Search Results (775)

This study investigates the delineation of management zones (MZs) to support site-specific crop management by simplifying within-field variability in irrigated (54.6 ha) and rainfed (7.9 ha) sorghum and soybean fields in Brazil. Historical yield, apparent soil electrical conductivity (ECa) at 0.75 m and 1.50 m, and terrain data were analyzed using multivariate statistics to define MZs. Two clustering methods—fuzzy c-means (FCM) and hierarchical clustering—were compared for variance reduction effectiveness. Rainfed areas showed greater spatial variability (yield CV 9–12%; ECa CV 20–27%) than irrigated fields (yield CV < 7%; ECa CV ~5%). Principal component analysis (PCA) identified subsoil ECa and elevation as key variables in irrigated fields, while surface ECa and topography influenced rainfed variability. FCM produced more homogeneous zones with fewer classes, especially in irrigated fields, whereas hierarchical clustering better detected outliers but required more zones for similar variance reduction. Yield correlated strongly with slope and moisture in rainfed systems. These results emphasize aligning MZ delineation with production system characteristics—enabling variable rate irrigation in irrigated fields and promoting moisture conservation in rainfed systems. FCM is recommended for operational efficiency, while hierarchical clustering offers higher precision in complex contexts. Full article

Wave deformation and sediment transport nearest the shoreside are among the main reasons for sand erosion and beach profile changes. In particular, identifying the areas of incident-wave breaking and longshore current generation parallel to the shoreline is important for understanding the morphological changes of coastal beaches. In this study, a two-phase incompressible flow model along with a sandy sloping topography was employed to investigate the wave deformation and longshore current generation areas in a circular wave basin model. The finite volume method (FVM) was implemented to discretize the governing equations in cylindrical coordinates, the volume-of-fluid method (VOF) was adopted to differentiate the air–water interfaces in the control cells, and the zonal embedded grid technique was employed for grid generation in the cylindrical computational domain. The water surface elevations and velocity profiles were measured in different wave conditions, and the measurements showed that the maximum water levels per wave were high and varied between cases, as well as between cross-sections in a single case. Additionally, the mean water levels were lower in the adjacent positions of the approximated wave-breaking zones. The wave-breaking positions varied between cross-sections in a single case, with the incident-wave height, mean water level, and wave-breaking position measurements indicating the influence of downstream flow variation in each cross-section on the sloping topography. The cross-shore velocity profiles became relatively stable over time, while the longshore velocity profiles predominantly moved in the alongshore direction, with smaller fluctuations, particularly during the same time period and in measurement positions near the wave-breaking zone. The computed velocity profiles also varied between cross-sections, and for the velocity profiles along the cross-shore and longshore directions nearest the wave-breaking areas where the downstream flow had minimal influence, it was presumed that there was longshore-current generation in the sloping topography nearest the shoreside. The computed results were compared with the experimental results and we observed similar characteristics for wave profiles in the same wave period case in both models. In the future, further investigations can be conducted using the presented circular wave basin model to investigate the oblique wave deformation and longshore current generation in different sloping and wave conditions. Full article

Land cover, topography, precipitation, and socio-economic factors exert both direct and indirect influences on urban land surface temperatures. Within the broader context of global climate change, these influences are magnified by the escalating intensity of the urban heat island effect. However, the interplay and underlying mechanisms of natural and socio-economic determinants of land surface temperatures remain inadequately explored, particularly in the context of cold-region cities located in the northern temperate zone of China. This study focuses on Changchun City, employing multispectral remote sensing imagery to derive and spatially map the distribution of land surface temperatures and topographic attributes. Through comprehensive analysis, the research identifies the principal drivers of temperature variations and delineates their seasonal dynamics. The findings indicate that population density, night-time light intensity, land use, GDP (Gross Domestic Product), relief, and elevation exhibit positive correlations with land surface temperature, whereas slope demonstrates a negative correlation. Among natural factors, the correlations of slope, relief, and elevation with land surface temperature are comparatively weak, with determination coefficients (R²) consistently below 0.15. In contrast, socio-economic factors exert a more pronounced influence, ranked as follows: population density (R² = 0.4316) > GDP (R² = 0.2493) > night-time light intensity (R² = 0.1626). The overall hierarchy of the impact of individual factors on the temperature model, from strongest to weakest, is as follows: population, night-time light intensity, land use, GDP, slope, relief, and elevation. In examining Changchun and analogous cold-region cities within the northern temperate zone, the research underscores that socio-economic factors substantially outweigh natural determinants in shaping urban land surface temperatures. Notably, human activities catalyzed by population growth emerge as the most influential factor, profoundly reshaping the urban thermal landscape. These activities not only directly escalate anthropogenic heat emissions, but also alter land cover compositions, thereby undermining natural cooling mechanisms and exacerbating the urban heat island phenomenon. Full article

The Caucasus region, characterized by its complex topography and diverse climatic regimes, exhibits pronounced spatial variability in temperature and precipitation patterns. This study investigates the seasonal behavior of air temperature, precipitation, vertical temperature gradients, and inversion phenomena across distinct landscape types using observational data from 63 meteorological stations for 1950–2022. Temperature trends were analyzed using linear regression, while vertical lapse rates and inversion layers were assessed based on seasonal temperature–elevation relationships. Precipitation regimes were evaluated through Mann-Kendall trend tests and Sen’s slope estimators. Results reveal that temperature regimes are strongly modulated by landscape type and elevation, with higher thermal variability in montane and subalpine zones. Seasonal temperature inversions are most frequent in spring and winter, especially in western lowlands and enclosed valleys. Precipitation patterns vary markedly across landscapes: humid lowlands show autumn–winter maxima, while arid and semi-arid zones peak in spring or late autumn. Some landscapes exhibit secondary maxima and minima, influenced by Mediterranean cyclones and regional atmospheric stability. Statistically significant trends include increasing cool-season precipitation in humid regions and decreasing spring rainfall in arid areas. These findings highlight the critical role of topography and landscape structure in shaping regional climate patterns and provide a foundation for improved climate modeling, ecological planning, and adaptation strategies in the Caucasus. Full article

The wind energy resources in the northwestern desert and semi-desert grassland regions of China are abundant. However, the ramifications of large-scale centralized wind farm operations on terrestrial rodents remain incompletely understood. In May and September 2024, we employed a grid sampling method combined with burrow counting and kernel density analysis to investigate the spatial distribution of Alashan ground squirrel (Spermophilus alashanicus) burrows in different wind turbine power zones (control, 750 kW, 1500 kW, 2000 kW, and 2500 kW) at the Taiyangshan wind farm in China. Using generalized additive models and structural equation models, we analysed the relationship between burrow spatial distribution and environmental factors. The results revealed no significant linear correlation between burrow density and turbine layout density, but was significantly positively correlated with turbine power (p < 0.05). The highest burrow density was observed in the 2500 kW zone, with values of 24.43 ± 7.18 burrows/hm² in May and 21.29 ± 3.38 burrows/hm² in September (p < 0.05). The squirrels exhibited a tendency to avoid constructing burrows within the rotor sweeping areas of the turbines. The burrow density distribution exhibited a multinuclear clustering pattern in both May and September, with a northwest–southeast spatial orientation. Turbine power, aspect, and plan convexity had significant positive effects on burrow density, whereas vegetation height had a significant negative effect. Moreover, vegetation height indirectly influenced burrow density through its interactions with turbine power and relief degree. Under the combined influence of turbine power, topography, and vegetation, Alashan ground squirrels preferred habitats in low-density, high-power turbine zones with shorter vegetation, sunny slopes, convex landforms, and minimal disturbance. Full article

The Alpine Periglacial Weathering Zone (APWZ) is a critical transitional belt between alpine vegetation and glaciers, and a highly sensitive region to climate change. Its dynamic variations profoundly reflect the surface environment’s response to climatic shifts. Taking Gongga Mountain as the study area, this study utilizes summer Landsat imagery from 1986 to 2024 and constructs a remote sensing method based on NDVI and NDSI indices using the Otsu thresholding algorithm on the Google Earth Engine platform to automatically extract the positions of the upper limit of vegetation and the snowline. Results show that over the past four decades, the APWZ in Gongga Mountain has exhibited a continuous upward shift, with the mean elevation rising from 4101 m to 4575 m. The upper limit of vegetation advanced at an average rate of 17.43 m/a, significantly faster than the snowline shift (3.9 m/a). The APWZ also experienced substantial areal shrinkage, with an average annual reduction of approximately 13.84 km², highlighting the differential responses of various surface cover types to warming. Spatially, the most pronounced changes occurred in high-elevation zones (4200–4700 m), moderate slopes (25–33°), and sun-facing aspects (east, southeast, and south slopes), reflecting a typical climate–topography coupled driving mechanism. In the upper APWZ, glacier retreat has intensified weathering and increased debris accumulation, while the newly formed vegetation zone in the lower APWZ remains structurally fragile and unstable. Under extreme climatic disturbances, this setting is prone to triggering chain-type hazards such as landslides and debris flows. These findings enhance our capacity to monitor alpine ecological boundary changes and identify associated disaster risks, providing scientific support for managing climate-sensitive mountainous regions. Full article

In response to the inability of traditional remote sensing technology to accurately capture the micro-topographic features of landslide surfaces in vegetated areas under complex terrain conditions, this paper proposes a method for enhanced landslide terrain display and trace recognition based on airborne LiDAR technology. Firstly, a high-precision LiDAR-DEM is constructed using preprocessed LiDAR point cloud data, and visual images are generated using visualization methods, including hillshade, slope, openness, and Sky View Factor (SVF). Secondly, pixel-level image fusion methods are applied to the visual images to obtain enhanced display images of the landslide terrain. Finally, a threshold is determined through a fractal model, and the Mean-Shift algorithm is utilized for clustering and denoising to extract landslide traces. The results indicate that employing pixel-level image fusion technology, which combines the advantageous features of multiple terrain visualization images, effectively enhances the display of landslide micro-topography. Moreover, based on the enhanced display images, the fractal model and the Mean-Shift algorithm are applied for denoising to extract landslide traces. Compared to orthophotos, this method can effectively and accurately extract landslide traces. The findings of this study provide valuable references for the enhanced display and trace recognition of landslide terrain in densely vegetated areas within complex mountainous areas, thereby providing technical support for emergency investigations of landslide disasters. Full article

In ecological restoration of arid/semi-arid sandy lands, micro-topographic variations and artificial shrub arrangement synergistically drive vegetation recovery and soil quality improvement. As a typical fragile ecosystem in northern China, the Mu Us Sandy Land has long suffered wind erosion, desertification, soil infertility, and vegetation degradation, demanding precise vegetation configuration for ecological rehabilitation. This study analyzed soil nutrients, plant diversity, and their correlations under various micro-topographic conditions across different types of artificial shrub plantations in the Mu Us Sandy Land. Employing one-way and two-way ANOVA, we compared the significant differences in soil nutrients and plant diversity indices among different micro-topographic conditions and shrub species. Additionally, redundancy analysis (RDA) was conducted to explore the direct and indirect relationships between micro-topography, shrub species, soil nutrients, and plant diversity. The results show the following: 1. The interdune depressions have the highest plant diversity and optimal soil nutrients, with relatively suitable pH values; the windward slopes and slope tops, due to severe wind erosion, have poor soil nutrients, high pH values, and the lowest plant diversity. Both micro-topography and vegetation can significantly affect soil nutrients and plant diversity (p < 0.05), and vegetation has a greater impact on soil nutrients. 2. The correlation between surface soil nutrients and plant diversity is the strongest, and the correlation weakens with increasing soil depth; under different micro-topographic conditions, the influence of soil nutrients on plant diversity varies. 3. In sandy land ecological restoration, a “vegetation type + terrain matching” strategy should be implemented, combining the characteristics of micro-topography and the ecological functions of shrubs for precise configuration, such as planting Corethrodendron fruticosum on windward slopes and slope tops to rapidly replenish nutrients, promoting Salix psammophila and mixed plantation in interdune depressions and leeward slopes to accumulate organic matter, and prioritizing Amorpha fruticosa in areas requiring soil pH adjustment. This study provides a scientific basis and management insights for the ecological restoration and vegetation configuration of the Mu Us Sandy Land. Full article

Rubber Tree (Hevea brasiliensis) phenology critically influences tropical plantation productivity and carbon cycling, yet topography and climate impacts remain unclear. By integrating multi-sensor remote sensing (2001–2020) and Google Earth Engine, this study analyzed spatiotemporal dynamics in Hainan Island, China. Results reveal that both the start (SOS occurred between early and late March: day of year, DOY 60–81) and end (EOS occurred late January to early February: DOY 392–406, counted from the previous year) of the growing season exhibit progressive delays from the southeast to northwest, yielding a 10–11 month growing season length (LOS). Significantly, LOS extended by 4.9 days per decade (p < 0.01), despite no significant trends in SOS advancement (−1.1 days per decade) or EOS delay (+3.7 days per decade). Topographic modulation was evident: the SOS was delayed by 0.27 days per 100 m elevation rise (p < 0.01), while the EOS was delayed by 0.07 days per 1° slope increase (p < 0.01). Climatically, a 100 mm precipitation increase advanced SOS/EOS by approximately 1.0 day (p < 0.05), preseasonally, a 1 °C February temperature rise advanced the SOS and EOS by 0.49 and 0.53 days, respectively, and a 100 mm January precipitation increase accelerated EOS by 2.7 days (p < 0.01). These findings advance our mechanistic understanding of rubber phenological responses to climate and topographic gradients, providing actionable insights for sustainable plantation management and tropical forest ecosystem adaptation under changing climatic conditions. Full article

The lower Yarlung Zangbo River Basin’s Great Bend region, characterized by extreme topography and intense orographic precipitation processes, presents significant challenges for accurate precipitation estimation using reanalysis products. Therefore, this study evaluates four widely used products (ERA5-Land, MSWEP, CMA, and TPMFD) against station observations (2014–2022) in this critical area. Performance was rigorously assessed using correlation analysis, error metrics (RMSE, MAE, RBIAS), and spatial regression. The region exhibits strong seasonality, with 62.1% of annual rainfall occurring during the monsoon (June-October). Results indicate TPMFD performed best overall, capturing spatiotemporal patterns effectively (correlation coefficients 0.6–0.8, low RBIAS). Conversely, ERA5-Land significantly overestimated precipitation, particularly in rugged northeast areas, suggesting poor representation of orographic effects. MSWEP and CMA underestimated rainfall with variable temporal consistency. Topographic analysis confirmed slope, aspect, and longitude strongly control precipitation distribution, aligning with classical orographic mechanisms (e.g., windward enhancement, lee-side rain shadows) and monsoonal moisture transport. Spatial regression revealed terrain features explain 15.4% of flood-season variation. TPMFD most accurately captured these terrain-precipitation relationships. Consequently, findings underscore the necessity for terrain-sensitive calibration and data fusion strategies in mountainous regions to improve precipitation products and hydrological modeling under orographic influence. Full article

The blue-eared pheasant (Crossoptilon auritum), a Near Threatened (NT) species endemic to China, is primarily distributed across the northeastern region of the Qinghai–Tibetan Plateau. To bridge the fine-scale spatiotemporal gap in blue-eared pheasant behavioral ecology, this study combines satellite telemetry, movement modeling, and field-based habitat assessments (vegetation, topography, human disturbance). This multidisciplinary approach reveals detailed patterns of their behavior throughout the breeding season. Using satellite-tracking data from six individuals (five males tracked at 4 h intervals; one female tracked hourly) in Wanglang National Nature Reserve (WLNNR), Sichuan Province during breeding seasons 2018–2019, we quantified their home ranges via Kernel Density Estimation (KDE) and examined the female movement patterns using a Hidden Markov Model (HMM). The results indicated male core (50% KDE: 21.93 ± 16.54 ha) and total (95% KDE: 158.30 ± 109.30 ha) home ranges, with spatial overlap among individuals but no significant temporal variation in home range size. Habitat selection analysis indicated that the blue-eared pheasants favored shrub-dominated areas at higher elevations (steep southeast-facing slopes), regions distant from human disturbance, and with abundant animal trails. We found that their movement patterns differed between sexes: the males exhibited higher daytime activity yet slower movement speeds, while the female remained predominantly near nests, making brief excursions before returning promptly. These results enhance our understanding of the movement ecology of blue-eared pheasants by revealing fine-scale breeding-season behaviors and habitat preferences through satellite-tracking. Such detailed insights provide an essential foundation for developing targeted conservation strategies, particularly regarding effective habitat management and zoning of human activities within the species’ range. Full article

The scenario adaptability of agricultural machinery chassis in hilly and mountainous regions has become a key area of innovation in modern agricultural equipment development in China. Due to the fragmented nature of farmland, steep terrain (often exceeding 15°), complex topography, and limited suitability for mechanization, traditional agricultural machinery experiences significantly reduced operational efficiency—typically by 30% to 50%—along with poor mobility. These limitations impose serious constraints on grain yield stability and the advancement of agricultural modernization. Therefore, enhancing the scenario-adaptive performance of chassis systems (e.g., slope adaptability ≥ 25°, lateral tilt stability > 30°) is a major research priority for China’s agricultural equipment industry. This paper presents a systematic review of the global development status of agricultural machinery chassis tailored for hilly and mountainous environments. It focuses on three core subsystems—power systems, traveling systems, and leveling systems—and analyzes their technical characteristics, working principles, and scenario-specific adaptability. In alignment with China’s “Dual Carbon” strategy and the unique operational requirements of hilly–mountainous areas (such as high gradients, uneven terrain, and small field sizes), this study proposes three key technological directions for the development of intelligent agricultural machinery chassis: (1) Multi-mode traveling mechanism design: Aimed at improving terrain traversability (ground clearance ≥400 mm, obstacle-crossing height ≥ 250 mm) and traction stability (slip ratio < 15%) across diverse landscapes. (2) Coordinated control algorithm optimization: Designed to ensure stable torque output (fluctuation rate < ±10%) and maintain gradient operation efficiency (e.g., less than 15% efficiency loss on 25° slopes) through power–drive synergy while also optimizing energy management strategies. (3) Intelligent perception system integration: Facilitating high-precision adaptive leveling (accuracy ± 0.5°, response time < 3 s) and enabling terrain-adaptive mechanism optimization to enhance platform stability and operational safety. By establishing these performance benchmarks and focusing on critical technical priorities—including terrain-adaptive mechanism upgrades, energy-drive coordination, and precision leveling—this study provides a clear roadmap for the development of modular and intelligent chassis systems specifically designed for China’s hilly and mountainous regions, thereby addressing current bottlenecks in agricultural mechanization. Full article

This study investigates the influence of environmental variables on the elemental composition of Hypnum cupressiforme Hedw. mosses in Georgia and the Republic of Moldova, within moss biomonitoring studies aimed at analyzing atmospheric deposition patterns. Moss samples of Hypnum cupressiforme, characterized by a cosmopolitan distribution and a wide range of habitats, were collected from diverse geographical and climatic zones and analyzed for Al, Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sr, V, and Zn. Statistical methods (Spearman correlations, PCA, Kruskal–Wallis tests) were applied to evaluate interactions between elemental concentrations and factors such as topography, climate, land cover, etc. Results revealed strong correlations among lithogenic elements (Al, Co, Cr, Fe, Ni, and V), indicating natural weathering sources, while Cu exhibited potential anthropogenic origins in the Republic of Moldova. Elevated Cd and Pb levels in Georgian high-altitude regions were linked to wet deposition and steep slopes, whereas Moldovan samples showed higher Sr and Zn concentrations, likely driven by soil erosion in carbonate chernozems. The study highlights geogenic and climatic influences on element accumulation by moss, offering insights into the effectiveness of moss biomonitoring across heterogeneous landscapes. Full article

The pronounced spatial heterogeneity of underlying surface characteristics within the parallel ridge–valley system of eastern Sichuan necessitated hydrological discretization of the watershed into nested subdomains comprising inter-ridge valley units and secondary slope cells. A distributed flood simulation framework specifically adapted to parallel ridge–valley topography was developed, coupled with a sequential intelligent parameter optimization algorithm. Model validation was conducted through the simulation of ninety flood events (2015–2023) in the Lishui watershed, a representative parallel ridge–valley basin. For parameter-calibrated sub-watersheds, mean relative errors of 13.8% (peak discharge) and 12.3% (runoff depth) were achieved, while non-calibrated watersheds exhibited marginally higher inaccuracies at 14.6% and 15.1%, respectively. Spatial parameter estimation was effectively implemented through the assimilation of limited hydrometeorological station data. The integrated modeling framework, incorporating terrain-adaptive parameterization and intelligent calibration protocols, demonstrated high-fidelity flood process simulation capabilities in complex parallel ridge–valley landscapes. Full article

The dynamics of large lake circulations are strongly modulated by wind forcing, thermal gradients, and shoreline topography, yet their integrated effects remain insufficiently quantified. To address this, numerical simulations were conducted in Lake Biwa to clarify the mechanisms underlying wind- and thermally driven gyres, with a focus on the influence of bathymetric asymmetry. In wind-driven cases, zonal and meridional wind stress gradients were imposed, revealing that cyclonic wind shear generated strong surface vorticity (up to 2.0 × 10⁻⁶ s⁻¹) in regions with gently sloped shores, while steep slopes suppressed anticyclonic responses. Cyclonic forcing induced upwelling in the lake center, with baroclinic return flows stabilizing the vertical circulation structure. In windless thermal experiments, surface temperature gradients of ±2.5 °C were applied to simulate seasonal heating and cooling. Cyclonic circulation predominated in warm seasons due to convergence and heat accumulation along gently sloping shores, whereas winter cooling produced divergent flows and anticyclonic gyres. The southern and eastern lake margins, characterized by mild slopes, consistently enhanced convergence and vertical mixing, while steep western and northern slopes limited circulation intensity. These results demonstrate that shoreline slope asymmetry plays a decisive role in regulating both wind- and thermally induced circulations, offering insights into physical controls on transport and stratification in enclosed lake systems. Full article