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%.

In this study, based on the RClimDex model, we considered daily precipitation data from 126 meteorological stations in Central Asia from 1960 to 2020 to calculate eight extreme precipitation indices in Central Asia. We performed linear regression, Mann-Kendall, correlation, wavelet, and rescaled range analyses to investigate the characteristics of extreme precipitation events in Central Asia. The results revealed that: (1) The frequency and intensity of extreme precipitation events in Central Asia have increased considerably in the last 60 years. The climate trend of the simple precipitation intensity index (SDII) increased at an average of 0.02 mm·d⁻¹·(10a)⁻¹. The change tendency rates of extreme precipitation index heavy precipitation (R95p), maximum daily precipitation (Rx1day), maximum precipitation for five consecutive days (Rx5day), total annual precipitation (PRCPTOT)] were 1.93 mm·(10a)⁻¹, 0.24 mm·(10a)⁻¹, 0.66 mm·(10a)⁻¹, and 0.73 mm·(10a)⁻¹, respectively. The extreme precipitation days index [middle precipitation days (R10), continuous dry days (CDD), continuous wet days (CWD)] also exhibited a slight increase, with the exception of the number of CDD, which exhibited a decreasing trend. The change tendency rates were 0.02 d·(10a)⁻¹, −0.65 d·(10a)⁻¹, and 0.08 d·(10a)⁻¹, respectively. Extreme precipitation exhibit obvious spatial variability and high altitude dependence and occur frequently near highlands and mountains. The extreme precipitation cycle in Central Asia is characterized by a multipeaked spectrum with short-period oscillations of approximately 5 years, medium-period oscillations of 6-9 years, and long-period oscillations of 10-15 years. (2) The extreme precipitation index exhibits an excellent correlation with the total annual precipitation, and CWD contributes most to the total annual precipitation. The Pacific interdecadal oscillation (PDO) and the North Atlantic interdecadal oscillation (AMO) exhibit significant positive correlation with extreme precipitation events. Both PDO and AMO are the primary climate system internal variability modes that affect abrupt changes in extreme precipitation in Central Asia. The results of the R/S analysis indicates that in the future, the indices of PRCPTOT R95p, Rx1day, Rx5day, SDII, and CWD are likely to continue to increase in the future with high persistence, whereas CDD is likely to continue to exhibit a decreasing trend with average persistence. This study can provide a scientific basis for the extreme climate prediction, natural environment protection, disaster prevention, and mitigation in Central Asia.

The southern region of Xinjiang has great potential for land resource utilization and is a crucial reserve supplying cultivated land resources in China. Evaluating soil salinization susceptibility in this area is necessary, as it aids in making informed decisions regarding water and land selection and land zoning management in southern Xinjiang. Sources, including total dissolved solids (TDS) in groundwater, groundwater depth, soil texture, geomorphic type, land-use type, and soil salt content, were collected via field surveys. By employing data-driven evidence weight, the spatial correlations of a single factor contributing to soil salinization were analyzed, followed by a multifactor comprehensive quantitative evaluation of soil salinization using a Logistic regression model. The results showed the following: (1) Shallow groundwater depth, high groundwater TDS, fine-grained soil, alluvial (lacustrine) plain geomorphology, and grassland land-use types showed strong positive spatial correlation with high soil salt content. (2) High soil salinization-prone areas were identified, encompassing the ancient channel in the alluvial plain and ancient lake marsh in the lacustrine plain, covering ~29 km² and accounting for 1.3% of the total area. Additionally, abandoned farmland around the irrigated area was a prone area of soil salinization, covering ~453 km², accounting for 20.5% of the total area. In contrast, the vast desert and water areas around the irrigated area exhibited a low salinization-prone area of ~1726 km², accounting for 78.2% of the total irrigated area. (3) The comprehensive evaluation using the Logistic regression model was validated with field investigation, affirming its accuracy and reliability. This comprehensive quantitative assessment of soil salinization susceptibility provides a scientific basis for soil salinization prevention and control measures and for making informed decisions regarding the selection of reserved cultivated land resources in southern Xinjiang.

Comparing the actual ecological sensitivity surveys with observed interpretation results for verification and correction is of great theoretical and practical importance to improve the accuracy and scientific rigor of ecological sensitivity evaluations. Herein, we focus on evaluating land desertification sensitivity in Shaanxi Province using indices constructed from remote sensing interpretation and climate observation data. The goal is to verify sensitivity evaluation results with the actual results of the Fifth Desertification and Sandification Survey in Shaanxi Province, analyze any differences, and ultimately refine the land desertification sensitivity results. The key findings are as follows: (1) The observation and interpretation results show notable spatial differences in land desertification sensitivity across Shaanxi Province. Particularly, the extremely sensitive areas are concentrated in Yulin, Yan’an, and Weinan cities in Shaanxi Province. (2) Actual survey results from the Fifth Desertification and Sandification Survey reveal that land sandification is primarily distributed in the northern regions of Yulin City along the Great Wall. (3) The difference characteristics show that 92.5% of the actual survey results of land sanding areas and land sanding sensitivity evaluation results exhibit spatial overlap. However, when assessing extremely sensitive land sandification areas and land sandification areas having spatial overlap between them, the overlap drops to 71.8%. (4) Various factors contribute to these discrepancies, including data source, model construction, and indicator assignment errors. (5) After addressing these discrepancies, the revised sensitivity evaluation of land desertification in Shaanxi Province shows that extremely sensitive areas are primarily located in Yulin City, northern Yan’an City, and Dali County in Weinan City, Shaanxi Province. The revised evaluation expands the area of extremely sensitive land desertification by 110.41 km² compared to the observation and interpretation-based sensitivity evaluation of land desertification.

Utilizing Landsat TM/ETM+/OLI imagery and digital elevation model (DEM) data, this study extracted the boundaries of glaciers and glacial lakes in Poiqu Basin, Xigaze City, Xizang Autonomous Region, China from 1990 to 2020 through the ratio threshold method and visual interpretation. The distribution and variation of glaciers and glacial lakes over three decades were analyzed, alongside the exploration of their co-evolution and response to climate change within the basin. The findings revealed: (1) A notable acceleration in glacier shrinkage within the Poiqu Basin over the last decade, with glaciers primarily situated between 5500 m and 6100 m. While the count of large-scale glaciers (≥10 km²) remained constant, small-scale glaciers (≤0.5 km²) exhibited an upward trend. (2) Both the number and area of glacial lakes witnessed a significant increase, with an expansion rate of 74.24%. Predominantly located between 4900 m and 5300 m, the expansion was more pronounced in larger glacial lakes (≥0.07 km²), whereas smaller lakes (≤0.03 km²) also saw a marked rise in numbers. (3) Glacial lakes connected to their parent glaciers emerged as the most significant type contributing to glacial lake expansion, registering a 72.08% increase. (4) The past 30 years have experienced a gradual temperature rise and a minor decline in precipitation. These climatic shifts, particularly the temperature increase and precipitation decrease, have been crucial in glacier retreat, while meltwater from glaciers has facilitated the expansion of glacial lakes. Through examining the distribution, changes, and interrelation of glaciers and glacial lakes in Poiqu Basin, this study aims to provide valuable data support for understanding glacier area dynamics and aiding in the prediction and mitigation of glacial lake outburst floods.

Improving urban ecological resilience and efficiency, and promoting coordinated development between these two systems are the primary objectives of ecological governance in the Yellow River Basin, China. Considering 57 cities in the Yellow River Basin as the research target, this study analyzed the spatial and temporal evolutionary characteristics of urban ecological resilience and efficiency based on the weighted summation method and the slacks-based measurement (SBM) model for the period from 2009 to 2018. Furthermore, a coupled coordination model was employed to analyze the coordinated development of urban ecological resilience and efficiency in cities along the Yellow River Basin. The study results showed the following: (1) During the study period, the urban ecological resilience of cities along the Yellow River Basin had a fluctuating declining trend overall, and these cities faced greater ecological threats and environmental pressures. Xi’an, Zhengzhou, and Jinan City are three provincial capitals that show high urban ecological resilience, whereas Guyuan, Dingxi, Haidong, and Lüliang City showed low urban ecological resilience. (2) The urban ecological efficiency of cities along the Yellow River Basin was generally characterized by a “U”-shaped evolution; in other words, the efficiency first decreased and subsequently increased. Dingxi, Longnan, Qingyang, Ordos, Guyuan, and Luoyang City showed a high level of urban ecological efficiency, while cities with low urban ecological efficiency were mainly located in Shanxi, Henan, and Shandong provinces in the middle and lower reaches of the Yellow River. (3) The coordination relationship between ecological resilience and efficiency is similar to that of the ecological efficiency subsystem, which changed from a continuous decline to a gradual recovery. During the study period, the number of cities with good and moderate coordination between urban ecological resilience and efficiency increased, while the number of cities with poor coordination decreased. Furthermore, while the coordinated development momentum of ecological resilience and efficiency of cities in the basin is apparent, the contradiction between economic development and environmental protection continues to be prominent in the short term. Thus, results of this study contribute to the knowledge base regarding the formulation of ecological policies, improvement of urban ecological resilience, and promotion of urban ecological efficiency in cities in the Yellow River Basin.

Soil salinization can hinder agricultural development. In this study, the degree of regional soil salinization was obtained to provide a theoretical reference for improving agricultural land quality. Using Yinchuan Plain of China as the study area with a grid size of 5 km×5 km, the soil salinity data of 166 sampling points at different depths were obtained. Combined with the Landsat 8 OLI image corresponding to the sampling time, the salt influence factor and salt index were used as input parameters, respectively, and soil salinity at field sampling points was used as output layer parameters. Support vector machine, back propagation neural network, and Bayesian neural network (BNN) were established as soil salinity inversion models. The determination coefficient and root mean square error of the different models were compared to screen the best model. Finally, soil salinization inversion at different depths was performed in the study area. The following results were obtained: (1) In the 0-20 cm soil salinity inversion model, the BNN model based on the influence factor variable group of salinization was the best, with a coefficient of determination (R²) and root mean square error (RMSE) of 0.618 and 2.986, respectively; the best inversion result of 20-40 cm soil salinity was the BNN model based on the salt index variable group (R²=0.651; RMSE=1.947); the comparative analysis of the modeling and verification effects of different variables of the selected algorithms revealed that the BNN model was the best inversion model with a better fitting degree than the other two models, and the introduction of a neural network had certain advantages in the model construction. (2) Non-salinized and mildly salinized soils were the main soil types in Yinchuan Plain. Soil salinization showed a low trend in the south and a high trend in the north. The 20-40 cm soil salinization was found to be lighter than the 0-20 cm soil salinization.

This study attempts to measure the eco-environmental effects of land use transformation in northwest China from 2000 to 2020 based on the perspective of land “production-living-ecological” function. For this, the study employs the eco-environmental quality index and ecological contribution rate model, and comprehensively uses hot-spots analysis tool, Geo-detectors tool, and other methods to discuss the evolution characteristics and differentiation mechanism of eco-environmental quality. The findings of this study show: (1) The “production-living-ecological” space in northwest China shows significant spatial differentiation, indicating an increasing trend of production and living space and a decreasing trend of ecological space. (2) The eco-environmental quality index increased from 0.22720 in 2000 to 0.22724 in 2010 and then decreased to 0.22699 in 2020, although the overall eco-environmental quality remained relatively stable. The change in eco-environmental quality exhibited both improvement and deterioration. The improvement of eco-environmental quality mainly depends on the protection of regional ecological space, while the deterioration of eco-environmental quality is that agricultural production land occupies ecological land in pastoral areas. (3) The eco-environmental quality is spatially characterized by “high in the southeast, second in the northwest, low in the middle”. The cold-spots and hot-spots in the evolution of the eco-environmental quality pattern are mainly concentrated in the southeast and northwest regions and have the same spatial distribution as the population and industry in the area. (4) The proportions of ecological land use, normalized vegetation index, and human active index were the leading factor of spatial differentiation of eco-environmental quality; the interactions between the influencing factors mainly include nonlinear enhancement and bi-factor enhancement. The internal interaction of natural factors and the interaction between natural factors and socio-economic factors affected the spatial differentiation characteristics of eco-environmental quality in northwest China. The results of this study may provide a theoretical basis for the optimization of the national land spatial pattern and ecological environment protection in northwest China.

Drought is one of the most widespread and destructive natural hazards, causing severe impacts on agriculture, energy, society, and ecology. Global warming results in changes in regional precipitation and evapotranspiration patterns, leading to changes in drought characteristics. China is drought prone and is also seriously affected by climate change. Therefore, it is necessary to analyze the characteristics of future meteorological drought response to climate warming in China. In this study, using historical climate simulation data and future projection data from 18 climate models of the Coupled Model Intercomparison Project phase 6 (CMIP6), the 2 ℃ temperature rise scenario was determined by applying a time sampling approach, and the standardized precipitation evapotranspiration index (SPEI) based on the Penman-Monteith method was calculated at a 1-month time scale as the meteorological drought monitoring index. Based on SPEI, drought events were identified using the three-threshold run theory, and four drought-characteristic indicators (drought frequency, average drought duration, average drought intensity, and average drought peak) were extracted for China under the historical reference period and the 2 ℃ temperature rise scenario. Finally, changes in meteorological drought characteristics in China and its seven natural regions were analyzed under the 2 ℃ temperature rise scenario using the future drought-characteristic indicator values minus those of the historical drought-characteristic indicators. The results show clear spatial differentiation patterns in the four drought-characteristic indicators under the 2 ℃ temperature rise scenario. Drought frequency is high in the northwest desert region of China, and is high in the south and low in the north of the eastern monsoon region, while average drought duration, intensity, and peak values are high in the northwest and low in the southeast. From a national perspective, average future values of drought frequency, average drought duration, average drought intensity, and average drought peak are 1.72 times·a^-1, 2.46 months, 1.37, and 1.70 respectively under the 2 ℃ temperature rise scenario, representing increases of 0.17 times·a^-1, 0.27 months, 0.14, and 0.25, respectively, compared with the historical reference period. From a regional perspective, the average values of drought frequency, average drought intensity, and average drought peak increase in all regions, while the average value of average drought duration shows a decrease only in the northeast humid/semi-humid temperate region. The region with the largest increases in values of the four drought-characteristic indicators is the northwest desert region. In summary, based on the results of the multi-model ensemble mean from the 18 CMIP6 models, we predict that more frequent and severe droughts will occur in China, and especially in northwest China, under the 2 ℃ temperature rise scenario. This prediction can serve as a warning in terms of future drought management, and the study can provide a basis for drought prevention and response decision-making in the global warming context.

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.

Water use efficiency (WUE) links the processes of carbon and water cycling in terrestrial ecosystems and is a crucial indicator for understanding the response of vegetated ecosystems to climate change. In this study, the spatial and temporal patterns of vegetation WUE in Xinjiang of China from 1990 to 2020 were systematically analyzed based on the Carnegie-Ames-Stanford approach model inversions of net primary productivity and evapotranspiration (ET). In this method, remote sensing images and reanalysis data products from past 31 years were combined. The results revealed that vegetation WUE in Xinjiang has been decreasing for 31 years and 2003 was a pivotal year with a fluctuating downward trend before the turning point and a subsequent fluctuating upward trend. The spatial pattern of vegetation WUE in Xinjiang has not changed considerably over the past 31 years, with high values concentrated in plains, especially in the oasis and desert-oasis transition zones, and low values concentrated in mountains. The results revealed that the changes in vegetation WUE in Xinjiang can be attributed to the influence of climatic factors such as precipitation, evapotranspiration and water vapor pressure. This study can be used as a reference for screening artificial and natural vegetation structure types with reasonable structure, high water conservation and productivity, and for achieving the sustainable development of vegetation construction in arid and semiarid regions, especially for the ecosystem security and sustainable development of agriculture and animal husbandry in Xinjiang.

This study employs the entropy weight method to determine index weights, utilizing the comprehensive evaluation method and kernel density to assess the spatial and temporal distribution characteristics of pressure-state-response resilience in 14 prefectures within the Xinjiang arid zone of China. In addition, geographic detectors are used to analyze the main influencing factors and factor interactions affecting the economic and ecological resilience of water. The findings reveal the following trends: (1) Stress resilience evaluation indices for Xinjiang prefectures generally decline from 2010 to 2020. Specifically, Kizilsu Kirgiz Autonomous Prefecture experiences a shift from high resilience to moderate resilience. Conversely, state resilience, response resilience, and comprehensive resilience exhibit an increasing trend, reflecting an overall improvement in resilience levels. (2) The spatial distribution of pressure-state-response resilience kernel density across all Xinjiang prefectures from 2010 to 2020 displays a staggered pattern, with higher values concentrated in the southwest compared to the northeast. Analyzing the three dimensions reveals a concentrated distribution of high-pressure resilience kernel density moving from the southwest to the central region. Meanwhile, high state resilience and response resilience kernel densities progress from the northeast to the southwest, displaying a more dispersed distribution. Toward the end of the study period, comprehensive resilience, state resilience, and response resilience kernel densities exhibit a decreasing trend, while spatial differences in pressure resilience kernel densities become more pronounced. (3) The influence of industrial structure, GDP per capita, and ecological self-purification capacity on water resources’ economic and ecological resilience has intensified, while the impact of man-made disasters and other factors has weakened. Interactions among industrial structure, ecological self-cleaning capacity, and retail sales of social consumer goods are more influential than individual factors in shaping system resilience. Notably, the number of nonlinear enhancement relationships in factor pairs surpasses the number of two-factor enhancements.

Based on daily precipitation and geographic and socioeconomic data collected from 50 national and 39 traffic meteorological stations in Qinghai Province of China from January 2012 to December 2021, this study analyzes the spatiotemporal distribution and characteristics of rainfall intensities along the highway. The analytic hierarchy process and natural breakpoint methods were applied to summarize the risk indices of rainstorms and flood disasters. These indices include the disaster-bearing environment, meteorological risk, and disaster prevention and reduction capability. By integrating these factors, a rainstorm and flood disaster risk model for a highway in Qinghai Province was developed. The key findings are as follows: (1) The spatial distribution of rainfall days along highways decreases from southeast to northwest. High-risk areas include the Xining-Tianjun section of National Highway G315 and the Xining-Ebaoling section of National Highway G227. (2) Environmental vulnerability risk gradually decreases from the southeast and northeast to the west. High-risk areas include the Qilian section of National Highway G227 and the Gonghe-Nangqian section of National Highway G214. (3) The risk of disaster body exposure is concentrated in the Minhe-Gonghe section of National Highway G109 and the Xining-Ebaoling section of National Highway G227. (4) Regions with high disaster prevention and reduction capability are mainly Xining City, Haidong City, east Haibei Prefecture, and west Haixi Prefecture. (5) The rainstorm and flood disaster risk model, categorized into five levels (lowest, low, medium, high, and higher risk), offers a practical tool for meteorological disaster risk management and provides a scientific basis for local transportation departments’ disaster prevention and relief efforts.

Glacial runoff is a major component of runoff in the northwest arid zone of China. Understanding the impact of climate change on glacial runoff is crucial, but few studies have been conducted in this field of study in the Bortala River Basin, Xinjiang, China. In this paper, we present the glacier module that was added to the SWAT model and used to simulate monthly runoff in the headwater area of the upper Bortala River Basin. We successfully simulated monthly runoff at the Wenquan hydrological station during the period 1972—2018. Further, we investigated the impact of future climate change scenarios (RCP4.5 and RCP8.5 scenarios for 2020—2050, based on CMIP5 climate data) on glacier runoff. The model was able to accurately simulate changes in the source area’s runoff process. The results showed that: For the whole simulation period, the Nash-Sutcliffe efficiency was 0.82, the percent bias was -3.22%, the ratio of root mean square error to standard deviation of measured value was 0.42, and the coefficient of determination was 0.84, thus allowing the model to be rated as “excellent”. Increasing runoff trends were identified in the simulations of both future climate scenarios, with total runoff increases of 0.31×10⁸ m³·(10a)^-1 and 0.40×10⁸ m³·(10a)^-1 and increases in the percentage of glacial runoff of 4.84% and 9.38%, respectively, when compared with the historical period, in which the glacial runoff percentage was 27.61%. These increases in glacial runoff percentage are the main causes of the increases in runoff volume. Correlation analysis revealed that as the temperature increases, glacier ablation advances and accelerates, and glacier accumulation time decreases, leading to further future shrinking of glacier area. The study provides a basis for making changes to historical hydrological information, exploring future evolutionary trends, and mitigating potential climate change risks 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 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.

Soil moisture is a crucial abiotic factor that limits the growth and development of plants and the ecological construction of sandy areas in semi-arid regions. In this study, continuous observations were performed on soil moisture at depths of 0-100 cm in shifting, semifixed, and fixed sandy land in the Mu Us Sandy Land during the growing seasons from 2008 to 2010 and from 2018 to 2021 (April to October). The dynamic changes in soil moisture and its response to rainfall were systematically analyzed. The results are as follows: (1) Affected by seasonal changes in rainfall, the seasonal variation of soil moisture in shifting, semifixed, and fixed sandy land exhibited a generally “∽”-shaped or double-peaked pattern. The soil moisture in the 10- and 30-cm depth ranges exhibited greater fluctuations, whereas that in the 60- and 100-cm depth ranges showed smaller fluctuations. (2) The dynamic differences in soil moisture during the growing season were significant among the three degrees of fixation. Overall, the shifting sandy land had the best soil moisture status with smooth changes, whereas the fixed sandy land had the worst soil moisture status with the most drastic changes. The semifixed sandy land fell between the two. The soil moisture in the 10-30 cm depth range of the fixed sandy land was better than that of the semifixed and shifting sandy lands, whereas the situation was opposite at depths of 30-100 cm. (3) The pattern of rainfall was the main factor determining the spatiotemporal distribution of soil moisture. As rainfall events occur and the amount of rain increases, the depth of rainwater infiltration gradually increases. However, deep replenishment of soil moisture in fixed sandy land requires higher rainfall amounts and longer periods. During the growing season, small rainfall events were dominant, resulting in greater fluctuations in soil moisture in the surface layers. At the beginning of the growing season, soil moisture below 10 cm was not replenished because of low rainfall and small rainfall events, resulting in poor soil moisture conditions. The shifting and semifixed sandy lands had better soil moisture at depths of 10-30 cm than at depths of 30-100 cm, whereas the opposite was true for the fixed sandy land. These results provide a scientific basis for the restoration of near-natural vegetation and the stable maintenance of sand-fixing vegetation on sandy decertified land in semi-arid regions.

In the contexts of the national strategies for ecological protection and high-quality development in the Yellow River Basin, as well as of the new era of development in western China, it is necessary to alter the ecological conditions and resource endowment of the “three water-related lines” area in northwest China (an area occupying two distinct basins of the Yellow River and the inland rivers) and to innovate a framework and paradigms for coordinated ecological-economic development specific to the area. Based on existing ecological-economics theories, as well as on the developing philosophy of “a benign environment equal to wealth” and the concept of the “human-nature community”, we propose a conceptual ecological-economic framework for the “three water-related lines” area, in which we identify the interactions between subsystems and their mechanisms and suggest four paradigms and four eco-economic hub areas. Further, we propose a layout for modern agriculture and indicate the pathway to coordinated urban and rural development in the four suggested eco-economic hub areas. We conclude that the proposed “three water-related lines” ecological-economic framework represents a theoretical foundation on which to base decisions concerning the layout of socio-economic development and ecological-environmental protection, the construction of ecological-economic hubs, and the overall harmonious ecological-economic development of northwest China.

Ecological civilization is a new concept of human civilization development. Scientific measurements of the correlation between human activities and habitat quality can provide theoretical support for the development of an ecological civilization. As a demonstration area for exploring the harmonious coexistence between humans and nature, national key ecological function zones play an important role in safeguarding the national ecological security pattern and coordinating the relationship between humans and the environment. Based on land use data and population, GDP, and traffic distribution data from 1995 to 2020, we used the InVEST model and the human footprint index method to explore the spatial and temporal distribution characteristics of habitat quality and human activities in national key ecological function zones. We used bivariate local autocorrelation and spatial Durbin model to measure their spatial dependence and effects. The results were as follows: (1) The habitat quality in the study area decreased yearly during the past 25 years, and generally showed a pattern of “decreasing from south to north in the west and staggered distribution in the east”. (2) The intensity and breadth of human activities increased during the past 25 years, and the distribution of high and low values was bound by the “Hu Line”. (3) There was a significant spatial dependence between human activities and habitat quality. The LISA cluster diagram showed that the number of ecological zones in high-high, high-low, and low-high cluster types was 15, 5, and 5, respectively, and there was no low-low cluster. (4) The spatial effects of typical human activities on habitat quality were different under different nature-social backgrounds, but they all had significant spatial spillover effects. Specifically, the total effect of population and GDP distribution in high-high agglomeration areas is positive, and population distribution is the main contributing factor. The spatial spillover effect of population and GDP in the high-low agglomeration area is still positive, but GDP has the highest contribution. The effect of population distribution in low-high agglomeration areas is negative, and GDP is still dominated by the positive spatial spillover effect of high contribution. No matter what kind of agglomeration area, traffic roads are dominated by a negative spatial spillover effect. The development status of the ecological environment and human activities in the national key ecological function areas is evaluated scientifically, the research methods and ideas are enriched, and the correlation discussion on the basis of mathematical analysis provides a policy basis for the construction of ecological civilizations in the study area.

This article chooses the Xiaohaizi Irrigation Area of the Third Division of the Xinjiang Production and Construction Corps, Xinjiang, China, as the research object. In April 2021, 324 soil samples were collected in layers (including 0-20 cm and 20-40 cm) to determine the total salt, eight major ions, and pH values. Descriptive statistics, significance testing, and spatial interpolation were used to analyze the soil salt content and distribution characteristics in the irrigation area. The results reveal that: (1) The varying degrees of salinization affect the soil in the Xiaohaizi Irrigation Area, and the distribution of total salt and various base ions in the soil is extremely uneven in space. The salt concentration generally exhibits a low distribution pattern in the southwest and high distribution characteristic in the northeast. The areas with the most severe soil salinization hazards are the 51^st and 53^rd regiments. (2) The research area is primarily composed of chloride sulfated soil, distributed in main areas of the 51^st and 44^th regiments and some areas of the 50^th and 53^rd regiments. Sulfated soil is distributed at the junction of the 44^th, 50^th, and 51^st regiments, whereas chloride saline soil is distributed in the majority of the 49^th regiment. (3) Moderately saline soil is the most widely distributed in the surface area of the study area, followed by lightly saline soil. Severely saline soil is concentrated in the 51^st regiment, the middle of the 44^th regiment, and the junction between the 50^th and 53^rd regiments. Lightly saline soil is the soil layer with the largest distribution area of 20-40 cm, followed by moderately saline and nonsaline soil. The research results provide theoretical basis and data support for targeted management of soil salinization by clarifying the characteristics, types, and degree of soil salinity within the region and continuously improving the local irrigation and drainage management system in the future.

This study utilizes panel data spanning 2010 to 2021 from seven counties and districts within the Xining section of the Huangshui Basin. Employing the Super-Undesirable SBM model and an extended coupling coordination model, we assess the levels of industrial structure upgrading and ecological efficiency enhancement. Additionally, we evaluate the coupling coordination between these two systems, identifying optimal paths through the coordinate classification method. The findings reveal: (1) Substantial regional variations exist in both industrial structure upgrading and ecological efficiency enhancement across the sample area. The spatial distribution exhibits a pattern of prominence in the center and weakness on the sides. (2) The overall coupling and coordination levels among the counties and districts demonstrate a lack of high coherence, marked by significant regional disparities. Most areas fall into the transitional coupling stage with weak elasticity. (3) The solidification of industrial structure upgrading emerges as the primary impediment to achieving a higher level of coupling coordination in the region. Developing coupling paths should prioritize regions characterized by the “double-low” type, steering clear of the pitfalls associated with “low-level coordination”. In conclusion, this study recommends internal breakthroughs to address resource constraints and external strategies to achieve a balanced distribution within the systems.

Habitat quality is an important basis for human well-being and regional sustainable development and has important practical significance for protecting regional biodiversity, improving regional ecosystem services, and building regional ecological security patterns. Based on the three-phase land use raster data from 2000, 2010, and 2020, this study comprehensively applied the InVEST model, topographic position index, distribution index, geographic detector, and spatial statistical analysis methods to analyze the spatiotemporal evolution characteristics and spatial distribution of habitat quality in the Weihe River Basin in China. The pattern and its topographic gradient effects and influencing factors were comprehensively analyzed. The results are as follows: (1) From 2000 to 2020, the habitat quality index of the Weihe River Basin exhibited a yearly increasing trend. The habitat quality index increased from 0.607 to 0.624, and the growth rate was 2.463%. It showed a polarized distribution pattern in space. The area of low habitat quality and high habitat quality continued to increase, whereas the area of medium and good habitat quality decreased. (2) The spatial distribution pattern of habitat quality in the Weihe River Basin was significantly affected by topographic factors, with a significant topographic gradient effect. It is extensively distributed on the topographic gradient, and its distribution index is the highest, whereas high habitat quality occupies a dominant position on the high topographic gradient. (3) From the perspective of different influencing factors, the land use type is the main reason for the spatial differentiation pattern of habitat quality in the Weihe River Basin. Influencing factors and the interaction of any two factors on the spatial differentiation of habitat quality have a greater impact than the independent effect of a single driving factor. Among them, the interactive determinants of land use type and natural factors such as rainfall, temperature, altitude, and normalized vegetation index are >0.6. The research results can provide scientific theoretical and decision support for the sustainable development of the Weihe River Basin, as well as ecological protection and high-quality development.

Based on the literature in the databases of the Web of Science (SCI) and CNKI, CiteSpace is used to conduct data mining and quantitative analysis of the research papers in farmland abandonment from 1990 to 2021 (data updating time: March 20, 2022). The number of papers and citations, main authors, relevant academic journals, and keywords regarding cultivated land abandonment in China and abroad are systematically sorted out and studied comparatively. The future research direction of cultivated land abandonment in China is then discussed. The following results were obtained: (1) The number of papers regarding cultivated land abandonment has increased in the past 32 years. Scholars in China and abroad pay different attention to the field. There are differences in the development of the research on cultivated land abandonment in China and abroad, and the research focus of each stage is different. (2) Abandoned cultivated land, abandoned land, land use, landscape, carbon sink, and soil degradation are high-frequency keywords of cultivated land abandonment in recent years. (3) The research hot spots of the field in China mainly focus on the causes and influencing factors of cultivated land abandonment, while foreign research is more focused on community diversity and farmland landscape dynamics. (4) The research of Chinese and foreign scholars mostly focus on the causes, mechanism, impacts, and suggestions of farmland abandonment on a small scale, and there are few large-scale studies, including those on remote sensing, big data, network data simulation, and dynamic monitoring, among others. This study suggests that future research should be based on a global perspective. In addition, this study explores the content, causes, evolution mechanism, and impact of cultivated land abandonment systematically. Meanwhile, it should make full use of AI technology to detect and obtain the temporal and spatial dynamics of cultivated land abandonment and try to adopt the agricultural models such as the high-quality development of forest-grass integration to formulate reasonable and effective measures to deal with farmland abandonment.

Groundwater is important for regulating the water cycle and ecosystem in arid areas. Understanding and managing groundwater resources is the key to preventing the reduction of river baseflow, ground subsidence and water quality degradation. Therefore, this study analyzed the groundwater chemical parameters and hydrogen-oxygen stable isotope characteristics of the Ebinur Lake Basin, Xinjiang, China, and explored the sources of groundwater recharge, dynamic changes of water chemical components in different regions by combining linear regression, two-terminal mixed model and GIS spatial analysis. The results showed that: (1) Different circulation processes of groundwater existed in different areas of the Ebinur Lake Basin, with the largest of hydrogen and oxygen isotopes (δ²H and δ¹⁸O) in the middle and lower reaches of the Bortala and Jing Rivers, followed by the area around Lake Ebinur Basin, and the smallest in the upper Bortala River area. (2) Deuterium excess parameter (d-excess) parameter and hydrochemical composition of groundwater reflected different groundwater recharge mechanisms and influencing factors. Groundwater in the upper Bortala River area was mainly recharged by glacial snow melt water. The main sources of groundwater in the middle and lower reaches of the Bortala and Jing Rivers were surface water and precipitation, which were also greatly influenced by the nature of rock formations, farmland development and irrigation measures. Groundwater around Lake Ebinur Basin mainly came from snow and ice melt and precipitation. The middle and lower reaches and groundwater in the river and lake confluence areas are the key areas for pollution prevention and control and management. (3) Different hydraulic connections existed in underground aquifers. The electrical conductance (EC) of flow system I ranged from 210.00 μS·cm^-1 to 2500.00 μS·cm^-1, and the d-excess ranged from 6.47‰ to 9.70‰. The EC of flow system II ranged from 141.60 μS·cm^-1 to 5260.00 μS·cm^-1, and the d-excess ranged from 9.61‰ to 17.45‰. In conclusion, this study investigated the driving mechanisms of hydrogen and oxygen isotopes and water chemistry in groundwater in the Lake Ebinur Basin, which provided some theoretical reference for the rational use and scientific development of groundwater resources in the basin.

The southern edge of the Taklimakan Desert of China belongs to the desert-oasis ecological transition zone, and the temporal and spatial changes in land surface properties are significant. The underlying surface properties and hydrothermal characteristics are unique. Therefore, it is of great significance to investigate the characteristics of micrometeorological elements in this region for future climate change. Based on meteorological element data measured through the land-atmosphere interaction observatory on the northern side of the Tibetan Plateau in 2022, the wind, temperature, and humidity profile structure, radiation flux, and energy exchange characteristics of the ecological transition zone on the southern edge of the Taklimakan Desert were analyzed. The results show the following: (1) The wind speed, temperature, and specific humidity of the southern margin of the Taklimakan Desert change significantly with increasing altitude, and the temperature and specific humidity profiles of the inversion and humidity inversions occur in the temperature and specific humidity profiles, the heights of the inversion layer and the inversion humidity layer reach 30 m, the maximum average wind speed occurs in spring at 6.23 m·s⁻¹, and the maximum average temperature and specific humidity are 28.93 ℃ and 6.36 g·kg⁻¹ in summer, respectively. (2) The surface radiation balance of the four seasons is mainly positive, and there are differences in the peak size and occurrence time of each radiation component, among which downward shortwave radiation is affected by sand and dust weather, which is manifested in spring>autumn>summer>winter. The surface albedo was negatively correlated with the solar altitude angle and soil moisture, with an annual average of 0.326, with the highest in December (0.366) and the lowest in August (0.297). (3) Sensible heat, soil heat flux, and net radiation changed significantly in the four seasons; the latent heat changed steadily, fluctuating up and down with 0 W·m⁻² as the center, and the energy consumption was dominated by sensible heat. The energy closure rates of the four seasons were 76%, 82%, 53%, and 48%, respectively, which were manifested in summer>spring>autumn>winter. (4) The effective energy varies significantly in the four seasons, with positive values during the day and heat sources on the ground, indicating that the ground transports heat to the atmosphere, whereas, at night, it is the opposite, exhibiting spring>summer>autumn>winter. These findings can provide a scientific basis for the parameterization of land surface processes in the southern edge of the Taklimakan Desert in the future and improve the understanding of land surface processes in this area.

In recent years, the recognition of the global disaster risk reduction (DRR) strategy on high-frequency and low loss extensive disaster risk and the query on the effectiveness of continuously giving priority to the management and control of low-frequency and high loss intensive disaster risk at a local scale have caused disputes on the theory and practice of disaster risk management (DRM) among academic and emergency management stakeholders. Therefore, this study conducted an empirical study on the agricultural risk assessment of meteorological disasters based on the hybrid loss exceedance curve (HLEC) in Shanxi Province, China. This paper identifies the characteristics of extensive and intensive meteorological disasters in Shanxi Province, demonstrating the comprehensiveness and accuracy of the HLEC replacing the retrospective loss exceedance curve and the prospective loss exceedance curve in measuring average annual agricultural economic loss (AAL). The following results are obtained: (1) The AAL of meteorological disasters in Shanxi Province is 2.22 billion Yuan, and the occurrence loss exceedance probability (OEP) for a single time exceeds 15 million Yuan, that is, the reserves of “meteorological disaster prevention and emergency management expenditure” for the whole year and the damaged counties and districts are not less than 2.22 billion Yuan and 15 million Yuan, respectively. (2) The HLEC model is effective in disaster risk assessment at the provincial level, and its applicability and efficiency at the prefecture-level city and county level are close to 60%. (3) More than 97% of the historical meteorological disasters in Shanxi Province are extensive disasters with high-frequency and low impact, resulting in more than 95% of the agricultural disaster areas and agricultural economic losses. The corresponding AAL and OEP account for more than 85%. The risk of extensive disasters is a real and cumulative risk in the province. Moreover, its consequences, such as poverty, welfare reduction, infectious diseases, and health deterioration, should attract the attention of DRR and DRM. Therefore, this study preliminarily confirmed the necessity of local or grassroots level to reduce the extensive risk (why to manage it), discussed the reasons for the lack of traditional emergency management and control of the extensive risk (dare not manage, cannot manage, and do not want to manage), and proposed the significance of timely response to the extensive risk and avoiding its cumulative socioeconomic impact (such as permanent poverty alleviation, high-quality urbanization, sustainable development). It is intended to provide the right direction for governments at all levels and emergency management departments to formulate DRR and DRM strategies and provide decision-making reference to improve the disaster resilience of cities, communities, and families.

China’s research and practice bases is a major source of research tourism in China. Comprehensive use of geospatial analysis methods to systematically explore the spatial distribution and influencing factors of China’s research and practice bases at different spatial scales show the following results: (1) On the national scale, the research and practice bases demonstrate a spatial distribution trend from “northeast to southwest”, and different types of research and practice bases demonstrate substantial agglomeration characteristics, forming a high-density area with the Beijing-Tianjin-Hebei region and the Yangtze River Delta as the core. (2) On the regional scale, the research and practice bases demonstrate a pattern of “more in the east and west, less in the middle” among the three major zones and a decreasing distribution pattern from the coastal areas to the middle and lower reaches of the Yangtze River, and then to the northwest inland areas among the eight regions. (3) On the provincial scale, the distribution of research and practice bases has substantial spatial autocorrelation characteristics. The hot spots are distributed in an “L-shaped” belt pattern, whereas the cold spots are distributed in a “V-shaped” piece pattern. (4) On the city scale, the research and practice bases are concentrated in type I and II metropolitan areas, and the hot spots are concentrated in the Yangtze River Delta and Beijing-Tianjin-Hebei metropolitan area. (5) Regional economic development level, potential tourist market, tourism industry scale, and policy support all have a considerable impact on the spatial distribution of research and practice bases, with the economic development level having the greatest impact, and the influence intensity of each factor exhibiting some spatial heterogeneity. The research results have considerable references for optimizing the spatial layout of research and practice bases in China and promoting the high-quality development of research tourism destinations.

Ecosystem services are closely linked to sustainable human development. Studying the supply and demand characteristics of regional ecosystem services and comprehending their spatial matching status are essential prerequisites for achieving the efficient allocation of ecological resources and promoting regional ecological security. The water production, carbon sequestration, and food services of the Shule River Basin in the Gansu Province of China were all examined on the basis of multisource data and with the assistance of the InVEST model as well as the ArcGIS and GeoDA software. The following are the results of this study: (1) There are discrepancies between different regions and ecosystem services; except for water production services, the supply of other ecosystem services in the Shule River Basin is more than the demand. (2) The supply-demand ratio of comprehensive services in the Shule River Basin is 0.063, and the supply-demand ratios of different ecosystem services are carbon sequestration services (0.1854)>food services (0.0078)>water production services (-0.0043). (3) Water production and carbon sequestration service spaces are mainly based on low-high-type and high-low-type spatial dislocation, respectively, whereas food service spaces are primarily based on low-low-type spatial matching, among which the spatial mismatch of water production services is the most severe.

In regions with scarce data, remote sensing precipitation products provide crucial data for the development of the hydrometeorological disaster mechanism and early warning studies. However, the performance of various remote sensing precipitation products exhibits regional heterogeneity. Comprehensively evaluating the performance of remote sensing precipitation products is critical for their use in hydrometeorological-related research and application. Based on this assumption, the study investigated the source region of the Yellow River of China by using the observed precipitation data (CMA) from 1983 to 2018 to drive and calibrate the ABCD hydrological model. Furthermore, the standardized runoff index (SRI) was used to evaluate the simulation performance of three sets of typical remote sensing precipitation products (PERSIANN-CDR, CHIRPS v2.0, MSWEP v2.0) on hydrological drought. Furthermore, hydrological drought events were identified by using run theory, and the potency of remote sensing precipitation to capture hydrological drought characteristics was investigated. The results revealed that: (1) The three precipitation products can accurately capture the temporal and spatial distribution pattern of CMA’s multiyear mean value. Furthermore, the CHIRPS product (Nash-Sutcliffe efficiency coefficient, NSE=0.72) outperformed other two products in term of hydrological simulation. (2) The SRI values (SRI1, SRI3, SRI6, and SRI12) of the four scales simulated by CMA and three sets of remote sensing precipitation products revealed a significant increase trend (P<0.01), which indicated that the river runoff in the source region increased in the last 36 years, and the hydrological drought slowed down. However, the SRI values of the three sets of remote sensing precipitation products were overestimated. This result revealed that the deviation correction of precipitation products in the source area of the Yellow River is necessary. In terms of basic statistical indicators, the SRI calculated by the MSWEP product was the most consistent with CMA and was the best. However, on an annual scale (SRI12), the PERSIANN product achieved the best performance. (3) Three sets of remote sensing precipitation products overestimated the drought duration and intensity of SRI1 and SRI3; the MSWEP product achieved the best simulation performance for SRI6; and the PERSIANN product has the best simulation performance for SRI12. The results of this study can provide scientific decision support for the selection of precipitation product data for studying hydrological drought in the source region of the Yellow River.

The monitoring of human urban and rural construction activities in the Inner Mongolia Plateau, China and the scientific assessment of their impact on regional ecosystem productivity have important scientific and practical significance for the construction of the national northern ecological barrier. Based on satellite images, land use data, meteorological observation data, and auxiliary information, this study assessed the impacts of the expansion and speed of urban and rural construction on the ecosystem productivity in the Inner Mongolia Plateau from 2000 to 2020 using dynamic attitude analysis and neighborhood substitution methods. The results show that: (1) The area of urban and rural construction land (URCL) in 2020 was 18206.49 km², accounting for 1.46% of the total area of the Inner Mongolia Plateau. (2) In the past 20 years, the area of URCL expansion was 7462.99 km², of which 59.76% came from the expansion of industrial land. URCL mainly occupied natural and cultivated ecosystems, in which urban land and rural residential land mostly occupied cultivated ecosystems, while industrial land mainly occupied grassland and desert ecosystems. (3) From 2000 to 2020, the total loss of net primary productivity (NPP) caused by human urban and rural construction activities reached 143.51×10⁴ tC in the Inner Mongolia Plateau. Industrial land activity is the main cause of NPP loss of natural ecosystems and increased from 60.72% in 2000—2010 to 73.91% in 2010—2020. Compared to 2000—2010, the NPP loss was alleviated in the cropland ecosystem but intensified in the grassland ecosystem in 2010—2020. (4) The NPP loss of Mu Us Sandy Land, Hulunbuir Sandy Land, Otindag Sandy Land, and Horqin Sandy Land were mainly caused by industrial land expansion. However, due to the impact of urban greening, the NPP of the ecosystem around the city increased slightly. The urban population, gross domestic product (GDP), and related policies led to the continuous expansion of URCL, which has a certain impact on ecosystem NPP. This study has an important reference value for urban and rural construction and ecological civilization construction, and ecological protection in the Inner Mongolia Plateau.

An ecological security pattern can promote regional ecological development and be highly beneficial for preserving ecologically fragile areas. Urumqi of Xinjiang, China, is a typical oasis city in an arid area. In an era of rapid development of industrialization and urbanization, because of the topographical and geological limitations and uneven spatial distribution of water and soil resources, the trade-off between regional agricultural development, ecological protection, and urbanization development is a concern. Therefore, the development of an effective method for the analysis of the temporal and spatial evolution of ecological security patterns is critical. In this study, the principle of “ecological source identification-resistance surface construction-ecological corridor extraction” was used. Based on these factors and the evaluation of the importance of ecosystem services and ecological sensitivity, the land use data of Urumqi in 2000, 2010, and 2020 were used to identify the ecological source. Next, the ecological corridors were extracted using the minimum cumulative resistance model. Furthermore, ecological pinch points were determined using the circuit theory. Finally, the resistance threshold method was used to develop the ecological security space and define the high alert restoration area. The results revealed the following: (1) In recent 20 years, the area of ecological source areas has increased considerably, and its area of 445.63 km² was more than 3.19% of the study area. The newly increased ecological source areas were distributed in Urumqi County and Dabancheng District in the southwest and east of the study area. (2) In the three periods, 27, 30, and 40 ecological corridors with a total length of 870.42 km, 1115.83 km, and 1277.12 km, respectively, were identified. (3) The spatial distribution of the five levels of ecological security in the study area was uneven. The northeast, southwest, and periphery regions of the study area had a concentration of high ecological security spaces, whereas the middle region had a moderate concentration. The two spatial distributions revealed a continuous expansion trend. The medium ecological security space showed zonal distribution from northwest to southeast in the study area, whereas low ecological security space was concentrated in the north and sparse in the south. The spatial distribution of the three space types exhibited a decreasing trend. (4) Seven ecological pinch points were observed in the study area. The areas of high alert repaired were 188.17 km². The maximum accumulated current was reduced from 4.75 A to 3.82 A after restoration. The results can effectively coordinate the contradictory relationship between economic development and ecological protection in the study area. The results of the study can provide a scientific foundation and support the territory development plan for optimizing ecological civilization construction.

Geohazards such as landslides, rock fall, debris flow, and ground collapse occur frequently in the Ili Valley, Xinjiang, China, and there are various influencing factors for the formation of these geohazards. Based on the database of geohazards in the Ili Valley, this paper uses statistical analysis methods such as the frequency ratio and receiver operating characteristic curve to study the distribution characteristics and main controlling factors of geohazards in the Ili Valley. The results show the following: (1) The overall development degree of geohazards in the Ili Valley is greater in the east than in the west, and they are distributed in the middle and low mountains with 500-3500-m elevation. In terms of time of occurrence, they are mainly clustered in the spring and summer snowmelt and rainfall seasons. (2) The development of geohazards is affected by stratigraphic lithology, geological structure, topography and geomorphology, precipitation, and other factors. However, the main controlling factors for different types of geohazards are different. Landslides are most obviously affected by stratigraphic lithology, elevation, slope, and annual precipitation, while rock falls are mainly controlled by slope, elevation, and distance from faults. Ground collapses are obviously affected by elevation, distance from fault, and precipitation, and are basically induced by underground mining activities. The distance and elevation from faults are the main controlling factors for the development of debris flows.

Timely and accurate understanding of crop distribution within irrigation areas is essential for the efficient allocation of irrigation water resources and precise field management. This study focuses on the Qingtongxia irrigation area in Ningxia, China, employing multitemporal Sentinel-2 satellite data to analyze early characteristics of rice and maize. Key “flooding” and “vegetation” signals are extracted, and a time-series dataset comprising the modified normalized difference water index (MNDWI) and normalized vegetation index (NDVI) is constructed. By analyzing sample thresholds for these key features, a decision tree model for the early planting distribution of rice and maize is established, facilitating the extraction of the spatial distribution for rice and maize planting in the Qingtongxia irrigation area in 2022. The results reveal the following: (1) During the latter half of the maize and rice seedling stages, from May 15 to 31, flooding and vegetation signals are crucial for differentiating between the two crops. (2) Based on the early crop phenological characteristics, the mapping accuracy of rice and corn images obtained from May 16 to May 31 was higher than 90%, with user accuracy exceeding 91% and overall accuracy exceeding 90%. The Kappa coefficient was higher than 0.88, significantly higher than the classification accuracy of the random forest classification method during the same period. (3) The proposed method demonstrates strong applicability in the early extraction of rice and maize planting distribution, requiring fewer ground samples for extension across both spatial and temporal scales. Therefore, this method provides significant support for early investigations of rice and maize planting distribution in the Qingtongxia irrigation area.

The Gurbantunggut Desert (GGD), the largest fixed and semi-fixed desert in northwestern China, is the region most obviously affected by westerly circulation in China. Holocene environmental evolution and its response to global climate change have important scientific significance in understanding the modern surface process and future environmental evolution trends in the GGD. The previously studies on the Holocene environmental evolution of the GGD and its surrounding areas are controversial: some studies have concluded that optimal periods of precipitation/humidity happened in the Middle-Late Holocene, while others concluded that the optimal periods occurred in the Middle Holocene and that the genetic mechanism is in dispute between the monsoon intruding inland and the overall control by the westerly. This study reconstructs the Holocene climate/humidity variation using dimensionality reduction and integrated analysis based on the multiarchive records published in the study area, and synthesizes the Holocene aeolian sand activity history by sorting out the chronological distribution of the regional aeolian sedimentary stratigraphy. The coupling relationship between regional aeolian activity and humidity change is also examined. The results show that the early Middle Holocene (12-6 ka) in this area was arid, with considerable aeolian activity; the humidity gradually increased and the aeolian activity gradually weakened from the Middle to the Late Holocene. According to the comparative analysis on the regional and hemispheric scales, it is concluded that the environmental evolution process in the GGD is mainly controlled by the westerly circulation.

In this study, based on the multidimensional perspective of economy, society, and ecology, the spatiotemporal change characteristics of urban resilience of districts and counties in Inner Mongolia, China, from 2000 to 2019 were investigated by using the entropy weight method, comprehensive index method, and global Moran’s I index. Furthermore, the geographical weighted regression model was used to investigate the influence of human activity intensity on the urban resilience of districts and counties. The results revealed that: (1) The level of urban resilience of districts and counties in Inner Mongolia increased from 2000 to 2019 because of the continuous improvement of the social economic development level. (2) The spatial distribution of the level of urban resilience of districts and counties in Inner Mongolia differed, and the level of urban resilience of districts and counties in the eastern and central regions was considerably higher than that of districts and counties in other leagues and cities. (3) The change in the human activity intensity of population density, construction land, and night-time light data significantly affected the change in the level of urban resilience of districts and counties in Inner Mongolia. This study provides a reference for the sustainable development of various districts and counties in Inner Mongolia and exhibits practical and theoretical significance for enriching research in urban resilience in China.

This study focuses on the barchan dunes situated in the hinterland of the Taklamakan Desert in Xinjiang, China. Our observations tracked the morphological evolution of a specific dune as it transforms from a barchan dune to an irregular dune and back to a barchan dune under the influence of sandstorms. By examining the particle size of surface sand across different dune morphologies, we investigate the impact of sandstorms on the particle size distribution in barchan dunes. Our findings reveal the following: (1) The particle size of surface sand along the central axis of the windward slope remains constant before and after the deformation and recovery of the barchan dune. However, there is a gradual increase in coarseness from the dune’s base to its summit. This suggests that, under similar wind direction and force conditions, sandstorms exert minimal influence on the particle size distribution pattern on the windward slope of barchan dunes with comparable morphology. (2) Both the central axis and sand ridges of the barchan dune predominantly feature extremely fine and fine sand. The average content of extremely fine sand and fine sand is 83.07% and 82.81% on the central axis of the windward slope and the leeward slope, and 84.42% and 91.20% on the left and right sand ridges, respectively. Moreover, after the sandstorm, the surface sand of the recovered barchan dune exhibits well-sorted and consistent characteristics, with an overall finer particle size, indicating a significant influence of the sandstorm on the particle size characteristics of the surface sand. These results offer valuable insights into the spatial distribution pattern of surface sand in barchan dunes under the impact of sandstorms.

The Shule River Basin is located in the northwest inland region of China and is a key node of the Belt and Road Initiative. In recent years, with the increasing intensity of global changes and economic and social activities, problems, such as the rapid expansion of construction land and desertification have affected the sustainable development of regional ecology and economic society. The Shule River Basin is located at the center of the northern sand prevention belt of China, and an evaluation of its wind prevention and sand fixation value is of great ecological significance for building a regional ecological security pattern and ensuring sustainable development of the basin. On the basis of the revised wind erosion equation model, the value of wind prevention and sand fixation in the Shule River Basin from 2008 to 2018 was evaluated. The results are as follows: (1) The total amount of wind prevention and sand fixation in the Shule River Basin from 2008 to 2018 was 43.927×10⁴ to 129.530×10⁴ t·km⁻², with an increasing trend in wind prevention and sand fixation capacity. (2) The value of wind prevention and sand fixation in the Shule River Basin rapidly increased from 2008 to 2018, with an annual average value ranging from high to low to reduce the value of land loss (99.46%), maintain the value of soil fertility (0.47%), maintain the value of soil organic matter (0.04%), and reduce the value of economic loss of transportation (0.03%). (3) The function of wind prevention and sand fixation in river basins is closely related to land use. Among them, the areas with stronger windproof and sand-fixing capability are primarily distributed in grassland, cropland, and other areas with higher vegetation cover; the low-value areas are primarily distributed in unused land of the land use type of the river basin. (4) Natural indicator factors have a greater impact on the value of wind and sand fixation functions in river basins than social factors. These findings can provide a basis for determining the subject and object of ecological compensation and compensation standards in the Shule River Basin.

The reduction in gross primary productivity (GPP) resulting from drought can significantly impact the terrestrial carbon sink. Based on the standard precipitation evapotranspiration index (SPEI) calculated from the monthly meteorological data of 618 sites from the entire country and two publicly available GPP datasets (i.e., EC-LUE GPP and GLASS GPP, respectively), changes in the GPP affected on different scales by different degrees of drought in a typical drought year during 1982—2017 (2001 and 2011) in China were analyzed systematically. The results revealed that: (1) Based on the five selected indicators of the SPEI, the typical drought years during 1982—2017 were selected as 2001 and 2011. (2) On the annual and seasonal scales, the drought-affected GPP in 2001 was observed mainly in north China, northeast China, and the northern part of middle east region of China, as well as in the southeast and middle east of the southwest region of China in 2011. On the monthly scale, the GPP in May 2001 was the most severely affected by drought, mainly concentrated in most of north China and northeast China; however, in January 2011, the GPP was mainly concentrated in majority of the middle east region of China. (3) Irrespective of the annual, seasonal, or monthly scale, with the increase in the degree of drought, the decline rate of GPP was higher, and the impact of extreme drought was the highest. For example, on the seasonal scale, the decline in the GPP during extreme drought in the summer of 2001 was 19.96% (EC-LUE GPP) and 15.57% (GLASS GPP), and the decline in the GPP during extreme drought in the spring of 2011 was 14.32% (EC-LUE GPP) and 8.75% (GLASS GPP). The results revealed can further deepen the understanding of the effect of different grades of drought on GPP, which is key for understanding the exchange of carbon between the land and atmosphere under drought conditions.

Predicting and analyzing the availability of green space resources for the elderly are crucial for improving their quality of life and addressing the challenges of an aging society. Taking Xining City, the area with the largest elderly population in Qinghai Province, as the study area, this study identifies and predicts the spatial distribution of older people based on mobile phone location data with age identification information. The Gaussian-based two-step floating catchment area (G2SFCA) method was then employed to study and predict the accessibility of parks and green spaces for the elderly. The following results were observed: (1) The elderly population increasing rate exhibited a circular distribution, displaying a low rate in the central city and outer suburbs and a high rate in the inner suburbs. (2) The overall spatial distribution pattern of accessibility of parks and green spaces for the elderly did not change significantly over the 10-year forecast period, but the general accessibility level declined. Under the condition of walking for 15 min, the population covered by relatively high and high grades of accessibility decreased from 17.58% to 6.70%. Moreover, under the condition of public transportation for 30 min, the population covered by relatively high and high grades of accessibility decreased from 26.41% to 9.28%. (3) It was found that the relative variability of accessibility of parks and green spaces for the elderly is significant from 2018 to 2028, with approximately 87% of the parks and green spaces experiencing a reduction of >70% in accessibility under both walking and public transportation conditions for 30 min. This study provides valuable insights for future urban park and green space planning, particularly in response to the needs of an aging population.

The Huangshui River Basin is an important part of the Huangshui Valley. Additionally, collaborative environmental factors that predict the spatial distribution of soil nutrients are particularly important for managing soil nutrients. Moreover, less attention is paid to the effect of model parameters on the results obtained from soil nutrient inversion studies. In this study, the Huangshui River Basin in Qinghai Province (China) was selected as the study area, and 28 factors, including elevation, aspect, slope, plane curvature, section curvature, relief degree of land surface, topographic wetness index, soil pH, and spectral reflectance, were selected. In addition, these factors were combined with the Bayesian optimization algorithm (BOA) to construct artificial neural network (ANN), support vector machine (SVM), and extreme gradient boosting (XGBoost) machine learning models for predicting the spatial distribution of four soil nutrients in farmlands: soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), and available potassium (AK), respectively. Further, the prediction accuracy of these three models was evaluated based on the model coefficient of determination (R²), root-mean-square error (RMSE), and relative percent deviation (RPD). The results revealed that: (1) All four soil nutrients exhibited a moderate degree of variability, with TN showing the highest variability of 69.481%. The XGBoost model based on the Bayesian optimized hyperparameter combination was better than other models in predicting the TN content (R², RMSE, and RPD were 0.893, 0.359, and 2.470, respectively). The R² values of the XGBoost model validation set for estimating the SOM, AK, and AP contents were 0.801, 0.509, and 0.442, respectively, and the corresponding RPD values were 2.152, 1.210, and 1.274, respectively. Moreover, this model exhibited a better prediction capability. (2) The comparison of the number of optimizations and errors of the three models revealed that the BOA-XGBoost model exhibited minimum number of parameter optimizations, higher efficiency, and better robustness. The ANN and SVM models demonstrated different prediction accuracies for different nutrients; additionally, the SVM model predicted the SOM content with high accuracy (RPD=1.580), while the ANN model predicted TN efficiently (RPD=2.460). Based on Landsat 8 remote sensing images, the XGBoost inversion model developed by combining 28 factors of the Huangshui River Basin was found to be more suitable for application in soil nutrient inversion research; furthermore, it can more accurately describe the spatial distribution pattern of the soil nutrient inversion in the Huangshui River Basin, better ensure precise agriculture fertilization, improve the fertilizer utilization rate and crop yield, and provide a reference for precise agriculture fertilization in the Huangshui River Basin.