Dust storms are a major weather hazard in arid and semiarid regions, causing significant harm to human health and welfare and productivity. This study examined a severe dust storm event in northwest China using surface observation data from the National Meteorological Information Center, MODIS satellite data, and urban air quality data from March 18 to 23, 2023. The study combined the HYSPLIT backward trajectory model and the WRF-Chem atmospheric chemistry model to examine the dust source and impact range, focusing on the mechanisms behind the severe dust storm at Zhangye, a central site along the transport path. The main findings were that the dust storm affected much of northern China in phases, with dust emissions occurring in distinct regions on March 19, 20, and 21, each with unique transport ranges and impact areas. Dust in the Hexi Corridor primarily originated from Jiuquan. WRF-Chem simulations showed that the highest PM₁₀ concentration occurred at Zhangye Station, reaching 6966.7 μg·m^-3 The dust event in Zhangye originated from upstream dust transport and local dust emission. First, near-surface intense northwesterly winds over 16 m·s^-1 near Jiuquan, under unstable atmospheric conditions, triggered upward movement, which lifted dust particles to high altitudes and transported them downstream, where they settled around 3-4 km above Zhangye. Second, before the arrival of upstream dust, Zhangye’s lower atmosphere exhibited instability, and the convergence of strong surface winds and wind direction triggered local dust uplift, further intensifying the dust storm.

Based on lidar observations combined with ERA5 reanalysis data, HYSPLIT trajectory model, environmental monitoring data and meteorological observations, we studied the vertical distribution of optical properties of dust aerosols in the Taklamakan hinterland in spring 2021. The formation, development processes, potential sources and transport pathways of large-scale aeolian dust weather in Tarim Basin were analyzed and discussed. The results showed that two strong dust processes occurred in the desert hinterland from 20:00 on April 19 to 14:00 on April 21 and from 14:00 on April 22 to 18:00 on April 26. Large amount of suspended dust particles were detected at the height of 0-5 km over the atmosphere. The extinction coefficient was above 0.3 km^-1, within 2 km of the surface, and the depolarization ratio was more than 0.6, which was much higher than the threshold value of 0.31. These two dust events were both affected by the low trough in the upper air and the ground cold air. The first dust weather event was mainly caused by cold air crossing over the Tianshan Mountains. Blowing dust weather occurred in Kashgar, Hotan and Aksu. The PM₁₀ concentration in Hotan reached a peak of 3763 µg·m^-3on April 22. And the dust source was from the western of the basin. The second dust weather event primarily resulted from cold air entering the basin from the northeast. The PM₁₀ concentration in Korla and Aksu cities increased sharply to 1200 µg·m^-3 from 25 to 26, April. Dust particles originated from the local sand, northeastern and northern of the basin. During the second dust weather process, dust particles were blown up and transported higher than before, and the air pollution lasts longer and is more widespread. The windblown dust can suspend above 4 km height during dust processes. The particles transport height was significantly higher than high-frequency areas of dust weather in Hotan and Minfeng.

The northern slope of the Kunlun Mountains has a complex terrain and unique diurnal variation of precipitation, which lead to low accuracy in refined precipitation forecasting. The ECMWF model has world-leading forecast performance, but its ability to predict the diurnal variation in precipitation in complex terrain is still unclear. This study used precipitation data from automatic meteorological stations during the summer of the 2020-2023 season to verify and evaluate the ECMWF model’s forecast performance for the diurnal variation of summer precipitation at various regions on the northern slope of the Kunlun Mountains. The results show the following. (1) The 24 h cumulative precipitation forecast performance of the ECMWF model initialized at 20:00 was better than that which initialized at 08:00; the model’s precipitation forecast capability for areas above 2000 m in altitude on the northern slope of the Kunlun Mountains was better than that for areas below 2000 m in altitude; the ECMWF model’s ability to capture precipitation in the Western Kunlun Mountains was superior to that in the Central Kunlun Mountains. (2) The ECMWF model’s forecasts of daily precipitation variations exhibited the greatest discrepancies from observed precipitation between 17:00 and 02:00 the following day. The model’s predicted frequency of precipitation events was much higher than the observed frequencies, but the predicted intensity of precipitation was markedly lower the observed. During periods of low observed precipitation, the model was prone to overestimating precipitation. In regions of the western (central) Kunlun Mountains, on the north-facing slopes with elevations above 2000 m (and up to 2000 m), the model’s daily variation in precipitation significantly diverged from that of the observed precipitation. (3) The ECMWF model’s precipitation forecasts were dominated by convective precipitation (CP) in the Western Kunlun Mountains and by large-scale precipitation (LSP) in the Central Kunlun Mountains. Within the ECMWF model, LSP had a better capturing ability for observed precipitation than CP, and the discrepancies between model precipitation forecasts and observed precipitation were more likely to come from CP. These findings provide a reference for improving the accuracy of summer precipitation forecasts on the northern slope of the Kunlun Mountains and for the correction of the ECMWF model’s precipitation forecasts.

Xinjiang features a unique mountain-oasis-desert ecological system, in which the surface water body plays a crucial role in maintaining the ecological balance and supporting regional socioeconomic development. This study used Landsat 5, 7, 8, and 9 satellite remote sensing images and a mixed index algorithm to estimate Xinjiang’s surface water area from 1990 to 2023 for analysis of its spatial patterns and changes over time. Geographic detector methods were used to identify the factors influencing changes in the surface water area. The findings revealed that between 1990 and 2023, the area of the permanent water body in Xinjiang increased by 36.25% (2466.20 km²), driven primarily by the mountain water body. Notably, the inland river basins of the Qiangtang Plateau expanded significantly by approximately two-thirds (1149.58 km²). The seasonal water bodies, mainly consisting of the oasis-desert water body, also rose by 181.90% (1924.84 km²), with the mainstream Tarim River nearly doubling in area (344.92 km²). Changes in mountain water bodies were largely influenced by climatic factors, with the snow water equivalent contributing the highest average rate (42.84%). In contrast, human activities had a more substantial impact on the oasis-desert water body, with population density and cultivated land exhibiting average contribution rates of 64.10% and 54.43%, respectively. This study provides a comprehensive analysis of the temporal and spatial changes in Xinjiang’s surface water body and their driving factors, thereby offering critical scientific insights for assessing water resource development potential and formulating effective water resource management strategies in the region.

The quality of precipitation data are critical factor influencing the accuracy of runoff simulation in high-cold mountainous districts as it plays an important role in the ecological environmental protection and water resource management. The spatiotemporal characteristics of precipitation are analyzed in the headwater catchment of the Yarkant River Basin on the basis of GPM (Global Precipitation Measurement), AIMERG (the Asian precipitation dataset by calibrating the GPM-era IMERG), CMFD (China Meteorological Forcing Dataset) and ERA5 (The fifth-generation atmospheric reanalysis of the European Center for Medium-Range Weather Forecasts). Subsequently, the accuracy of the multisource precipitation data are evaluated against the observed precipitation. The error characteristics of various precipitation products was analyzed by means of the error decomposition model. The main findings were as follows: (1) The spatial pattern for CMFD and AIMERG was characterized by the increase from the north to south, which was consistent with the spatial pattern for the grid observation data set CN05.1 (the National Climate Center of China Meteorological Administration precipitation dataset). An opposite pattern was detected for ERA5 and GPM. Additionally, AIMERG and CMFD displayed higher precipitation in the glacier area. (2)The inter-annual variation characteristics of various precipitation products were significantly different, and the ratio of summer and autumn precipitation to annual precipitation for most precipitation products was more than 60%. Among all the precipitation products, only AIMERG reproduced the seasonal patterns, such as the time when the maximum monthly precipitation occurred and the peak shape for the monthly precipitation at all stations. AIMERG had the greatest ability to reproduce gauged monthly precipitation, with a higher correlation coefficient (>0.6) and lower root mean square error (8.45-11.57 mm), whereas ERA5 show the poorest ability. (3) All precipitation products showed a higher performance in reproducing daily precipitation during the wet period (from May to October) than during the dry period (from November to April). AIMERG had a greater critical success index in both wet period and dry period than for other precipitation products. (4) The dominant error of the various precipitation products in summer was the hit error, whereas the dominant error in winter varied with the precipitation product. These findings provide some reference for the runoff simulation and algorithm improvement of precipitation products in the high-cold region, where meteorological data are limited.

As an important passage of the Silk Road, the water resources carrying capacity of the inland river basin is a key factor impacting the sustainable development of society and economy in the Gansu Province. Therefore, by constructing an evaluation index system of “water resources-society-economy-ecology,” based on the CRITIC and the entropy methods for calculating the comprehensive weight of the evaluation index, this study evaluated the carrying capacity of the water resources of the region. The study involved analyzing the coupling and coordination situation of each subsystem and the main obstacle factors affecting the capacity by using the TOPSIS model, the coupling and coordination function model, and the obstacle factors function model, respectively. The results suggested that the water resources and social subsystem development of the water resources capacity in Jiuquan, Jiayuguan, Zhangye, Jinchang, and Wuwei lagged behind the economic and ecological subsystem development of the region from 2011 to 2022. The water resource carrying capacity of the inland river basin was generally in a slow upward trend in the Gansu Province, thus escalating its shortage state to a reasonable level progressively. Additionally, relative to the average relative proximity degree, the water carrying capacity of Jiuquan, Jinchang, and Zhangye is at a shortage level, whereas the water carrying capacity of Jiayuguan and Wuwei is at a reasonable level. The level of coupling coordination of the four subsystems in the five cities was at its primary coordination stage. The key to improving the water resource carrying capacity of the inland river basin in the Gansu Province is to improve the carrying capacity of water resources and social subsystems. The main obstacles to improving the carrying capacity of water resources are the rate of cultivated land, proportion of ecological water use, population density, and Chemical Oxygen Demand (COD) from wastewater.

Based on the in situ observation of evaporation and water vapour isotope, the study investigated the characteristics of near-surface soil-water-vegetation evaporation and transpiration in Wangjiaxiang, a typical area in source region of the Yellow River, and explored the isotopic features of water vapour emitted from soil, vegetation, and water bodies. The study also calculated the proportion of evaporation and migrating water vapour. The results show that the peak time of soil and vegetation evaporation is delayed relative to the peak time of water body evaporation, and the influence of evaporation on soil water depth is 20 cm. There are significant differences in the isotopic values of evaporation between different observation objects (bare soil, vegetation, water bodies, and mixed), the isotope fractionation process during plant transpiration is generally stronger than that during soil evaporation. The isotopic fractionation effect becomes stronger as the depth of soil water consumed by evaporation increases. Evaporation causes the observed water vapour δ¹⁸O, δD and δ¹⁷O to initially enrich and then stabilize, indicating the existence of an isotopic equilibrium process, while the d-excess continues to decrease during evaporation. The hourly Rayleigh fractionation model can reflect the changes in the isotopic composition of evaporation water vapour to a good extent. The results of the endmember mixing model for water vapour isotopes show that the near-surface observation site, water vapour is mainly dominated by evapotranspirationn. Future water resource allocation and management should pay more attention to the impact of climate change on soil evaporation.

The classification of the ground substrate is a fundamental basis for conducting ground substrate surveys and monitoring. It reveals the synergistic coupling relationship between the ground substrate and the surface cover layer, which aids in understanding the mechanisms of interaction between the ground substrate and the ecological environment from both the surface cover and subsurface spatial elements. This study targeted the Sangong River Basin in Xinjiang, a typical inland river basin in an arid region. Based on the heterogenous distribution of the mountain-oasis-desert landscape in arid regions, a three-tier classification and zoning system for ground substrates was developed, considering the distribution area, elevation range, and main surface cover of the surface substrates. The overall classification was divided into four primary categories, 17 secondary categories, and 28 tertiary categories. Considering the physical and chemical properties of the soil and the distribution characteristics of vegetation root systems, the suitable survey depth for ground substrates in the southern mountainous area was 50 cm; in the central plain area, it was 3 m; and in the northern desert area, it was less than 10 m. Additionally, based on the differentiation characteristics of Net Primary Productivity in vertical zonal ecosystems, the rationality of the classification system was validated, reflecting the role of ground substrate layers in nurturing and supporting land cover. These results provide theoretical and technical support for future natural resource surveys, monitoring, and scientific management decisions in arid regions.

Cuscuta plants are classified as quarantine plants due to their parasitic stem characteristics, and it is important to investigate the potential spatial distribution characteristics of Cuscuta plants in China for effective control. In this study, three species of Cuscuta (C. cupulata, C. campestris and C. monogyna) were selected as the research subjects. Based on 932 records of geographical distribution, 144 records of field investigation and 20 environmental variables, the maximum entropy model and ArcGIS were used to predict potential niche distributions under current and future scenarios (2041-2060, 2061-2080) considering of greenhouse gas emissions from SSP2-4.5. The suitable areas for the 3 species of Cuscuta under the current climate conditions and land use date were analyzed. The results showed that: (1) The area under the work characteristic curve (AUC) for all subjects was greater than 0.9 indicating high prediction accuracy. (2) The main environmental factors affecting the distribution of the three species of Cuscuta within their habitable zones with a relatively small contribution rate from topographic factors varied, but all of them were dominated by climatic factors. (3) Currently C. cupulata and C. monogyna distributions are concentrated in northern China, while C. campestris is not only distributed in the north, but also concentrated in southeastern China, and in future scenarios they will expand further northward. (4) In the current period, most land areas suitable for these three species of Cuscuta have already been exploited.

The five typical plant communities in the ecological public welfare forest in the desert area of Minqin County, namely, Phragmites communis+Achnatherum splendens, Suaeda glauca+Nitraria tangutorum, Sarcozygium xanthoxylon+Nitraria tangutorum, Salsola passerine+Haloxylon ammodendron, Reaumuria songarica+Haloxylon ammodendron as research objects, through the field plant community survey and soil sampling, studied the plant community structure, plant species diversity and its relationship with soil factors, the results show that: (1) Minqin County desert area ecological public welfare forests plant species composition is relatively simple, there are only 10 families, 19 genera and 22 species, and the Reaumuria songarica+Haloxylon ammodendron community is relatively rich in species composition. The Margalef richness index (R), Simpson’s dominance index(D), and Shannon-Wiener diversity index (H') of the Reaumuria songarica+Haloxylon ammodendron community were the largest among the five plant communities, and the Pielou evenness index (Jsw) of the five communities ranged from 0.55 to 0.99 with no significant difference among the five communities. (2) In terms of soil physicochemical properties of the five communities, the Reaumuria songarica+Haloxylon ammodendron community had the smallest soil bulk density and the highest soil organic carbon content. (3) The relationship between the α-diversity index and soil factors was found by Redundancy Analysis (RDA) that the soil bulk density (SBD) and soil organic carbon (SOC) content explained a higher percentage of α-diversity, which were 56% and 14.3%, respectively. Therefore, the Reaumuria songarica+Haloxylon ammodendron community has relatively high species richness and relatively good soil physicochemical properties, which can improve the vegetation ecology in the desert area of Minqin County, and is of positive significance for the protection and enhancement of plant community diversity in the ecological public welfare forests in the desert area of Minqin County.

The purpose of this study was to explore the relationship between the soil fungal community structure and function and soil chemical properties and enzyme activity in Pinus tabuliformis sand-fixing forests of different ages, so as to provide a theoretical basis for the rational management and protection of P. tabuliformis sand-fixing forests. Taking the mobile sand of Horqin Sandy Land as the control (0 year), P. tabuliformis forests with sand fixation for 18, 34, 48 and 56 years were selected as the research objects, and high-throughput sequencing technology was used to analyze the differences in soil fungal community structure and functional groups. The results show: (1) The 2517 OTUs obtained from the soil of the P. tabuliformis sand-fixing forest belong to 14 phyla, 48 classes, 127 orders, 286 families, and 579 genera of fungi. The dominant phyla were Ascomycota (47.91%-67.34%), Basidiomycota (18.45%-43.70%), and Mortierellomycota (1.41%-8.36%); the dominant genera were Biappendiculispora, Scleroderma, Tomentella, Knufia, and Amphinema. (2) Venn diagram and NMDS analysis showed that afforestation has a greater impact on soil fungal community structure. The ace index and chao index of soil fungi at each stand age increased significantly (P<0.05), and were related to organic matter, total nitrogen, and total phosphorus, urease, dehydrogenase, catalase, neutral phosphatase, sucrase and neutral protease have a significant positive correlation (P<0.05). (3) The fungal community was mainly composed of symbiotic and saprophytic types. After afforestation, the relative abundance of symbiotic types increased compared with the control, while the relative abundance of saprophytic types was relatively stable. Afforestation plays an important regulatory role on the structure and function of soil fungal communities. The research results enrich the research content of soil microbial communities in sand-fixing forests and provide a basis for soil health evaluation of P. tabuliformis sand-fixing forests in Horqin Sandy Land.

In this study, three typical sand-fixing plants in the desert-oasis transition zone were used as the research objects. To simulate water infiltration of 10 L, 15 L, and 20 L, respectively (simulating light rain, moderate rain, and heavy rain), the field staining tracer method and computer image processing technology were used. The distribution rules and characteristic parameters of the priority flow in the vertical and horizontal sections of the dyed images were analyzed, and the characteristic parameters were selected as evaluation indexes. The mean square decision method was used to determine the degree of development of the soil priority flow in the root zone of typical sand-fixation plants, which provided a reference for the restoration of sand-fixation vegetation and effective utilization of water resources in the desert-oasis transition zone. The results showed that (1) Soil preferential flow occurred in the root zone of sand-fixing plants in the desert-oasis transition zone, and the main types were funnel flow and finger flow. When infiltration water water was increased, the preferential flow occurred laterally. (2) Under the various conditions of water infiltration, the soil staining area ratio in the root zone of the three sand-fixing plants showed a nonlinear decrease with an increase in soil depth. The curve of the soil staining area ratio in the root zone of Haloxylon sacralis and Jujube sacralis showed an “S” shape, and the water infiltration was non-uniform. (3) The priority flow evaluation index P_FI was from large to small: Haloxell (0.685), Sphaerophora sphaerophora (0.543), and Hippophora hippophobia (0.502). The degree of priority flow development of the soil in the root zone was the highest.

Few studies have used the characteristic variables extracted from the details of the hyperspectral reflectance curves of bare soil to evaluate the separability of various desert types. In this study, salt desert, gravel desert, mud desert, and desert in the lower reaches of the Shiyang River were used as the research objects, and cumulative difference, first-order differentiation, continuum removal, vegetation index calculation and principal component analysis were used to identify the hyperspectral reflectance features of various desert types, extract the key categorical variables, and quantify the degree of differentiation of various desert types. The results showed that (1) the absorption valleys at 446-600 nm and 2150-2285 nm differed significantly among the desert types. (2) the Carter index 1, Greenness Index, and Green NDVI hyper 2 differed significantly among the desert types. (3) The Modified Chlorophyll Absorption Ratio Index, Soil Adjusted Vegetation Index, and 2265 nm and 1790-1810 nm reflectance had larger weight values in constructing the principal component indexes; and (4) the differentiation index of each desert type: desert & salty desert>desert & muddy desert>muddy & salty desert>gravelly & salty desert>desert & gravelly desert>mud & gravelly desert. These findings provide ground verification and data support for the remote sensing monitoring of deserts in the northwest Arid Zone.

The agro-pastoral ecotone of northern China is a typical ecologically vulnerable region. It is important to explore the spatiotemporal change in habitat quality for the scientific protection of the ecology and environment. This study analyzed the spatiotemporal patterns of habitat quality during the period 2000-2020, and simulated the future land use and habitat quality under various scenarios until 2040, based on the land-use data, FLUS-InVEST model, and spatial autocorrelation method. The results showed that (1) Grassland was the main land-use type in the region, accounting for more than 41% of land use. The cultivated land area accounted for more than 32% and the forest land area accounted for more than 16%. During the 2000-2020 period, the cultivated land changed the most, decreasin by 10157 km², where the unused land changed the least with an area reduction of 771 km². The areas of grassland and construction land had increased. (2) The habitat quality in the southeast boundary of the region was relatively high. From 2000 to 2020, the average habitat quality index changed from 0.498 to 0.494, indicating a slight decrease. The area with low habitat quality increased by 2281 km² and that with high grade habitat increased by 1375 km². The areas with a high degree of degradation showed a point distribution and were mainly concentrated in some construction land. (3) In 2040, the habitat quality is projected to improve in each scenario, but the habitat quality will improve the most in the ecological protection scenario. The area of high grade habitat increased by 2514 km² relative to that in 2020. In the trend development scenario, the relatively low ecological quality area would be reduced by up to 162625 km² relative to that in 2020. The area under cultivation, grassland, and unused land under the trend development and economic development scenarios will not change. The area of forest land under the ecological protection scenario was the largest, being 18547 km² more than that under the trend development scenario. In light of these findings, it is suggested that in future land-use planning and ecological environmental protection, we should focus on the areas with low habitat quality in the southeast of Inner Mongolia and northern of Hebei.

The method for estimating evapotranspiration using remote sensing evapotranspiration models has been widely applied, but there is need for research into improving its accuracy. Crop growth models exhibit strong mechanistic foundations and accuracy in simulating crop transpiration. This study integrated the WOFOST crop growth model with the three-temperature remote sensing evapotranspiration model to design a novel method for estimating remote sensing-based evapotranspiration in maize fields. The core approach involved localizing the WOFOST model, validating its simulation accuracy, and using its simulated crop transpiration data to construct an auxiliary calibration function. This function calibrated the transpiration component of the three-temperature model and combined it with the calibrated soil evaporation component to derive the evapotranspiration for the maize fields. Using actual evapotranspiration observed by an eddy covariance system as a reference, the estimation accuracy and applicability of the novel method were evaluated. The results showed that the correlation coefficients of evapotranspiration, crop transpiration, and soil evaporation in the uncalibrated three-temperature model were 0.61, 0.71, and 0.12, respectively, with root mean square errors (RMSE) of 1.76 mm·d^-1, 1.91 mm·d^-1, and 3.02 mm·d^-1, respectively, and negative Nash-Sutcliffe efficiency coefficients. After calibrating only the soil evaporation component, the correlation coefficients improved to 0.77, but the error remained large (1.91 mm·d^-1) with a Nash-Sutcliffe efficiency coefficient of -0.74. However, when the three-temperature model was calibrated using the WOFOST-simulated crop transpiration data, the correlation coefficient between the estimated and observed values significantly increased to 0.89, the RMSE decreased to 0.65 mm·d^-1, and the Nash-Sutcliffe efficiency coefficient reached 0.79. These results indicate that the proposed method effectively improves the estimation accuracy of the three-temperature remote sensing evapotranspiration model and offers insights for enhancing the accuracy of other remote sensing evapotranspiration models.

Using agricultural data from Xinjiang from 1991 to 2021, this study examined the temporal variations in carbon effects induced by cultivation in the region by using the carbon absorption and emission coefficient method. The spatial correlation, distribution, and evolution patterns of these carbon effects were explored by integrating Moran’s I, centroid migration, and the standard deviational elliptical model. The aim of this paper was to investigate the spatiotemporal dynamics of carbon effect changes in cultivated land over a long-term series in Xinjiang and to assess the region’s potential for carbon sequestration. The results were as follows: (1) Carbon absorption in Xinjiang’s cultivated land significantly exceeded carbon emissions, demonstrating a net carbon sink effect. Furthermore, the carbon sink capacity had consistently increased, rising from 8.3 million tons in 1991 to 34.29 million tons in 2021. (2) Regions with strong carbon sink capacity were concentrated in areas with extensive cultivated land and high production of corn, wheat, and cotton. (3) The net carbon sink of cultivated land exhibits significant spatial agglomeration patterns at the county and city scales, with the center of gravity of cropland carbon sinks generally migrating to the northeast. However, over the past 30 years, it has remained situated in the Aksu region of southern Xinjiang. (4) Cropland carbon sinks are primarily attributed to carbon absorption by cotton, wheat, and corn. Conversely, the main sources of carbon emissions include the application of chemical fertilizers, farmland tillage, irrigation, and the use of agricultural films. Notably, the contribution of chemical fertilizers and agricultural films to carbon emissions is on the rise. Based on these findings, we propose an appropriate expansion of the cultivated land area and increasing the cultivation of cotton, as well as grain and oil crops in southern Xinjiang. Additionally, we should promote the planting of corn and cotton in accordance with local conditions and boost the investment in green agricultural technologies and materials to improve the production capacity of cultivated land, ensure food security, and enhance carbon sequestration.