The Balkhash Lake Basin (BLB), a vital Central Asian watershed, faces hydrological uncertainty under climate warming. This study integrated multi-source remote sensing data (Sentinel-1 snow depth, Randolph Glacier Inventory (RGI) v.7.0 glacier inventory, and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) mass balance) with a degree-day model to reconstruct decadal snow and ice dynamics across 13 sub-basins and analyzed their hydrological impacts from 1950 to 2014. The results showed that: (1) while flows from the downstream river of the BLB decreased from 1950 to 1982 due to land surface changes, runoff increased significantly after 1982 in the Ili River (18.0%) and moderately increased in most rivers in the east (1.3%-8.3%), driven by increased precipitation and glacier melt. Runoff in the Ayaguz catchment (no glaciers with the highest climate warming) declined (10.5%); (2) climate warming reduced precipitation falling as snow caused snow melt water to decline (0.03-0.22 mm/a) across the BLB, leading to downward shifts in runoff and runoff coefficient, especially in the rivers in the east. However, snow melt during April-June positively correlated with runoff coefficient, contributing to an upward shift in the Ili River Basin; and (3) meltwater from glacierized areas (<5.0% of basin area) contributed to 14.3% of total ablation water. Net glacier melt provided substantial excess flows (11.6 m³/s in the Ili River and <1.0 m³/s in the rivers in the east), generally counterbalancing the negative effect of rising potential evaporation at decadal scales and positively correlating with the runoff coefficient. Therefore, water stress in the BLB may be more severe in the future due to the accelerating glacier melt after the abrupt increase in air temperature in 2000, the continuing decline in snow melt, and the significant inter-annual variations in precipitation.

Surface water plays an essential role in the ecohydrological cycle, especially in water-scarce regions. Changes in surface water restrict social, economic, and agricultural development. However, the patterns and underlying causes of surface water changes over varying frequencies in global arid regions remain unclear. Thus, this study investigated the changes in surface water and the underlying causes using the trend analysis and Spearman correlation coefficient on the basis of multi-source remote sensing and climate datasets across global arid regions during 2000-2020. The surface water was divided into temporary surface water (TSW), seasonal surface water (SSW), and permanent surface water (PSW) by calculating the surface water inundation frequency. Considering that surface water may be influenced by precipitation in the upper basins, we analyzed the response of surface water area to climatic factors at the basin scale. The area of all surface water (ASW) increased dramatically in global arid regions from 2000 to 2020, increasing from 61.88×10⁴ to 67.40×10⁴ km²; however, this increase was accompanied by a decrease in surface water inundation frequency. TSW increased by 55.46% relative to its area in 2000, with a net change rate of 3284.00 km²/a. Changes in surface water were predominantly observed in the Kyzylkum Desert in Central Asia, the Thar Desert in southwestern Asia, and the deserts in Oceania. Precipitation had a significant effect on SSW and TSW at the basin scale. The correlation between precipitation and SSW area can reach 0.808 in the Indus River Basin of the Thar Desert (P<0.01). The findings provide a more comprehensive understanding of surface water variability in global arid regions, carrying significant practical implications for the scientific management of surface water at different frequencies.

Northern Xinjiang, an arid inland area in Northwest China, is highly vulnerable to air pollution under intensifying climate extremes, yet the relative roles of temperature and precipitation extremes remain insufficiently understood. Using multi-source datasets for 2000-2023, including China High Air Pollutants (CHAP) particulate matter 2.5 (PM_2.5), particulate matter 10 (PM₁₀), and ozone (O₃) products and Expert Team on Climate Change Detection and Indices (ETCCDI) extreme climate indices derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5)-Land, together with trend detection, change-point analysis, pixel-wise Pearson correlation, and random forest (RF) modeling, we investigated the spatiotemporal evolution of major air pollutants and their responses to meteorological extremes in northern Xinjiang. PM_2.5 and PM₁₀ generally declined from 2000 to 2023, whereas O₃ increased, indicating a shift from particulate-dominated pollution toward stronger photochemical pollution. Interannually, PM_2.5 showed a rise-decline pattern, PM₁₀ exhibited a rise-decline-rebound pattern, and O₃ increased markedly after 2015. Clear seasonal contrasts were observed, with PM_2.5 peaking in winter, PM₁₀ in spring, and O₃ in summer. During the same period, northern Xinjiang exhibited a pronounced warming-drying tendency, characterized by increasing heat-related indices, decreasing cold-related indices, reduced precipitation totals and heavy-rainfall frequency, and increasing consecutive dry days. Pollutant-climate relationships showed strong spatial heterogeneity and pollutant-specific contrasts across the Urumqi-Changji-Shihezi corridor, the Ili River Valley, and the Junggar Basin. PM_2.5 responses to precipitation shifted from predominantly positive to negative, PM₁₀ showed mainly negative associations with precipitation extremes, and O₃ responses varied by subregion. Temperature-related extremes generally explained more pollutant variability than precipitation-related extremes, with PM_2.5 showing the highest sensitivity. These findings highlight the coupled influences of warming, drying, emissions, and terrain-controlled transport on air quality and support region-specific, multi-pollutant strategies for coordinated climate adaptation and air pollution control in northern Xinjiang.

In recent years, intensified land use change driven by climate change and human activities have markedly impacted the ecological environmental quality of the arid inland river basins. The implementation of forestry projects, coupled with continuous population growth, has increased the need for systematic assessments of ecological effects to ensure sustainable development in arid inland river basins. This study generated a 22-a (2000-2021) remote sensing ecological index (RSEI) data series for the Manas River Basin, a typical arid inland river basin in China, utilizing Moderate Resolution Imaging Spectroradiometer (MODIS) data and the Google Earth Engine (GEE) platform. We examined the spatiotemporal patterns of ecological environmental quality in the Manas River Basin through the Theil-Sen estimator, Mann-Kendall trend test, coefficient of variation (CV), and Hurst index. Furthermore, we employed the Optimal Parameter-based Geographical Detector (OPGD) method to quantify the influence of seven key drivers: elevation, slope, temperature, precipitation, gross domestic product (GDP), population density, and land use change. The key findings revealed that the basin's ecological environmental quality showed significant improvement (mean RSEI of 0.38, with a range of 0.34-0.41), with areas exhibiting good and excellent grades increasing by 16.71%, particularly in the midstream oasis region and upstream mountainous region, while areas exhibiting poor and relatively poor grades decreased by 11.52% in the downstream desert region. Spatial heterogeneity of ecological environmental quality was pronounced, with 32.23% of the areas showing localized degradation, the midstream oasis region exhibiting sustainable recovery potential (Hurst index>0.50), and only 36.67% of the areas maintaining stable and highly stable conditions (primarily in the upstream mountainous region). The OPGD analysis revealed that temperature (q-value=0.496-0.780), land use change (q-value=0.705-0.782), and elevation (q-value=0.245-0.637) were dominant factors, with the influence of land use change increasing during 2000-2020. Strong interaction effects emerged between land use change and temperature (q-value>0.705) and between land use change and elevation (q-value=0.751 in 2020), highlighting intensified human-nature coupling. These findings provide vital perspectives for ecosystem management in arid inland river basins under both climate and anthropogenic pressures.

Per- and poly-fluoroalkyl substances (PFAS) have garnered significant global attention due to their widespread presence and potential environmental and health risks. However, research on the occurrence and environmental behavior of PFAS across different media remains limited. We analyzed the occurrence, distribution, sources, and ecological risks of 32 PFAS across multiple media in the Weihe River, China. The concentrations of PFAS ranged from 5.89 to 472.84 ng/L in the pore water and from 9.93 to 459.50 ng/L in surface water, exhibiting significant spatial variability (P<0.05). In contrast, the PFAS concentration range in the sediments was 0.74-1.81 ng/g dry weight, with no pronounced spatial variation in solid-phase PFAS (P>0.05). Vertically, concentrations in 33.00% of pore water samples exceeded those in surface water, showing a heterogeneous vertical distribution with enrichment at depths of 40-60 cm. The physical-chemical characteristics of PFAS and the hydrological and sedimentary processes at the basin scale were responsible for PFAS partitioning between the aquatic environment and sediments. Four major sources were identified through integrated source apportionment: industrial and domestic wastewater (58.25%), aqueous film-forming foam (18.07%), combined input from household pollution and metal plating (8.70%), and stormwater runoff and landfill leachate (14.98%). The ecological risk assessment revealed negligible risks from short-chain PFAS in surface water and pore water, whereas long-chain PFAS posed low to moderate ecological risks. Furthermore, the discharge of PFAS from the Weihe River to the Yellow River was estimated up to 708.20 kg/a. This study provides critical data informing strategies for mitigating PFAS pollution in rivers across typical arid and semi-arid areas of China.

Under arid and semi-arid bioclimates, steppes are increasingly threatened by anthropogenic disturbance and climatic variability, which strongly affects ecosystem functioning and subsequently leads to desertification. We investigated the morphological and physiological responses of Stipa tenacissima L. across three disturbance levels (undisturbed, slightly disturbed, and highly disturbed) in three Tunisian steppe areas (Kasserine, Sidi Bouzid, and Sfax). Morphological and physiological traits were monitored over one year, together with microclimatic variables. Result showed that disturbance was a strong driver of plant functional dynamics, with significant effects on all traits and strong interactions with site and season. Disturbance reduced photosynthetic activity and water use efficiency, particularly in Sfax, where plants adopted conservative strategies (i.e., higher leaf dry matter content and reduced leaf area). In contrast, undisturbed populations maintained a stronger coordination between physiological and morphological traits. Seasonal analyses revealed that disturbance amplified physiological stress with limited recovery. Heatmap analyses further showed that disturbance weakened trait coordination and reshaped trade-offs between acquisitive and conservative traits. Partial least squares-path modeling showed that morphology strongly drove physiological performance (path coefficient=0.48). Disturbance (path coefficient=0.41) and tussock cover (path coefficient=0.47) influenced morphology both directly and indirectly through their effects on physiology. In conclusion, S. tenacissima adjusts physiological and morphological traits under disturbance, favoring stress tolerance, while undisturbed sites maintain high physiological efficiency and coordinated trait integration, reflecting a trade-off between survival and performance while overriding local site differences. Disturbance strongly restructures trait networks, drives site-specific adjustments, and modulates the seasonal balance between morphological stability and physiological flexibility.

Identifying plant water sources is fundamental for elucidating ecohydrological processes and improving water resource management in arid zones under climate change. Stable hydrogen and oxygen isotopes are commonly used to trace plant water uptake; however, cryogenic vacuum extraction (CVE), the standard method for extracting plant xylem water, may induce deuterium depletion, thereby biasing source attribution. To systematically assess the effects of CVE-induced deuterium depletion across species, size classes, and habitats, we excavated five representative soil profiles along the mainstream of the Tarim River in northwestern China, in mid-July 2022. A total of 29 individuals, comprising both Populus euphratica and Tamarix ramosissima, were sampled. We divided P. euphratica individuals into four groups based on diameter at breast height (<50, 50-100, 100-250, and >250 cm), while categorized T. ramosissima individuals into four groups according to plant height (<1.0, 1.0-2.0, 2.0-4.0, and >4.0 m). Plant xylem water was extracted using CVE, and five deuterium depletion scenarios (-5.00‰, -7.00‰, -9.00‰, -11.00‰, and -13.00‰) were simulated. The Bayesian Mixing Model for Stable Isotope Analysis in R (MixSIAR) was applied under six input modes to quantify the proportional contributions of potential water sources and associated prediction errors. Model evaluation revealed that P. euphratica achieved the highest accuracy with a -9.00‰ correction of depletion, whereas a -11.00‰ correction was optimal for T. ramosissima, reducing relative prediction errors by 68.65% and 67.73%, respectively, compared with uncorrected scenario. Small-sized P. euphratica individuals exhibited less deuterium depletion, whereas no clear size-dependent pattern was observed for T. ramosissima. Spatially, plant individuals located farther from the river exhibited reduced deuterium depletion in xylem water. Despite differences in species traits and habitat conditions, both species predominantly relied on deep soil water and groundwater, which together contributed, on average, 61.45% and 59.95% for P. euphratica and T. ramosissima, respectively. These findings highlight the necessity of accounting for CVE-induced deuterium depletion when identifying plant water-use strategies and provide methodological guidance for isotope-based ecohydrological studies in arid environments.

The Qaidam Basin, a typical alpine arid inland basin on the northern Qinghai-Xizang Plateau, China, hosts wetland ecosystems that are strongly constrained by topography and extreme climate. These ecosystems exhibit pronounced spatiotemporal heterogeneity and fragmented distribution patterns, rendering them highly sensitive to environmental change. This study integrated Sentinel-2 remote sensing imagery with the SedInConnect model to delineate wetland patch distributions and calculate the Index of Connectivity (IC) values across the basin. Based on IC values, we stratified field sampling sites into high-, moderate-, and low- connectivity gradient groups to analyze the relationships among plant community characteristics, vegetation spatial patterns, and wetland connectivity in the Qaidam Basin. Partial Least Squares Path Modeling (PLS-PM) was further employed to quantify the driving mechanisms underlying wetland vegetation characteristics. The results revealed that wetland connectivity across the basin was generally low, with IC values up to 1.32 and displaying a west-to-east decreasing gradient. The west and northwest were characterized by relatively continuous high-connectivity wetland networks, while fragmented and low-connectivity wetlands predominated in the east and southeast. Connectivity regulated wetland vegetation patterns primarily by affecting patch size, fragmentation, and internal adjacency. High-connectivity areas had higher class area (CA), largest patch index (LPI), and area-weighted mean patch size (AREA_AM) than low-connectivity areas. Connectivity had the strongest effect on vegetation coverage, which declined sharply from 87.577% in high-connectivity areas to 12.152% in low-connectivity areas. Meanwhile, species diversity showed a moderately negative response to connectivity changes, whereas species evenness remained relatively unaffected. PLS-PM explained 78.300% and 67.500% of the variance in vegetation community and vegetation pattern, respectively. Climate played a dominant role in shaping vegetation characteristics, with significant negative effects on both vegetation community and pattern. Topography influenced vegetation indirectly through climate, and connectivity was influenced by both drivers and exerted positive effects on vegetation community and pattern. This study reveals the multi-pathway driving mechanisms underlying vegetation pattern formation in alpine wetlands, providing a theoretical foundation and decision-support framework for the scientific conservation and adaptive management of wetlands in the Qaidam Basin.

Gravel mulching plays a vital role in modifying the hydrological cycle in arid and semi-arid areas. Yet, the mechanisms underlying long-term mulching effects on soil evaporation remain poorly understood. To investigate the hydrological effects of mixed gravel-soil mulching (MGSM), we conducted a controlled 39-d soil evaporation experiment (from 22 July to 30 August 2021) using micro-lysimeters at the field experimental site of Ningxia University, China. The soil evaporation rate (E), cumulative soil evaporation (E_c), soil water content (SWC), mulch resistance (r_m), and micro-meteorological variables were assessed for six mulch treatments, each containing a different proportion of gravel by volume: 100.00% (M1), 80.00% (M2), 60.00% (M3), 40.00% (M4), 20.00% (M5), and 0.00% (M6). The treatments (M2-M6) showed a prolonged soil moisture depletion phase and greater E_c (28.71%-83.31%) relative to the gravel-only treatment (M1) (P<0.050); these effects were primarily attributed to reduced r_m. As compared to E_c, the SWC showed an inverse response, decreasing as Cg decreased. A robust exponential relationship was observed between E and r_m (P<0.001). Evaporation suppression mediated by r_m was particularly pronounced during the residual evaporation stage (>312 h post-wetting), with the strongest effect occurring in M3, where the mean r_m doubled. The SWC, mulch properties, and micro-meteorological parameters (i.e., air relative humidity and surface net radiation flux) were the most important predictors of r_m in the mulch treatments. Together, these results suggested that MGSM unexpectedly exacerbated surface soil moisture loss by reducing r_m. To mitigate this effect, an optimized mixed gravel-soil mulch, containing 60.00% gravel by volume, might be used; this mixture balances evaporation control with hydrological sustainability and represents a practical strategy for dryland management, offering a compromise between short-term water retention and sustained soil moisture regulation.