The Ili River Basin, spanning China and Kazakhstan, features a delicate ecological environment. Understanding the vegetation changes throughout the basin is essential for the region’s sustainable development. This study analyzed spatiotemporal vegetation variations in the Ili River Basin from 2000 to 2022, utilizing enhanced vegetation index data from MODIS. We examined vegetation change disparities within and outside China’s portion of the basin, among various vegetation types, and across different elevations. Our findings reveal: (1) Since 2000, vegetation conditions have generally improved across the Ili River Basin, notably in Kazakhstan, whereas a decline was observed within China. Degraded regions are predominantly at elevations between 1000 m and 3000 m. Grasslands and croplands exhibited positive trends, in contrast to forests. (2) Over the past 20 years, the Ili River Basin experienced minor vegetation fluctuations, with more pronounced variations within China. Grasslands encountered higher fluctuations compared to croplands and forests, and the 2500 m to 3000 m elevation range showed relatively stable vegetation. (3) Future projections indicate a prevailing positive trend in vegetation across the Ili River Basin, with approximately 52% of the areas expected to see ongoing improvement. Grasslands are anticipated to have higher improvement ratios than croplands and forests. Regions below 1000 m and above 3000 m in elevation are likely to experience sustained positive changes. This study’s insights into vegetation dynamics will inform ecological protection strategies in the Ili River Basin.

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.

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.

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.

The bedrock of the Danxia landscape is predominantly cemented by calcareous and ferruginous cements; thus, it has special landscape elements and formation mechanisms. It has become an important tourism resource with much attention because of its high scientific and ornamental values. However, compared with southeast humid areas, little attention has been paid to the characteristics and causes of the Danxia landscape in the arid climate of Northwest China. The Wensu Grand Canyon in the Aksu Prefecture of Xinjiang was selected and investigated to explore the characteristics and causes of the Danxia landscape by field investigation, sample microscope observations, salt chemistry and element geochemistry experiments, and ArcGIS hypsometry. The results are as follows: (1) The study area is characterized by canyon, peak and peak forest landscapes, well-developed mud flow films along slopes, and cap rock columns. The bedrock comprises red fluvial conglomerates and sandstones of Neogene age. The hard conglomerate beds are favorable for the formation of cap rock columns. (2) The study area is located near the Wensu salt dome with a high salt content, and the main salt minerals are probably chlorides, nitrates and sulfates, as inferred from the salt experiment. Most of the major elements of sandy debris samples within caverns migrated compared with the surface rock, indicating active chemical weathering in the arid climate. (3) The hypsometric integral (HI) shows that the HI value of the southern part of the study area is 0.61, which suggests an early stage. The HI value of the northern part is 0.38, which indicates a late stage. Therefore, the geomorphic evolution and development stages differ in the study area. Although the precipitation in the study area is very low, river erosion is obvious. Tectonism is also considered the main controlling factor of Danxia landscape evolution.

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 northern slope of the Kunlun Mountains is a strategically important area for safeguarding national security in the new era and a key passage in the “Silk Road Economic Belt”, with a prominent strategic position. However, due to historical and natural reasons, the economic development in this region is relatively lagging. This paper systematically analyzes the current issues in the high-quality development in the northern slope of the Kunlun Mountains, including low water utilization limit, serious lag in water conservancy construction, relatively single industrial layout, slow urbanization process with a lack of important industrial layout, and insufficient driving force for high-quality regional development. In conjunction with the regional natural environmental characteristics and development opportunities, this paper proposes to accelerate the construction of an urban cluster system for this economic belt with multi-industry coordinated development, significantly improve the water resource utilization limits and enhance water management capabilities with conservancy engineering, guarantee the water resource security for agricultural upgrading and efficiency improvement in the economic belt of the northern slope of the Kunlun Mountains. It is proposed to systematically build a multi-functional agricultural-forestry-pastoral base in the region, construct a diversified food supply system, bridge the water deficit with energy, improve comprehensive resource utilization efficiency. By advantages leveraging and resource sharing between the Production and Construction Corps of Xinjiang and local communities, it aims to accelerate the construction and high-quality development of the economic belt of the northern slope of Kunlun Mountains. The research findings can provide technological support for ecological security and accelerating high-quality development in the economic belt of the northern slope of the Kunlun Mountains.

Estimating lake water evaporation losses is of significant importance for addressing water scarcity in arid regions and for the protection of lake ecosystems. This study analyzed the spatiotemporal variations of actual evapotranspiration (ET) in three typical lakes within the Kumukuli Basin of East Kunlun Mountains over the past 20 years. Using empirical formulas, we estimated the evaporation losses and applied a random forest model to identify potential factors influencing changes in lake water evaporation. This study examines the spatiotemporal variation in ET of typical lakes in the Kumukuli Basin of East Kunlun Mountains using PML-V2 data, estimates water loss due to lake evaporation through empirical formulas, and explores the influencing factors of lake ET changes using a random forest model. Key findings include (1) From 2001 to 2020, the annual ET of Ayakkum Lake, Aqqikkol Lake, and Whale Lake exhibited a fluctuating trend, initially increasing, then decreasing, and subsequently showing a gradual increase, with peak and trough occurring in 2004 and 2012, respectively. (2) The ET of the three lakes demonstrated an inverted U-shaped pattern within the year, with Ayakkum Lake peaking in June and the other two lakes in July. Aqqikkol Lake exhibited a relatively gentle increase, while Whale Lake saw a significant rise from May to July, reaching 48.45 mm·month^-1. (3) During the same period, the evaporation water volume of the three lakes increased, with Ayakkum Lake recording the highest at 10.33×10⁸ m³·a^-1, followed by Aqqikkol Lake at 4.54×10⁸ m³·a^-1, and Whale Lake at 3.33×10⁸ m³·a^-1. (4) Analysis using the random forest model indicates that lake area significantly influences evaporation volume. Additional factors, including increases in wind speed, maximum temperature, and precipitation, also drive evaporation changes, contributing over 45% cumulatively.

Changes in water level serve as crucial indicators of dynamic variations in lake systems, significantly impacting lake ecological environments and water resource management. This study employs data from ICESat-1, CryoSat-2, EnviSat, and ICESat-2 multi-source altimetry satellites to analyze water levels of Aksai Chin Lake, Ayagkumu Lake, Aqqikkol Lake, Jingyu Lake, Changhong Lake, and Surigh Yilganing Kol Lake on the northern slope of Kunlun Mountains. It also incorporates data on lake watershed areas, temperature, precipitation, and land use from 2003 to 2022. Quantitative analyses of lake water level changes were conducted using trend analysis, Mann-Kendall test, Pearson correlation, and other methods to explore the influencing mechanisms of these changes. The findings are as follows: (1) The accuracy of water levels derived from multiple altimetry satellites was validated against the water level dataset, showing consistent trends and passing the significance F test in all correlation analyses. (2) Over the past 20 years, water levels of the lakes, except for Surigh Yilganing Kol Lake, have shown a significant upward trend, with Changhong Lake exhibiting the highest rate of increase at 0.71 m·a^-1, while Aksai Chin Lake has the lowest rate of increase at 0.29 m·a^-1. (3) Climatic factors differ significantly across lake catchment areas, with temperatures showing a consistent rising trend and precipitation varying across regions. A positive correlation exists between water levels and precipitation for Aqqikkol Lake, Ayagkumu Lake, and Jingyu Lake, while water levels of typical lakes show a positive correlation with temperature, except for Surigh Yilganing Kol Lake. This study leverages data from multiple altimetry satellites to analyze lake water level changes, aiming to elucidate the hydrological variations of lakes on the northern slope of the Kunlun Mountains. The findings provide a scientific basis for the management of lake ecological environments.

As a typical ecologically vulnerable area in northern China, the ecologically vulnerable area of the Loess Plateau is significantly affected by extreme rainfall events because of its unique topography and climatic conditions. Twenty-eight meteorological stations in the water-wind erosion crisscross region were selected, and eleven extreme precipitation indices were calculated using the RClimDex model. Linear correlation analysis, the Mann-Kendall trend test, and the wavelet crossing method were used to analyze the spatial-temporal distribution characteristics of extreme precipitation events in the water-wind erosion crisscross region of the Loess Plateau from 1970 to 2020. Driving factors for extreme precipitation events are discussed. The results are as follows: (1) The number of continuous dry days in the water and wind erosion interlacing zone from 1970 to 2020 shows a decreasing trend, whereas the other 10 indices show an increasing trend, reflecting the increasing frequency, magnitude, and intensity of extreme precipitation events in the study area during the past 50 years. There is a close relationship between increases in annual precipitation and extreme precipitation events, and an increase in extreme precipitation events is mainly caused by the number of moderate and heavy rain days. (2) Extreme precipitation events show an increasing trend in the entire region from 1970 to 2020, with significant extreme precipitation events occurring in the central and southwest parts of the crisscross region. The extreme precipitation and intensity in the Shaanxi section show a significant increasing trend, and the extreme degree is very significant. (3) The three extreme precipitation indices, total wet day precipitation, number of heavy rain days, and 5-day maximum precipitation, have varying degrees of influence from El Nino-Southern Oscillation, East Asian Summer Monsoon, and sunspot number (SN), with cross wavelet transform with SN having the greatest influence. This shows that the correlation between SN and extreme precipitation index is the highest among the influencing factors, and SNs have the greatest influence on extreme precipitation events.

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.

As an important photovoltaic (PV) power generation base, the Inner Mongolia Autonomous Region (IMAR), China has seen the problem of blindly constructing PV power stations become more prominent in recent years. It is of great significance to grasp the suitability of regional PV development, power generation potential, and emission reduction benefits for the healthy development of the PV industry. To explore the suitability of PV development in the IMAR and the benefits of emission reduction, this study makes comprehensive use of meteorological, natural geographic, economic, and social data, constructs a comprehensive evaluation index system of PV development suitability in the form of meteorology-terrain-location-vegetation, uses an analytic hierarchy process to determine the weights of the evaluation indexes, and performs a spatially explicit evaluation of the suitability of PV development in the IMAR with the aid of a geographic information system tool to quantitatively assess the potential of PV power generation and emission reduction benefits under different development intensities. The PV power generation potential of the leagues and cities and the demand for electric power are compared. The results are as follows: (1) The suitability of PV development in the western part of the IMAR is greater than that in the central and eastern parts, and the various suitable areas are mainly located in the western Alagxa League and Bayannur City, with particularly suitable areas for PV development accounting for 23.66% of the total area of the IMAR. (2) The IMAR PV power generation potential is enormous, especially for regional development, where 12.57% of it can meet the IMAR 2021 electricity consumption. (3) The distribution of PV power generation potential and electricity demand in the IMAR has strong spatial heterogeneity, and the spatial pattern is characterized by significant features. (4) The energy saving and emission reduction effect of PV power generation in the IMAR is remarkable. Compared with conventional coal-fired thermal power generation, the annual carbon emission reduction is approximately 2.947×10⁹ t if the development of a special suitable area is performed, which is 4.46 times the total carbon emission of the IMAR in 2021 and accounts for 21.20% of China’s total carbon emission in 2021. These results provide scientific references and guiding suggestions for the placement of PV power stations and the healthy development of the PV industry in the IMAR.

The phenology of lake ice is a sensitive indicator of regional climate change. Through comprehensive analysis of long-term surface reflectance data, meteorological data, and lake information for seven large lakes (Karakul Lake, Balkhash Lake, Aral Sea, Alakol Lake, Zaysan Lake, Chatir Kol Lake, and Markakol Lake) with an area greater than 100 km² in Central Asia from 2000 to 2020, GIS-related technologies were used to explore the characteristics of lake ice phenology and its influencing factors. The results are as follows: (1) Lakes in Central Asia began to freeze from mid-September to early November and completely froze from late November to late December, with an average freezing time of 35 days; lake ice began to melt from late March to mid-May and would completely melt from early April to early June, with an average melting time of 18 days. (2) From 2000 to 2020, the start dates of ice formation in five of the seven lakes in Central Asia exhibited a delayed trend, with an average delay rate of 4.86 days per decade, whereas the start date of Balkhash Lake exhibited an advancing trend, with an advancing rate of 1.44 days per decade. The analysis suggests that this may be due to a decrease in the annual average temperature in the winter half of the year. The complete melting dates showed an advancing trend, with an average advancement rate of 2.90 days per decade. The average ice-covered period for the seven lakes was 171 days, with four of the lakes exhibiting a trend of shortening of the ice-covered period. The complete freezing period shows an overall trend of shortening, with Balkhash Lake exhibiting the most significant reduction, with a rate of 9.02 days per decade. (3) The spatial pattern of the formation and melting of lake ice in the seven lakes in Central Asia can be mainly divided into two categories: the lake water gradually freezes from both sides to the center and melts from the lake shore to the opposite side, or the lake water freezes from the shore to the opposite side and the earlier freezing, lake area melts the sooner. (4) The lake ice phenology changes in Central Asia are influenced by multiple factors such as lake characteristics (altitude and area) and climate (temperature and precipitation). Temperature is the key factor affecting lake ice phenology, and the higher the temperature, the shorter the ice-covered period. The area primarily affects the freezing date of the lake, and the larger the area, the shorter the ice-covered period. As the altitude increases, the ice-covered period of the lake extends.

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.

Based on air pollution and meteorological data (2015—2021) from Qingyang City, Gansu Province, China, this study employed mathematical statistics and Pearson correlation analysis to examine AQI, primary pollutants, and their concentration changes. It aims to explore the influence of meteorological factors on pollution levels and establish response indicators to aid the prevention and control of air pollution in the area. Results indicate that Qingyang City predominantly experiences excellent air quality, with distinct seasonal variations in AQI. The best air quality occurs from mid-summer to mid-autumn, followed by spring, and deteriorates significantly in winter. The primary pollutants identified are O₃, PM₁₀, and PM_2.5, with O₃ peaking in summer, and a combination of PM₁₀, O₃ and PM_2.5 in spring and autumn. Winter and the heating season primarily feature PM₁₀ and PM_2.5. A complex interplay between particulate matter and O₃ is evident. Annually, concentrations of SO₂, NO₂, CO, PM_2.5, and PM₁₀ demonstrate a declining trend, whereas O₃ shows an average increase of 1.5 µg·m^-3·a^-1. Monthly and seasonal concentration fluctuations are significant, with elevated levels of PM₁₀ and PM_2.5 in winter and spring, and the highest O₃ concentrations in June. Moderate or severe pollution episodes predominantly occur from late autumn to winter and spring, driven by local climate conditions and pollution sources. Temperature significantly enhances O₃ concentrations, with high temperatures in early summer and low precipitation serving as primary contributors. External transport and local emissions during the heating season lead to exceedances in PM₁₀ and PM_2.5 standards. Daily O₃ variations display a unimodal pattern, without significant nighttime decreases. Conversely, other pollutants exhibit a bimodal daily pattern, with peaks around 04:00 and 15:00, and elevated levels at 20:00 and 09:00. Exceedance days for PM₁₀, PM_2.5, and O₃ typically coincide with dry conditions or precipitation less than 3 mm. Meteorological factors such as air pressure, temperature, humidity, maximum wind speed, and wind direction show marked variations on these days. The periods with the highest frequency of PM₁₀ exceedances span from March to April, PM_2.5 from December to January of the following year, and O₃ from June to July. For PM₁₀, the exceedance thresholds include temperatures of 10-20 ℃, humidity levels of 20%-50%, air pressure between 850-863 hPa, and maximum wind speeds of 4 m·s^-1 or above, predominantly with NW winds. PM_2.5 exceedances occur at temperatures of -5-3 ℃, humidity of 40%-80%, air pressure between 854-867 hPa, and maximum wind speeds of 2-6 m·s^-1, with SW and S winds. O₃ exceedances are noted at temperatures of 19-26 ℃, humidity of 25%-60%, air pressure between 851-858 hPa, and maximum wind speeds of 3-5 m·s^-1, under S and SW winds.

Improving agricultural eco-efficiency based on resource endowment and development stage is the only means to build a strong agricultural country. Based on the measurement of agricultural eco-efficiency at the city scale in northwest China from 2010 to 2020 using the non-expectation nonradial SE-SBM model, the spatial and temporal differentiation characteristics and influencing factors were analyzed using the indices and methods of difference coefficient, Dagum Gini coefficient, global trend analysis, spatial autocorrelation, and spatial error model. The results indicate the following: (1) The median of agricultural eco-efficiency in northwest China increased from 0.512 to 1.001, with an average annual growth rate of approximately 6.93%; however, the difference in agricultural eco-efficiency between cities showed a narrowing trend. (2) The spatial distribution of agricultural eco-efficiency in northwest China shows hierarchical spatial distribution characteristics. The projection trend line shows a “U-shaped” feature in the north-south direction, whereas the east-west direction gradually shows an “inverted U-shaped” feature in the process of smooth rise from west to east. (3) The results of the spatial error model show that the per workforce arable land area, per capita disposable income of rural residents, and urbanization level positively influence the agricultural eco-efficiency in the northwest China, whereas the agricultural machinery density and fertilizer use intensity negatively influence the agricultural eco-efficiency in the region.

Utilizing meteorological observation data from 20 national meteorological stations in Ningxia, China, spanning from 1961 to 2020, along with socioeconomic statistical data from the past four decades, this study established indicators for drought process events in Ningxia. Subsequently, it developed an interdecadal drought disaster risk assessment model in line with disaster risk assessment theory. The study analyzed the interdecadal variation characteristics and regional differences of drought events and the associated risks to major crops in Ningxia, aiming to identify the factors influencing regional crop interdecadal risk changes. The findings are as follows: (1) The cumulative effect, duration, and intensity indicators of drought events in Ningxia over the past six decades exhibit distinct interdecadal variation characteristics, with notable shifts in trends and mean values in the central northern region and southern mountainous areas around 1980 and 2010, respectively. Additionally, the spatial distribution of high-value areas for drought event and disaster risk indicators demonstrated a pattern of initial increase, followed by a decrease, another increase, and a final decrease over the decades. (2) Since the 1980s, the risk levels of corn drought disasters in Ningxia’s regions, in descending order, are the Yellow River irrigation area, the central arid zone, and the southern mountainous area. Influenced by the continuous expansion of the corn planting area and the growth of the gross domestic product (GDP), the drought risk levels in the central and southern regions have seen an interdecadal increase. Moreover, the increase amplitude in wheat drought disaster risk levels, in descending order, are the central arid zone, the southern mountainous area, and the Yellow River irrigation area. The primary reasons for the heightened drought risk in parts of the central arid zone during the 2010s include the confluence of high disaster risk, wheat planting area, and GDP. (3) Given the future challenges of water scarcity and inadequate irrigation in Ningxia’s central and southern regions, it is advisable to adopt measures such as enhancing artificial rainfall capabilities, developing new crop varieties, and encouraging farmland returning to forestry and grassland or migration to mitigate the disaster risk. These strategies aim to reduce the induced disaster risk, disaster bearing body exposure and pregnant environment vulnerability, thereby lowering the drought disaster risk levels for local corn and wheat production. The insights from this analysis offer a scientific foundation for the region’s strategic agricultural planning, efficient water use, drought mitigation, and disaster response efforts, contributing to the ecological protection and high-quality development initiatives in the Yellow River Basin of Ningxia.

The Saur Mountains, one of the 14 mountain ranges with glaciers in western China, span across China and Kazakhstan. Although the glaciers are relatively small, scientific research is challenged by the division between two political entities. The water resources from the Saur Mountains’ glaciers are crucial for the development of Jeminay County, Xinjiang, China. This study integrates aerial topographic maps, Landsat and Sentinel satellite remote sensing images, existing glacier inventories, Google Earth high-resolution historical images, and other data. Remote sensing observations were verified on-site, and a detailed study on the current status and historical evolution of the Saur Mountains’ glaciers over the past 30 years was conducted. The results indicate that: (1) As of 2022, there are 31 glaciers in the Saur Mountains, covering a total area of 11.47 km². The Muz Taw glacier, the largest in the range, is located in Jeminay County with an area of 2.95 km². The remaining 90% of glaciers are each less than 1 km², but collectively account for 54.55% of the total glacier area. The latitude height and lower altitude limit of glacier distribution in the Saur Mountains are second only to those in the Altay Mountains, making the Saur Mountains a typical high-latitude, low-altitude glacier distribution region in China. (2) Over the past 30 years, the glaciers in the Saur Mountains have experienced increased splitting, area shrinkage, and terminal retreat. The number of glaciers increased from 12 to 31, while the total glacier area decreased by 8.11 km², a retreat rate of 41.42%. During the same period, the length of each glacier retreated by 373 m, with an average annual retreat of 11.30 m. Rising temperatures, reduced glacier albedo, and increased glacier fragmentation are the primary reasons for this retreat. (3) Compared to the other 13 mountain ranges in western China, the Saur Mountains have experienced the largest relative retreat in glacier area over the past half-century. With global warming, the glaciers in the Saur Mountains are likely to completely melt, significantly impacting the sustainable development of Jeminay County, which is already dry and water-poor. Early planning is essential to address the impending water resource crisis in Jeminay County.

The Hexi Corridor, as China’s most densely populated arid region, necessitates a thorough understanding of the evolution of its spatial patterns and the underlying driving mechanisms to reconcile regional development with environmental protection within a three-zone framework. This research employs a suite of quantitative methods, including the spatial transition matrix, landscape pattern index, and optimal parameter geographical detector, to examine the spatiotemporal characteristics and determinants of territorial spatial pattern changes in the Hexi Corridor from 2000 to 2020, focusing on “quantitative change” and “form change”. The findings reveal as follows: (1) The Hexi Corridor’s urban, agricultural, and various ecological spaces have expanded, accompanied by a notable decline of 2758.87 km² in green ecological areas. Despite heightened developmental activities across the three-zone space, ecological conservation efforts have yet to yield significant results. (2) The predominant form of territorial space transition is the internal “desert-green land” dynamics within ecological zones, marked by considerable variability in the extent of cross-transformation across different functionally oriented zones. This cross-transformation of territorial spaces is characterized by increasing fragmentation, dispersion, and complexity in landscape patterns. (3) The territorial spatial pattern evolution in the Hexi Corridor is influenced by multifaceted factors. “Quantitative change” is primarily driven by national policy directives, natural geographic conditions, transportation-related constraints, and socio-economic drivers, whereas “form change” is shaped by natural geography and further modified by transportation and socio-economic factors.

Based on the theory of resilience governance, this paper utilizes panel data from 30 provinces (cities) in China from 2004 to 2021 to construct evaluation indices from the pressure, state, and response dimensions. It objectively measures and systematically portrays the spatial and temporal evolution characteristics of China’s rural ecological resilience, employing the spatial Durbin model to empirically explore the factors influencing rural ecological resilience. The findings indicate that: (1) Although the overall ecological resilience of rural areas nationwide shows an upward trend, it remains at a low level, exhibiting the pattern of main grain marketing areas>main grain producing areas>areas with balanced grain production and marketing. (2) The rural ecological resilience scores display the characteristics of “the curve shifts rightward, the right tail extends, and the width broadens” during the study period. Decomposition of regional disparities using the Dagum Gini coefficient reveals that overall regional differences are not severe and show a persistent trend of narrowing. (3) Analysis of spatial spillover effects indicates that the intensity of environmental regulation significantly and positively influences rural ecological resilience, accompanied by a significant negative spillover effect. Conversely, the urbanization rate significantly and negatively impacts rural ecological resilience, with a significant positive spillover effect. The levels of rural economic growth and government financial support for agriculture also influence rural ecological resilience positively and negatively, respectively, though these effects are not statistically significant. Both factors exhibit significant negative spillover effects in terms of indirect influence.