In the overall national security concept in the new era, historical blocks are facing dual challenges of disturbances and resilience building. Taking the historical block of Kashi Old City as the research object, this studybuilds a pressure-state-response model comprising six elements: Extreme disaster pressure, climate environment pressure, alley composition capacity, alley component density, infrastructure response, and public service response. It selects 44 key factors closely related to resilience to natural disturbances and uses the entropy weight method and the analytic hierarchy process to establish a multidimensional resilience evaluation system for historical blocks. The evaluation results show that (1) The comprehensive resilience index of the historical block of Kashi Old City is 1.84 (Level II), and the overall coping ability is weak. The resilience of the state layer (38.83%) is significantly higher than that of the response layer (27.45%), indicating its strong self-regulating ability but weak postdisaster management. (2) The key restrictive factors are the flood inundation radius, historical street and alley greening rate, and average summer solar radiation intensity, highlighting the synergistic risks between high-density built environments and climate sensitivity. (3) The wisdom of traditional construction is not linked to modern disaster prevention needs, leading to a contradiction between protection and safety. The results reveal a quantitative framework for integrated multi-hazard defense and living conservation of historic districts in arid zones, thereby promoting the synergistic development of cultural heritage conservation and ecological security.

While the synergistic development of rural public services and rural tourism is critical for advancing rural revitalization, academic research focusing on coupling coordinated development between these two domains remains notably scarce. This study analyzes coupling coordination between rural public services and rural tourism and its impact on rural revitalization, This study uses methods including the coupling coordination degree model, the gravity center and standard deviation ellipse model, and spatial econometric models to quantitatively measure the spatiotemporal characteristics of the coupling coordination degree between the two in western China from 2010 to 2023, as well as their impacts and spatial spillover effects on rural revitalization. The findings reveal that the coupling coordination between rural public services and rural tourism in western China has increased year by year, with the overall level shifting from extreme disorder to intermediate coordination, and presenting a spatial differentiation pattern of high coupling coordination in the south and northwest, and low in the northeast. The gravity center of the coupling coordination degree exhibited a southwestward migration trend, while the standard deviation ellipse consistently maintained a northwest-southeast orientation, demonstrating a trend of first clustering and then dispersing. Furthermore, the degree of coupling coordination has a significant positive impact on rural revitalization and exhibits spatial spillover effects. The research findings can provide a theoretical basis and policy recommendations for the coordinated development of the two aspects and the region’s overall rural revitalization.

Promoting the coordinated development of different elderly care models is an effective way to optimize the allocation of elderly care service resources in our country. Based on panel data from 2018 to 2022, this study empirically analyzes spatiotemporal coupling coordination and influencing factors of home community elderly care and institutional elderly care in China using a coupling coordination model, a geographic detector, and other methods. The results indicate that (1) The coupling coordination degree and relative development degree between home community elderly care and institutional elderly care are generally on the rise. The coupling coordination degree has shown a continuous improvement trend over time. The relative development degree of home community elderly care is gradually becoming clear with the trend of “synchronous development>advanced development>lagging development”. (2) The number of provinces entering the coordination stage (III and IV) continues to increase and shows an evolutionary pattern of gradually spreading from the central and eastern regions to the western and northeastern regions in space. The phenomenon of stage transition in relative development is more pronounced, and the western region has significantly more provinces in transition than the central and eastern regions. (3) The coupling coordination degree has a positive spatial correlation and a fluctuating upward trend. The correlation strength shows a spatial pattern of “western>eastern>central>northeast”, with mostly HH-type and LL-type clustering. (4) Organizational strength, elderly care demand, and technological level are the main influencing factors of the coupling coordination degree. This study’s findings can provide a theoretical basis and policy recommendations for addressing structural contradictions in China’s elderly care service supply and for innovating the development of the elderly care policy system.

With the acceleration of global urbanization, the severe PM_2.5 pollution in arid zone cities, owing to their unique geographical and climatic conditions, exhibits strong non-stationarity and complex spatiotemporal characteristics, making it difficult for traditional prediction models to effectively capture its dynamic patterns. To address this challenge, this study proposes a hybrid prediction framework of an “adaptive noise complete ensemble empirical mode decomposition-Ivy optimization algorithm-Kolmogorov Arnold network-bidirectional long short-term memory neural network” (CEEMDAN-IVY-KAN-BiLSTM), aiming to enhance the prediction accuracy of PM_2.5 concentrations. This framework jointly extracts multi-scale features through noise reduction decomposition as well as parameter optimization and integrates the strong nonlinear fitting and bidirectional time series modeling capabilities of the KAN-BiLSTM model, effectively improving the prediction performance. The results reveal that the PM_2.5 concentration in Urumqi City from 2021 to 2024 shows significant seasonal fluctuations, with an average of 41.97 μg·m^-3 in winter due to coal heating and the influence of the inversion layer and drops to 14.04 μg·m^-3 in summer due to enhanced atmospheric convection. Moreover, it shows an overall decreasing trend annually. Moreover, the importance ranking of the data indicates that PM_2.5 is significantly positively correlated with air quality index, PM₁₀, CO, and NO₂, and negatively correlated with temperature and dew point temperature, suggesting that coal emissions, vehicle exhaust, and meteorological diffusion conditions are the main influencing factors. Moreover, the model effectively separates the high-frequency fluctuations (such as sandstorm events) and low-frequency trends (seasonal changes) in the PM_2.5 sequence, reducing the impact of data non-stationarity. Finally, the experiments were based on daily air quality data in Urumqi City from 2021 to 2024, results of which demonstrate that this model achieves the coefficient of determination, mean absolute error, and root mean square error values of 0.991, 1.391, and 1.881, respectively, significantly outperforming conventional machine learning and common deep learning models. This verifies the applicability of the “decomposition-optimization-integration” deep learning framework in the prediction of arid zone cities.

Tourism is an important industry in Xinjiang, and sports tourism plays an important role in promoting tourism strategies to prosper Xinjiang of China. Identifying the characteristics of spatial distribution and influencing factors of sports tourism resources can provide a scientific basis for the sustainable development of the sports tourism industry in Xinjiang. Adopting the sports tourism resources in Xinjiang in 2022 as the research object, this study uses exploratory spatial data analysis and geographical detectors to quantitatively explore their spatial distribution characteristics and influencing factors. The results indicate that: (1) The spatial distribution of sports tourism resources across Xinjiang in 2022 shows a significant imbalance, with a highly aggregated distribution, mainly concentrated in Urumqi, Changji Hui Autonomous Prefecture, and Ili Kazakh Autonomous Prefecture; on the whole, it is distributed more across the north and less across the south, forming a three-core spatial distribution pattern; in addition, the spatial dependence is obvious, with large differences being spatially correlated and with an uneven distribution of coldspot and hotspot areas. (2) The spatial distribution of sports tourism resources in Xinjiang is affected by such multi-dimensional factors as geography, traffic, and resources, among which, the average annual precipitation, distance from transportation hubs, average annual temperature, and elevation are the main influencing factors, while the road network density and amount of population have relatively minimal influence; this type of interaction is mainly dominated by dual-factor enhancement, indicating that the spatial distribution of sports tourism resources in Xinjiang is the result of the joint action of multiple factors. From this, scientific and reasonable suggestions are put forward for the sustainable development of the sports tourism industry in Xinjiang.

Determining the capacity of regional agricultural water resources to support irrigated areas, restraining agricultural water usage, and controlling the expansion of irrigated farmland are crucial strategies for solving sustainable water use problems in the Hexi Corridor of northwest Gansu Province, China. In this paper, we applied the water balance principle and utilized the stepwise regression model to calculate the thresholds of water resource availability and the carrying capacity of the irrigated areas for the Hexi Corridor in different development scenarios. We used information on local water resources, water resource use, and the effective utilization coefficient of irrigation water. The analysis shows the following results: (1) Under the economic priority development scenario, the total exploitable water resources in the Hexi Corridor region is 48.22×10⁸ m³, and the threshold value of the carrying irrigated area is 58.92×10⁴-67.16×10⁴ hm². (2) Under the ecological priority development scenario, the total exploitable water resources are 34.44×10⁸ m³, and the threshold value of the carrying irrigated area is 37.90×10⁴-43.20×10⁴ hm². (3) Under the economic and ecological development scenario, the total exploitable water resources are 41.33×10⁸ m³, and the threshold of the carrying irrigated area is 48.41×10⁴-55.18×10⁴ hm². (4) The proportion of the micro-irrigation area and the effective utilization coefficient of irrigation water have a significant positive correlation. This study can provide a basis for determining a reasonable irrigation area and optimizing the Hexi Corridor’s soil and water planning and distribution system.

The interaction between tourism and urbanization has become increasingly significant, and the coupling coordination of tourism and urbanization is crucial for the promotion of the high-quality development of regional tourism economies. Using the coupling mechanism of tourism efficiency and urbanization with the Super-SBM model, the entropy method, the coupling coordination degree model, and the obstacle degree model, this study explores the spatiotemporal evolution characteristics and the obstacle factors of the coupling of tourism efficiency and urbanization in a core section of the Belt and Road (six provinces, including Shaanxi, Gansu, Qinghai, Ningxia, Xinjiang, and Inner Mongolia) from 2000 to 2022. The results show that: (1) The average tourism efficiency of the six provinces is 0.73, which is low; the overall level of urbanization is growing steadily, with obvious inter-provincial differences. (2) The coupling coordination degree of tourism efficiency and urbanization in the six provinces has evolved from a near imbalance to primary coordination, with a spatial pattern of distribution that is higher in the southeast and lower in the northwest, and with a center of gravity showing an offset southeast-northeast-southwest pattern, with the degree of agglomeration to the southeast region gradually increasing. (3) The key obstacle factors constraining the degree of coupling coordination of tourism efficiency and urbanization are total tourism revenue, total number of tourists, total postal and telecommunication businesses, number of students in general higher education institutions, and the amount of employees in the tourism industry. The results of the study provide a scientific basis for the high-quality synergistic development of regional tourism and urbanization.

Tourism is a strategic pillar industry of the national economy, playing a role in cultural prosperity, national unity and stabilizing the border. Border ethnic areas in western China are rich in cultural and tourism resources, and promoting the high-quality development of cultural and tourism integration is an important hand in promoting the interaction, communication and integration of various ethnic groups and casting a firm sense of Chinese national community. Taking the border ethnic areas as the research object, based on the multi-indicator panel data from 2011 to 2020, we measure the level of high-quality development of culture and tourism, analyze the spatiotemporal evolution of the coordination degree, and identify the driving factors. The study found that: (1) The level of high-quality development of culture and tourism in the border ethnic areas is generally on the rise, the impact of the new crown epidemic on tourism is obvious in 2020, and the level of high-quality development of culture is higher than the level of high-quality development of tourism due to the influence of historical and cultural precipitation and cultural exchanges. (2) The degree of coordination of high-quality development of cultural and tourism integration in all provinces and regions is rising in fluctuation, and the level of coordination is gradually optimized. The coordination level of high-quality development of cultural and tourism integration is higher in Guangxi and Yunnan, forming the “Matthew effect”. (3) The investment level, policy support, market supply and transportation conditions are the important driving force for the high-quality development of cultural and tourism integration in the border ethnic areas, among which the investment level shows the strongest utility. The results of the study provide theoretical basis and data support for the high-quality development of culture and tourism integration in border ethnic areas, which can help strengthen the construction of cultural tourism, realize the transformation and upgrading of tourism, and enhance the vitality and influence of culture.

Exploring the impact of territorial spatial ecological protection and restoration on the economic development of China’s poverty-alleviated regions provides valuable insights for promoting sustainable economic development and rural revitalization in these areas during the post-poverty era. Using the double-difference propensity score matching (PSM-DID) model, this study analyzed economic panel data from 58 national-level poverty-alleviated regions involved in the first and second batches of national integrated protection and restoration projects for mountains, rivers, forests, farmlands, lakes, grasslands, and deserts (the “Shanshui Project”) during China’s 13^th and 14^th Five-Year Plans. These were compared with data from 182 non-participating poverty-alleviated regions that had similar natural, social, and economic conditions from 2010 to 2020. This study assesses the impact of ecological protection and restoration on the economic development of these regions. The results indicate the following: (1) Under otherwise unchanged conditions, the economic development rate of poverty-alleviated regions implementing territorial spatial ecological protection and restoration increased significantly by 0.0329 compared to regions that did not implement such measures. This conclusion remains robust after balance tests, parallel trend tests, and placebo tests. (2) In the implementation of spatial ecological protection and restoration, both short-term and long-term economic development effects should be considered. Realizing the value of ecological products is a key driver of sustainable economic development in poverty-alleviated regions. To achieve this, increased policy support is recommended for this region, with a focus on improving systems for realizing the value of ecological products. This approach would enable these areas to successfully transform “green waters and mountains” into “golden mountains and silver mountains”.

This study examines 474 national nature reserves in China from 1956 to 2023, utilizing kernel density estimation to analyze their spatiotemporal distribution patterns. A social network analysis model is then employed to measure the attributes of these reserves and to propose integrated protection strategies. The findings reveal the following. (1) The evolution of China’s national nature reserves can be categorized into four distinct stages: Preliminary exploration, vigorous development, slow development, and consolidation and improvement. This development has resulted in a spatial pattern characterized by large and scattered reserves in the west, and small and clustered reserves in the east. (2) Topological analysis reveals that the nodes within the national nature reserve network exhibit strong cohesion, small-world characteristics, and a prominent “core-periphery” effect. (3) The network’s spatial pattern demonstrates significant heterogeneity among protection clusters, forming a “triangular” framework for reserve aggregation, with key vertices located in the middle and lower reaches of the Yangtze River, the Northeast Plain, the Changbai Mountain area, and the Qinghai-Xizang Plateau. Based on the natural endowments and geographic conditions of these reserve clusters, we propose corresponding integrated protection strategies from the perspective of the association network, aimed at providing guidance for the integration and optimization of nature reserves.

It is very important to reduce regional social vulnerability to natural disasters and integrated risk governance. At the county and district unit scale, a social vulnerability assessment index system was constructed for three disaster-bearing bodies that would be suitable for Gansu Province: Population, economy and agriculture. The social vulnerability of natural disasters in Gansu Province was evaluated, including exposure, sensitivity, and adaptability. Then, based on the paradigm of natural geographic regionalization, a comprehensive social vulnerability regionalization was developed. The results show the following: (1) The comprehensive social vulnerability index in Gansu Province is generally high in the east, low in the west, high in the south, and low in the north. High-vulnerability areas are mainly concentrated in the eastern, central, and southern regions of Gansu, and they cluster in densely populated disaster-prone areas, such as cities and nearby counties. (2) Comprehensive regionalization includes two levels: The first level is divided into four leading natural disaster types, including sandstorm-leading disaster areas in the western section of the Hexi Corridor, the Lanzhou drought-leading disaster area, the southern Gansu rainstorm flood landslide/debris flow-leading disaster area, the central-eastern Hexi Corridor, and east, central, and southern Gansu multihazard disaster areas. Secondary-level zones include 14 comprehensive vulnerability level zones with different structures. The regionalization scheme systematiclly expresses macrospatial differentiation in social vulnerability structures under regionally dominant natural disaster types that can serve diverse regional differences and help reduce social vulnerability to natural disasters.

The Guanzhong Plain urban agglomeration is the largest urban cluster in the water-scarce region of northwest China. Exploring the coordination among water resources, the socio-economic system, and the ecosystem is crucial for regional water governance and sustainable development. This study examines 11 prefecture-level cities within the Guanzhong Plain urban agglomeration. By establishing a comprehensive evaluation index system for the coordinated development of water resources, socio-economic, and ecological systems, the comprehensive evaluation indices of these three systems from 2006 to 2020 are calculated. The coupling coordination model is employed to measure and analyze their coordination, while the obstacle degree function is used to identify the primary constraints affecting the coupling coordination degree. The results indicate that: (1) From 2006 to 2020, the development levels of water resources, socio-economic, and ecological systems across the cities in the Guanzhong Plain urban agglomeration exhibited an overall upward trend with distinct spatial gradation. Cities with higher water resource system levels include core and surrounding cities, while those with higher socio-economic system levels are predominantly core cities. Prefecture-level cities with higher ecological system levels are either core or peripheral cities. (2) The coupling coordination degree of the Guanzhong Plain urban agglomeration improved from a state of slight imbalance in 2006 to basic coordination by 2020. Spatially, the coupling coordination followed a hierarchical pattern of “core cities>surrounding cities>peripheral cities”. (3) Significant differences exist in the primary obstacles affecting the coupling coordination degree across the 11 prefecture-level cities. Based on the detection results of obstacle factors, the coordinated development of the water-socio-economic-ecosystems in the study area can be categorized into three types: comprehensive development constrained by water resources (core cities), ecological environment lagging behind (surrounding cities), and socio-economic lagging behind (peripheral cities).

Based on the China high air pollutants (CHAP) dataset from 2000 to 2023, this study identifies wintertime air pollution events in the urban agglomeration on the northern slope of Tianshan Mountains (Xinjiang, China) using the air quality index (AQI) and analyzes their spatiotemporal patterns (annual mean number of days, annual mean frequency, maximum duration, and intensity). The results demonstrated that (1) PM_2.5 was the dominant air pollutant in the urban agglomeration on the northern slope of Tianshan Mountains, present on more than 95% of the polluted days (AQI>100). (2) A climatological analysis revealed that pollution intensity peaks in the Urumqi-Changji-Shihezi region, where the long-term annual mean AQI exceeds 190 and the annual mean number of days accounts for more than 80% of the winter period. Mild pollution events (101≤AQI≤150) are especially frequent and widespread, with an annual mean of 25.7 days, a maximum annual mean frequency of 17.4 occurrences per year, and a maximum duration of up to 29.0 days. Moderate events (151≤AQI≤200) predominantly occur in the central and eastern subregions, averaging 5 days per year with a maximum annual mean frequency of 14.5 occurrences per year and a maximum duration of up to 12.3 days. In contrast, heavy and severe events (AQI≥201) are concentrated in the Urumqi-Changji-Shihezi region, where AQI peaks can exceed 500. The maximum duration of these events is 11.3 days, exhibiting a “short-duration, high-intensity” evolution pattern. (3) Mild and moderate pollution events have declined in 75.8% of the polluted regions in the urban agglomeration on the northern slope of Tianshan Mountains, but heavy and above pollution events have increased in the Urumqi-Changji-Shihezi core. (4) The characteristics of air pollution events among the nine key cities in the urban agglomeration on the northern slope of Tianshan Mountains varied significantly. Urumqi, Changji and Shihezi are most severely affected, followed by Wujiaqu, Kuytun, and Fukang, while Usu, Karamay, and Bole maintaine the cleanest air. The intensity, annual mean number of days, annual mean frequency, and maximum duration of moderate to severe pollution events in the Urumqi-Changji-Shihezi region are significantly higher than those in other cities, whereas Bole and Karamay are primarily affected by light pollution.

Evaluating rural development from a resilience perspective is significant for breaking the urban-rural dual structure and promoting comprehensive rural revitalization. This article takes 86 counties in Gansu Province as the research object and constructs a rural resilience evaluation index system based on three dimensions: “resilience, adaptability, and reconstruction capability”. Using spatial autocorrelation analysis and geographic detector models, it reveals the spatiotemporal evolution of rural resilience and its driving mechanisms in counties of Gansu Province from 2010 to 2022. The results indicated that (1) The resilience level of rural areas in Gansu Province has significantly improved, with obvious spatial differentiation characteristics. The resilience of rural areas in central and eastern Gansu is relatively high, while some counties in Hexi, Gannan, and Linxia have lower resilience. The number of high-resilience counties continues to increase, while the number of low-resilience counties continues to decrease. (2) There is a spatial positive correlation in rural resilience, and the correlation is gradually weakening. The degree of spatial agglomeration is declining, with high-agglomeration areas shrinking toward the central Gansu region and low-agglomeration areas concentrated in counties such as Gannan and Linxia. (3) The level of rural social services, economic development, and agricultural production has a significant impact on rural resilience. The explanatory power of rural industrial structure for rural resilience is steadily increasing, and rural resilience is driven by economic development, resource optimization, industrial transformation, and service guarantee mechanisms. This study’s results provide scientific reference for the implementation of rural resilience development in Gansu Province.

To investigate the chemical characteristics of groundwater and its evolutionary patterns in the middle and lower reaches of the Hotan River Basin, Xinjiang, China, this study analyzed 21 groundwater samples from the area. It included an examination of the constituents and origins of groundwater solutes and the reverse simulation of hydrogeochemical processes. The analysis employed Piper trilinear diagrams, Gibbs diagrams, PHREEQC software, and mathematical statistics to explore the chemical properties of groundwater, the principal sources of solutes, and their evolution in the study region. The results revealed that: (1) High concentrations of eight conventional ions in the groundwater, with Cl^-, SO₄^2-, Na⁺, Ca²⁺, and HCO₃^- being particularly abundant. (2) There was a significant spatial variability in the dissolved constituents of the groundwater. The predominant chemical types were SO₄·Cl-Ca·Mg and SO₄·Cl-Na, with the latter being more common across most areas. The groundwater’s alkalinity was generally low, and the water quality in most regions met daily drinking water standards. However, in some oasis plains, elevated NO₃^- levels were attributed to human activities. (3) The dissolution of minerals such as halite, calcite, dolomite, and gypsum, facilitated by water-rock interactions and cation exchange, was identified as the main source of Na⁺, Ca²⁺, Mg²⁺, Cl^-, and SO₄^2- ions in the groundwater. During transit to finer soil plains and desert areas, ion concentrations increased due to evaporation and concentration processes. (4) In open system conditions, CO₂ enhanced the dissolution of various minerals, leading to increased ion concentrations. As groundwater flowed into the alluvial plains downstream, the fine sand layer acted as a barrier, reducing the intensity of groundwater flow and solute leaching, with evaporation and concentration processes becoming more dominant. This study provides a theoretical foundation for the sustainable development and management of water resources and environmental protection in the Hotan River Basin.

Based on six carbon sources in agricultural production, namely fertilizers, pesticides, agricultural films, diesel oil, plowing, and agricultural irrigation, this study applied the carbon emission coefficient method proposed by the United Nations Intergovernmental Panel on Climate Change to measure and analyze the spatiotemporal variation in agricultural carbon emissions at provincial and municipal scales in the Yellow River Basin of China from 2005 to 2020. The spatial heterogeneity of the influencing factors was assessed using a geographically weighted regression model. The conclusions are as follows: (1) From 2005 to 2020, agricultural carbon emissions in the Yellow River Basin initially increased before declining, following an overall upward trend. Emissions rose from 4431.95×10⁴ t in 2005 to 4915.87×10⁴ t in 2020. Among the carbon sources, fertilizers and plowing were the primary contributors, accounting for more than 65% of total agricultural carbon emissions. Pesticide-related carbon emissions consistently remained the lowest. (2) In 2005, Shandong Province was the leading contributor to agricultural carbon emissions in the Yellow River Basin, with emissions of 1241.68×10⁴ t. However, from 2010 to 2020, Henan Province became the largest emitter, with annual emissions ranging from 1360×10⁴ t to 1470×10⁴ t. Qinghai Province consistently recorded the lowest agricultural carbon emissions. In 2020, agricultural carbon emissions at the municipal scale exhibited a stepped decline from east to west in the Yellow River Basin. (3) The positive effect of agricultural production efficiency on agricultural carbon emissions was stronger in the southeast and northwest and lower in the northeast of the Yellow River Basin. The negative impact of agricultural structure was most pronounced in Shanxi Province. The highest positive impact of agricultural economic development was observed at the borders of Shaanxi Province, Shanxi Province, and Henan Province. The positive effect of the agricultural labor force was higher in the southeast and northwest and lower in the southwest.

Using daily rainfall data from 45 national meteorological observation stations in southern Xinjiang of China from 1961 to 2022, we analyzed the spatiotemporal distribution and variability of rainfall, identified extreme rainfall thresholds, and examined extreme rainfall characteristics. The results show that (1) Over the past 62 years, the region with the highest and most rapidly increasing annual average rainfall in southern Xinjiang has been located in the middle mountain belt at an altitude of 1500-2500 m, with a growth rate of 5.4 mm·(10a)^-1. This increase is mainly reflected in the greater number of rainfall days, particularly large-scale rainfall days, while the increase in heavy-rainstorm-level rainfall and above is especially pronounced. (2) Based on a comparative analysis using the percentile method, the 99^th percentile was identified as the threshold for extreme rainfall in southern Xinjiang, corresponding to 14.1-35.4 mm. Thresholds in the western and mountain-adjacent regions are higher than those in the eastern basin-desert areas, and the extreme rainfall threshold has increased at a rate of 0.7 mm·(10a)^-1. Stations with the most rapid increases are primarily located in the mountainous areas of Kashgar, western Hotan, and northern Bayingol Mongolian Autonomous Prefecture. (3) Over the past 62 years, the number of extreme rainfall events in southern Xinjiang has generally ranged from 10-20 times, while in the Tianshan Mountains, events can persist for more than 20 times. Extreme rainfall events have increased in frequency at a rate of 0.9 events per decade.

Changes in surface radiation budgets significantly affect regional and global climates, particularly in arid and semi-arid areas. The underlying surface of the Gobi wetland and desert steppe vegetation in the area surrounding the Akedala atmospheric background station is representative of northern Xinjiang and the hinterland of Asia and Europe. Meanwhile, its atmospheric background is clean and experiences long winter snow, making its surface radiation special. However, research on the radiation budget of the Gobi in northern Xinjiang is limited. Therefore, it is necessary to study the characteristics of its radiation budget. The four components of surface radiation from November 1, 2021-October 31, 2022 of the Akedala atmospheric background station reference radiation observation system were used to analyze the changes in surface radiation and albedo in different time scales and precipitation processes of Akedala atmospheric background station. The results indicated an annual exposure of total solar radiation of 5772.74 MJ·m^-2. The seasonal variation of total solar radiation exposure is manifested as the largest in summer, followed by spring, and the smallest in winter. The daily peak of total solar radiation and reflected short-wave radiation in different months is concentrated between 11:00 and 12:00, while the daily peak of ground long-wave radiation is concentrated between 12:00 and 13:00. In addition, the daily peak occurrence time of atmospheric counter radiation is not obvious. The maximum net income radiation occurs mainly at noon, while the net expenditure radiation peaks mainly at sunset. Total solar radiation, reflected short-wave radiation, ground radiation, and surface albedo are weakened during rainfall, while total solar radiation is weakened during snowfall. Ground snow leads to increased surface albedo, while reflected short-wave radiation is enhanced, thereby weakening daytime ground radiation and ground net radiation. Simultaneously, influenced by the thermal insulation effect of snow, ground radiation is enhanced compared to before snowfall at night. Both rainfall and snowfall have an enhanced effect on atmospheric counter radiation. The minimum surface albedo on rainy days is 0.16, while a snow depth of 5 cm can increase surface albedo to 0.96. New snow has a higher surface albedo than old snow, and stable snow has a daily average surface albedo of 0.72-0.88. The changes in the surface radiation budget, surface albedo, and snow albedo in the Gobi wetland are revealed to a certain extent, providing a reference for understanding the evolution of the underlying land surface process of the Gobi wetter in northwest China and offering a theoretical and scientific basis for further exploration of the physical process of land-atmosphere interaction and climate change in arid and semiarid areas of China.

Using water regime data from Xiagou Reservoir and Yiwu Hydrological Station in Yiwu County, Hami City, Xinjiang, China alongside hourly precipitation observations from five automatic weather stations in the reservoir’s upstream basin, routine upper-air observations, and NCEP reanalysis data, this study analyzed the hydrological characteristics and precipitation features of eight medium and small flood events at Xiagou Reservoir during 2015—2022. The findings are as follows: (1) Upstream-type floods exhibit peak durations within 10 hours, with concentrated flood volumes and stable rising and falling stages. In contrast, downstream-type floods rise rapidly and have peak durations exceeding 10 h. While the average rainfall and maximum hourly rainfall intensity of upstream-type flood-inducing heavy precipitation are lower than those of downstream-type, and the average rainfall duration is longer. The flood peak durations exceeding the blue warning threshold are shorter for upstream-type floods, and their corresponding maximum peak discharge, highest water level, and reservoir storage increase are significantly less than those of downstream-type floods. (2) A positive correlation exists between the peak discharge at Yiwu Hydrological Station and maximum rainfall during different time periods within the basin above the reservoir. The peak discharge shows the strongest correlation with maximum 3-hour precipitation at upstream meteorological stations and maximum 6-hour precipitation at downstream meteorological stations. (3) During downstream-type flood-inducing heavy precipitation, the 100 hPa South Asian High adopts a double-lobed structure, with the Central Asian long-wave trough and 500 hPa low trough positioned further south compared to upstream-type floods, while the subtropical high is located further north. Specific humidity between 700 hPa and 500 hPa, the 700 hPa moisture flux and vorticity, and the pseudo-equivalent potential temperature between 700 hPa and 500 hPa are higher during downstream-type flood-inducing heavy precipitation, serving as favorable indicators for forecasting such events. This study provides insights into the distinct characteristics of upstream- and downstream-type floods and offers valuable indicators for forecasting flood-inducing heavy precipitation.

This study employs a quantitative approach to analyze the spatiotemporal distribution patterns of five ecosystem services in the Guanzhong Plain urban agglomeration, northwest China from 2000 to 2020. Utilizing K-means clustering analysis, ecosystem service clusters are identified, dominant service functions are determined, and ecological functional zones are delineated based on the functional characteristics within each cluster. Results indicate: (1) Grain production and soil retention exhibit a trend of initial increase followed by a decrease, while water yield demonstrates a rapid increase followed by a slow rise. Habitat quality and carbon sequestration services show a relatively mild decrease. High-value zones for grain production are concentrated in the central and northeastern parts, soil retention in the southern and western areas, and habitat quality and carbon sequestration services in the southern region. (2) Grain production shows a trade-off relationship with other services, while soil retention exhibits synergies with habitat quality and soil retention with carbon sequestration, as well as synergies between habitat quality and carbon sequestration, with varying strengths of inter-service correlations over time. (3) Ecological functional zones are identified as primary grain-producing areas, ecological conservation zones, important urban areas, and ecological balance zones. This study is crucial for maintaining the balance of ecosystems and fostering sustainable economic development, providing guidance for ecosystem management in different functional zones within the Guanzhong Plain urban agglomeration.

Based on the flood disaster data set of the Ili River Basin from 1990 to 2022, this study combined with disaster-prone environment factors, such as elevation and normalized vegetation index, to examine the spatial and temporal distribution of flood disasters and the characteristics of disaster-prone environment in the Ili River Basin. This study analyzes the relationship between the occurrence rule of flood disasters and the disaster-prone environment. The results reveal the following: (1) Flood disasters in the study area can be categorized into three types: rainstorm, snowmelt, and mixed floods (caused by rainstorm and snowmelt floods), with rainstorm flood being the most prevalent (80.0%) and snowmelt flood the least (3.4%). The spatial distribution of flood disasters is greater in the north than in the south, greater in the east than in the west, with Nilke County experiencing the most and Khorgas City the least. (2) Over the past 30 years, the frequency of flood disasters has shown a substantial interannual and interdecadal increasing trend, with an average annual occurrence of about 11.6·a^-1. The highest occurrence was in 2010 (43), and the highest period was from 2000 to 2011 (149). Flood disasters were most frequent in summer, followed by spring, and least frequent in autumn. They were most frequent in June (annual mean 3.3 times·a^-1) and least frequent in October (annual mean 0.06 times·a^-1). Rainstorm flood disasters were most frequent in summer (annual mean 9.3 times·a^-1), most frequent in June (110 times), and least frequent in October (2 times). Mixed flood disasters were more frequent in spring and less frequent in summer, with the most in March (36 times) and at the least in July (8 times), with an average annual rate of 1.9 times·a^-1; snowmelt flood was most frequent in March (12 times), only occurring in spring, with an average annual rate of 0.4 times·a^-1. (3) The comprehensive distribution of disaster-prone environment sensitivity levels shows that all disaster-prone factors work together to affect the spatial distribution and intensity of flood disasters. More extremely sensitive areas exist in Nilka, Tekes, Xinyuan, Zhaosu Counties and Khorgas City. Based on the spatial and temporal distribution of flood disasters and the comprehensive distribution of the disaster-prone environment, flood disasters mostly occur in the eastern and northern parts of the basin, where the extremely and highly sensitive areas are distributed.

In agricultural ecosystems, rhizosphere microbial communities serve as the driving force for the successful cycling and transformation of nutrients and organic matter in soil, exerting a significant impact on the growth, health, and nutritional status of crops. To investigate the diversity of rhizosphere fungi in different habitats in the northern Tianshan Mountains and the driving factors behind their variations, this study employed high-throughput sequencing to analyze the diversity, structures, functions, and driving factors of rhizosphere and non-rhizosphere fungi in alfalfa rhizosphere soils in mountainous and plain habitats. The results revealed that: (1) Soil nitrogen, potassium, organic matter, and enzyme activity in the mountainous alfalfa rhizosphere soil were significantly higher than those in plain alfalfa rhizosphere soil, while electrical conductivity and pH were significantly lower than those in plain alfalfa rhizosphere soil. (2) Significant differences were observed in the fungal communities in mountainous and plain soils, with the operational taxonomic units (OTUs), Chao1, and ACE indices of plain alfalfa rhizosphere soil being significantly higher than those of mountainous alfalfa rhizosphere soil; additionally, the OTUs, Chao1, ACE, and Shannon indices showed significantly higher values in rhizosphere soils than those in non-rhizosphere soils. (3) The dominant fungal phyla in the region were Ascomycota, Mortierellomycota, Basidiomycota, and Blastocladiomycota, with notable differences in their distribution across different habitats. (4) Based on FUNGuild’s fungal functional predictions, pathogenic fungi in mountainous areas were significantly higher than those in plain areas, while arbuscular mycorrhizal fungi were significantly lower in mountainous areas. (5) Redundancy analysis and Mantel tests indicated that soil pH, total nitrogen, total potassium and available potassium were the main driving factors for the differential distribution of fungal community structures in soils.

The Loess Plateau of China has been experiencing an increase in extreme climate events due to global warming. Understanding the spatiotemporal characteristics of extreme precipitation events in this region is crucial for disaster prevention. This study analyzes daily precipitation data from 111 meteorological stations across the Loess Plateau, spanning the years 1960 to 2023. Using detrended fluctuation analysis (DFA), we established thresholds for extreme precipitation events and examined their spatiotemporal characteristics through the Mann-Kendall test and other methods. The findings reveal the following. (1) Extreme precipitation thresholds at meteorological stations vary between 27.4 mm and 89.1 mm, with 54% of the stations exceeding a threshold of 50 mm. The average threshold values across different ecological regions range from 35.0 mm to 59.6 mm, exhibiting a gradient that is lower in the northwest and higher in the southeast. (2) The amount and intensity of extreme precipitation events increase from 10.6 mm·a^-1 and 33.0 mm·d^-1 in the northwest to 71.5 mm·a^-1 and 133.0 mm·d^-1 in the southeast, respectively. The frequency of their occurrence increases from 0.3 d·a^-1 in the north to 0.8 d·a^-1 in the south. The number of extreme precipitation days closely aligns with heavy rain days, particularly in the loess hilly gully B2 sub-region. (3) The loess tableland gully, earth-rocky mountainous, and river valley plain regions are identified as high-risk areas for extreme precipitation events and should be prioritized for disaster prevention and control. (4) Over the past 64 years, extreme precipitation events have shown distinct interannual variability, with an overall increase observed, particularly in July and August. (5) In the last decade, the loess tableland gully and loess hilly gully regions have seen increased precipitation amounts and frequencies of extreme events. By contrast, the declining trend of extreme precipitation events in the sandy land and irrigated agricultural regions has slowed, whereas both the earth-rocky mountainous and river valley plain regions experienced a sudden spike in extreme precipitation events in 2020. This study serves as a reference for disaster prevention and mitigation regarding extreme precipitation events across the different ecological regions of the Loess Plateau.

This study analyzes daily temperature data from 38 meteorological stations in Xizang, China, covering the period from 1981 to 2023. A new method for seasonal division in Xizang was employed to categorize the four seasons, and the regional climate changes, temporal shifts in the start dates of each season, and trends in seasonal changes were examined. The results show the following. (1) Areas with four distinct seasons in Xizang are primarily found along the Yarlung Zangbo River and in Nyingchi City, whereas regions with less distinct seasonal variations (including areas without a summer season) are mainly situated in the western and northern parts of Xizang as well as in the high-altitude regions of the Himalayas. (2) In Xizang, the beginning of spring and summer tends to occur earlier, whereas the onset of autumn and winter tends to be delayed. Notably, the start date of spring was significantly earlier in 2000, whereas the onset of autumn and winter was significantly delayed in 2003 and 1995, respectively. (3) Regarding the timing of seasonal starts, the first empirical orthogonal function (EOF1) for spring and autumn exhibited a pattern of “northwest low and southeast high in spring, and middle high and both sides low in autumn”. In spring, the second EOF (EOF2) presented a contrasting distribution pattern of “northwest positive and southeast negative”, whereas in autumn, EOF2 showed an opposite spatial distribution pattern characterized by “southwest positive and northeast negative”. The EOF1 in winter revealed a “high in the north and low in the southwest” pattern, whereas the EOF2 shared similarities with that of spring’s EOF2. (4) Looking ahead, we anticipate that the start dates of spring and summer will be delayed, whereas those for autumn and winter will be advanced.

In order to evaluate the soil quality status of farmland in Shawan City of Xinjiang, China and to clarify the key influencing factors on productivity level, and promote the construction of high standard farmland in Shawan City, this paper build the minimum dataset of farmland soil quality with principal component analysis and cluster analysis, and combined with an obstacle factor diagnostic model, the characteristics and obstacle factors of agricultural soil quality in the Shawan area were revealed. The results led to three main conclusions. (1) There were significant differences between the results of soil quality evaluations using different datasets. The soil quality indices determined using the minimum dataset based on cluster analysis and using the total dataset significantly positively correlated (R²=0.591, P<0.1),the Nash effective coefficient was -4.923, indicating that the minimum dataset based on cluster analysis gave better results than the minimum dataset based on principal component analysis. This indicated that the minimum dataset based on cluster analysis was more suitable than the minimum dataset based on principal component analysis for replacing the total dataset when evaluating farmland soil quality. (2) The overall soil quality in the study area was found to be moderate and better, and the soil quality indices were 0.130-0.641. Farmland in Shawan City was divided into five classes using the soil quality index minimum dataset. Class I soil was mainly in the northern and northwestern parts, and class V soil was mainly in the southeastern part of the study area, indicating that the soil quality was generally high in the northwest and low in the southeast. (3) There were obvious obstacles in the research area, which low organic matter contents, insufficient nitrogen, and high electrical conductivities were the main obstacles. The research results can be used to effectively improve the soil quality of local farmland. It is recommended that in the process of farmland management, not only applying organic fertilizer, take measures such as deep tillage, planting weeds, covering straw, and plastic film to improve the soil.

Soil salinization is a major factor in arid and semi-arid regions, adversely affecting agricultural production and the ecological environment. Accurately capturing the spatiotemporal distribution of soil salinization has become a key focus in current research across the fields of ecology, geography, and agriculture. In this study, Sentinel-2A imagery from April and July, along with corresponding in-situ measurements of the salinity of surface soil, were utilized to construct soil salinity inversion models for the Ebinur Lake region. Five machine learning algorithms [random forest (RF), support vector regression, decision tree regression, adaptive boosting (Adaboost), and gradient boosting regression tree] and two deep learning methods(deep belief network and fully convolutional network] were employed for this purpose. Variables were selected using the Boruta algorithm to enhance the performance of the model. The results indicate that: (1) In April, the soil salinity exhibited a strong positive correlation with various spectral bands, whereas the overall correlation strength decreased in July. Among multispectral indices, the intensity indices (Int₁, Int₂), salinity indices (S₃, S₅, S₆, SI, SI₁, SI₂, SI₃), and the ratio index showed strong positive correlations with the soil salinity, whereas the normalized difference index displayed a strong negative correlation. (2) The RF model achieved the highest predictive accuracy in both time periods, with an average R² and RMSE of 0.72 and 0.13 in April and 0.66, and 0.15 in July, respectively. Therefore, the RF model was identified as the optimal model in this study. Furthermore, in terms of temporal selection, soil salinity inversion in April yielded higher accuracy compared to July, indicating that April is more favorable for soil salinity monitoring in arid regions.

The coupling coordination of water and soil resources is of great significance to the sustainable development of ecosystem services in small watersheds. Taking small watersheds of Ningxia, China as the research unit, this study employs the coupling coordination degree model to measure the coupling coordination degree of water-soil resources in the study area. Additionally, the multi-scale geographically weighted regression model is used to explore the influencing factors and spatial heterogeneity of the coupling coordination degree of water-soil resources. The results indicate that: (1) From 2005 to 2020, the coupling coordination degree of water-soil resources in small watersheds of Ningxia increased from 0.37 to 0.43, demonstrating a transition from imbalance to coordination in the regional water and soil resource matching degree. (2) The coupling coordination degree of water-soil resources in small watersheds of Ningxia exhibits a spatial pattern of being higher in the south and lower in the north. Furthermore, from 2000 to 2020, areas of water-soil resources having a coupling coordination degree of high value expanded outward in the southern small watersheds. (3) The proportion of terraced field area, county-level accessibility, and annual average precipitation exert a significant positive impact on the coupling coordination degree of water-soil resources, whereas annual average temperature, vegetation coverage, and erosion intensity have a significant negative impact. The proportion of terraced field area and annual average temperature exert a greater influence on the coupling coordination degree of water-soil resources in the southern small watersheds of Ningxia compared to northern ones, while county-level accessibility and annual average precipitation demonstrate a more significant impact on the same coupling coordination degree in the northern small watersheds of Ningxia than in the southern counterparts. The findings of this study provide a scientific reference for the planning of soil and water conservation measures at the small watershed scale in Ningxia.

Evapotranspiration is an important component of the terrestrial water cycle, and is complex in cold and arid environments. The northern slope of the Kunlun Mountains in Xinjiang of China, situated on the northern edge of the Qinghai-Xizang Plateau, lacks a comprehensive understanding of potential evapotranspiration due to the absence of long-term meteorological observations. This study examined the spatiotemporal variations of potential evapotranspiration from 1979 to 2021, especially from a sub-basin perspective, and analyzed the relationship between potential evapotranspiration and other meteorological parameters using the Mann-Kendall test and empirical orthogonal function. The results indicate that: (1) The long-term mean of potential evapotranspiration is 733.5 mm per year, exhibiting a spatial variation trend that decreases gradually from the southern edge of the Tarim Basin towards the south. (2) From 1979 to 2021, the mean potential evapotranspiration has increased by 8.7 mm·(10a)^-1. Before 2007, there was an increasing trend, although a decreasing trend can be seen after 2007. (3) Among the six sub-basins, i.e., the Kaxgar River Basin, the Yarkant River Basin, the Hotan River Basin, the Keriya River Basin, the Qarqan River Basin and the Kumkol Basin, the Qarqan River Basin has the highest annual mean potential evapotranspiration of 810.8 mm and the highest linear trend of 11.4 mm·(10a)^-1. In contrast, the linear trends in the Hotan River Basin (4.9 mm·(10a)^-1) and the Keriya River Basin (5.0 mm·(10a)^-1) are lower. In the future, efforts should be made to enhance hydro-meteorological observations in high-altitude regions of the northern slope of the Kunlun Mountains in Xinjiang to understand hydrological uncertainties under the background of global change.

The distribution of soil carbon in desert riparian forests is shaped by multiple factors. This study examines the Ejina Oasis in the lower reaches of the Heihe River, China. Soil samples from 20 Populus euphratica Oliv. plots at depths of 0-100 cm were analyzed to investigate the spatial variation of soil organic carbon (SOC) and soil inorganic carbon (SIC) and their influencing factors. The results reveal: (1) The mean SOC and SIC contents in the 0-100 cm soil layer were 2.90 g·kg^-1 and 10.79 g·kg^-1, respectively, with SIC being 3.72 times of SOC. (2) Vertically, both SOC and SIC contents exhibited a declining trend with increasing soil depth, while horizontally, SOC and SIC from the upper to lower sections of East River of the Heihe River show a decreasing trend, but the total amount of SIC is still greater than SOC. This suggests that inorganic carbon predominates in the lower reaches of inland rivers in arid regions. (3) Soil physical and chemical properties showed a stronger explanatory power for SOC, whereas their influence on SIC was comparatively lower. Specifically, soil chemical properties such as electrical conductivity (EC), sodium ion (Na⁺), sulfate (SO₄^2-), chloride ion (Cl^-), calcium ion (Ca²⁺), magnesium ion (Mg²⁺), and potassium ion (K⁺) had the most significant influence on SOC. In conclusion, the soil carbon pool in desert riparian forests in the lower reaches of inland river basins in arid areas is predominantly composed of SIC, with notable spatial variations in both horizontal and vertical directions. Basic cations are identified as the primary factor influencing SOC spatial differentiation, while soil sand content and bulk density are the key factors affecting SIC spatial differentiation.

Establishing a robust ecological network is essential for enhancing urban ecological resilience. Using the central urban area of Yinchuan City, a representative oasis city in the Yellow River Basin of China, as a case study, changes in the urban ecological network and its resilience responses to impervious surface expansion were simulated and analyzed using the PLUS model. The results indicate the following: (1) Rapid expansion of impervious surfaces has occurred in central Yinchuan City. The impervious surface area in 2020 expanded to be 2.61 times larger than that in 2000, and by 2030, the area is projected to be 3.24 times larger than in 2000. The spatial pattern of impervious surfaces evolved from an east-west longitudinal “一” pattern to a rightward-tilting “T” pattern, with further strengthening of this horizontal “T” pattern by 2030. (2) With the expansion of impervious surfaces, the ecological network pattern in the central urban area has undergone substantial changes. In 2000, a single-ring ecological network was observed around the urban fringe. By 2020, the outer ring expanded westward, and the inner ring shifted northward, forming a more intricate circuit in the northeastern sector. Simulations predict that by 2030, the ecological network will exhibit a “川” structure. (3) Both structural and functional resilience of the ecological network have improved. Between 2000 and 2020, the α, β, and γ indices increased by 0.09, 0.17, and 0.06, respectively, while network dissemination and diversity rose by 0.08 and 0.29, respectively. By 2030, further enhancements in structural and functional resilience are expected, though the overall resilience level will remain low.

Grassland vegetation biomass is a key indicator of grassland ecosystem productivity and carbon storage. Its spatial distribution pattern and driving mechanisms are of great scientific significance for understanding the maintenance of regional grassland ecosystem structure and function and their responses to climate change. Taking the Qinghai Lake Basin as the study area, this research integrates field sampling data (collected in July-August 2023) and remote sensing data to analyze the spatial distribution characteristics of grassland vegetation biomass (including aboveground and belowground components) and to explore its driving pathways using statistical analysis, correlation analysis, and structural equation modeling. The results reveal (1) Significant differences in biomass among different vegetation types, with meadow types demonstrating higher values than steppe types. Aboveground biomass is highest in mountain shrub meadows (311.54 g·m^-2) and lowest in mountain solifluction meadows (64.67 g·m^-2), whereas belowground biomass is highest in dwarf kobresia meadows (3534.05 g·m^-2) and lowest in rhodiola desert (339.12 g·m^-2). (2) High aboveground biomass values are primarily concentrated in the middle and lower reaches of the Shaliu River Basin and the southern region surrounding the lake, whereas the high-value areas for belowground and total biomass are primarily located in the middle reaches of the Buha River, the Quanji River, the Qiadangqu River Basin and middle reaches of the Shaliu River. Lower altitude areas provide more suitable temperatures and fertile soil, thereby promoting the growth of aboveground parts. Conversely, due to colder conditions and poorer soils, higher altitude regions drive plants to enhance root system development and improve resource acquisition capacity. (3) Structural equation modeling revealed that ecosystem carbon use efficiency (total effect: -0.44) and soil bulk density (total effect: -0.59) were direct factors affecting both aboveground and belowground biomass of grassland vegetation. In conclusion, vegetation type, and regional environment collectively affected grassland vegetation in the Qinghai Lake Basin, identifying ecosystem carbon use efficiency and soil bulk density as the primary determinants. This study provides critical data and scientific support for understanding vegetation biomass spatial patterns and for guiding grassland conservation and restoration in the Qinghai Lake Basin.

In the context of complex risks and regional synergy, exploring a multi-center, multi-level, and multi-node resilience spatial network structure for the resilience building, risk prevention, and sustainable development of urban agglomerations holds significant practical value. This study applies social network theory and uses the three major urban agglomerations in the Yellow River Basin as a case study. The modified gravity model calculates the spatial correlations of urban resilience development, and based on this, social network analysis is employed to evaluate the structural characteristics of the resilience spatial association network in these urban agglomerations. The findings reveal the following: (1) The resilience level of the three major urban agglomerations in the Yellow River Basin is trending upward, with increasing intensity in network connections, indicating that the overall resilience network is becoming more robust and integrated. (2) The spatial connectivity of resilience among the urban agglomerations is tightening, with provincial capitals demonstrating a strong radiation effect and holding dominant positions, although development among sub-agglomerations remains uneven. A typical network-type spatial pattern has emerged, where the Shandong Peninsula urban agglomeration forms a resilient spatial network characterized by “one main and two subordinate” centers, with Jinan City as the central node and Qingdao City and Yantai City as secondary centers. The Central Plains urban agglomeration forms a “radial” resilient spatial network with Zhengzhou City as the center and Kaifeng City, Luoyang City, and other cities as secondary centers. The Guanzhong Plain urban agglomeration shows a closely interconnected resilience network, presenting a “dual-core” spatial pattern linked by the provincial capitals of Xi’an City and Xianyang City.

Rural revitalization is a key strategic measure for China to achieve the comprehensive construction of a modern socialist country. Drawing on the connotation of the rural revitalization strategy, this paper constructs an evaluation index system to measure the level of rural revitalization development. It uses the entropy method to assess the rural revitalization development level of 85 counties (districts) in Gansu Province, China, from 2013 to 2022 and utilizes the Dagum coefficient and kernel density estimation to analyze regional differences in rural revitalization. The results indicate that: (1) The overall level of rural revitalization and development in Gansu Province is on the rise, with the most significant growth being observed in industrial prosperity and ecological livability. (2) The level of rural revitalization and development among counties in Gansu Province exhibits a pattern of spatial distribution characterized by being high in the northwest and low in the southeast. High-level areas are concentrated in the Hexi region, and low-level areas are primarily located in the Hedong region. (3) The overall Dagum coefficient for the level of rural revitalization demonstrates a fluctuating trend downward, with interregional differences marking the primary source of these regional disparities. Levels of rural revitalization and development of the 85 counties in Gansu Province show a gradual trend of convergence, indicating a certain degree of stability. These findings support the proposal that rural revitalization and development efforts in Gansu Province formulate precise policies tailored to local conditions to promote coordinated regional rural revitalization.

To investigate the water-soluble ion components and their sources in the major air pollutant PM_2.5 in atmospheric environment of Urumqi City, Xinjiang, China, sampling points were established in the city center in 2023. A total of 164 samples were collected using membrane sampling, and the mass concentration of PM_2.5 along with the concentration of various water-soluble ion components was measured following relevant testing standards. The sources of these components were also analyzed. The results indicate that: (1) The mass concentration of PM_2.5 and the concentration of ion components are higher during the heating period than that in the non-heating period. (2) The total ion concentration during the heating period is 15 times of the non-heating period, accounting for 73.84% and 26.26% of the PM_2.5 concentration, respectively. The anion-to-cation ratio (AE/CE) is 0.914 in the heating period and 0.600 in the non-heating period, indicating that the chemical properties of PM_2.5 tend to be alkaline. (3) The annual average sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) are 0.43±0.30 and 0.15±0.13, respectively, suggesting a higher probability of secondary transformation pollution of gaseous precursors SO₂ and NO₂ during the heating period due to external meteorological conditions. $\mathrm{NH}_4^{+}$ primarily exists as (NH₄)₂SO₄ and NH₄NO₃ during the heating period, whereas in the non-heating period, it mainly exists as NH₄NO₃. (4) Principal component analysis indicates that during the heating period, the main sources of pollutants are secondary pollution, industrial production, and vehicle exhaust, followed by mineral dust and coal combustion, with a cumulative contribution rate of 80.24%. In the non-heating period, the primary sources are dust and industrial production, followed by secondary pollution and coal combustion, with a cumulative contribution rate of 86.34%. These findings demonstrate significant differences in the sources of water-soluble ions in PM_2.5 between the heating and non-heating periods.

Understanding the spatiotemporal distribution and the internal complex relationships of ecosystem services is essential for their management. With the Shiyang River Basin, Gansu Province, China as the research area, six ecosystem services were evaluated in 2010, 2015, and 2020. The trade-off/synergy of ecosystem services and the spatial changes of service bundles on the grid and township scale were analyzed, and a boosted regression tree model was used to analyze the driving mechanism of ecosystem service bundles in the research area. The results showed the following: (1) The spatial differences of various services were obvious. The spatial pattern of water yield, carbon storage, soil conservation, and habitat quality was “southwest high-northeast low”. Food production was mainly distributed in the farming areas in the north-central part of the basin, and the high-value areas of recreational service were distributed in the southern areas and the central parts of the basin and in densely populated areas in the north. During the research period, all kinds of services were improved to varying degrees, with the increase in soil conservation having the largest improvement and the increase in carbon storage and habitat quality having the smallest. (2) The trade-offs and synergies of ecosystem services on two scales showed similarities, but their intensities were different. Overall, there were twelve pairs of synergy and three pairs of trade-off relationships. (3) The spatial patterns of ecosystem service bundles on two scales were similar. In addition to food production, there were five service-related service bundles in the southern part of the river basin. In the central and northern Minqin oasis areas of the basin, there were service bundles related to food production and recreational service. The ecological environment in other areas was relatively harsh. There was no outstanding service supply in the service bundles, but there were obvious changes in the number and space transfer of service bundles during the study period. (4) Many factors played an important role in the changes in ecosystem service bundles in the research area, and the impact factors were slightly different in different years. Among them, land use type, normalized difference vegetation index, annual precipitation, and altitude were the main drivers of the changes in ecosystem service bundles.

There is a close relationship between the carbon stock in terrestrial ecosystems and the global climate crisis. Using the InVEST model and ArcGIS software, combined with land use data for Gansu Province, China across three phases (2000, 2010, and 2020), the dynamic changes in land use types and carbon stock were assessed and analyzed. The results indicate that: (1) The areas of unused land and arable land decreased significantly between 2000 and 2020, while construction land, grassland, forest land, and water bodies exhibited an increasing trend. Land type transitions within the province were primarily dominated by conversions between grassland and arable land. (2) The cumulative increase in carbon stock in Gansu Province from 2000 to 2020 amounted to 331.24×10⁴ t, following a trend of initial increase followed by a decline. (3) The conversion of unused land to arable land and grassland to forest land contributed to the enhancement of regional carbon stock, whereas the conversion of arable land to construction land and grassland to unused land posed significant constraints on the increase in regional carbon stock. This study provides a valuable reference for future land use planning and ecological restoration efforts in Gansu Province.

The analysis of the spatial and temporal variations in potential evapotranspiration and its sensitivity to meteorological factors in different dry and wet zones is essential for optimizing water resource management in agriculture, animal husbandry, forestry, and water resource planning and allocation, as well as for predicting the impact of climate change on water resources. Given the diverse dry and wet conditions and climatic conditions in Inner Mongolia, China, a region significantly affected by climate change, the sensitivity coefficients of potential evapotranspiration to air temperature, wind speed, water vapor pressure, and sunshine hours were calculated based on the Penman-Monteith formula of the FAO for 76 meteorological stations in Inner Mongolia from 1961 to 2023. The dominant factors influencing potential evapotranspiration in different dry and wet zones and its quantitative response to climate change were investigated. The results indicate that: (1) Spatially, potential evapotranspiration generally decreases from west to east in the longitudinal direction and from south to north in the latitudinal direction. In arid and semi-arid zones, the trend in potential evapotranspiration is not pronounced, whereas in semihumid zones, an increasing trend is observed. (2) The sensitivity of potential evapotranspiration to meteorological factors follows this order: maximum air temperature is the most sensitive factor, followed by water vapor pressure, wind speed, and minimum air temperature, with sunshine hours being the least sensitive. (3) The sensitivity coefficients of all meteorological factors exhibit consistent trends across different dry and wet zones. The temperature sensitivity coefficient and vapor pressure sensitivity coefficient show a decreasing trend, whereas the wind speed sensitivity coefficient and sunshine hours sensitivity coefficient display an increasing trend, with significant changes observed for the water vapor pressure sensitivity coefficient and wind speed sensitivity coefficient. (4) Maximum and minimum air temperatures contribute positively to changes in potential evapotranspiration, whereas wind speed, water vapor pressure, and sunshine hours contribute negatively. Among these, sunshine hours have the least influence on potential evapotranspiration in all dry and wet zones. Wind speed is the dominant factor driving potential evapotranspiration changes in arid and semi-arid zones, while maximum air temperature is the dominant factor in semihumid zones.

Objectively understanding the ecosystem services of the Mongolian Plateau and their response to climate factors is of great significance for formulating scientific strategies for ecosystem protection and utilization under the climate change. Based on the data of land use/cover and meteorological observation, this study combined model simulation, spatial analysis and statistical analysis to explore the spatiotemporal patterns of main ecosystem services and theirs relationships with climate factors in the Mongolian Plateau. The results showed that: (1) The habitat quality, water production, carbon storage, and green leisure services of the Mongolian Plateau were high in the east and low in the west, high in the north and low in the south. The air purification service was high in the west and low in the east, high in the middle and low in the surrounding areas. (2) From 2000 to 2020, habitat quality, water yield, carbon storage and green leisure services showed increasing trends with the increase rate of 9.76%, 36.02%, 7.96% and 7.37%, respectively, and the variation of ecosystem services showed an obvious spatial heterogeneity. (3) Climate factors including annual average precipitation, temperature and wind speed are significantly correlated with different ecosystem services. For the whole region of Mongolian Plateau, precipitation contributed most to changes of habitat quality, water yield, carbon storage and green space leisure; wind speed contributed most to the changes of air purification. The contribution of various factors also varied in different subregions. The study comprehensively evaluated the ecosystem status of Mongolian Plateau from the perspective of ecosystem services. The findings could provide scientific reference for China-Mongolia cooperation in ecosystem management to adapt the climate change.

The typical meteorological year (TMY) is crucial for assessing solar energy resources, significantly impacting the scientific evaluation of regional solar resource assessments and the optimal design of photovoltaic power generation systems. These systems directly influence the technical and economic performance of solar energy utilization. With ongoing climate warming, key indicators of the climate system have shown rapid changes. Over the past 60 years, global surface solar radiation initially decreased and then increased. However, since the 1980s, approximately 25% of observation stations have recorded a continuous decline, highlighting significant temporal and spatial variations in surface solar radiation. Xinjiang, China, a region sensitive to global climate changes, has experienced significant shifts in temperature, precipitation, and other meteorological elements. This study analyzes global horizontal irradiations (GHI) data collected from eight stations in Xinjiang from 1961 to 2022, examining temporal and spatial variations. Additionally, using wind speed, temperature, humidity, and dew point temperature data, we employed the Sandia method to select the TMY for solar energy resource assessment. We compared the differences in GHI TMY selected with the Sandia method every 30 years (four standard climatological normals of 1961—1990, 1971—2000, 1981—2010 and 1991—2020). The findings indicate that while GHI in northern Xinjiang initially decreased and then increased, it continued to decline in southern and eastern Xinjiang from 1961 to 2022. Post-1990s, the rate of decline slowed. Seasonally, GHI reduction rates in autumn and winter were notably higher than that in spring and summer. The GHI values of TMY calculated with the Sandia method were close to the annual average, with a relative error within ±3%. As meteorological elements changed, the absolute error between TMY with Sandia and the annual average increased. Furthermore, monthly GHI exhibited considerable volatility, with fluctuations notably larger between 1981—2000 and 1991—2020 compared to earlier periods. In these four periods, the variability in typical months was less in northern Xinjiang than that in the south and east due to smaller interannual GHI variations. The highest monthly GHI values in TMY typically occurred from June to July, while the values from January to March were generally higher than those from October to December.

Using the HYSPLIT model and other methods, we analyzed the spatiotemporal variations and sources of PM_2.5 and PM₁₀ in the Urumqi, Changji Hui Autonomous Prefecture, and Shihezi urban agglomeration from 2015 to 2023. The results indicate the following: (1) Spatial scale: From 2019 to 2022, PM_2.5 and PM₁₀ concentrations were higher in the central and northwestern parts of the urban agglomeration. PM₁₀ concentrations showed an inverse relationship with elevation. (2) Temporal scale: From 2015 to 2023, on an interannual scale, the annual average concentrations of PM_2.5 and PM₁₀ in Urumqi City and Changji Hui Autonomous Prefecture showed an overall downward trend. In contrast, Shihezi City and Wujiaqu City experienced significant decreases in PM_2.5 and PM₁₀ concentrations only in 2023. On a seasonal scale, the average concentrations of PM_2.5 and PM₁₀ generally declined, with the largest relative reduction in spring, followed by summer and autumn, and the smallest reduction in winter. On a monthly scale, the average concentrations of PM_2.5 and PM₁₀ displayed a “U-shaped” distribution, with a significant reduction in January. On a weekly scale, heavy weekday traffic congestion led to a “negative weekend effect” for PM_2.5 concentrations across all four cities, while PM₁₀ concentrations exhibited a “positive weekend effect” only in Urumqi City. On a daily scale, PM_2.5 and PM₁₀ concentrations in winter were significantly higher than in other seasons. PM_2.5 concentrations decreased overall, with fewer high-concentration days, while PM₁₀ concentrations fluctuated more due to dust events. (3) Pollution sources (2019—2021): In 2019, pollution was predominantly from local sources, resulting in widespread and high concentrations. In 2020, pandemic-related restrictions reduced local emissions, shifting pollution sources toward Central Asia. In 2021, pollution sources expanded again, returning to domestic regions. This study provides essential data for air pollution control and environmental policy optimization in the Urumqi, Changji Hui Autonomous Prefecture, and Shihezi urban agglomeration, contributing to regional ecological protection and sustainable economic development.