Stable water isotopes are natural tracers quantifying the contribution of moisture recycling to local precipitation, i.e., the moisture recycling ratio, but various isotope-based models usually lead to different results, which affects the accuracy of local moisture recycling. In this study, a total of 18 stations from four typical areas in China were selected to compare the performance of isotope-based linear and Bayesian mixing models and to determine local moisture recycling ratio. Among the three vapor sources including advection, transpiration, and surface evaporation, the advection vapor usually played a dominant role, and the contribution of surface evaporation was less than that of transpiration. When the abnormal values were ignored, the arithmetic averages of differences between isotope-based linear and the Bayesian mixing models were 0.9% for transpiration, 0.2% for surface evaporation, and -1.1% for advection, respectively, and the medians were 0.5%, 0.2%, and -0.8%, respectively. The importance of transpiration was slightly less for most cases when the Bayesian mixing model was applied, and the contribution of advection was relatively larger. The Bayesian mixing model was found to perform better in determining an efficient solution since linear model sometimes resulted in negative contribution ratios. Sensitivity test with two isotope scenarios indicated that the Bayesian model had a relatively low sensitivity to the changes in isotope input, and it was important to accurately estimate the isotopes in precipitation vapor. Generally, the Bayesian mixing model should be recommended instead of a linear model. The findings are useful for understanding the performance of isotope-based linear and Bayesian mixing models under various climate backgrounds.

Over the last three decades, more than half of the world's large lakes and wetlands have experienced significant shrinkage, primarily due to climate change and extensive water consumption for agriculture and other human needs. The desiccation of lakes leads to severe environmental, economic, and social repercussions. Urmia Lake, located in northwestern Iran and representing a vital natural ecosystem, has experienced a volume reduction of over 90.0%. Our research evaluated diverse water management strategies within the Urmia Lake basin and prospects of inter-basin water transfers. This study focused on strategies to safeguard the environmental water rights of the Urmia Lake by utilizing the modeling and simulating (MODSIM) model. The model simulated changes in the lake's water volume under various scenarios. These included diverting water from incoming rivers, cutting agricultural water use by 40.0%, releasing dam water in non-agricultural seasons, treated wastewater utilization, and inter-basin transfers. Analytical hierarchy process (AHP) was utilized to analyze the simulation results. Expert opinions with AHP analysis, acted as a multi-criteria decision-making tool to evaluate the simulation and determine the optimal water supply source priority for the Urmia Lake. Our findings underscore the critical importance of reducing agricultural water consumption as the foremost step in preserving the lake. Following this, inter-basin water transfers are suggested, with a detailed consideration of the inherent challenges and limitations faced by the source watersheds. It is imperative to conduct assessments on the impacts of these transfers on the downstream users and the potential environmental risks, advocating for a diplomatic and cooperative approach with adjacent country. This study also aims to forecast the volumes of water that can be transferred under different climatic conditions—drought, normal, and wet years—to inform strategic water management planning for the Urmia Lake. According to our projection, implementing the strategic scenarios outlined could significantly augment the lake's level and volume, potentially by 3.57×10⁹-9.38×10⁹ m³ over the coming 10 a and 3.57×10⁹-10.70×10⁹ m³ in the subsequent 15 a.

Methane (CH₄) is a potent greenhouse gas that has a substantial impact on global warming due to its substantial influence on the greenhouse effect. Increasing extreme precipitation events, such as drought, attributable to global warming that caused by greenhouse gases, exert a profound impact on the intricate biological processes associated with CH₄ uptake. Notably, the timing of extreme drought occurrence emerges as a pivotal factor influencing CH₄ uptake, even when the degree of drought remains constant. However, it is still unclear how the growing season regulates the response of CH₄ uptake to extreme drought. In an effort to bridge this knowledge gap, we conducted a field manipulative experiment to evaluate the impact of extreme drought on CH₄ uptake during early, middle, and late growing stages in a temperate steppe of Inner Mongolia Autonomous Region, China. The result showed that all extreme drought consistently exerted positive effects on CH₄ uptake regardless of seasonal timing. However, the magnitude of this effect varied depending on the timing of season, as evidenced by a stronger effect in early growing stage than in middle and late growing stages. Besides, the pathways of CH₄ uptake were different from seasonal timing. Extreme drought affected soil physical-chemical properties and aboveground biomass (AGB), consequently leading to changes in CH₄ uptake. The structural equation model showed that drought both in the early and middle growing stages enhanced CH₄ uptake due to reduced soil water content (SWC), leading to a decrease in NO₃^--N and an increase in pmoA abundance. However, drought in late growing stage primarily enhanced CH₄ uptake only by decreasing SWC. Our results suggested that seasonal timing significantly contributed to regulate the impacts of extreme drought pathways and magnitudes on CH₄ uptake. The findings can provide substantial implications for understanding how extreme droughts affect CH₄ uptake and improve the prediction of potential ecological consequence under future climate change.

Vapor pressure deficit (VPD) plays a crucial role in determining plant physiological functions and exerts a substantial influence on vegetation, second only to carbon dioxide (CO₂). As a robust indicator of atmospheric water demand, VPD has implications for global water resources, and its significance extends to the structure and functioning of ecosystems. However, the influence of VPD on vegetation growth under climate change remains unclear in China. This study employed empirical equations to estimate the VPD in China from 2000 to 2020 based on meteorological reanalysis data of the Climatic Research Unit (CRU) Time-Series version 4.06 (TS4.06) and European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5 (ERA-5). Vegetation growth status was characterized using three vegetation indices, namely gross primary productivity (GPP), leaf area index (LAI), and near-infrared reflectance of vegetation (NIRv). The spatiotemporal dynamics of VPD and vegetation indices were analyzed using the Theil-Sen median trend analysis and Mann-Kendall test. Furthermore, the influence of VPD on vegetation growth and its relative contribution were assessed using a multiple linear regression model. The results indicated an overall negative correlation between VPD and vegetation indices. Three VPD intervals for the correlations between VPD and vegetation indices were identified: a significant positive correlation at VPD below 4.820 hPa, a significant negative correlation at VPD within 4.820-9.000 hPa, and a notable weakening of negative correlation at VPD above 9.000 hPa. VPD exhibited a pronounced negative impact on vegetation growth, surpassing those of temperature, precipitation, and solar radiation in absolute magnitude. CO₂ contributed most positively to vegetation growth, with VPD offsetting approximately 30.00% of the positive effect of CO₂. As the rise of VPD decelerated, its relative contribution to vegetation growth diminished. Additionally, the intensification of spatial variations in temperature and precipitation accentuated the spatial heterogeneity in the impact of VPD on vegetation growth in China. This research provides a theoretical foundation for addressing climate change in China, especially regarding the challenges posed by increasing VPD.

Understanding the dynamics of surface water area and their drivers is crucial for human survival and ecosystem stability in inland arid and semi-arid areas. This study took Gansu Province, China, a typical area with complex terrain and variable climate, as the research subject. Based on Google Earth Engine, we used Landsat data and the Open-surface Water Detection Method with Enhanced Impurity Control method to monitor the spatiotemporal dynamics of surface water area in Gansu Province from 1985 to 2022, and quantitatively analyzed the main causes of regional differences in surface water area. The findings revealed that surface water area in Gansu Province expanded by 406.88 km² from 1985 to 2022. Seasonal surface water area exhibited significant fluctuations, while permanent surface water area showed a steady increase. Notably, terrestrial water storage exhibited a trend of first decreasing and then increasing, correlated with the dynamics of surface water area. Climate change and human activities jointly affected surface hydrological processes, with the impact of climate change being slightly higher than that of human activities. Spatially, climate change affected the 'source' of surface water to a greater extent, while human activities tended to affect the 'destination' of surface water. Challenges of surface water resources faced by inland arid and semi-arid areas like Gansu Province are multifaceted. Therefore, we summarized the surface hydrology patterns typical in inland arid and semi-arid areas and tailored surface water 'supply-demand' balance strategies. The study not only sheds light on the dynamics of surface water area in Gansu Province, but also offers valuable insights for ecological protection and surface water resource management in inland arid and semi-arid areas facing water scarcity.

Nature reserves play a significant role in providing ecosystem services and are key sites for biodiversity conservation. The Tianchi Bogda Peak Natural Reserve (TBPNR), located in Xinjiang Uygur Autonomous Region, China, is an important ecological barrier area in the temperate arid zone. The evaluation of its important ecosystem services is of great significance to improve the management level and ecological protection efficiency of the reserve. In the present study, we assessed the spatiotemporal variations of four ecosystem services (including net primary productivity (NPP), water yield, soil conservation, and habitat quality) in the TBPNR from 2000 to 2020 based on the environmental and social data using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. In addition, the coldspot and hotspot areas of ecosystem services were identified by hotspot analysis, and the trade-off and synergistic relationships between ecosystem services were analyzed using factor analysis in a geographic detector. During the study period, NPP and soil conservation values in the reserve increased by 48.20% and 25.56%, respectively; conversely, water yield decreased by 16.56%, and there was no significant change in habitat quality. Spatially, both NPP and habitat quality values were higher in the northern part and lower in the southern part, whereas water yield showed an opposite trend. Correlation analysis revealed that NPP showed a synergistic relationship with habitat quality and soil conservation, and exhibited a trade-off relationship with water yield. Water yield and habitat quality also had a trade-off relationship. NPP and habitat quality were affected by annual average temperature and Normalized Difference Vegetation Index (NDVI), respectively, while water yield and soil conservation were more affected by digital elevation model (DEM). Therefore, attention should be paid to the spatial distribution and dynamics of trade-off and synergistic relationships between ecosystem services in future ecological management. The findings of the present study provide a reference that could facilitate the sustainable utilization of ecosystem services in the typical fragile areas of Northwest China.

Quantifying surface cracks in alpine meadows is a prerequisite and a key aspect in the study of grassland crack development. Crack characterization indices are crucial for the quantitative characterization of complex cracks, serving as vital factors in assessing the degree of cracking and the development morphology. So far, research on evaluating the degree of grassland degradation through crack characterization indices is rare, especially the quantitative analysis of the development of surface cracks in alpine meadows is relatively scarce. Therefore, based on the phenomenon of surface cracking during the degradation of alpine meadows in some regions of the Qinghai-Tibet Plateau, we selected the alpine meadow in the Huangcheng Mongolian Township, Menyuan Hui Autonomous County, Qinghai Province, China as the study area, used unmanned aerial vehicle (UAV) sensing technology to acquire low-altitude images of alpine meadow surface cracks at different degrees of degradation (light, medium, and heavy degradation), and analyzed the representative metrics characterizing the degree of crack development by interpreting the crack length, length density, branch angle, and burrow (rat hole) distribution density and combining them with in situ crack width and depth measurements. Finally, the correlations between the crack characterization indices and the soil and root parameters of sample plots at different degrees of degradation in the study area were analyzed using the grey relation analysis. The results revealed that with the increase of degradation, the physical and chemical properties of soil and the mechanical properties of root-soil composite changed significantly, the vegetation coverage reduced, and the root system aggregated in the surface layer of alpine meadow. As the degree of degradation increased, the fracture morphology developed from "linear" to "dendritic", and eventually to a complex and irregular "polygonal" pattern. The crack length, width, depth, and length density were identified as the crack characterization indices via analysis of variance. The results of grey relation analysis also revealed that the crack length, width, depth, and length density were all highly correlated with root length density, and as the degradation of alpine meadows intensified, the underground biomass increased dramatically, forming a dense layer of grass felt, which has a significant impact on the formation and expansion of cracks.

To comprehensively evaluate the alterations in water ecosystem service functions within arid watersheds, this study focused on the Bosten Lake Basin, which is situated in the arid region of Northwest China. The research was based on land use/land cover (LULC), natural, socioeconomic, and accessibility data, utilizing the Patch-level Land Use Simulation (PLUS) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) models to dynamically assess LULC change and associated variations in water yield and water conservation. The analyses included the evaluation of contribution indices of various land use types and the investigation of driving factors that influence water yield and water conservation. The results showed that the change of LULC in the Bosten Lake Basin from 2000 to 2020 showed a trend of increasing in cultivated land and construction land, and decreasing in grassland, forest, and unused land. The unused land of all the three predicted scenarios of 2030 (S1, a natural development scenario; S2, an ecological protection scenario; and S3, a cultivated land protection scenario) showed a decreasing trend. The scenarios S1 and S3 showed a trend of decreasing in grassland and increasing in cultivated land; while the scenario S2 showed a trend of decreasing in cultivated land and increasing in grassland. The water yield of the Bosten Lake Basin exhibited an initial decline followed by a slight increase from 2000 to 2020. The areas with higher water yield values were primarily located in the northern section of the basin, which is characterized by higher altitude. Water conservation demonstrated a pattern of initial decrease followed by stabilization, with the northeastern region demonstrating higher water conservation values. In the projected LULC scenarios of 2030, the estimated water yield under scenarios S1 and S3 was marginally greater than that under scenario S2; while the level of water conservation across all three scenarios remained rather consistent. The results showed that Hejing County is an important water conservation function zone, and the eastern part of the Xiaoyouledusi Basin is particularly important and should be protected. The findings of this study offer a scientific foundation for advancing sustainable development in arid watersheds and facilitating efficient water resource management.