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Plastic film mulching (PFM) technology plays an important role in agricultural production in “drought and cold” regions, and macroplastics pollution in farmland has become a major concern affecting the sustainable development of regional agricultural production. However, there remains a lack of research on the effects of film application and macroplastics characteristics on soil nutrients in farmland. In this study, the characteristics of plastic film application and macroplastics, and their effect on soil nutrients in typical plastic film cropland in northern Xinjiang were explored by field research and a review of the relevant literature. It was found that the average annual growth rate was higher in areas where the amount, usage intensity, and proportion of plastic film were lower. The amount of plastic film input was a key factor affecting the amount of macroplastics. The macroplastics amount of plastic film was positively correlated with soil organic carbon content and negatively correlated with soil available phosphorus; however, it had no effect on soil available potassium. It is necessary to take immediate action regarding the characteristics of plastic film application and macroplastics and the impact of macroplastics on soil nutrients, in order to establish a response to the dual challenges of food security and sustainable agricultural development in terms of plastic film pollution prevention and control measures.

Calibration and validation of flood risk maps at a national or a supra-national level remains a problematic aspect due to the limited information available to carry out these tasks. However, this validation is essential to define the representativeness of the results and for end users to gain confidence in them. In recent years, the use of information derived from social networks is becoming generalized in the field of natural risks as a means of validating results. However, the use of data from social networks also has its drawbacks, such as the biases associated with age and gender and their spatial distribution. The use of information associated with phone calls to Emergency Services (112) can resolve these deficiencies, although other problems are still latent. For example, a bias does exist in the relationship between the size of the population and the number of calls to the Emergency Services. This last aspect determines that global regression models have not been effective in simulating the behavior of related variables (calls to Emergency Services–Potential Flood Risk). Faced with this situation, the use of local regression models (such as locally estimated scatterplot smoothing (LOESS)) showed satisfactory results in the calibration of potential flood risk levels in the Autonomous Community of Castilla-La Mancha (Spain). This provides a new methodological path to the calibration studies of flood risk cartographies at national and supra-national levels. The results obtained through LOESS local regression models allowed us to establish the correct relationship between categorized potential risk levels and the inferred potential risk. They also permitted us to define the cases in which said levels differed ostensibly and where potential risk due to floods assigned to those municipalities led to a lower level of confidence. Therefore, based on the number of calls to the Emergency Service, we can categorize those municipalities that should be the subject of a more detailed study and those whose classification should be revised in future updates.

In this paper characteristics of loess are discussed from a pedological perspective. A new model of loess formation is presented, developed in different soil formation processes according to its pedogenic characteristics, including soil structure, organic matter content and CaCO 3 content. Loess has all the characteristics of typical soils and all five soil-forming factors have important roles in loess formation. In this regard, loess is a type soil and the previous concept of loess actually comprises various kinds of palaeosols developed in cold and arid climatic conditions. The loess-forming process is, in fact, equivalent to a pedogenic process and loess layers with different characteristics represent different pedogenic processes indicative of different environments, such as desert-steppe, steppe or forest-steppe climatic conditions. In contrast to red-brown palaeosol layers, which develop in warm and wet climates, loesses–more accurately called ‘loessial palaeosols’–are grey-yellow palaeosols and can be regarded as a reliable indicator of cold and arid climate. The model of loess formation suggests that aeolian dust transfers to grey-yellow palaeosols via pedogenesis and the characteristics of loess are mainly a result of climatic conditions and diagenesis processes after its sedimentation. This new model of loess formation also suggests that traditional pedological theory has its limitations when explaining soil formation processes.

Midlatitude Asia (MLA), strongly influenced by westerlies-controlled climate, is a key source of global atmospheric dust, and plays a significant role in Earth’s climate system . However, it remains unclear how the westerlies, MLA aridity, and dust flux from this region evolved over time. Here, we report a unique high-resolution eolian dust record covering the past 3.6 Ma, retrieved from the thickest loess borehole sequence (671 m) recovered to date, at the southern margin of the Taklimakan desert in the MLA interior. The results show that eolian dust accumulation, which is closely related to aridity and the westerlies, indicates existence of a dry climate, desert area, and stable land surface, promoting continuous loess deposition since at least ∼3.6 Ma. This region experienced long-term stepwise drying at ∼2.7, 1.1, and 0.5 Ma, coeval with a dominant periodicity shift from 41-ka cyclicity to 100-ka cyclicity between 1.1 Ma and 0.5 Ma. These features match well with global ice volume variability both in the time and frequency domains (including the Mid-Pleistocene Transition), highlighting global cooling-forced aridity and westerlies climate changes on these timescales. Numerical modeling demonstrates that global cooling can dry MLA and intensify the westerlies, which facilitates dust emission and transport, providing an interpretive framework. Increased dust may have promoted positive feedbacks (e.g., decreasing atmospheric CO₂ concentrations and modulating radiation budgets), contributing to further cooling. Unraveling the long-term evolution of MLA aridity and westerlies climate is an indispensable component of the unfolding mystery of global climate change.

Seepage erosion in loess is closely related to the internal mechanism on which various geological disasters in loess depend. Because of its special microstructure, characteristics such as agglomeration structure and matrix cementation, loess has strong water sensitivity, which also determines that loess has complex and unique seepage erosion characteristics. However, there is still a lack of numerical methods suitable for characterizing loess seepage erosion. Therefore, in this study, a fluid solver is established in PFC program to realize fluid–solid coupling. It can solve Navier–Stokes equation and transfer data between Discrete Element Method (DEM) and Computational Fluid Dynamics (CFD) module. In addition, a parallel bond cementation method based on loess microstructure model is established, which enables the numerical model to simulate the matrix cementation characteristics of loess. Finally, the microscopic parameters of the numerical model are calibrated by macro-mechanical tests, and a numerical seepage model similar to the actual loess is successfully established. The results of actual seepage test and numerical seepage simulation show that the response and mechanism of loess with different dry densities to hydraulic erosion are different. When the dry density is small, the erosion is obvious. It is characterized by the fracture of cementation bond between particles and a large erosion movement distance. With the increase of dry density, erosion gradually decreases. It shows that the contact between particles is slightly deformed and the particles do not move. In addition, with the increase of osmotic pressure, the erosion rate and erosion degree increase.

The soil thickness is very important for investigating and modeling soil-water processes, especially on the Loess Plateau of China with its deep loess deposit and limited water resources. A digital elevation map (DEM) of the Loess Plateau and neighborhood analysis in ArcGIS software were used to generate a map of loess thickness, which was then validated by 162 observations across the plateau. The generated loess thickness map has a high resolution of 100 m × 100 m. The map indicates that loess is thick in the central part of the plateau and becomes gradually shallower in the southeast and northwest directions. The areas near mountains and river basins have the shallowest loess deposit. The mean loess thickness is the deepest in the zones with 400–600-mm precipitation and decreases gradually as precipitation varies beyond this range. Our validation indicates that the map just slightly overestimates loess thickness and is reliable. The loess thickness is mostly between 0 and 350 m in the Loess Plateau region. The calculated mean loess thickness is 105.7 m, with the calibrated value being 92.2 m over the plateau exclusive of the mountain areas. Our findings provide very basic data of loess thickness and demonstrate great progress in mapping the loess thickness distribution for the plateau, which are valuable for a better study of soil-water processes and for more accurate estimations of soil water, carbon, and solute reservoirs in the Loess Plateau of China.

The Water Quality Index (WQI) provides comprehensive assessments in river systems; however, its calculation involves numerous water quality parameters, costly in sample collection and laboratory analysis. The study aimed to determine key water parameters and the most reliable models, considering seasonal variations in the water environment, to maximize the precision of WQI prediction by a minimal set of water parameters. Ten statistical or machine learning models were developed to predict the WQI over four seasons using water quality dataset collected in a coastal city adjacent to the Yellow Sea in China, based on which the key water parameters were identified and the variations were assessed by the Seasonal-Trend decomposition procedure based on Loess (STL). Results indicated that model performance generally improved with adding more input variables except Self-Organizing Map (SOM). Tree-based ensemble methods like Extreme Gradient Boosting (XGB) and Random Forest (RF) demonstrated the highest accuracy, particularly in winter. Nutrients (Ammonia Nitrogen (AN) and Total Phosphorus (TP)), Dissolved Oxygen (DO), and turbidity were determined as key water parameters, based on which, the prediction accuracy for Medium and Low grades was perfect while it was over 80% for the Good grade in spring and winter and dropped to around 70% in summer and autumn. Nutrient concentrations were higher at inland stations; however, it worsened at coastal stations, especially in summer. The study underscores the importance of reliable WQI prediction models in water quality assessment, especially when data is limited, which are crucial for managing water resources effectively.

Loess environments such as the Chinese Loess Plateau are geologically fragile because of their great thickness, loose structure, crisscrossing ravines and gullies, broken terrain, dry climate, severe erosion and unevenly distributed rainfall. As a consequence, loess areas are highly prone to environmental problems and geological hazards. The geological structure of the loess is one of the main factors that controls occurrence of these geohazards. This study investigated the mechanism of loess landslides and their sliding control mode from the perspective of their geological structure. Using this mechanism, a three-dimensional geological model of loess landslides was established. The study shows that the structural planes in loess divide a complete slope into separate blocks, which enables the fast and deep infiltration of surface water via seepage channels and reduces the shear strength of the soil mass, inducing landslides. The development and formation of loess landslides are primarily controlled by structural planes and influenced by infiltrated water softening the structural plains. Various types of structural planes may combine and form structural bodies of different types and scales, which control the type, depth and scale of loess landslides.

Loess slopes with steep gradients are particularly prone to vertical tension cracks at the crest, resulting from unloading and other factors. These cracks significantly affect the spatiotemporal distribution of moisture infiltration during rainfall, potentially leading to slope instability. This study investigates the impact of crest-tension cracks on moisture infiltration in loess slopes under extreme rainfall conditions, focusing on crack position, depth, and width. Soil moisture content and the dynamics of wetting fronts were monitored to assess how these tension cracks influence infiltration patterns. The results indicate that tension cracks at the slope crest act as preferential infiltration pathways, causing water retention within the cracks and forming a “U-shaped” preferential infiltration zone. The extent of this “U-shaped” wetting front is influenced by the crack’s width, depth, and proximity to the slope shoulder; wider, deeper cracks closer to the shoulder result in a more pronounced wetting front. Over time, as rainfall persists, the influence of preferential infiltration decreases, and the infiltration patterns of slopes with crest cracks begin to resemble those of homogeneous slopes. In both cases, wetting fronts exhibit intersecting patterns: one parallel to the slope crest and the other parallel to the slope surface. During the initial stages of rainfall, the migration speed of wetting fronts in slopes with crest-tension cracks was significantly higher than in homogeneous slopes. However, after prolonged rainfall, the migration speeds of wetting fronts in both scenarios converged. A strong linear correlation was observed between the average migration depth of the horizontal wetting front at the slope crest and the parallel wetting front on the slope surface, for both slope types. These findings deepen our understanding of moisture migration dynamics in loess slopes with crest-tension cracks, providing insights for developing effective slope hazard mitigation strategies.