Search Results (266)

Soil erosion is a global issue—with gully erosion recognized as one of the most important forms of land degradation. The purpose of this study is to compare and contrast the outcomes of four machine learning models, Classification and Regression (CART), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machine (SVM), used for mapping susceptibility to soil gully erosion. The controlling factors of gully erosion in the Piraí Drainage Basin, Paraíba do Sul Middle Valley were analysed by image interpretation in Google Earth and gully erosion samples (n = 159) were used for modelling and spatial prediction. The XGBoost and RF models achieved identical results for the area under the receiver operating characteristic curve (AUROC = 88.50%), followed by the SVM and CART models, respectively (AUROC = 86.17%; AUROC = 85.11%). In all models analysed, the importance of the main controlling factors predominated among Lineaments, Land Use and Cover, Slope, Elevation and Rainfall, highlighting the need to understand the landscape. The XGBoost model, considering a smaller number of false negatives in spatial prediction, was considered the most appropriate, compared to the Random Forest model. It is noteworthy that the XGBoost model made it possible to validate the hypothesis of the study area, for susceptibility to gully erosion and identifying that 9.47% of the Piraí Drainage Basin is susceptible to gully erosion. Furthermore, replicable methodologies are evidenced by their rapid applicability at different scales. Full article

Soil erosion is a global environmental problem, and soil conservation is the prevention of soil loss from erosion. The Ten Kongduis (kongdui is the translation of “short-term flood gullies” in Mongolian) are ten tributaries in the upper Inner Mongolia section of the Yellow River Basin. The study of the spatial and temporal variability in soil conservation in the Ten Kongduis is of extraordinary scientific significance both in terms of the discipline and for the ecological and environmental management of the region. With the InVEST model, the characteristics of the spatial and temporal variations in soil conservation service in the Ten Kongduis since 2000 and how rainfall and land use have influenced soil conservation were analyzed. The results show that both avoided erosion and avoided export varied considerably between years. The minimum values of avoided erosion and avoided export were both in 2015, with values of 17.59 × 10⁶ t and 0.92 × 10⁶ t, respectively. The maximum value of avoided erosion was 57.03 × 10⁶ t in 2020 and that of avoided export was 4.08 × 10⁶ t in 2000. Spatially, avoided export was primarily found in the upper reaches of the east–central portion of the study area, and avoided erosion, with values of >40 t·(ha·yr)⁻¹, was in the upper east–central portion of the study area, followed by the upper west–central portion. The difference between upstream and downstream was larger in the western part of the study area. The effect of rainfall was dominant and positive in both avoided erosion and avoided export. The relationships between the rain erosivity factor and the values of avoided erosion and avoided export were significantly positive. Where more erosion occurs, more erosion is retained. Soil that has been eroded away from slopes under vegetation or other water conservation measures may not necessarily be transported to the stream channel in the current year. These conclusions will help us to have a clearer understanding of where sediments are generated and transported and provide a scientific basis for soil and water conservation and ecosystem safety management of watersheds. Full article

Abstract: In the context of the large-scale management of the Loess Plateau and efforts to reduce water and sediment in the Yellow River, this study focuses on a typical watershed within the Loess Plateau. The potential for vegetation restoration in the Kuye River Basin is estimated based on the assumption that vegetation cover should be relatively uniform under similar habitat conditions. The potential for terrace restoration is assessed through an analysis of topographic features and soil layer thickness, while the potential for silt dam construction is evaluated by considering various hydrological and geomorphological factors. Based on these assessments, the overall potential for soil erosion control in the watershed is synthesized, providing a comprehensive understanding of target areas for ecological restoration within the Kuye River Basin. The study demonstrates that the areas with the greatest potential for vegetation restoration in the Kuye River Basin are concentrated in the upper and middle reaches of the basin, which are in closer proximity to the river. The total potential for terracing is 1013.85 km², which is primarily distributed across the river terraces, farmlands, and gentle slopes on both sides of the riverbanks. Additionally, the potential for the construction of check dams is 14,390 units. The target areas for terracing measures in the Kuye River Basin are primarily situated in the middle and lower reaches of the basin, which are in closer proximity to the river. Conversely, the target areas for forest, grass, and check dams, as well as other small watershed integrated management measures, are predominantly located in the hill and gully areas on the eastern and southern sides of the basin. The implementation of the gradual ecological construction of the watershed, based on the aforementioned objectives, will facilitate the protection, improvement, and rational utilization of soil, water, and other natural resources within the watershed. Full article

Heavy rainfall is the main factor inducing the failure of loess slopes. However, the failure mechanism and mode of terraced loess slopes under heavy rainfall have not been well investigated and understood. This paper presents the experimental study on the deformation and failure of terraced loess slopes with different gradients under extreme rainfall conditions. The deformation and failure processes of the slope and the migration of the wetting front within the slope during rainfall were captured by the digital cameras installed on the top and side of the test box. In addition, the mechanical and hydrological responses of the slope, including earth pressure, water content, pore water pressure, and matric suction, were monitored and analyzed under rainfall infiltration and erosion. The experimental study shows that the deformation and failure of terraced loess slopes under heavy rainfall conditions exhibit the characteristic of progressive erosion damage. In general, the steeper the slope, the more severe the deformation and failure, and the shorter the time required for erosion failure. The data obtained from sensors embedded in the slope can reflect the mechanical and hydraulic characteristics of the slope in response to rainfall. The earth pressure and pore water pressure in the slope exhibit a fluctuating pattern with continued rainfall. The failure mode of terraced loess slopes under extreme rainfall can be summarized into five stages: erosion of slope surface and formation of small gullies and cracks, expansion of gullies and cracks along the slope surface, widening and deepening of gullies, local collapse and flow-slip of the slope, and large-scale collapse of the slope. The findings can provide preliminary data references for researchers to better understand the failure characteristics of terraced loess slopes under extreme rainfall and to further validate the results of numerical simulations and analytical solutions. Full article

Black soil is a precious soil resource, yet it is severely affected by gully erosion, which is one of the most serious manifestations of land degradation. The determination of the location and shape of gullies is crucial for the work of gully erosion control. Traditional field measurement methods consume a large amount of human resources, so it is of great significance to use artificial intelligence techniques to automatically extract gullies from satellite remote sensing images. This study obtained the gully distribution map of the southwestern region of the Dahe Bay Farm in Inner Mongolia through field investigation and measurement and created a gully remote sensing dataset. We designed a multi-scale content structure feature extraction network to analyze remote sensing images and achieve automatic gully extraction. The multi-layer information obtained through the resnet34 network is input into the multi-scale structure extraction module and the multi-scale content extraction module designed by us, respectively, obtained richer intrinsic information about the image. We designed a structure content fusion network to further fuse structural features and content features and improve the depth of the model’s understanding of the image. Finally, we designed a muti-scale feature fusion module to further fuse low-level and high-level information, enhance the comprehensive understanding of the model, and improve the ability to extract gullies. The experimental results show that the multi-scale content structure feature extraction network can effectively avoid the interference of complex backgrounds in satellite remote sensing images. Compared with the classic semantic segmentation models, DeepLabV3+, PSPNet, and UNet, our model achieved the best results in several evaluation metrics, the F1 score, recall rate, and intersection over union (IoU), with an F1 score of 0.745, a recall of 0.777, and an IoU of 0.586. These results proved that our method is a highly automated and reliable method for extracting gullies from satellite remote sensing images, which simplifies the process of gully extraction and provides us with an accurate guide to locate the location of gullies, analyze the shape of gullies, and then provide accurate guidance for gully management. Full article

The gully morphology parameter is an important quantitative index for monitoring gully erosion development. Its extraction method and accuracy evaluation in the “soil-rock dual structure area” are of great significance to the evaluation of gully erosion in this type of area. In this study, unmanned aerial vehicle (UAV) tilt photography data were used to evaluate the accuracy of extracting gully morphology parameters from high-resolution remote sensing stereoscopic images. The images data (0.03 m) were taken as the reference in Zhangmazhuang and Jinzhongyu small river valleys in Yishui County, Shandong Province, China. The accuracy of gully morphology parameters were extracted from simultaneous high-resolution remote sensing stereo images data (0.5 m) was evaluated, and the parameter correction model was constructed. The results showed that (1) the average relative errors of circumference (P), area (A), linear length of bottom (L1), and curve length of bottom (L2) are mainly concentrated within 10%, and the average relative errors of top width (TW) are mainly within 20%. (2) The average relative error of three-dimensional (3D) parameters such as gully volume (V) and gully depth (D) is mainly less than 50%. (3) The larger the size of the gully, the smaller the 3D parameters extracted by visual interpreters, especially the absolute value of the mean relative error (R_mean) of V and D. (4) A relationship model was built between the V and D values obtained by the two methods. When V and D were extracted from high-resolution remote sensing stereo images, the relationship model was used to correct the measured parameter values. These findings showed that high-resolution remote sensing stereo images represents an efficient and convenient data source for monitoring gully erosion in a small watershed in a “soil-rock dual structure area”. Full article

Understanding the effects of short-term artificial revegetation on preventing soil degradation in erosion gullies of black soil areas is essential to choosing the most suitable species of vegetation for controlling the development of erosion gullies. A field experiment with short-term artificial revegetation with herbaceous species (Medicago sativa L., Glycyrrhiza pallidiflora Maxim., Elytrigia repens (L.) Desv. ex Nevski, Rheum palmatum L., Asparagus officinalis L., Trifolium repens L., Bromus inermis Leyss., Elymus dahuricus Turcz.) and a runoff scouring test were conducted in a typical erosion gully in a black soil area. Soil erosion, physicochemical characteristics, and shoot/root characteristics were measured to evaluate the effects of short-term artificial revegetation. Short-term artificial revegetation significantly decreased (p < 0.05) sediment yield by 91.1% ± 7.2% compared with that of bare soil. Soil total nitrogen (TN), total potassium (TP), available phosphorus (AP), cation exchange capacity (CEC), water-stable aggregates > 0.25 mm (WR_0.25), and aggregate mean weight diameter (MWD) and mean geometric diameter (GWD) were significantly correlated with vegetated treatments, indicating they were factors sensitive to short-term artificial revegetation. Except for total potassium (TK), the other soil characteristics decreased in vegetated treatments. In addition to increasing TK, vegetated treatments also increased soil available nitrogen (AN)/TN ratios in the short term. The overall effects of different herbaceous species on soil and water conservation, soil quality, and vegetation growth were evaluated, and Trifolium repens L. is the most suitable for preventing soil degradation in an erosion gully. The results of this study will provide a reference for the restoration and protection of the ecological environment in black soil areas with gully erosion. Full article

There has been a frequent occurrence of tailing dam failures in recent years, leading to severe repercussions. Flood overtopping is an important element contributing to these failures. Nevertheless, there is a scarcity of studies about the evolutionary mechanisms of dam breaches resulting from flood overtopping. In order to fill this knowledge vacuum, this study focused on the evolutionary characteristics and triggering mechanisms of overtopping failures, utilizing the Heshangyu tailings pond as a prototype. The process of overtopping breach evolution was revealed by the conduction of small-scale model testing. A scaled-down replica of the tailings pond was constructed at a ratio of 1:150, and a controlled experiment was conducted to simulate a breach in the dam caused by water overflowing. Based on the results, the following conclusions were drawn: (1) The rise in water level in the pond caused the tailings to become saturated, leading to liquefaction flow and local slope sliding at the initial dam. If the sediment-carrying capacity of the overflowing water exceeded the shear strength of the tailings, water erosion would accelerate landslides on the slope, generating a sand-laden water flow. (2) The breach was primarily influenced by water erosion, which subsequently resulted in both laterally widened and longitudinally deepened breach. As the breach expanded, the sand-carrying capacity of the water flow increased, leading to a faster rate of failure. The breach process of overtopping can be categorized into four distinct stages: gully formation stage, lateral broadening stage of gully, cracks and collapse on the slope surface, and stable stage of collapse. (3) The tailings from the outflow spread downstream in a radial pattern, forming an alluvial fan. Additionally, the depth of the deposited mud first increased and subsequently declined as the distance from the breach grew. The findings of this research provide an important basis for the prevention and control of tailings dam breach disasters due to overtopping. Full article

Benggang erosion is one of the most severe geomorphological hazards occurring on deeply weathered crusts in the hilly regions of southern China. Unraveling the susceptibility and pinpointing the risk areas of Benggang erosion are essential for developing effective prevention and management strategies. This study introduced the Maxent model to investigate Benggang erosion susceptibility (BES) and compared the evaluation results with the widely used Random Forest (RF) model. The findings are as follows: (1) the incidence of Benggang erosion is rising initially with an increase in elevation, slope, topographic wetness index, rainfall erosivity, and fractional vegetation cover, followed by a subsequent decline, highlighting its distinct characteristics compared to typical types of gully erosion; (2) the AUC values from the ROC curves for the Maxent and RF models are 0.885 and 0.927, respectively. Both models converge on elevation, fractional vegetation cover, rainfall erosivity, Lithology, and topographic wetness index as the most impactful variables; (3) both models adeptly identified regions prone to potential Benggang erosion. However, the Maxent model demonstrated superior spatial correlation in its susceptibility assessment, contrasting with the RF model, which tended to overestimate the BES in certain regions; (4) the Maxent model’s advantages include no need for absence samples, direct handling of categorical data, and more convincing results, suggesting its potential for widespread application in the BES assessment. This research contributes empirical evidence to study the Benggang erosion developing conditions in the hilly regions of southern China and provides an important consideration for the sustainability of the regional ecological environment and human society. Full article

Terrace erosion has become increasingly pronounced due to the rising incidence of heavy rainfalls resulting from global climate change; however, the processes and mechanisms governing erosion of loess terraces during such events remain poorly understood. A field investigation was performed following a heavy rainfall event in the Tangjiahe Basin to examine the soil erosion characteristics of loess terraces subjected to heavy rainfall events. The results show that various types of erosion occurred on the terraced fields, including rill, gully, and scour hole in water erosion, and sink hole, collapse, and shallow landslide in gravity erosion. Rill erosion and shallow landslide erosion exhibited the highest frequency of occurrence on the new and old terraces, respectively. The erosion moduli of the gully, scour hole, and sink hole on the new terraces were 171.0%, 119.5%, and 308.7% greater than those on the old terraces, respectively. In contrast, lower moduli of collapse and landslide were observed on the new terraces in comparison to the old terraces, reflecting reductions of 34.2% and 23.4%, respectively. Furthermore, the modulus of water erosion (32,102 t/km²) was 4.5 times that of gravity erosion on the new terraces. Conversely, on the old terrace, the modulus of gravity erosion (8804.1 t/km²) exceeded that of water erosion by 14.5%. Gully erosion and collapse dominated the erosion processes, contributing 67.8% and 9.4% to soil erosion on the new terraces and 38.7% and 34.0%, respectively, on the old terraces. In the study area, the new terraces experienced significantly greater erosion (39,252 t/km²) compared to the old terraces (16,491 t/km²). Plastic film mulching, loose and bare ridges and walls, inclined terrace platforms, and high terrace walls, as well as the developing flow paths, might be the key factors promoting the severe erosion of the terraces during heavy rainfall. Improvements in terrace design, construction technologies, temporary protective measures, agricultural techniques, and management strategies could enhance the prevention of soil erosion on terraces during heavy rainfall events. Full article

Gully erosion poses a significant global concern due to its role in land degradation and soil erosion, particularly pronounced in Northeast China’s diverse agro-geomorphic regions. However, there is a lack of comprehensive studies on gully characteristics, development rates, and the topographic threshold of gully formation in these areas. To address this gap, we selected three different agro-geomorphic watersheds, named HL (Hailun), ML (Muling), and YKS (Yakeshi), with areas of 30.88 km², 31.53 km², and 21.98 km², respectively. Utilizing high-resolution (2.1 m, 2 m) remote sensing imagery (ZY-3, GF-1), we analyzed morphological parameters (length, width, area, perimeter, etc.) and land use changes for all permanent gullies between 2013 and 2023. Approximately 30% of gullies were selected for detailed study of the upstream drainage area and gully head slopes to establish the topographic threshold for gully formation (S = a·A^−b). In HL, ML, and YKS, average gully lengths were 526.22 m, 208.64 m, and 614.20 m, respectively, with corresponding widths of 13.28 m, 8.45 m, and 9.32 m. The gully number densities in the three areas were 3.14, 25.18, and 0.82/km², respectively, with a gully density of 1.65, 5.25, and 0.50 km km⁻², and 3%, 5%, and 1% of the land has disappeared due to gully erosion, respectively. YKS exhibited the highest gully head retreat rate at 17.50 m yr⁻¹, significantly surpassing HL (12.24 m yr⁻¹) and ML (7.11 m yr⁻¹). Areal erosion rates were highest in HL (277.79 m² yr⁻¹) and lowest in YKS (105.22 m² yr⁻¹), with ML intermediate at 243.36 m² yr⁻¹. However, there was no significant difference in gully expansion rate (0.37–0.42 m yr⁻¹) among the three areas (p > 0.05). Differences in gully development dynamics among the three regions were influenced by land use, slope, and topographic factors. The topographic threshold (S = a·A^−b) for gully formation varied: HL emphasized drainage area (a = 0.052, b = 0.52), YKS highlighted soil resistance (a = 0.12, b = 0.36), and the parameters a and b of ML fell within the range between these of HL and YKS (a = 0.044, b = 0.27). This study has enriched the scope and database of global gully erosion research, providing a scientific basis for gully erosion prevention and control planning in Northeast China. Full article

Gully erosion is a serious environmental threat, compromising soil health, damaging agricultural lands, and destroying vital infrastructure. Pinpointing regions prone to gully erosion demands careful selection of an appropriate machine learning algorithm. This choice is crucial, as the complex interplay of various environmental factors contributing to gully formation requires a nuanced analytical approach. To develop the most accurate Gully Erosion Susceptibility Map (GESM) for India’s Raiboni River basin, researchers harnessed the power of two cutting-edge machine learning algorithm: Extreme Gradient Boosting (XGBoost) and Random Forest (RF). For a comprehensive analysis, this study integrated 24 potential control factors. We meticulously investigated a dataset of 200 samples, ensuring an even balance between non-gullied and gullied locations. To assess multicollinearity among the 24 variables, we employed two techniques: the Information Gain Ratio (IGR) test and Variance Inflation Factors (VIF). Elevation, land use, river proximity, and rainfall most influenced the basin’s GESM. Rigorous tests validated XGBoost and RF model performance. XGBoost surpassed RF (ROC 86% vs. 83.1%). Quantile classification yielded a GESM with five levels: very high to very low. Our findings reveal that roughly 12% of the basin area is severely affected by gully erosion. These findings underscore the critical need for targeted interventions in these highly susceptible areas. Furthermore, our analysis of gully characteristics unveiled a predominance of V-shaped gullies, likely in an active developmental stage, supported by an average Shape Index (SI) value of 0.26 and a mean Erosivness Index (EI) of 0.33. This research demonstrates the potential of machine learning to pinpoint areas susceptible to gully erosion. By providing these valuable insights, policymakers can make informed decisions regarding sustainable land management practices. Full article

The Pisha sandstone area in the Yellow River Basin is one of the regions with the most severe soil erosion in China and globally, and its erosion is particularly challenging to control. W-OH, a hydrophilic polyurethane material, possesses controllable degradation properties. It can react with water to achieve soil stabilization and erosion resistance during the curing process. The material has been successfully utilized in erosion control in Pisha sandstone areas. This study aims to investigate the impact of W-OH material on water/fertilizer retention and plant growth through experiments on soil hardness, permeability, soil evaporation, soil column leaching, pot tests, and a small-scale demonstration in practical engineering applications. The results indicate that different concentrations of W-OH solution can effectively permeate Pisha sandstone, solidifying the particles to create a flexible and porous consolidation layer on the surface with a specific depth. As the W-OH concentration (3%, 4%, and 5%) increases, the harnesses of the consolidation layer also increase but remain below 1.5 kPa, which does not impede plant root growth. The soil evaporation rate decreased by approximately 45.2%, 45.8%, and 50.3% compared to the control group. The reduction rates of cumulative total nitrogen (TN) content are around 43.57%, 48.14%, and 63.99%, and, for cumulative total phosphorus (TP), are approximately 27.96%, 45.70%, and 61.17% under the 3%, 4%, and 5% concentrations of W-OH solution, respectively. In the pot tests, concentrations of W-OH solution below 5% are suitable for germination and growth of monocotyledons, while the optimal concentration for dicotyledons is around 3%. In the demonstration, the vegetation coverage of the treated gully increases by approximately 11.35%. This research offers a promising and effective approach to enhance ecological restoration in Pisha sandstone areas. Full article

The seasonal Xiangka debris flow, breaking out frequently in Xinghai County, Qinghai Province, poses a serious threat to resident safety, has significant potential economic impacts, and inflicts severe damage on the geological environment, vegetation, and land resources in the area. Therefore, a susceptibility assessment is crucial. Utilizing data from field investigations, meteorology, and remote sensing, this study devised an assessment system using 10 evaluation factors with pronounced regional characteristics as susceptibility indices. Based on data processing using ArcGIS 10.7 and MATLAB R2016B, this study assessed the susceptibility of the Xiangka debris flow using AHP, the fuzzy comprehensive evaluation method, and a cloud model. The analysis results show that, based on AHP, the primary index affecting the occurrence of Xiangka debris flow is mainly source factor (0.447). The secondary indices are mainly the length ratio of the mud sand supply section (0.219), fractional vegetation cover (FVC, 0.208), and watershed area (0.192). Combined with the actual characteristics, it can be seen that the formation conditions of the Xiangka debris flow primarily encompass the following: sources such as slope erosion and accumulation at gully exits, challenging topography and terrain conducive to the accumulation of water and solid materials, and water source aspects like surface runoff from intense rainfall. Based on the fuzzy mathematical method—fuzzy coordinate method—cloud model, it is concluded that the degree of susceptibility is mild-to-moderate. The combination of these methods provides a new idea for the evaluation of debris flow susceptibility. This study can provide a theoretical basis for the layout of treatment engineering and geological disaster prevention in this area and promote the sustainable development of the ecological environment. Full article

The formation and evolution of management gullies is a highly intense process of soil erosion often overlooked in policies and river basin strategies. Despite the worldwide spread of the phenomenon, our ability to assess and simulate gullying and its impacts remains limited; therefore, predicting the development and evolution of these river reaches represents a significant challenge, especially in areas where the loss of productive soil or the hazards linked to landslides or floods represent critical factors. Our study demonstrates how an exclusively morphometric approach, based on the construction of the hypsometric curve and applied to small hydrographic basins that are lithologically homogeneous and hierarchized according to the Strahler classification method, is able to predict the triggering height of the gullies; this height corresponds to the mean elevation of the basin and the inflection point of the hypsometric curve itself, confirming the hypothesis that this point coincides with the point at which a sudden change in surface runoff energy occurs, The study also shows that the portion of the basin necessary to trigger these intense erosive processes is always within a small range, regardless of the size and morphology (slope) of the basin itself. Such an approach, which is quick and relatively easy to apply, could help develop hydrogeological hazard mitigation practices in land planning projects. Full article