Quantitative assessment of the impact of climate variability and human activities on runoff plays a pivotal role in water resource management and maintaining ecosystem integrity. This study considered six sub-basins in the upper reaches of the Yangtze River basin, China, to reveal the trend of the runoff evolution and clarify the driving factors of the changes during 1956-2020. Linear regression, Mann-Kendall test, and sliding t-test were used to study the trend of the hydrometeorological elements, while cumulative distance level and ordered clustering methods were applied to identify mutation points. The contributions of climate change and human disturbance to runoff changes were quantitatively assessed using three methods, i.e., the rainfall-runoff relationship method, slope variation method, and variable infiltration capacity (Budyko) hypothesis method. Then, the availability and stability of the three methods were compared. The results showed that the runoff in the upper reaches of the Yangtze River basin exhibited a decreasing trend from 1956 to 2020, with an abrupt change in 1985. For attribution analysis, the runoff series could be divided into two phases, i.e., 1961-1985 (baseline period) and 1986-2020 (changing period); and it was found that the rainfall-runoff relationship method with precipitation as the representative of climate factors had limited usability compared with the other two methods, while the slope variation and Budyko hypothesis methods had highly consistent results. Different factors showed different effects in the sub-basins of the upper reaches of the Yangtze River basin. Moreover, human disturbance was the main factor that contributed to the runoff changes, accounting for 53.0%-82.0%; and the contribution of climate factors to the runoff change was 17.0%-47.0%, making it the secondary factor, in which precipitation was the most representative climate factor. These results provide insights into how climate and anthropogenic changes synergistically influence the runoff of the upper reaches of the Yangtze River basin.

Rain-on-snow (ROS) events involve rainfall on snow surfaces, and the occurrence of ROS events can exacerbate water scarcity and ecosystem vulnerability in the arid region of Northwest China (ARNC). In this study, using daily snow depth data and daily meteorological data from 68 meteorological stations provided by the China Meteorological Administration National Meteorological Information Centre, we investigated the spatiotemporal variability of ROS events in the ARNC from 1978 to 2015 and examined the factors affecting these events and possible changes of future ROS events in the ARNC. The results showed that ROS events in the ARNC mainly occurred from October to May of the following year and were largely distributed in the Qilian Mountains, Tianshan Mountains, Ili River Valley, Tacheng Prefecture, and Altay Prefecture, with the Ili River Valley, Tacheng City, and Altay Mountains exhibiting the most occurrences. Based on the intensity of ROS events, the areas with the highest risk of flooding resulting from ROS events in the ARNC were the Tianshan Mountains, Ili River Valley, Tacheng City, and Altay Mountains. The number and intensity of ROS events in the ARNC largely increased from 1978 to 2015, mainly influenced by air temperature and the number of rainfall days. However, due to the snowpack abundance in areas experiencing frequent ROS events in the ARNC, snowpack changes exerted slight impact on ROS events, which is a temporary phenomenon. Furthermore, elevation imposed lesser impact on ROS events in the ARNC than other factors. In the ARNC, the start time of rainfall and the end time of snowpack gradually advanced from the spring of the current year to the winter of the previous year, while the end time of rainfall and the start time of snowpack gradually delayed from autumn to winter. This may lead to more ROS events in winter in the future. These results could provide a sound basis for managing water resources and mitigating related disasters caused by ROS events in the ARNC.

Gobi spans a large area of China, surpassing the combined expanse of mobile dunes and semi-fixed dunes. Its presence significantly influences the movement of sand and dust. However, the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces. It is challenging to describe these processes according to a uniform morphology. Therefore, it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional (3D) size and shape of gravel. Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation. To enhance the efficiency and information yield of gravel parameter measurements, this study conducted field experiments in the Gobi region across Dunhuang City, Guazhou County, and Yumen City (administrated by Jiuquan City), Gansu Province, China in March 2023. A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed, alongside improved calculation formulas for 3D parameters including gravel grain size, volume, flatness, roundness, sphericity, and equivalent grain size. Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality. Additionally, the proposed methodology incorporated point cloud clustering, segmentation, and filtering techniques to isolate individual gravel point clouds. Advanced point cloud algorithms, including the Oriented Bounding Box (OBB), point cloud slicing method, and point cloud triangulation, were then deployed to calculate the 3D parameters of individual gravels. These systematic processes allow precise and detailed characterization of individual gravels. For gravel grain size and volume, the correlation coefficients between point cloud and manual measurements all exceeded 0.9000, confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels. The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels, providing essential data support for subsequent studies on Gobi environments.

The unique geomorphological features and farming methods in the Mollisol region of Northeast China increase water catchment flow and aggravate the erosion of ephemeral gully (EG). Vegetation suffers from rain erosion and damage during the growth stage, which brings serious problems to the restoration of grass in the early stage. Therefore, effects of coir geotextile and geocell on EG erosion under four confluence intensities were researched in this study. Results of the simulated water discharge erosion test showed that when the confluence strength was less than 30 L/min, geocell and coir geotextile had a good effect on controlling EG erosion, and sediment yield of geocell and coir geotextile was reduced by 25.95%-37.82% and 73.73%-88.96%, respectively. However, when confluence intensity increased to 40 L/min, protective effect of coir geotextile decreased, and sediment yield rate increased sharply by 189.03%. When confluence intensity increased to 50 L/min, the protective effect of coir geotextile was lost. On the other hand, geocell showed that the greater the flow rate, the better the protective effect. In addition, with the increase in confluence intensity, erosion pattern of coir geotextile developed from sheet erosion to intermittent fall and then to completion of main rill, and the protective effect was gradually weakened. In contrast, the protective effect of EG under geocell was gradually enhanced from the continuous rill to the intermittent rill and finally to the intermittent fall. This study shows that coir geotextile and geocell can prevent EG erosion, and the effect of geocell is better than that of coir geotextile on the surface of EG.

The maintenance of sand-fixing vegetation is important for the stability of artificial sand-fixing systems in which seed dispersal plays a key role. Based on field wind tunnel experiments using 11 common plant species on the southeastern edge of the Tengger Desert, China, we studied the secondary seed dispersal in the fixed and semi-fixed sand dunes as well as in the mobile dunes in order to understand the limitations of vegetation regeneration and the maintenance of its stability. Our results indicated that there were significant variations among the selected 11 plant species in the threshold of wind speed (TWS). The TWS of Caragana korshinskii was the highest among the 11 plant species, whereas that of Echinops gmelinii was the lowest. Seed morphological traits and underlying surface could generally explain the TWS. During the secondary seed dispersal processes, the proportions of seeds that did not disperse (no dispersal) and only dispersed over short distance (short-distance dispersal within the wind tunnel test section) were significantly higher than those of seeds that were buried (including lost seeds) and dispersed over long distance (long-distance dispersal beyond the wind tunnel test section). Compared with other habitats, the mobile dunes were the most difficult places for secondary seed dispersal. Buried seeds were the easiest to be found in the semi-fixed sand dunes, whereas fixed sand dunes were the best sites for seeds that dispersed over long distance. The results of linear mixed models showed that after controlling the dispersal distance, smaller and rounder seeds dispersed farther. Shape index and wind speed were the two significant influencing factors on the burial of seeds. The explanatory power of wind speed, underlying surface, and seed morphological traits on the seeds that did not disperse and dispersed over short distance was far greater than that on the seeds that were buried and dispersed over long distance, implying that the processes and mechanisms of burial and long-distance dispersal are more complex. In summary, most seeds in the study area either did not move, were buried, or dispersed over short distance, promoting local vegetation regeneration.

Vegetation restoration and reconstruction are effective approaches to desertification control and achieving social and economic sustainability in desert areas. However, the self-succession ability of native plants during the later periods of vegetation restoration remains unclear. Therefore, this study was conducted to bridge the knowledge gap by investigating the regeneration dynamics of artificial forest under natural conditions. The information of seed rain and soil seed bank was collected and quantified from an artificial Caragana korshinskii Kom. forest in the Tengger Desert, China. The germination tests were conducted in a laboratory setting. The analysis of species quantity and diversity in seed rain and soil seed bank was conducted to assess the impact of different durations of sand fixation (60, 40, and 20 a) on the progress of vegetation restoration and ecological conditions in artificial C. korshinskii forest. The results showed that the top three dominant plant species in seed rain were Echinops gmelinii Turcz., Eragrostis minor Host., and Agropyron mongolicum Keng., and the top three dominant plant species in soil seed bank were E. minor, Chloris virgata Sw., and E. gmelinii. As restoration period increased, the density of seed rain and soil seed bank increased first and then decreased. While for species richness, as restoration period increased, it gradually increased in seed rain but decreased in soil seed bank. There was a positive correlation between seed rain density and soil seed bank density among all the three restoration periods. The species similarity between seed rain or soil seed bank and aboveground vegetation decreased with the extension of restoration period. The shape of the seeds, specifically those with external appendages such as spines and crown hair, clearly had an effect on their dispersal, then resulting in lower seed density in soil seed bank. In addition, precipitation was a crucial factor in promoting rapid germination, also resulting in lower seed density in soil seed bank. Our findings provide valuable insights for guiding future interventions during the later periods of artificial C. korshinskii forest, such as sowing and restoration efforts using unmanned aerial vehicles.

Land use change affects the balance of organic carbon (C) reserves and the global C cycle. Microbial residues are essential constituents of stable soil organic C (SOC). However, it remains unclear how microbial residue changes over time following afforestation. In this study, 16-, 23-, 52-, and 62-year-old Mongolian pine stands and 16-year-old cropland were studied in the Horqin Sandy Land, China. We analyzed changes in SOC, amino sugar content, and microbial parameters to assess how microbial communities influence soil C transformation and preservation. The results showed that SOC storage increased with stand age in the early stage of afforestation but remained unchanged at about 1.27−1.29 kg/m² after 52 a. Moreover, there were consistent increases in amino sugars and microbial residues with increasing stand age. As stand age increased from 16 to 62 a, soil pH decreased from 6.84 to 5.71, and the concentration of total amino sugars increased from 178.53 to 509.99 mg/kg. A significant negative correlation between soil pH and the concentration of specific and total amino sugars was observed, indicating that the effects of soil acidification promote amino sugar stabilization during afforestation. In contrast to the Mongolian pine plantation of the same age, the cropland accumulated more SOC and microbial residues because of fertilizer application. Across Mongolian pine plantation with different ages, there was no significant change in calculated contribution of bacterial or fungal residues to SOC, suggesting that fungi were consistently the dominant contributors to SOC with increasing time. Our results indicate that afforestation in the Horqin Sandy Land promotes efficient microbial growth and residue accumulation in SOC stocks and has a consistent positive impact on SOC persistence.

Arid areas with low precipitation and sparse vegetation typically yield compact urban pattern, and drought directly impacts urban site selection, growth processes, and future scenarios. Spatial simulation and projection based on cellular automata (CA) models is important to achieve sustainable urban development in arid areas. We developed a new CA model using bat algorithm (BA) named bat algorithm-probability-of-occurrence-cellular automata (BA-POO-CA) model by considering drought constraint to accurately delineate urban growth patterns and project future scenarios of Urumqi City and its surrounding areas, located in Xinjiang Uygur Autonomous Region, China. We calibrated the BA-POO-CA model for the drought-prone study area with 2000 and 2010 data and validated the model with 2010 and 2020 data, and finally projected its urban scenarios in 2030. The results showed that BA-POO-CA model yielded overall accuracy of 97.70% and figure-of-merits (FOMs) of 35.50% in 2010, and 97.70% and 26.70% in 2020, respectively. The inclusion of drought intensity factor improved the performance of BA-POO-CA model in terms of FOMs, with increases of 5.50% in 2010 and 7.90% in 2020 than the model excluding drought intensity factor. This suggested that the urban growth of Urumqi City was affected by drought, and therefore taking drought intensity factor into account would contribute to simulation accuracy. The BA-POO-CA model including drought intensity factor was used to project two possible scenarios (i.e., business-as-usual (BAU) scenario and ecological scenario) in 2030. In the BAU scenario, the urban growth dominated mainly in urban fringe areas, especially in the northern part of Toutunhe District, Xinshi District, and Midong District. Using exceptional and extreme drought areas as a spatial constraint, the urban growth was mainly concentrated in the "main urban areas-Changji-Hutubi" corridor urban pattern in the ecological scenario. The results of this research can help to adjust urban planning and development policies. Our model is readily applicable to simulating urban growth and future scenarios in global arid areas such as Northwest China and Africa.