Climatic dry-wet conditions are important indicators of climate characteristics, whereas soil dry-wet conditions are complex and multidimensional hydroclimatic concepts. There are significant differences and certain consistencies between these conditions. Under the background of global warming, the evolution trends and differences of these conditions must be further studied. Thus, this paper analyzed the characteristics and differences of climate dry-wet and soil moisture conditions in China and clarified their similarities and differences. Therefore, the overall climate dry-wet status and regional fluctuation were studied using the humidity index, and the soil dry-wet trends were analyzed in the same period. The results showed little change in the boundary line of different climates in China over the past 60 years. However, compared with the climate state period from 1961 to 1990, there was a vast climate drying zone from west to east in the north of China and its humidity index had a slightly decreasing trend, but the variation did not necessitate changing the climate classification. The monthly variations of climate dry-wet and soil dry-wet conditions were different in each climate zone in China, and the consistencies of humid and semihumid zones were better than those of semiarid and arid zones. The monthly variations of PET and precipitation differences in each climatic region in China were obviously different. For arid and semiarid regions, March-September and March-June were dry periods, respectively, and drought was more likely to occur in these periods. The semihumid climate area entered the water surplus stage from July to August, whereas the humid climate area, except for a few months, was basically in the water surplus state throughout the year. There were obvious differences between climate dry-wet changes and perennial soil moisture changes in China’s land regions. The annual humidity index in different climate regions showed a slightly increasing trend, but most of the soil moisture showed a drying trend, especially the shallow soil in the plough layer, which showed a potentially increasing agricultural and pastoral drought risk in different climate regions of China. The results of this study can help us fully understand the relationship between climate dry-wet and soil dry-wet conditions and promote further studies on their relationships. Moreover, this study can strengthen the awareness of drought risk prevention and control and improve agricultural and pastoral drought resistance measures.

To investigate the characteristics of wind farm wake effects and their relationship with meteorological conditions, 33 wind turbines from a wind farm in central Inner Mongolia, China were selected for analysis. Wind resource assessment parameters, including average wind speed, wind direction, and wind frequency distribution, were statistically analyzed from 2021 to 2023. Using the Jensen wake model, wind speeds in the wake area were calculated for different wind directions, with a focus on the refined dominant wind direction. The correlation between wind speeds and meteorological factors, accounting for wake effects, was also explored. The findings are as follows: (1) From 2021 to 2023, the wind farm in central Inner Mongolia was predominantly influenced by southwest winds. High-frequency wind directions shifted from west to south throughout the year. Monthly wind directions were relatively stable, with concentrated wind directions and small wind speed variations. The average wind speed was highest under the dominant wind direction, and the wind speed frequency curve exhibited a positively skewed distribution. (2) Under average wind speeds for each direction, turbines most affected by the wake experienced wind speed losses exceeding 10%. More than half of the turbines were affected by wake effects under northwest and southeast winds, with the most significant losses occurring in the northeasterly downstream positions of the wind farm. Wind speed reductions were particularly pronounced under westerly winds. (3) The impact of barometric pressure, air temperature, and humidity on daily wind speed variation differed across wind directions. For southwest winds, the wake model performed best in the 4-5 m·s^-1 wind speed range, with the average absolute percentage error of wind speed negatively correlated with relative humidity. For northwest winds in the 9-10 m·s^-1 range, the wake model calculations closely matched measured wind speeds, with errors positively correlated with barometric pressure and temperature. In addition, the wake model performed well in the 9-10 m·s^-1 and 7-8 m·s^-1 ranges for southeast and northeast winds, respectively. These results provide valuable insights into the analysis of wind turbine wake effects and wind speed predictions for wind farms.

The evaluation area of Qinghai area of Kunlun Mountain National Park is located on the northern slope of the Kunlun Mountains in Qinghai Province, China. Due to its steep terrain and harsh natural environment, the area is sparsely populated and is one of the most complete and authentic mountainous ecosystems in China. In order to comprehensively grasp the vegetation types, distribution, and survival in the evaluation area, this study used the method of sample plot survey to set up 168 quadrats in the evaluation area of Qinghai area of Kunlun Mountain National Park, recording species composition, quantitative characteristics, habitat information, and referring to the classification of vegetation types and naming in the “Vegegraphy of China”, etc. The results show that: (1) There are a total of 384 species of seed plants in 46 families, 146 genera, in the evaluation area, mainly Poaceae, Asteraceae, Fabaceae, and Amaranthaceae. (2) The vegetation in the assessment area can be divided into 7 vegetation type groups, 11 vegetation types, 17 vegetation subtypes, and 36 formations, mainly including Stipa purpurea grassland, Carex parvula meadow, and Oreosalsola abrotanoides desert. Overall, the plant diversity in the assessment area is low, and the vegetation exhibits uniqueness and transitional characteristics; the vertical vegetation zonation along the altitudinal gradient is incomplete, mainly composed of mountainous desert zone, alpine grassland zone, alpine meadow zone, and sparse alpine vegetation zone; The horizontal distribution gradually transitions from grassland vegetation to desert vegetation from east to west and from south to north. The research results provide basic data for the creation and vegetation protection of the Qinghai area of Kunlun Mountain National Park.

Utilizing detailed climate data collected from 105 national meteorological observation stations in Xinjiang, China during 1990—2020, this study systematically evaluates the tourism climate comfort and comfort period across fifteen prefectural and municipal cities in Xinjiang. Three key indicators [the temperature and humidity index (THI), wind-cold index (WCI), and index of clothing (ICL)] were employed for the analysis. The findings reveal as follows: (1) The months with the highest tourism climate comfort in Xinjiang are primarily May, June, and September. (2) According to the comprehensive tourism climate comfort index, Hami City, Altay Prefecture, Bortala Mongol Autonomous Prefecture, and counties and cities directly under Ili Kazakh Autonomous Prefecture and Kizilsu Kyrgyz Autonomous Prefecture exhibit an inverted U-shaped annual pattern. In contrast, Urumqi City, Karamay City, Shihezi City, Turpan City, Changji Hui Autonomous Prefecture, Bayingol Mongol Autonomous Prefecture, Tacheng Prefecture, Aksu Prefecture, Kashgar Prefecture, and Hotan Prefecture demonstrate an “M”-shaped pattern. (3) Analysis of the travel comfort period indicates that the southern border region enjoys the longest travel comfort period, followed by the northern border region, with the eastern border region having the shortest. Notably, Kashgar Prefecture and Hotan Prefecture have the longest comfort period, spanning March to October. However, the duration of the comfort period is not the sole determinant of tourist flow, as travel conditions may sometimes contradict comfort levels.

To assess the impact of future climate change on geological hazard zoning in the Ili River Basin, Xinjiang, China, climate data from different scenarios of the Coupled Model Intercomparison Project Phase 6 (CMIP6) were selected to analyze climate change characteristics under various shared socioeconomic pathway (SSP) scenarios from 2021 to 2040. The information quantity-random forest model was employed to conduct the geological hazard assessment and generate a prediction map. The results indicate that: (1) High and extremely high hazard areas are primarily concentrated in northern Yining County, southern Nilka County, and northern Xinyuan County in the middle mountainous hilly regions; debris flow hazard areas are mainly located in southern Zhaosu County, the northern region of Keguqin Mountain in Huocheng County, Hejing County, and the middle-to-high mountainous areas in eastern Nilka County. (2) From 2021 to 2040, the Ili River Basin is projected to experience a general increase in temperature and precipitation, with a maximum annual average temperature rise of approximately 1.53 ℃ and a maximum precipitation increase of about 19.3 mm. (3) Under future SSP126, SSP245, SSP370, and SSP585 scenarios, high-hazard areas for landslides and rockfalls are expected to expand. The severity of landslides in southern Yining County, northern Xinyuan County, and southwestern Nilka County, as well as debris flows in northern Khorgas City and Yining County, is anticipated to worsen, with maximum increases of 17.31% and 8.77%, respectively. The findings of this study provide valuable insights for future disaster prevention and mitigation efforts in the Ili River Basin.

Using summer daily precipitation data from 102 meteorological stations from June to August during 1961—2022, the spatial and temporal characteristics of extreme and non-extreme precipitation were analyzed, and variations in these two precipitation types across different areas of the arid region of northwest China were compared. The results reveal the following: (1) Summer precipitation in the arid region of northwest China exhibited an increasing trend, particularly in the Ili River Valley and the western Tarim Basin, contributing an average of more than 40% to total annual precipitation. (2) Extreme precipitation in summer accounted for approximately 45% of total precipitation in the arid region, with an overall increasing trend, notably in the western Tarim Basin, Hexi-Alagxa, and northern Xinjiang. (3) Most meteorological stations in the region recorded increasing trends in extreme precipitation, extreme precipitation days, and extreme precipitation intensity. However, the number of non-extreme precipitation days showed significant decreases at most stations, while non-extreme precipitation intensity increased significantly. In the western Tarim Basin, the increase in summer precipitation was driven by both extreme and non-extreme precipitation, contributing 61% and 39% of the total increase, respectively. In other regions, the rise in summer precipitation was predominantly due to the increase in extreme precipitation. These findings enhance understanding of summer precipitation climate change in the arid region of northwest China.

With the warming of the Qinghai-Tibet Plateau, the trend of increase in the number and size of plateau lakes is on the rise, with a noticeable expansion of lakes over the Kumkuli Basin in the eastern Kunlun Mountains. Ayakkum Lake is the largest saltwater lake in the Kumkuli Basin, and the Third Xinjiang Scientific Expedition data indicates that the lake has expanded to become the largest lake in Xinjiang. Based on the expedition data and remote sensing imagery, this study analyzes and subsequently discusses the change in the water volume of Ayakkum Lake and replenishment of its water sources, including glacier, permafrost, temperature, and precipitation. The results show that: (1) The area of Ayakkum Lake expanded from 623.03 km² in 1990 to 1141.67 km² in 2023, and the lake level rose by 7.28 m from 2002 to 2023, corresponding to an increase in water storage of 66.64×10⁸ m³. (2) The glacier area in the Ayakkum Lake Basin decreased by 16.4 km² from 1990 to 2023, with a volume reduction of 1.96 km³. Until 2023, there were 451 glaciers with a total area of 324.26 km² in the region. (3) A distribution map of permafrost over the Qinghai-Tibet Plateau in 2010 shows that the continuous permafrost area was 12395 km² and seasonal permafrost area was 10652 km². (4) A water balance analysis of the area indicates that glacier and permafrost meltwater account for 9% and 5% of the total inflow into Ayakkum Lake, respectively, whereas runoff from land surface precipitation in seasonal frost and permafrost regions accounts for 67% of the total inflow into Ayakkum Lake. Additionally, replenishment to the lake water surface via direct precipitation accounts for 19% of the total inflow into Ayakkum Lake. In other words, the expansion of the lake mainly resulted from an increase in precipitation over the Ayakkum Lake Basin. This study reveals the land surface hydrological processes in the Kumkuli Basin and provides reference for local governments to optimize water resource allocation and management.

Soil salinization is a manifestation of land degradation caused by the combined effect of natural processes and human activities. This issue is particularly common in irrigation districts, where various factors exacerbated by frequent human interventions influence soil salinity. To prevent soil salinization, it is essential to have a comprehensive understanding of soil water-salt transport mechanisms in irrigation districts with frequent human activities. After reviewing the factors that influence soil water-salt transport in irrigation districts and the characteristics and applications of water-salt transport model, we propose a potential direction for simulating water-salt transport in irrigation areas. The formation of salinization in irrigation areas is closely related to natural factors such as climatic aridity, terrain, seasonal soil freeze-thaw cycles, groundwater salinity, and parent material of soils, as well as anthropogenic factors such as irrational irrigation practices, agricultural methodologies, and fertilization regimes. To understand the process of water-salt transport, soil water-salt transport models are effective tools. The commonly used models for water-salt transport include water-salt balance models, physical models, and statistical models. They are mainly used to optimize irrigation water-saving regimes and drainage management for salinity control at the field scale. However, applying these models at the regional scale presents challenges due to the difficulty of obtaining observational data to calibrate and validate models that involve soil water-salt transport processes and crop growth. The rapid development of modern large-scale irrigation districts has changed the spatiotemporal distribution of soil water-salt transport. However, the continuous improvements of the model and the rapid development of computer technology have provided possibilities for investigating the spatiotemporal evolution mechanisms of water-salt transport in large-scale irrigation districts. Future models should focus on strengthening the soil water-salt transport mechanisms based on ecological safety. It is recommended to develop a multi-process water-salt transport model that is coupled with a climate model or an economic model.

Global warming has led to the increased frequency of extreme events such as droughts, posing significant threats to ecological security and sustainable socioeconomic development, particularly in arid regions, which are highly sensitive and responsive to climate changes. This paper employs the distributed hydrological model HEC-HMS, utilizing observed meteorological and hydrological data from basin stations and global climate model data from the Sixth International Coupled Model Intercomparison Program (CMIP6), to simulate and forecast the historical (1986—2014) and future (2015—2100) runoff trends and hydrological drought risks in the Yarkant River Basin (an essential tributary of the Tarim River), Xinjiang, China. The findings indicate that: (1) The HEC-HMS model is well-suited for arid basin areas. Under the three shared socioeconomic pathways (SSPs) scenarios, the runoff and standardized runoff index (SRI) in the Yarkant River Basin are projected to significantly increase (P<0.1), with the SRI growth rate estimated at approximately 0.13-0.27·(10a)^-1. (2) A comparative analysis of the marginal distributions of four drought characteristic variables in the basin for both historical and future periods reveals that the duration and intensity of future droughts will exceed those in the historical record, with a continuous rise in drought event magnitudes. (3) Moreover, the joint probability of future hydrological droughts in the Yarkant River Basin is expected to decrease relative to the historical period, leading to a prolonged return period for future droughts. The outcomes of this study offer valuable scientific references for water resource management and the development of strategies to mitigate hydrological drought risks in the basin.

Drought and water scarcity are inherent features of Xinjiang’s physical geography. It is crucial to understand the spatiotemporal evolutionary patterns and influencing factors of water use for effective water resources demand management. In this study, we investigated the influencing factors which drive the temporal change and spatial heterogeneity in water use pattern in Xinjiang from 1990 to 2020 using the logarithmic mean Divisia index (LMDI) method. In addition, we quantified the main influencing factors contributing to higher per capita water use in Xinjiang in comparison to the average levels of other regions in northwest China and whole China. The conclusions can be drawn: (1) The total water use in Xinjiang showed a first increasing then decreasing trend, whereas per capita water use showed an overall declining trend. (2) The change of water use intensity and industrial structure were the main reasons for the decline of total water use in Xinjiang. (3) High water intensity and agriculture dominated industrial structure were the main reasons for higher per capita water use in Xinjiang than other regions in northwest China and whole China. (4) Per capita water use across various prefectures in Xinjiang exhibited significant spatial heterogeneity, primarily attributable to variations in water use intensity, per capita GDP, and industrial structure. Based on the main results, we propose relevant water management policy recommendations, which can provide a scientific reference for sustainable water use and management in Xinjiang.

Utilizing data from population censuses conducted in 2000, 2010, and 2020, this study employs the offset-sharing analysis, the random forest model and other methods to examine the spatio-temporal evolution and driving factors of population distribution in Lanzhou City, Gansu Province, China, from 2000 to 2020. The findings reveal that: (1) Population growth exhibits significant differences across periods and regions in Lanzhou City, with clear suburbanization trends characterized by a “jumping” diffusion from the central urban area to the far suburbs. The central urban area remains the most populous, although its growth rate has slowed, while suburban growth is accelerating. Population in the far suburbs initially declined but later increased rapidly. (2) The population offset growth pattern in Lanzhou City is uneven. Taking 2010 as a pivotal year, blocks with positive population deviation growth were primarily located in the central urban area before 2010 but shifted to the far suburbs afterward, particularly in national new districts and development zones, which demonstrate “enclave” population agglomeration. (3) Natural factors, economic conditions, social development levels, and historical evolution are the main drivers of population spatial changes. Meanwhile, the influence of policy interventions and environmental comfort is increasingly significant. The impact of these driving factors on population distribution is nonlinear. These findings provide valuable insights for optimizing population distribution policies in inland cities of northwest China.

From January 2021 to January 2022 and from December 2022 to January 2024, we conducted a camera-trap survey to investigate wildlife resources in the Qimantag Mountain, located northeast of the Altun Mountain National Nature Reserve, Xinjiang, China. Over the course of 17529 camera-trap days, we obtained 7237 independent detections. The results indicated the following: (1) We recorded 6045 independent detections of mammals, identifying 19 species across five orders and eight families. The Shannon-Wiener and Pielou evenness indices for the mammal community were 3.05 and 0.71, respectively. Based on the relative abundance index (R_AI), the five most abundant mammal species were Equus kiang (85.85), Lepus oiostolus (82.26), Pseudois nayaur (44.04), Bos mutus (35.26), and Canis lupus (26.41). (2) We recorded 1182 independent detections of birds, identifying 50 species from 10 orders and 21 families. The Shannon-Wiener and Pielou evenness indices for the bird community were 4.31 and 0.76, respectively. The five most abundant bird species were Tetraogallus himalayensis (9.81), Oenanthe deserti (8.04), Pyrrhocorax pyrrhocarax (7.25), Grus nigricollis (6.33), and Eremophila alpestris (5.42). (3) Among the detected species, 11 are listed as Class I state key protected wildlife, and 18 as Class II, in China. Six species are classified as endangered, seven as vulnerable, and 13 as near threatened according to the Red List of China’s Vertebrates. Additionally, four species: Cuon alpinus, Meles fonia, Turdus mandarinus, and Alauda leucoptera were new records for the Altun Mountain Reserve. (4) The activity patterns of Pseudois nayaur, Bos mutus, and Canis lupus were predominantly diurnal, while Lepus oiostolus was more nocturnal, and Equus kiang exhibited both diurnal and nocturnal activity. These findings provide a baseline for wildlife resources in the Altun Mountain Reserve and offer fundamental data for the creation of Kunlun Mountain National Park and for long-term wildlife monitoring in the region.

Desertification is a critical global ecological and environmental challenge. The Mu Us Sandy Land is a pivotal region for desertification control in China. Over the past three decades, numerous studies have examined desertification dynamics in this area; however, a systematic analysis of these dynamics over the past 70 years has been lacking. This study conducted a Meta-analysis of desertification dynamics by integrating the findings of 39 case studies on the Mu Us Sandy Land since the 1950s and discussed the factors influencing desertification. The results indicate the following: (1) Over the past 70 years, the proportion of light desertification areas initially decreased and then increased, the proportion of moderate desertification areas exhibited a slight increasing trend, and the proportion of severely desertified areas first increased and then decreased, reflecting a notable reversal of desertification trends in the Mu Us Sandy Land. (2) A slight reversal trend of desertification was observed from 1980 to 1989, desertification expanded from 1990 to 1999, the expansion trend was reversed from 2000 to 2009, and desertification continued to steadily reverse from 2010 to 2019. The year 2000 marked a significant turning point in the reversal of desertification in the Mu Us Sandy Land. (3) Continuous drought has significantly promoted desertification expansion. The sustained reversal of desertification since 2000 is attributed to extensive ecological engineering efforts and the implementation of policies such as “prohibition against grazing, closed grazing, rotational grazing, and limiting grazing animal numbers based on pasture availability”. These findings provide valuable insights for understanding the development patterns of desertification in the Mu Us Sandy Land and formulating effective desertification control strategies.

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.

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.

By collecting data from the national population census, the location of primary schools and residential areas in Urumqi City, Xinjiang, China in 2020, urban road network and other data, this paper uses numerical statistics, buffer zone analysis, cost matrix analysis and other methods to explore the spatial balance of primary education resources in Urumqi City. The study findings are as follows: (1) The distribution of elementary school education resources in Urumqi City is uneven, with a relatively greater abundance in the Tianshan and Shayibake Districts, and a relative lack of resources in parts of the Xinshi, Toutunhe, and Shuimogou Districts. (2) Some elementary schools located in the Tianshan, Shayibake, and Xinshi Districts, and within 0-4 min driving distance, may become candidates for exporting or optimizing primary education resources in Urumqi City in the future. (3) Affected by changes in the structure of the school-age population, Urumqi education resources in 2026 may again be in greater supply than demand, objectively providing favorable conditions for improving the imbalance of education resources in the city. (4) Parts of the Xinshi, Shuimogou, Shayibake, Toutunhe Districts, and other high light index districts have relatively scarce elementary school education resources; it is recommended to focus on these areas in the future. This study provides a scientific reference for the future spatial adjustment of educational resources in Urumqi City.

The project titled “Scientific Investigation of Water Resources Development Potential and Utilization Pathways on the northern Slope of the Kunlun Mountains” was initiated in October 2021 as part of the initial set of projects for the Third Xinjiang Scientific Expedition. This study integrates multi-source remote sensing data and field research conducted from 2022 to 2023 to examine hydrological changes, water resources dynamics, and water resource utilization patterns on the northern slope of the Kunlun Mountains. The findings reveal the following: (1) A temperature increase of 0.14 ℃·(10a)⁻¹ and precipitation increase of 6.53 mm·(10a)⁻¹ from 1990 to 2020 was observed on the northern slope of the Kunlun Mountains. (2) Glacier variations have remained relatively stable, with a slight expansion observed in snow cover area and depth. (3) Permanent water bodies have experienced a significant growth rate of 79.89%, while seasonal water bodies have expanded by an impressive margin of 144.49%. (4) Ayakkum Lake and Akikkule Lake, two major lakes within the Kumukuli Basin, witnessed increases in their water areas by approximately 68.91% and 58.22%, respectively, and several rivers within this basin exhibit potential for further development regarding water resources utilization. (5) Terrestrial water storage on the northern slope of the Kunlun Mountains generally exhibits an increasing trend, particularly more pronounced from west to east. (6) Average annual runoff of Hotan River, Keriya River, and Qarqan River, the main rivers on the northern slope of the Kunlun Mountains, increased by 20.24%, 27.85%, and 45.17%, respectively, during the period of 2010—2023 when compared with the period of 1957—2023. (7) Based on simulations considering different climate change scenarios, it is predicted that major river runoff will continue to increase throughout the middle-to-later stages of the 21^st century, alongside regional augmentation in available water resources. The conditions of water resources on the northern slope of the Kunlun Mountains can provide favorable water resources for the green development of the region.

The social network of urban ecological resilience and its influencing factors were analyzed to promote regional green synergistic development. Data from 2012 to 2021 for 63 prefecture-level cities in the Yellow River Basin, China, were used to construct a pressure-state-response model. The CRITIC-TOPSIS method, gravity model, and multi-scale geographic weighting model were applied to examine the ecological resilience of cities in the Yellow River Basin, the linkage relationships, and the influencing factors. The results reveal the following: (1) The ecological resilience of the Yellow River Basin fluctuates around 0.5, with the pattern “upstream>downstream>midstream”, and the average annual increase rates of each river reach was 0.41%, 0.30%, and 0.40%, respectively. (2) The Yellow River Basin is divided into seven major city networks (N₁-N₇). The degree of basin agglomeration and city association increases sequentially from the upper to the lower reaches. (3) Considering the influence of direct effect, regulatory effect and substitution effect, industrial structure upgrades significantly enhance the urban ecological resilience of city networks N₁-N₄, with impact coefficients of 0.4213, 0.4210, 0.5085, and 0.8883, respectively. In contrast, industrial structure rationalization more effectively enhances the ecological resilience of city networks N₅-N₇, with impact coefficients of 0.8483, 0.5669, and 0.8128.

An index system was developed by measuring variables such as agricultural surface source pollution and agricultural net carbon sinks. Super-efficiency SBM and Malmquist index methods were used to calculate the green efficiency values of agricultural water resources and their decomposition index values in 14 administrative regions of Xinjiang, China, from 2011 to 2020. Standard deviation ellipses were drawn to analyze the movement of centers of efficiency, and a Markov chain probability matrix was constructed to analyze their spatial pattern of changes. The Tobit model was also used to analyze its impact on the green efficiency of agricultural water resources in Xinjiang in terms of cropping structure, agricultural economy, water supply structure, water conservation facilities, urbanization level, resource endowment, and economic development level. The results show the following: (1) The average value of green efficiency of agricultural water resources during the study period in each administrative region of Xinjiang is 0.865; there are obvious differences in the level, improvement effect, and speed of the green efficiency of agricultural water resources in each region. (2) The coordinates of the center of gravity during the study period always moved within Bayinbuluk Town, Hejing County, Bayingol Mongolian Autonomous Prefecture, first to the northeast and then to the southwest, and eventually turned back to the northeast; there is a probability of transferring to each other or across types between lower, higher, and high green efficiency types of the regions, and it is difficult for inefficient regions to grow rapidly or across types. (3) The levels of economic development, agricultural economy, and water supply structure have a significant positive impact on the green efficiency of agricultural water resources, and resource endowment and water conservation facilities have a significant negative impact on the efficiency of agricultural water resources. The results of this study are of great practical significance for the sustainable use of agricultural water resources and the construction of green and efficient agriculture in Xinjiang.

Conducting a systematic study on lake area changes and their underlying causes in the east Kunlun Kumukuli Basin holds significant practical importance. This research enhances our understanding of climate change patterns and the regional water cycle in the east Kunlun Mountains, addressing critical water shortage issues in southern Xinjiang, China. Utilizing the Google Earth Engine (GEE) remote sensing cloud computing platform, this study extracted water bodies from remote sensing images of the east Kunlun Kumukuli Basin between 1986 and 2023. It analyzed lake area changes and their influencing factors, incorporating meteorological data, glacier activity, and land use patterns. The findings reveal several key trends from 1986 to 2023. (1) The number and area of lakes in the east Kunlun and Kumukuli regions increased significantly, with the total lake area expanding from 1196.47 km² in 1986 to 2190.43 km² in 2023, representing an average annual increase of 26.16 km². (2) Ayakumu Lake, the largest in the region, experienced a 50.17% increase in area, while the number of lakes larger than 1 km² grew from six in 1986 to nine in 2023. (3) The primary driver behind this lake expansion is moderate precipitation, which accounts for 63.80% of the increase. Although air temperature plays a role in glacier melt, its contribution to lake area growth is less significant than that of precipitation.