exhibiting tire-wear fragments, artificial turf contributing polyethylene particles, and residential areas contributing 43% textile fibers. Rainfall intensity and antecedent dry days differentially influenced transport mechanisms. Antecedent dry days strongly predicted parking lot runoff fluxes surpassing rainfall intensity effects and underscored impervious surfaces as transient microplastic reservoirs. Full article

Urban agriculture’s potential for food production and other social benefits is widely documented. However, the diversity of organisational structures and contextual factors that shape and drive the practice leads to a range of productivity levels. Yet, most studies estimate productivity using average production data, which compromises the reliability of the estimates. The objective of the study presented here is to develop a GIS-based spatial analytical framework that takes into account varying levels of productivity for four urban food garden types: Home, Community, Educational, and Commercial. We apply this analytical framework in Bogotá, Colombia, a city at the forefront of policies promoting urban agriculture, where we collected data from a sample of urban food gardens (i.e., produce yield, resource use, and social benefits). To increase the precision and reliability of the estimates, we perform a spatial Multi-Criteria Decision Analysis through several ArcGIS pro 3.1 functions. This allows the identification of suitable areas for each urban agriculture type, based on key spatial and social characteristics (location, proximity to roads and to rivers, private or public land, urban density, and socio-economic demographic conditions). Results suggest that 25% of Bogotá’s surface area (including vacant urban land and roofs) presents potential physical and social conditions for food growing, within which Home Gardens occupy the largest share of suitable land. This shows that land availability is not a key limiting factor to a possible expansion of urban agriculture, particularly at a household level. Resource consumption and educational benefits are also estimated, hence providing a comprehensive picture of the impact of urban food production at a city scale. Full article

Advances in distributed electric propulsion and urban air mobility technologies have spurred a surge of research on electric Vertical Take-Off and Landing (eVTOL) aircraft. Distributed Multi-Propeller Tilting-Wing (DMT) eVTOL configurations offer higher forward flight speed and efficiency. However, aerodynamic challenges during the transition phase have limited their practical application. This study develops a high-fidelity body-fitted mesh CFD numerical simulation method for flow field calculations of DMT aircraft. Using the reverse overset assembly method and CPU-GPU collaborative acceleration technology, the accuracy and efficiency of flow field simulations are enhanced. Using the established method, the influence of dynamic tilting speeds on the flow field of this configuration is investigated. This paper presents the variations in the aerodynamic characteristics of the tandem propellers and tilt-wings throughout the full tilt process under different tilting speeds, analyzes the mechanisms behind reductions in the propeller’s aerodynamic performance and tilt-wing lift overshoot, and conducts a detailed comparison of flow field distribution characteristics under fixed-angle tilting, slow tilting, and fast tilting conditions. The study explores the influence mechanism of tilting speed on blade tip vortex-lifting surface interactions and interference between tandem propellers and tilt-wings, providing valuable conclusions for the aerodynamic design and safe transition implementation of DMT aircraft. Full article

Resource-based regions play an indispensable role as strategic bases for national energy and raw material supply in the global industrialization and urbanization process. However, intensive and large-scale natural resource exploitation—particularly mineral extraction—often triggers dramatic land use/cover changes, leading to a series of problems including cultivated land degradation, ecological function deterioration, and human settlement environment degradation. However, a systematic understanding of the functional transitions within the land use system and their drivers in such regions remains limited. This study takes Shenmu City, a typical resource-based city in the ecologically vulnerable Loess Plateau, as a case study to systematically analyze the transition characteristics and driving mechanisms of land use functions from 2000 to 2020. By constructing an integrated “element–structure–function” analytical framework and employing a suite of methods, including land use transfer matrix, Spearman correlation analysis, and random forest with SHAP interpretation, we reveal the complex spatiotemporal evolution patterns of production–living–ecological functions and their interactions. The results demonstrate that Shenmu City has undergone rapid land use transformation, with the total transition area increasing from 27,394.11 ha during 2000–2010 to 43,890.21 ha during 2010–2020. Grassland served as the primary transition source, accounting for 66.5% of the total transition area, while artificial surfaces became the main transition destination, receiving 38.6% of the transferred area. The human footprint index (SHAP importance: 4.011) and precipitation (2.025) emerged as the dominant factors driving land use functional transitions. Functional interactions exhibited dynamic changes, with synergistic relationships predominating but showing signs of weakening in later periods. The findings provide scientific evidence and a transferable analytical framework for territorial space optimization and ecological restoration management not only in Shenmu but also in analogous resource-based regions facing similar development–environment conflicts. Full article

Increasing aridity across the Middle East Region has intensified concerns about the impacts of drought in conflict-affected Northeast Syria (NES). In this study, drought dynamics and their drivers from 2000 to 2023 were analyzed by integrating ERA5-Land meteorological data, MODIS land-surface indicators, FLDAS soil moisture, and ISRIC soil properties at 250 m resolution. The integration of these multisource datasets contributes to a more comprehensive understanding of drought dynamics by combining information on weather conditions, vegetation status, and soil characteristics. The proposed drought analysis framework clarifies independent controls on meteorological, agricultural, and hydrological drought, underscoring the role of land-atmosphere feedback through soil temperature. This workflow provides a transferable approach for drought monitoring and hypothesis generation in arid regions. For this purpose, different XGBoost models were trained for the vegetation health index (VHI), the standardized precipitation-evapotranspiration index (SPEI), and surface soil-moisture anomalies, excluding target-related variables to prevent data leakage. Model interpretability was achieved using SHAP, complemented by time-series, trend, clustering, and spatial autocorrelation analyses. The models performed well (R² = 0.86–0.90), identifying soil temperature, SPEI, relative humidity, precipitation, and soil-moisture anomalies as key predictors. Regionally, soil temperature rose (+0.069 °C yr⁻¹), while rainfall (−1.203 mm yr⁻¹) and relative humidity (−0.075% yr⁻¹) declined. Spatial analyses demonstrated expanding heat hotspots and persistent soil moisture deficits. Although 2018–2019 were anomalously wet, recent years (2021–2023) exhibited severe drought. Full article

Southern China, despite its humid climate, has increasingly faced severe hydrological droughts (HDs) in recent decades, highlighting the complexity of drought propagation. Most existing studies primarily examined the relationship between drought propagation and climatic factors, whereas quantitative analyses of interactive effects of underlying surface characteristics on drought propagation remain insufficient. This study introduces an integrated framework combining GRACE satellite-derived terrestrial water storage anomalies with topography, land use, geology, and climate data to examine HD formation and its drivers. The results show a clear divergence between meteorological drought (MD) and HD patterns, revealing that underlying surface characteristics, rather than precipitation deficits alone, drive HD spatial patterns. Among drought propagation indicators, intensity has the strongest link to environmental factors, positively correlating with elevation and slope, and negatively with mean annual precipitation and temperature. Forest coverage helps mitigate drought intensification, while karst geology and land use influence propagation timing. HD intensity follows an elevational gradient, with severe droughts in high-altitude areas and mild, frequent droughts in low-lying basins. These insights provide a mechanistic basis for developing early-warning systems and spatially adaptive water management strategies, thereby supporting sustainable drought resilience and promoting long-term water resource sustainability in Southern China. Full article

The accessibility of rural tourism attractions is a key factor affecting their tourism development potential. Although forest land is the primary land cover type, the mechanism by which forest land influences accessibility has not been fully elucidated. This study takes Yongchun County in Fujian China as an example to explore the spatial relationship between forest land and the accessibility of rural tourism attractions. Based on multi-source spatial data and using a GIS cost raster analysis method, the study incorporates the road network, transportation modes, and land cover characteristics. Specifically, forest land was assigned a resistance coefficient of 1.5 to quantitatively assess the spatial pattern of attraction accessibility. In addition, spatial autocorrelation analysis was applied to reveal the spatial correlation characteristics between forest land distribution and attraction accessibility. The results indicate that: (1) There is a significant spatial complementarity between forest land distribution and attraction accessibility, which needs to be considered when building tourism networks. (2) The spatial pattern of forest land directly affects the layout of regional transportation networks, so planning for regional transportation network layouts should prioritize the impact of forest land. (3) By altering surface cover characteristics, forest land increases regional traversal resistance, thereby further affecting the spatial distribution pattern of attraction accessibility. This study provides empirical evidence for understanding the spatial relationship between forest land and rural tourism attraction accessibility and offers valuable reference for optimizing rural spatial structure and promoting tourism development. Full article

We evaluated six global digital elevation DEMs at 1-arc-sec resolution: CopDEM and AW3D30, which are digital surface models (DSMs), and EDTM, GEDTM, FABDEM, and FathomDEM, which are digital terrain models (DTMs). We compared them to reference DTMs created by mean aggregation from 1–2 m lidar-derived DTMs from national mapping agencies, using 1510 approximately 10 × 10 km test tiles from the United States and western Europe. Our criteria used the grids for elevation and derived land surface parameters (LSPs), including characteristics of the difference distributions and the fraction unexplained variance derived from grid correlations. The best DEM depends on the LSP used and the characteristics of the test tile, especially average slope, barrenness, and forest coverage. FathomDEM emerged as the best among the DEMs, with CopDEM the best overall for the DEMs with unrestricted licenses. GEDTM performed poorly. This is especially important for LSPs like curvature measures, which require higher-order partial derivatives for computation, and which should be used very cautiously. Full article

The urban heat island (UHI) has been a critical social problem as urbanization intensifies worldwide, significantly impacting human life by exacerbating heat-related health issues, increasing energy demand for cooling, and resulting in associated environmental problems. However, the fine-scale diurnal and spatial characteristics of UHI remain poorly understood due to the limited resolution of traditional satellite datasets. This study aims to quantify the diurnal and spatial dynamics of surface urban heat islands (SUHI) in Busan and Daegu—the two hottest metropolitan cities in Korea—by integrating high-resolution ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) (70 m) and Geostationary Korea Multi-Purpose Satellite-2A (GK-2A) (2 km) land surface temperature (LST) data. Using the combined datasets, season-representative diurnal LST variations were characterized, and locational heat intensification (LHI) was evaluated across land use types and densities at sub-district scales. The results show that the maximum SUHI intensity reached 10 °C in Daegu and 7 °C in Busan during summer, up to 8 °C higher than estimates from coarse-resolution data. Industrial areas recorded the highest LST (47 °C in Daegu and 43 °C in Busan) with rapid morning intensification rates of 2.0 °C/h and 1.9 °C/h, respectively. Dense urban land uses amplified LHI by nearly twofold compared to less dense urban areas. These findings emphasize the critical role of land use density and industrial heat emissions in shaping urban thermal environments, providing key insights for use in urban heat mitigation and climate-adaptive planning. Full article

China’s Yellow River basin encounters widespread risks of reduced runoff and intensified hydrological drought. This study focuses on the middle and upper reaches of the Dahei River, the Yellow River’s primary tributary. In this region, the Soil & Water Assessment Tool (SWAT) hydrological model was employed to simulate hydrological processes, identify runoff changes and hydrological drought characteristics, and conduct attribution analysis from 1983 to 2022, as well as to project trends over the next 40 years. The results indicate that total runoff during the impact period (1999–2022) decreased by 55.26% compared to the baseline period (1983–1998). Climate change accounted for a contribution rate of 38.6% to this decline, while human activities accounted for 61.4%. Additionally, climate primarily altered surface runoff (SURQ) and lateral groundwater flow (LATQ) through precipitation changes, while land use had a predominant influence on total runoff volume by modifying SURQ. Both factors exhibited relatively minor effects on LATQ. Moreover, human activities contribute to hydrological drought at a rate of 36.11% to 94.25%. Drought probability is significantly influenced by climate through precipitation and temperature changes, while land use primarily mitigates hydrological drought by impacting the three runoff components. It is predicted that over the next 40 years, total runoff will decrease by 2.08% to 60.16%, along with hydrological droughts that are more frequent, longer in average duration, and more intense; however, the Maximum Drought Duration is anticipated to shorten. In the east and northeast, hydrological drought presents a trend of intensification, with central and western regions exhibiting weaker or declining changes. Full article

With the accelerated launch of spaceborne Global Navigation Satellite System Reflectometry (GNSS-R) satellites, GNSS-R has gradually emerged as an important technique for remote sensing. However, due to its pseudo-random observation mode, the use of a single system makes it difficult to provide continuous spatiotemporal coverage over a specific area within the short term. Although interpolation methods can partially alleviate the coverage gaps, their application is limited by accuracy and reliability constraints, which still restrict the practical use of GNSS-R in terrestrial surface monitoring. To address this issue, conducting joint analyses and data fusion of multi-satellite GNSS-R observations has become an important approach to improving the continuity and accuracy of surface monitoring. However, systematic studies on the integration of multi-satellite GNSS-R data remain relatively limited. Moreover, differences in orbital inclination, antenna design, and signal bandwidth among various spaceborne GNSS-R systems lead to discrepancies in their land observations. Therefore, this study systematically analyzes the reflectivity differences among multiple GNSS-R satellites (e.g., the Cyclone Global Navigation Satellite System (CYGNSS), Fengyun-3 (FY-3), and Tianmu-1 (TM-1)) under consistent surface roughness and land cover conditions, with the aim of providing a theoretical and methodological foundation for the fusion and integrated application of multi-satellite GNSS-R data. The results show that, except for desert regions, the spatial distribution of the correlation coefficients from the least squares fitting of reflectivity between different spaceborne GNSS-R satellites exhibits a pattern similar to that of an established variable, i.e., the vegetation–roughness composite variable (VR), with higher inter-system correlations occurring in areas characterized by lower VR values. Significant reflectivity deviations were observed near water bodies and river networks, such as the Amazon, Paraná, Congo, Niger, Nile, Ganges, Mekong, and Yangtze, where both the fitting intercepts and biases are relatively large. In addition, the reflectivity correlations between CYGNSS–TM-1 and CYGNSS–FY-3 are both strongly influenced by surface vegetation cover type. As the correlation increases, the proportion of non-vegetated and forested areas decreases, while that of grasslands, shrublands, and cropland/vegetation mosaics increases. Analysis of inter-system reflectivity correlations across different land cover types indicates that forested areas exhibit low-to-moderate correlations but maintain stable structural characteristics, whereas wooded areas show moderate correlations slightly lower than those of forests. Grasslands, shrublands, and croplands are mainly distributed within regions of moderate surface roughness and correlation, among which croplands have the highest proportion of highly correlated grids, demonstrating the greatest potential for multi-source data fusion. Wetlands display high roughness and low correlation, largely influenced by dynamic water variations, while bare soils show low roughness (0.2–0.4) but still weak correlations. Full article

Water scarcity has become one of the most pressing challenges to agricultural sustainability, particularly in arid and semi-arid regions where climate change, dam construction, and rapid population growth have intensified the pressure on water and food resources. Groundwater adjacent to rivers represents a potential supplementary resource that can reduce reliance on restricted surface water supplies. This study assessed the hydrochemical characteristics and agricultural suitability of shallow groundwater located near the Tigris River, Iraq. Fieldwork involved monitoring four active wells and collecting samples over six periods from October 2022 to May 2023, combined with twelve soil samples from surrounding agricultural fields. Laboratory analyses determined key water and soil properties, including pH, electrical conductivity, major cations and anions, and a range of salinity and sodicity indices such as total dissolved solids (TDS), sodium adsorption ratio (SAR), residual sodium carbonate (RSC), potential salinity (PS), magnesium ratio, Simpson ratio (SR), Jones ratio (JR), and sodium percentage (Na%). Results indicated that groundwater levels fluctuated seasonally in tandem with the Tigris River, which directly influenced salinity levels. SI values were positive, TDS values were in the high salinity class, RSC values were consistently negative, PS values were in the medium to poor category, Na% values and MR values were within acceptable limits for irrigation, and SR values were moderately to highly contaminated. Groundwater quality, according to the U.S. Salinity Laboratory classification, was categorized between the C4S1 class (very high salinity, low sodium) and the C3S1 (high salinity, low sodium). Soil analyses showed predominantly light-textured soils with moderate Ec and SAR values below sodicity thresholds. The combination of soil permeability and groundwater characteristics suggests that irrigation is feasible under specific management practices. The study concludes that groundwater adjacent to rivers can serve as a valuable supplementary source for agriculture in semi-arid regions. Its use is most effective when applied to salt-tolerant crops, supported by leaching requirements, or blended with fresh water. These findings emphasize the importance of integrated groundwater management for enhancing agricultural resilience and sustainable land use under water-scarce conditions. Excessive extraction of groundwater near rivers can also pose long-term sustainability challenges. Full article

With the intensification of climate change and the urban heat island effect, there is growing awareness of the role of urban greening in improving the urban climate. The aim of this study is to explore how various characteristics of green spaces—including type, configuration (size and shape), location, and distance from the urban centre—affect their cooling effect. Landsat remote sensing land surface temperature data were analysed through Geographic Information Systems, using Sheffield as a case study. The results show that the cooling effect of woodland was significantly stronger than that of grassland and urban parks, with a cooling intensity reaching up to 2.93 °C, and a cooling extent that can reach up to 500 m beyond its boundary. When closer to the city centre, both the shape and size of green spaces show a positive correlation with their cooling effect, but this relationship becomes less evident as the distance from the city centre increases. The size of a woodland had a greater effect in terms of a reduction in land surface temperature than the shape of the woodland. The findings of this study can provide a better framework for landscape architects and urban planners to plan for climate change and propose stronger green strategies to mitigate the urban heat island effect. Full article

Urban densification intensifies the heat island effect, threatening ecological security. Green spaces, as crucial spatial elements in regulating the urban thermal environment, remain poorly understood in terms of their morphological characteristics and regulatory mechanisms, with a lack of systematic quantification and recognition of diurnal variations. This study, focusing on Shanghai’s main urban area, constructs physiological, physical, and morphological variables of green spaces based on high-resolution remote sensing data and the MSPA landscape morphology analysis framework. By integrating machine learning models with the SHAP interpretation algorithm, it analyses the influence mechanism of green spaces on Land Surface Temperature (LST) and its non-linear characteristics from the perspective of diurnal variation. The results indicate the following: (1) Green spaces exhibit pronounced diurnal variation in LST influence. Daytime cooling is primarily driven by vegetation cover, vegetation activity, and surface albedo through evapotranspiration and shading; night-time cooling depends on soil moisture and green space spatial structure and is achieved via thermal storage-radiative heat dissipation and cold air transport. (2) Green space indicators exhibit pronounced nonlinearity and threshold effects on LST. Optimal cooling efficiency occurs under moderate vegetation activity and moderate humidity conditions, whereas extreme high humidity or high vegetation activity may induce heat retention effects. (3) Day–night thermal regulation mechanisms differ markedly. Daytime cooling primarily depends on vegetation transpiration and shading to suppress surface warming; night-time cooling is dominated by soil thermal storage release, longwave radiation dissipation, and ventilation transport, enabling cold air to diffuse across the city and establishing a stable, three-dimensional nocturnal cooling effect. This study systematically reveals the distinct diurnal cooling mechanisms of high-density urban green spaces, providing theoretical support for refined urban thermal environment management. Full article