Search Results (74)

Beam bridges in mountainous and high-altitude transport corridors are frequently exposed to large diurnal temperature differences, intense solar radiation, low humidity, freeze–thaw action and repeated wetting–drying cycles. These coupled actions can accelerate concrete surface cracking and reduce the durability of prestressed concrete T-girder bridges, but field evidence linking crack morphology, crack depth, concrete cover and short-term environmental response remains limited. This study investigates a representative 40 m in-service prestressed concrete T-girder bridge on the Western Sichuan Plateau through field survey and four-month continuous monitoring. Crack location, length, width, depth and concrete cover thickness were measured, and representative crack-width responses to ambient temperature were analyzed. The results show that web cracks are dominated by reticular and irregular microcracks, bottom cracks are mainly longitudinal intermittent short cracks, and diaphragm cracks are concentrated near reticular zones and local corner discontinuities. The sunny side of the edge girder contained approximately 598 cracks, about 4.8 times the 123 cracks observed on the shaded side. Web and diaphragm crack widths were mainly 0–0.04 mm, while bottom-crack widths of 0–0.10 mm accounted for about 92.7%; most crack lengths were 2–20 cm. During monitoring, newly developed cracks accounted for about 6.0% of all recorded cracks, and only 3 of 721 existing cracks increased by 4–6 cm. Representative crack widths fluctuated by about 0.02 mm under −1 to 24 °C without sustained growth. Cracks wider than 0.20 mm generally exceeded the approximately 40 mm concrete cover. Such penetrating cracks should be prioritized in durability maintenance and long-term monitoring. Full article

The Tibetan Plateau sustains major Asian rivers through extensive cryospheric resources. However, hydrological associations of frozen ground degradation on downstream water availability remain insufficiently quantified. This study presents a preliminary assessment of thermal dynamics of frozen ground in the Yangtze–Yellow River source regions and their hydrological associations with the western Sichuan basins during 1961–2017. Using the near-surface ground freezing index (GFI) as a proxy indicator, we quantified contrasting streamflow responses between the Yangtze River source region (YaSR) and Yellow River source region (YeSR), and their connections with four major rivers in the western Sichuan basins. Results reveal divergent streamflow responses across four rivers, with predominantly positive anomalies despite widespread precipitation decline since the 2000s. As a permafrost-dominated basin, the YaSR exhibits enhanced streamflow generation, with contributions increasing from 6.63% to 31.31% as degradation intensifies. Conversely, the YeSR, mainly occupied by seasonally frozen ground, shows immediate streamflow attenuation that diminishes from 65.71% to 13.86% as degradation advances. The YaSR exhibits statistically significant positive associations with Jinsha and Yalong streamflows, while the YeSR develops significant statistical associations with Min River variability despite limited physical connectivity. These findings highlight the importance of frozen ground dynamics in regional water resource assessments under continued climate change. Full article

Wildfire regimes in mountain forest landscapes are shaped by complex interactions among topography, climate, vegetation, and human activity. However, predicting and interpreting fire occurrence in topographically heterogeneous regions remains challenging because fire–environment relationships vary strongly across elevation gradients and temporal scales. This study developed a hybrid machine-learning framework integrating an Information Value Model (IVM), Random Forest (RF), and Convolutional Neural Network (CNN) to decode elevation-mediated wildfire regimes in western Sichuan, China, a mountainous forest region characterized by strong vertical environmental gradients and high ecological conservation value. Multi-source datasets, including Moderate Resolution Imaging Spectroradiometer (MODIS) burned-area records, topographic variables, monthly meteorological data, vegetation indices, land-cover information, and human-accessibility proxies, were integrated at a 500 m spatial resolution. Environmentally comparable non-fire samples were generated from unburned vegetated pixels, and model training, RF-based feature selection, hyperparameter tuning using Particle Swarm Optimization (PSO), and performance evaluation were conducted within a nested spatial block cross-validation framework. The model produced continuous wildfire occurrence probabilities and showed strong discriminatory performance under the adopted validation protocol, with AUC values exceeding 0.95 across temporal datasets and low probability-error metrics. RF importance and correlation analyses identified mean temperature, elevation, and precipitation as the dominant predictors of wildfire probability. Spatial analyses revealed pronounced elevation-mediated differentiation in wildfire regimes: low-elevation valleys showed higher fire probability and stronger associations with human-accessibility proxies, whereas high-elevation plateau areas exhibited lower and more scattered fire patterns associated with climatic constraints. Seasonal and monthly analyses further showed that winter and spring fires dominated the regional fire regime, with risk intensifying during the pre-monsoon dry period. By combining probabilistic fire-risk mapping, spatial-context learning, and elevation-gradient interpretation, this study provides a transferable framework for understanding wildfire regimes in complex mountain forest landscapes. The findings support adaptive forest fire management, targeted monitoring, and risk zoning in mountainous regions where forest ecosystems, human activities, and conservation values intersect. Full article

Due to its unique hydrogeological conditions, the Southwest Karst Area (SKA) in China experiences droughts far more frequently than non-karst regions. Exploring the distribution patterns and driving factors of different drought types is crucial for enhancing the region’s disaster prevention and mitigation capabilities and effectively addressing climate change risks. Using meteorological data from 1979 to 2023 in the SKA—including precipitation, temperature, humidity, potential evapotranspiration, and soil moisture—this study employed Copula theory to construct the Standardized Temperature Deficit Index (SDTI), the Standardized Humidity–Temperature Deficit Index (SDHTI), and the Standardized Atmosphere–Soil Index (SASI). Based on these indices and run theory, this study revealed the spatial distribution characteristics of different drought types (general, atmospheric, and composite) in terms of intensity, frequency, severity, and duration. Furthermore, the Mann–Kendall test and random forest analysis were applied to investigate drought trends and primary driving factors. The results indicate that droughts in the SKA exhibit significant regional characteristics and an overall worsening trend. Among them, droughts in karst-developed regions are generally more severe, though their manifestations vary across areas: compound droughts are particularly severe on the western Sichuan Plateau but relatively mild in Guangxi. In contrast, atmospheric droughts are more pronounced in Guangxi. Regarding trends, the rate of drought intensification was relatively moderate in Guangxi and the western Sichuan Plateau but more pronounced in other regions, with the maximum increase reaching 0.59. However, this upward trend is not statistically significant. Additionally, drought in karst areas was characterized by high frequency and intensity but shorter duration and lower severity, whereas the opposite was true in non-karst areas. Random forest analysis revealed that temperature is the primary driver of SDTI (2.60), while relative humidity and temperature have significant impacts on SDHTI (3.21 and 2.42, respectively). Soil moisture and temperature contribute most significantly to SASI (2.08 and 1.48, respectively). These findings provide important insights to guide the rational allocation of regional water resources and optimize agricultural management strategies. Full article

Transmission lines in Southwestern China are highly exposed to compound hazards induced by extreme winds and ice and snow conditions. This study assesses future changes in extreme wind hazards and their spatial overlap with baseline ice susceptibility under the SSP2-4.5 emission scenario, using high-resolution dynamically downscaled climate projections. Compared to the historical period (1995–2014), the results indicate a marked intensification of extreme spring wind events over northwestern Southwestern China and the transitional zone between the Sichuan Basin and the Hengduan Mountains during 2041–2060. The occurrence frequency of wind speeds exceeding historical 50-year return levels is projected to increase by 5–10 times in complex terrain, particularly along the Golmud–Qaidam belt. The Comprehensive Extreme Wind Index (CEWI) identifies the Golmud–Wulanwusu–Qaidam river basin belt as the region of highest wind hazard amplification. Meanwhile, analysis of historical observations reveals that icing-prone conditions occur on more than 25 days each spring in the Nyenchentanglha Mountains and southeastern Tibetan Plateau valleys, establishing a baseline map of ice susceptibility. Due to methodological limitations in projecting future icing, this susceptibility map is used as a static indicator of ice-prone areas. By superimposing projected wind intensification onto the baseline ice susceptibility map, four relative hazard exposure categories are delineated. Regions of highest potential exposure are concentrated in the Bayan Har Mountains and portions of the western Hengduan Mountains, whereas northwestern basins are dominated by high wind risk alone. These results reveal pronounced spatial heterogeneity in the relative amplification of compound hazards under future warming and provide a scenario-informed scientific basis for prioritizing regions in disaster risk reduction and resilient planning of transmission infrastructure in mountainous regions. Full article

Prefabricated buildings offer high industrialization, construction efficiency, and sustainability benefits, making them particularly well suited for adverse construction conditions. As railway networks expand into western China’s high-altitude regions, prefabricated structures have been increasingly adopted for living quarters along railway lines in cold, high-altitude areas. This study proposes a method that accounts for thermal-bridge effects by using the average thermal transmittance coefficient K_m and the linear thermal transmittance ψ calculated via two-dimensional steady-state simulations with PTemp software. The approach was validated against 48 h field measurements from a prefabricated building in Weinan: the model incorporating thermal bridges reduced the mean temperature error from 15.6% to 7.74%, confirming its accuracy. Using DeST software, the indoor thermal environment of a railway living-quarter building in the Ganzi region was simulated. Results show that south-facing rooms have an average temperature 2.3 °C higher than north-facing rooms and a 17.74% lower annual discomfort time. Building orientation, south-facing window-to-wall ratio, and envelope thermal transmittance significantly affect overall indoor temperature and energy consumption. The optimal orientation range is 15–45° west of south, and the least favorable range is 135–165°. A south-facing WWR of 0.35–0.45 and an exterior wall insulation thickness of 60–120 mm are recommended. For the typical high-altitude locations Litang, Batang, Qamdo, Nyingchi, Lhasa, and Ganzi, region-specific optimal parameters are provided: exterior wall K_m values range from 0.10 to 0.65 W/(m²·K) and window K values from 1.0 to 3.0 W/(m²·K), depending on the local solar radiation and altitude. These findings offer quantitative design guidance for improving indoor thermal comfort and reducing energy use in prefabricated railway buildings on the western Sichuan and Tibetan plateaus. Full article

Precise, spatially explicit sub-provincial GDP estimates are essential for regional planning, especially in mountainous areas where official economic data remain spatially coarse and unevenly distributed. This study develops a multisource county-level GDP spatialization framework for Sichuan Province, China, integrating corrected NPP/VIIRS nighttime-light (NTL) data with Points of Interest (POIs), land-use structure indicators (proportion of farmland (PFL); proportion of construction land (PCL)), elevation, precipitation, accessibility and population density within a unified indicator system. Two regression approaches—Ordinary Least Squares (OLS) as a global benchmark and Geographically Weighted Regression (GWR) as the spatially adaptive primary model—are calibrated on county-level cross-sectional data for 2020 (n = 183) and evaluated using R², adjusted R², AICc and residual spatial diagnostics. The multisource GWR model achieves R² = 0.882 (adjusted R² = 0.872, AICc = 5712.26), substantially outperforming both the global OLS benchmark (R² = 0.801) and NTL-only GWR baseline (R² = 0.662), confirming that spatial nonstationarity is an intrinsic feature of the GDP–proxy relationship and that integrating complementary geospatial proxies is the primary pathway to improved estimation accuracy in topographically heterogeneous regions. The GWR-based GDP surface exhibits a pronounced basin–plateau contrast: high-value clusters concentrate along the Chengdu Plain and adjacent city corridors, while extensive low-value zones prevail across the western highlands (global Moran’s I = 0.33, Z = 14.26, p < 0.001). Spatially varying GWR coefficients reveal that elevation and precipitation constrain GDP most strongly in high-altitude counties, construction land exerts a consistently positive but spatially graded effect, and the influences of accessibility and population density are context-dependent and locally differentiated. These findings support differentiated territorial development policies: plateau counties require accessibility-first strategies; hill counties benefit from targeted small-city industrialization; and basin cores need managed growth to balance agglomeration advantages against congestion pressures. The framework relies exclusively on globally or nationally available data and is portable to other mountainous regions, though cross-regional validation and extension to multi-year panels using geographically weighted panel regression remain important directions for future work. Full article

Ecological zoning is a critical instrument for coordinating economic development with environmental conservation, ensuring regional ecological security, and fostering sustainable development. Using the Western Sichuan Plateau (WSP) as a case study and taking 2000, 2010, and 2020 as the time nodes, this research employed an optimized landscape ecological risk assessment model to comprehensively evaluate the spatiotemporal evolution of regional landscape ecological risk (LER) and ecosystem services (ESs). By analyzing the spatial correlation between LER and ESs, we constructed an ecological zoning framework, identified key driving factors, and proposed differentiated management strategies. The results showed the following: (1) The LER generally declined from 2000 to 2020, with the high-risk areas mainly distributed in the high-elevation meadow belt in the west and north, and the low and lowest-risk areas concentrated in the eastern part of the plateau continued to expand in area. (2) The overall level of ESs showed a downward and then upward trend, with a spatial pattern of “high in the east and low in the west”. (3) LER was significantly negatively correlated with most ESs (except WY), and localized agglomeration was clearly characterized. (4) Based on the four-quadrant model, the study area was categorized into four types of ecological zones, high LER–high ES, low LER–high ES, low LER–low ES and high LER–low ES, whose spatial patterns were mainly significantly influenced by factors such as elevation, per capita GDP and precipitation (PRE). The “risk-service” synergistic zoning framework proposed in this study provides a spatially explicit decision-making basis for ecological protection and restoration on the WSP, and is useful for the sustainable management of similar ecologically fragile areas. Full article

In July 2024, a severe rainfall event struck Sichuan Province, Southwest China, triggering deadly landslides and causing significant societal impacts. This study investigates the spatiotemporal characteristics and underlying mechanisms of the event using high-resolution surface observations, radar reflectivity, and ERA5 reanalysis data. The rainfall exhibited distinct mesoscale organization, with two primary precipitation centers identified: subregion A located within the plateau-lain transitional zone of the western Sichuan Basin, and subregion B situated over the Chengdu Plain. Synoptic-scale analysis indicated that the rainfall developed under favorable large-scale atmospheric conditions, including a mid-tropospheric trough, a pronounced low-level jet, and a well-defined Southwest Vortex (SWV), which is a dominant lower-tropospheric circulation system in this region. The evolution of rainfall was closely tied to the initiation and subsequent eastward progression of the SWV. The rainfall-producing mesoscale convective system (MCS) first formed over subregion A at approximately 2300 BST (UTC + 8) on 19 July. Vorticity budget diagnostics revealed that vertical advection and low-level convergence significantly contributed to vortex intensification during this initial phase, closely associated with the orographic lifting of low-level airflow. Convective activity in subregion B commenced roughly four hours later, coinciding with the eastward propagation of the SWV, during which horizontal vorticity advection became the primary mechanism sustaining the vortex. After 1400 BST on 20 July, the SWV weakened significantly, leading to the dissipation of the MCS and the cessation of rainfall. Full article

Against the intensifying global climate change, rural tourism destinations in plateau areas are confronted with the dilemma of balancing economic development with ecological conservation. Pro-environmental behavior (PEB)has become pivotal to achieving regional environmental and tourism sustainability. This study proposes a conceptual model using a sample of 230 rural residents grounded in the Stimulus–Organism–Response (S-O-R) theory. A mediation model incorporating place attachment (PA) is constructed to examine the effects of climate change perception (CCP) and perceived value of tourism (PV) on pro-environmental behavior. Results from structural equation modeling (SEM) reveal the following: (1) Climate change perception directly and positively influences pro-environmental behavior. (2) Place attachment not only directly promotes pro-environmental behavior but also mediates the relationship between perceived value of tourism and pro-environmental behavior. (3) Perceived value of tourism exerts a direct positive effect on pro-environmental behavior in life, whereas its influence on pro-environmental behavior in agricultural production is indirect, mediated through place attachment. These findings suggest that strengthening residents’ emotional and functional connections to the local environment can effectively encourage pro-environmental actions in tourism areas, providing a theoretical basis for formulating environmental policies in high-altitude tourism destinations. Full article

The b-value is a critical parameter for gauging seismic activity and is essential for seismic hazard assessment, monitoring stress evolution in focal zones, and forecasting major earthquakes. The minimum magnitude of completeness ($M_c$), a key indicator of the completeness of an earthquake catalog, reflects the monitoring capability of a seismic network and serves as a crucial foundation for the accurate calculation of the b-value. We began by integrating multi-source earthquake catalogs for mainland China using the nearest-neighbor method. Building on this, we employed a combination of partitioned time-series analysis and a grid-based spatial scanning technique to systematically investigate the spatiotemporal evolution of the $M_c$ and the b-value across mainland China and its adjacent regions. Our findings indicate the following: (1) Since the 1980s, the overall trend of $M_c$ has shifted from high and unstable values to low and stable ones. However, significant earthquake events can cause a notable short-term increase in the $M_c$. (2) The b-value exhibits strong fluctuations, primarily influenced by the dual effects of the tectonic stress field and catalog completeness. These fluctuations are particularly pronounced in highly active seismic regions such as the Sichuan–Yunnan area and Taiwan, whereas the western Tibetan Plateau has consistently maintained a low b-value. (3) The spatial distributions of both the $M_c$ and the b-value are markedly heterogeneous. By developing a unified and complete earthquake catalog for mainland China, our research highlights the qualitative leap in monitoring capabilities brought about by the continuous densification and technological upgrading of seismic networks. This dataset provides a solid foundation for future seismological research, disaster prevention practices, and especially for the development of AI-based earthquake prediction models. Full article

Forests are pivotal to hydrologic regulation, yet province-wide dynamics across complex terrain remain insufficiently quantified. We quantified Sichuan’s forest water conservation dynamics (1990–2023), coupling the InVEST water yield model with a topographic–hydraulic correction (topographic index, saturated hydraulic conductivity, land-cover-specific flow velocity). The model used precipitation and potential evapotranspiration, land-use/cover, soil texture, and rooting depth, and was calibrated to provincial water resources statistics. Outputs were stratified by elevation and slope and monetized via a replacement cost (reservoir capacity) method. Sichuan exhibited a persistent high-capacity belt along basin–mountain transitions and the southeastern ranges, contrasting with low values on the western plateau; period maxima intensified in 2020–2023. Interannual variability closely tracked precipitation anomalies against largely stable atmospheric demand; per-unit capacity declined monotonically with slope, and total capacity generally increased with elevation, with >3500 m both highest and most variable. Economic value rose overall but fluctuated and showed marked inter-city heterogeneity. We conclude that climate pacing operating on a terrain-anchored template governs Sichuan’s forest water conservation service, supporting precision, slope-aware forest management, and differentiated ecological compensation to stabilize hydrologic regulation under climate variability. Full article

Based on five years of data (2017–2021) from the China National Lightning Detection Network (CNLDN), this study compares and analyzes the temporal and spatial distribution characteristics of cloud-to-ground (CG) lightning activities in the Hengduan Mountain region and its surroundings. It explores the relationship between CG lightning occurrences and altitude, topography, and various meteorological elements. Our findings reveal a stark east–west divide: high lightning density in the Sichuan Basin and the central Yungui Plateau contrasts sharply with lower densities over the eastern Tibetan Plateau and Hengduan Mountains. This geographical dichotomy extends to the diurnal cycle, where positive cloud-to-ground (PCG) lightning activities are more prevalent in the western part of the study area, while significant nocturnal activity defines the eastern basin and plateau. The study also finds that the relationship between CG lightning activities in the four sub-regions and 2 m temperature, precipitation, convective available potential energy, and Bowen ratio (the ratio of sensible heat flux to latent heat flux) exhibits similarities. Furthermore, we show that the relationship between lightning frequency and altitude is highly region-specific, with each area displaying a unique signature reflecting its underlying topography: a normal distribution over the eastern Tibetan Plateau, a bimodal pattern in the Hengduan Mountains, a sharp low-altitude peak in the Sichuan Basin, and a complex trimodal structure on the Yungui Plateau. These distinct regional patterns highlight the intricate interplay between large-scale circulation, complex terrain, and local meteorology in modulating lightning activity. Full article

This study employs a systems theory approach to investigate the coupling coordination and driving mechanisms within the economic–social–environmental (ESE) system in China’s ethnic regions. It analyzes 67 ethnic counties in Sichuan Province, using an integrated framework that combines dynamic Shannon entropy, coupling coordination modeling, and GeoDetector. Based on data from 2005 to 2024, the study reveals the spatiotemporal patterns of ESE coupling coordination. The key findings are as follows: (1) The coupling coordination degree has gone through four stages: moderate imbalance → mild imbalance → primary coordination → moderate coordination. By 2024, 81.8% of counties had achieved coordinated development, and “highly coordinated” counties emerged for the first time. (2) The Western Sichuan Plateau has formed a high–high agglomeration zone by monetizing ecological assets and utilizing ethnic cultural resources. In contrast, the hilly and parallel ridge–valley regions in central and eastern Sichuan remain in low–low agglomerations due to their dependency on traditional industrialization paths. The decrease in high–low and low–high outliers indicates the recent policy polarization effects. (3) The interaction between habitat quality and per capita GDP has the strongest explanatory power. The rising marginal contributions of energy and carbon emission intensity suggest that green industrialization is crucial to breaking the “poverty–pollution” trap. Full article

Currently, the Longmaxi shale in the Sichuan Basin is the most successful stratum of shale gas production in China. However, because Longmaxi shale mostly has high over-maturity, a low-maturity sample cannot be obtained for gas generation thermal simulations, and as a result, a gas generation model has not yet been established for it. Therefore, models of other shales are usually used to calculate the amount of gas generated from Longmaxi shale, but they may produce inaccurate results. In this study, a Longmaxi shale sample with an equivalent vitrinite reflectance calculated from Raman spectroscopy (EqVR_o) of 1.26% was obtained from Well Yucan 1 in the Chengkou area, northeast Sichuan Province. This Longmaxi shale may have the lowest maturity in nature. Pyrolysis simulations based on gold tubes were performed on this sample, and the gas generation line was obtained. The amount of gas generated during the low-maturity stage was compensated by referring to gas generation data obtained from Lower Silurian black shale in western Lithuania. Thus, a gas generation model of the Longmaxi shale was built. The model showed that the gas generation process of Longmaxi shale could be divided into three stages: (1) First, there is the quick generation stage (EqVR_o 0.5–3.0%), where hydrocarbon gases were generated quickly and constantly, and the generation rate was steady. A maximum of 458 mL/g TOC was reached at a maturity of 3.0% EqVR_o. (2) Second, there is the stable stage (EqVR_o 3.0–3.25%), where the amount of generated gas reached a plateau of 453–458 mL/g TOC. (3) Third, there is the rapid descent stage (EqVR_o > 3.25%), where the amount of generated gas started to decrease, and it was 393 mL/g TOC at an EqVR_o of 3.34%. This model allows us to more accurately calculate the amount of gas generated from the Longmaxi shale in the Sichuan Basin. Full article