Aeolian Research最新文献

The evolution of saltating tracks driven by strong wind remains unknown due to the low accuracy or recall rates of saltating particle tracking algorithms (SPTs). Manual identification of saltating tracks becomes a primary bottleneck because of low efficiency, restricting the development of new SPTs with high accuracy. Herein, we proposed an optimized tree model for automatically identifying saltating tracks in the high-speed video under strong wind through establishing the dataset with multiple statistical quantities of instant saltating velocity (MSQV) and the workflow embracing the Tree-structured Parzen Estimator (TPE). The optimized Categorical Boosting model by the D3 dataset (CatBoost-D3) could be considered the best classifier among the tree models, owning the higher accuracy (0.9352), precision (0.9348), recall (0.9352), F1-score (0.9350) and area under an receiver operating characteristics curve (AUC, 0.9730), and lower time cost. The best performances were associated with the ensemble effect of critical and secondary features, distinct from the previous finding which revealed only the effect of critical features on enhancing AUC value. Additionally, one observed that the present model was comparable to other optimized tree model by the dataset with double-class and outperformed the other tree model by the dataset with multi-class. The present work offers a new avenue for identifying hop trajectories and tracking sand particle flow via machine learning in the future, and a new channel for reunderstanding the relationship between midair collision and saltation under strong wind through automatic identification of saltating tracks.

The southern margins of the northern European loess belt on the foothills of Eastern Sudetes Mountains are less explored sedimentation zones. This study provides new data about the development of aeolian silty-sandy sediments overlying the glaciofluvial succession on the rugged topography near the village of Kolnovice. The Kolnovice sand quarry (360 × 200 m), which lies at the margin of the upland plateau, is the only active-mined outcrop on the foothills of the Eastern Sudetes and is large enough to study Pleistocene (peri-)glacial sediments. To examine the origin of these sediments, we applied lithofacies analysis (both macro-description of outcrop walls and micromorphological study of thin sections) and surface analysis of quartz grains. Periglacial structures have been identified within the sediments, allowing us to further interpret the post-sedimentary evolution of the sedimentary succession. The studied sediments resulted from colluvial redeposition of aeolian sediments, which was controlled particularly by the topography, glaciofluvial substrate, and climatic conditions. The underlying glaciofluvial sediments are the most crucial source of the studied sediments, although the fine-grained material could have been transported from more distant areas.

Soil erosion by water and wind is a critical challenge for sustainable management of catchments in drylands and accurate spatial information can help in mitigation of its destructive consequences. Here, seven machine learning (ML) models were applied to map simultaneously the water and wind erosions in the Bakhtegan catchment, south Iran, with three dried lakes in its southern part and three dams established in upstream parts of the lakes. The analysis identified 10 and 11 effective variables controlling water and wind erosions, among 20 and 17 potential variables, respectively, via the MARS feature selection algorithm. According to the most accurate ML models (artificial neural network for water erosion, and Cubist for wind erosion), an integrated model was developed to map soil erosion by water and wind simultaneously. Permutation feature importance (PFI) and Shapley additive exPlanation (SHAP) interpretation techniques were employed to explain the model outputs, revealing that 19.7 % of the total area belonged to high and very high susceptibility classes to soil erosion by water and wind. The PFI plot revealed that the slope and wind speed were the most influencing factors for water and wind erosion, respectively. According to SHAP decision plot, slope had the highest contribution on the predictive water erosion model’s output, whereas vegetation cover exhibited the highest contribution on the predictive wind erosion model’s output. Due to climate change and intensified drought during the recent years, as well as due to construction of dams upstream of the lakes, the southern part of the study area was converted to a source of sand and dust storms. The hotspots with severe water erosion are distributed all over the study area, rendering it quite vulnerable to adverse climate change projections.

The loess accumulation processes in the Azov Sea region leaves a record of atmospheric circulation trends in southern Russia, which can be used to explore aeolian dynamics and atmospheric circulation evolution. However, the historical aeolian transportation and accumulation processes of the loess deposits in this region remain controversial, which limits our understanding of aeolian dust dynamics. In the present study, based on grain size analysis and scanning electron microscopy imaging, grain size end-member and microtextural characteristics of loess sediments in the Beglitsa section of the Sea of Azov were studied to reveal their sedimentary environments and processes. According to the results, the Beglitsa section exhibits typical characteristics of aeolian sediment. EM analysis revealed that the Sea of Azov loess is composed of materials from both distant and proximal sources transported by high-altitude westerly and mesoscale regional winds, respectively. Particle shape and morphology indicated that the Azov loess materials have experienced wind and flow action. The application of the two methods revealed that the formation of the Azov loess is a complex process from source to sink. It results from the combined effects of high-altitude westerly winds, low-altitude local wind systems, and near-surface air flow in the course of development, which is also influenced by sea-level rise and fall. The results of the present study lay a foundation for the interpretation of historical aeolian dynamics and environmental significance of the Azov loess.

Sand dunes are a landscape feature with a quick response time to climate change and human influences (e.g. grazing, greening projects, and fixation structures). Their migration rates and their development can help to gather information about changing environmental conditions over time. The Source Area of the Yellow River (SAYR), located upon the Tibetan Plateau, is highly complex with topographical, hydrological, and climatological influences on active dunes, making it a good study area for these interactions. Based on remote sensing datasets, spanning the last 54 years, 415 dunes were mapped for migration rate calculations. Further, climate data from ERA-5 reanalysis and a local climate station was used to assess their changes within a changing climate. Generally, dune migration rates are rather slow with an average of 3.62 m y^-1. In accordance, the averaged resultant drift potential (RDP) values are lower than 10 m3/s⁻³(−|-). Further, we assessed the density development of the main active barchan dune field in direct premise of the Yellow River. Throughout the past 54 years, we observed the emergence of more than 5 new barchans per square kilometer. This increase is likely attributed to higher sand flux from the Yellow River, which has resulted from increased discharge due to declining snowfall and rising precipitation levels.

Dust events are caused by strong winds that lift dust particles into the air. Due to surrounding deserts and agriculture, West Texas experiences many dust events. This study examines dust events that occurred between 2000 and 2020 across four locations: Amarillo, Lubbock, Midland, and El Paso. A total of 1,834 dust events were identified across the four locations with an average of 22 dust events annually. 227 dust events were observed in Amarillo, 609 in Lubbock, 545 in Midland, and 453 dust events were observed in El Paso. A slight increasing trend of dust events over time was observed for Amarillo, Lubbock, and Midland while El Paso showed a decreasing trend. Most dust events occurred during the spring to early summer months and they lasted an hour or less. Many dust events occurred during times of drought and periods of La Niña. Separation of the dust events based on the meteorological disturbance that caused them (convective vs. synoptic) showed that synoptic disturbances contribute to >60 % of the dust events, while convective disturbances were responsible for most of the remaining. Synoptic disturbances were predominately in spring while convective disturbances were common in the early summer months. A comparison of meteorological parameters measured during each disturbance shows that synoptic dust events were associated with lower temperatures, dew point, and relative humidity, but with higher wind speeds and gusts.

The floodplain of the Yellow River (FPYR) is threatened by severe soil erosion. Soils are often susceptible to wind erosion owing to their coarse-textures and weak aggregation, yet studies are yet to describe the ability of soils to resist wind erosion in this region. Accordingly, this study aimed to quantify how soil wind erosion potential is affected by soil aggregate properties, such as dry aggregate geometric mean diameter (GMD), aggregate geometric standard deviation (GSD), aggregate stability, and soil bulk density, and to assess the effects of soil type, crop rotation, irrigation, fertilization, and tillage treatments on these aggregate properties in the main wind erosion area across the FPYR. Significant differences in GMD and aggregate stability were found between crop rotation treatments, whereas crop rotation marginally affected the soil bulk density. Further, the impact of management practices on aggregate properties differed for each soil type. The soil aggregate erodible fraction (EF) in the FPYR ranged from 1.14 to 82.73% across sites, with a mean of 26.14% across soil types and management practices, which was lower than that previously reported in other wind erosion regions. We incorporated these measured EFs into the Revised Wind Erosion Equation (RWEQ) to evaluate the wind erosion risk of the FPYR. The results indicated that the central FPYR was more susceptible to wind erosion than the other regions, although the total wind erosion potential in the FPYR was small. Adoption of soil conservation practices could help minimize wind erosion and improve atmospheric quality in the region.