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 Aral Sea was once the fourth largest lake in the world. Since the 1960s, due to the demands of agricultural irrigation, the regions of the Aral Sea basin have diverted a large amount of water from the Amu Darya and Syr Darya rivers, resulting in the rapid shrinkage of the Aral Sea, the reduction of water levels, and also the deterioration of water quality. By the beginning of the 21^st century, the lake’s surface had shrunk to 1/8 of its original size, and the dried lake bottom had become a salt desert with high salinity. Many biological species decreased and the ecological environment deteriorated, causing an ecological crisis. After the independence of the Central Asian countries, the conflict between the upper and lower parts of the Amu Darya River and Syr Darya River resulted from the lack of water, which seriously affected the relations between these countries. Despite repeated negotiations, the Central Asian countries failed to come up with a common solution to the Aral Sea water crisis. In the absence of regional cooperation, Kazakhstan took independent measures and saved part of the waters of the northern part of Aral Sea. Moreover, Uzbekistan also took a proactive approach to managing the Aral Sea crisis in recent years. The prevailing academic opinion is that the Aral Sea crisis is human-made and that linking it to global climate change is inappropriate. Thus, the Aral Sea crisis, which has been improved because of governance and groundwater recharge, may not disappear as previously predicted and considerable uncertainty remains as to how much it will recover. This study offers a complete discussion of the history, status, and prospects of the Aral Sea crisis to provide a reference for the governance of the arid environment in northwestern China.

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.

Terrestrial evapotranspiration (ET) is an important process of land-atmosphere exchange and an important link in the global water migration and energy transfer system. Identifying the temporal and spatial dynamic characteristics of ET is of great significance in the study of regional water cycle and energy conversion. In this study, we compared the appropriateness of the three different ET products (GLEAM, MOD16, and PML-V2) in China using the flux data of nine tower stations in the country. We used the dataset of ET products between 2003 and 2020 to analyze the temporal and spatial dynamic characteristics of evapotranspiration in China. The results showed the following: (1) The ET products of PML-V2 is the most suitable for China. (2) On the time scale, ET gradually increased during the research period. On the spatial scale, ET exhibited an increasing tendency during 2003—2020 from northwest to southeast of China. (3) According to the Hurst index, the future ET of the whole nation is expected to show the opposite trend compared to the past. This means that ET increased in the past but is expected to decrease in the future. This study analyzed the spatiotemporal dynamic characteristics of ET in China, which could provide a reference for regional water resources utilization and optimal allocation.

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.

The variation in fractional vegetation cover (FVC) is not only closely related to climatic factors but is influenced by human activities. Only a few studies have been conducted on the spatiotemporal characteristics of FVC in China at the provincial scale and quantitative analysis of the impact of climate factors combined with human activities on FVC. Based on the Google Earth Engine platform and Landsat data for 2000—2020, as well as contemporaneous climate and nighttime lighting data, the study is analyzed using the dimidiate pixel method, linear regression analysis, coefficient of variation, partial correlation analysis, and contribution model. The results showed the following: (1) The rate of increasing of FVC in China is 0.32%·a^-1 from 2000 to 2020. The vegetation cover area is dominated by the high cover level, accounting for 38% of the study area, with an overall decreasing trend from southeast to northwest. (2) FVC of the Loess Plateau, Yunnan Province, Tibet Autonomous Region, and western Xinjiang Uygur Autonomous Region showed an increasing trend. Interannual fluctuations in the FVC are more stable in the south than in the north and in the east than in the west. Heilongjiang Province has the highest vegetation cover at 91.7%, while Xinjiang Uygur Autonomous Region has the lowest at 14.4. The rate of variation of FVC in the Ningxia Hui Autonomous Region is 0.98%·a^-1, with significant improvement in FVC. (3) A significant spatial variability was observed in the effects of climatic factors and urbanization on FVC. Temperature and precipitation have negative and positive correlations on FVC in northern China, respectively, and urbanization mainly affects the more economically developed provinces. Temperature is the main contribution factor in the Ningxia Hui Autonomous Region, with an average contribution of 84.3%. Precipitation is the main contribution factor in Taiwan Province, with an average contribution of 71.7%. Moreover, urbanization is the main contribution factor in Shanghai, with an average contribution of 26.5%.

The accurate and dynamic monitoring of the relative content of chlorophyll in corn canopy under drought stress can improve the early warning level of corn drought and help realize precise irrigation. In this study, multispectral images captured by unmanned aerial vehicles (UAVs) were used as data sources, and various vegetation indices with clear physical significance and strong correlation with soil and plant analyzer development (SPAD) values of the chlorophyll relative content in corn canopy were selected. Multiple stepwise regression, support vector machine, the back propagation neural network (BPNN), and a remote sensing monitoring model of the corn canopy SPAD value were established and verified. The optimal estimation model was selected to extract corn canopy SPAD values under various degrees of drought stress in different growth periods. Furthermore, the changes in the corn canopy SPAD value in different growth periods were analyzed to investigate the effects of various degrees of drought stress on the corn canopy SPAD value. The results revealed that the chlorophyll-sensitive vegetation index of corn canopy was different at different growth stages. Furthermore, the inversion models with the best estimation ability varied at different growth stages. Comparing the three modeling methods revealed that the modeling results and verification results of the BPNN model were the best, which indicated that the BPNN model exhibited the best estimation ability and stability performance and can be used as the optimal method for the modeling of the SPAD value of corn canopy based on UAV multispectrum. Furthermore, drought stress can reduce the estimation accuracy of the SPAD value of corn canopy by using a remote sensing monitoring model. This reduction in accuracy affects the seedling stage. Mild drought did not significantly affect the SPAD value of corn canopy, which indicated that corn exhibited a certain adaptability and resistance to drought stress. Therefore, the BPNN model based on the vegetation index can estimate the SPAD value and can be a novel method for SPAD value monitoring based on UAV remote sensing. Furthermore, the model can be used as a reference for the nondestructive monitoring of the summer corn canopy SPAD value and precise field water management under drought stress.

Oases are unique and ecologically sensitive landscape types in arid and semiarid regions and play a crucial role in sustaining human survival and socioeconomic development. However, climatic changes and human activities are causing drastic changes to water resources and the oasis eco-environment. This study analyzes terrestrial water storage changes and assesses the ecological security of oases in the Tarim River Basin of Xinjiang, China. The assessment was performed using the fraction of vegetation cover, a remote sensing ecological index, and net primary productivity (NPP) using the Carnegie-Ames-Stanford approach. The analysis used moderate-resolution imaging spectroradiometer satellite images, GRACE data, land use data, and climatic gridded and observed data from 2002 to 2020. The results indicate the following: (1) Terrestrial water storage in the Tarim River Basin decreased at a rate of 0.27 mm per month. Spatially, terrestrial water storage in the northern and western regions of the Tarim River Basin exhibited a negative trend, whereas that in the southern regions of the Basin showed a positive trend. (2) The total oasis area in the Tarim River Basin expanded by 6.49% (0.42×10⁴ km²) from 2000 to 2020. The ecological security of the basin improved, and the eco-environment ranged from poor to general grade. Approximately 69% of the region’s eco-environment improved, whereas the area of ecological degradation was less than 5%. The normalized difference vegetation index increased from 0.13 in 2000 to 0.16 in 2020, the fraction of vegetation cover increased by 36.79%, and the NPP expanded by 31.55% in the past 20 years. (3) Rising temperatures and precipitation contributed to increased downstream river runoff and spatiotemporal variability of water resources in the Tarim River Basin. However, human activities are a key factor in the expansion of oases.

In the context of rural tourism in Turpan City of Xinjiang, China, this paper explores the influences of tourism involvement, restorative environment perception, and tourist satisfaction on tourists’ intention to revisit, together with the related moderating effect of consumption expectation. The study adopts a structural equation model based on attention recovery theory, in which tourist satisfaction and restorative environment perception as the mediating variables and consumption expectation is the moderating variable. Through data collected through a questionnaire survey, 374 valid samples were obtained. The study found that (1) Tourism involvement had a significant positive impact on restorative environment perception, tourist satisfaction and revisit intention, among which the effect on restorative environment perception is the largest and the effect on tourist satisfaction is the least. (2) Restorative environment perception and tourist satisfaction had multiple chain mediating effects in the structure of “tourism involvement-revisit intention”. (3) The influence of tourism involvement and tourists’ satisfaction on revisiting intention was positively regulated by consumption expectation. The traditional mediation model understates the role of restorative environment perception and many previous studies on this factor have considered it an independent variable. Few studies, in contrast, have considered consumption expectation. To explore the impacts on tourists’ willingness to revisit, the present study innovatively applies restorative environment perception as a mediating variable in the chain mediation effect and applies consumption expectation as a moderating variable, thus providing broader guidance for the governance of scenic locations. The study’s results provide a theoretical basis and a practical reference for the management and development of rural tourism in Turpan City.

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.

Wavelet analysis and other methods were used to analyze the spatiotemporal distribution characteristics of rainstorm in Shanxi Province of China based on the daily precipitation data of 27 meteorological stations in Shanxi Province from 1957 to 2019. Based on the theory of natural disaster, the decision analysis method (AHP) is used to conduct the risk assessment of rainstorm disasters. The following results were obtained: (1) Regarding the timescale, the time of rainstorm has presented periodicity and seasonality. The interannual variation of rainstorm has four-timescale oscillations of 4 years, 9 years, 14-15 years, and 27-28 years. The oscillation period shortened, and the frequency shows an increasing trend. Rainstorm season uneven distribution mostly concentrated in the summer and the probability of the formation of rainstorm disasters was great. The number of cumulative rainstorm days between June and August each year accounted for 85.23% of the total, with July accounting for the largest proportion of 45.18%. (2) Regarding the spatial scale, the rainstorm mostly occurs in the central and southern parts and the mountainous areas with higher altitudes, presenting a decreasing trend from southeast to northwest and obvious regional differences. The heavy rainfall and the amount of rainstorm in the south area show a high probability than the north area with Hengshan as the boundary, among which the annual average rainstorm is more than 65 mm in Yuanqu, Wutaishan, and Yangcheng meteorological stations, and the number of cumulative rainstorm days is over 60 days. (3) The result of the assessment of rainstorm disaster risk shows that the comprehensive risk classification of rainstorm disaster in Shanxi Province shows a decreasing trend from south to north. The northeast of the Yuncheng Basin belongs to the high-risk area, while the northeast and northwest of Shanxi Province belong to the low-risk area. The rest belong to the medium-risk and the sub-high-risk areas.

Determining the spatial distribution characteristics and changes in terrestrial water storage and understanding the reasons behind these terrestrial water storage changes (TWSC) are necessary for the sustainable and comprehensive management of water resources. Based on the data of the TWSC obtained by the gravity recovery and climate experiment satellite retrieval, this study first analyzes the trend and spatiotemporal variation characteristics of the TWSC in China using the Mann-Kendall trend test and empirical orthogonal function (EOF) analysis. Subsequently, 10 influencing factors were selected to comprehensively analyze their relationship with the TWSC by employing the following three methods: geographic detector, Pearson correlation analysis, and random forest. The 10 influencing factors were temperature, precipitation, standardized precipitation evapotranspiration index (SPEI), area proportion of impervious layer, area proportion of water body, normalized difference vegetation index (NDVI), elevation, slope, gross domestic product (GDP), and population. The results showed that areas with a significant increase in terrestrial water storage were mainly distributed in the areas near the Songhua River, Nenjiang River, and Songnen Plain, and the belt of the Qaidam Basin-Yangtze River-southeast coastal region, while areas with a significant decrease in terrestrial water storage were mainly distributed in southwest China and the belt of the Xinjiang-Loess Plateau-North China Plain. From high to low latitudes, the terrestrial water storage showed an alternating change pattern of high-low-high-low. Overall, meteorological factors had the strongest explanatory power for the TWSC, followed by socioeconomic factors and geomorphologic and geologic factors. Lag-correlation analyses showed that the monthly TWSC had a time lag response to precipitation, temperature, SPEI, and NDVI. The time lag of the monthly TWSC for each factor was different in the different regions. The response of TWSC to precipitation and SPEI mainly showed one-month lag, and the response of TWSC to temperature and NDVI mainly showed no lag (i.e. 0-month lag).

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.