In the loess tableland, gully slope instability induces severe soil erosion and land degradation, yet the synergistic effects of dominant vegetation under varying restoration modes combined with dynamic rainfall regimes and topographic variations on gully slope stabilization mechanisms remain inadequately quantified. Therefore, the dominant vegetation species under natural (NR) and artificial restoration (AR) was chosen as the object. Through field sampling, root-soil complex mechanical experiments, and numerical simulations, the protection effect of dominant vegetation under different restoration modes combination with rainfall and topographic variations was investigated. The result revealed significant differences in basic soil physical properties, root morphological characteristics, root and root-soil complex mechanical properties among five dominant vegetated plots under the different restoration modes (P < 0.05). The soil properties in the Scop plot under AR were slightly better than those in the other plots. The roots in the Spp plot developed better under NR. The shear strength of Lespedeza bicolor Turcz. was the highest under NR. The tensile strength of Digitaria sanguinalis (L.) Scop. was greatest under AR. The tensile force and tensile strength of single roots exhibited a significant positive linear correlation and a significant negative exponential correlation, with root diameter, respectively (P < 0.01). For the unstable gully slopes (F-s < 1.0), maximum displacement occurred at the slope foot, where tensile shear failure dominated, while the interior experienced compressive yielding. The grey relational analysis identified rainfall intensity as the primary destabilizing factor, followed by dominant vegetation species, slope height, and slope gradient. Notably, when rainfall intensity reaches or exceeds 0.06 m/h, or when slope height exceeds 20 m combined with long-duration rainfall, the regulatory impacts of dominant vegetation under different restoration modes on the gully slope stability are substantially diminished and become negligible. This study provides a theoretical basis for gully slope protection and ecological environmental construction in loess tableland.

Engineered loess-filled gullies, which are widely distributed across China's Loess Plateau, face significant stability challenges under extreme rainfall conditions. To elucidate the regulatory mechanisms of antecedent rainfall on the erosion and failure processes of such gullies, this study conducted large-scale flume experiments to reveal their phased erosion mechanisms and hydromechanical responses under different antecedent rainfall durations (10, 20, and 30 min). The results indicate that the erosion process features three prominent phases: initial splash erosion, structural reorganization during the intermission period, and runoff-induced gully erosion. Our critical advancement is the identification of antecedent rainfall duration as the primary pre-regulation factor: short-duration (10-20 min) rainfall predominantly induces surface crack networks during the intermission, whereas long-duration (30 min) rainfall directly triggers substantial holistic collapse. These differentiated structural weakening pathways are governed by the duration of antecedent rainfall and fundamentally control the initiation thresholds, progression rates, and channel morphology of subsequent runoff erosion. The long-duration group demonstrated accelerated erosion rates and greater erosion amounts. Concurrent monitoring demonstrated that transient pulse-like increases in pore-water pressure were strongly coupled with localized instability and gully wall failures, verifying the hydromechanical coupling mechanism during the failure process. These results quantitatively demonstrate the critical modulatory role of antecedent rainfall duration in determining erosion patterns in engineered disturbed loess, transcending the prior understanding that emphasized only the contributions of rainfall intensity or runoff. They offer a direct mechanistic basis for explaining the spatiotemporal heterogeneity of erosion and failure observed in field investigations of the engineered fills. The results directly contribute to risk assessments for land reclamation projects on the Loess Plateau, underscoring the importance of incorporating antecedent rainfall history into stability analyses and drainage designs. This study provides essential scientific evidence for advancing the precision of disaster prediction models and enhancing the efficacy of mitigation strategies.

Gully erosion on agricultural land severely damages land resources and affects agricultural production. Topographic features, tillage methods, and roads are major elements constituting the farmland landscape, but the effect of their distribution in the farmland on the gully erosion is still unclear. This study examined the long-term impacts of changes in the farmland environment and climate change on gully erosion over a long temporal scale of nearly 60 years, the results showed that farmland reclamation over the past 60 years had led to a 2324.2 % increase in gully length density and a 3563.3 % increase in gully area density. The increase in annual rainfall amount and the frequency of extreme rainstorms had led to a rapid increase of gully erosion intensity in the last decade, with an average development rate in length density and area density of 61.5 m km- 2 and 778.7 m2 km- 2, respectively. Farmlands with slope aspects between 135 and 270 degrees were more prone to gully erosion, which was related to the redistribution of snow on hillslopes caused by prevailing wind directions. Tillage methods and roads simultaneously affect gully erosion, with newly formed gullies located in farmlands and roadsides accounting for 63.0 % and 29.8 %. Gullies in regions where the angle between furrows and unpaved roads exceeded 70 degrees accounted for 61.1 % of the total roadside gullies. Over the last decade, the annual average increase of gully length and area was 9.8 m yr-1 and 246.1 m2 yr-1. The development rate of gully area was significantly correlated with the drainage area.

The problem of unpaved road erosion is prominent in the Loess Plateau hilly and gully region. Unpaved roads contribute substantially to watershed sediment due to their high soil bulk density, low infiltration rates and extensive network. In this study, a field investigation was conducted on typical unpaved roads within a typical watershed in this region, focusing on assessing the damage state, annual soil loss and the factors influencing erosion in a comparatively wet year. The results showed that the soil erosion from unpaved roads was very severe, with an annual erosion intensity of 470 t hm(-2), following three heavy rain events and two rainstorm events in the summer of 2022. The main unpaved roads (MUR) suffered the most severe road erosion, with 22.2 % of road segments experiencing severe erosion with classical gullies. The erosion gullies on the road had an average depth of 16.1 cm and an average width of 36.5 cm, with the widest being 146.0 cm and the deepest being 174.0 cm. The road erosion intensity was significantly related to drainage area, road area, road length and coverage. Road erosion reduced significantly when the land use in the drainage areas of the road was covered with shrub or grass, or road surface was covered with grass or gravel. Our findings offer valuable insights for road construction and erosion prevention in similar terrains.

In the black soil region of Northeast China, the issue of gully erosion persists as a significant threat, resulting in extensive damage to farmland, severe degradation of the black soil, and decreased productivity. It is therefore of utmost importance to accurately identify areas that are susceptible to gully erosion to effectively prevent and control its negative impact. This study tried to utilize geographical detectors (geodetectors) as a means to identify the factors that contribute to the distribution of gullies and assess the risk of gully erosion (GER) in five catchments within the region, with areas ranging from approximately 80 km(2)-- km(2) . By employing the geodetectors method, fourteen geo-environmental factors were analyzed, including topographic attributes (such as aspect, catchment area, convergence index, elevation, plan curvature, profile curvature, slope length, slope, stream power index, and topographic wetness index), channel network distance, vegetation index (NDVI and EVI), as well as land use/ land cover (LULC). The modeling of GER was conducted using the random forest algorithm (RFA). Out of the fourteen examined geo-environmental factors, only a subset, comprising less than or equal to 50%, demonstrated a significant (p < 0.05) influence on the spatial distribution of gullies. These selected factors were sufficient in assessing GER, with LULC (mean q-value 1 / 4 0.270) and elevation (mean qvalue 1 / 4 0.113) identified as the two most important factors. Furthermore, the RFA exhibited satisfactory performance across all catchments, achieving AUC values ranging from 0.712 to 0.933 (mean 1 / 4 0.863) in predicting GER. Overall, the catchment areas were classified into high, moderate, low, and very low-risk levels, representing 9.67%-15.95%, 19.28%-26.08%, 24.59%-30.55%, and 30.54%-39.08% of the total area, respectively. Importantly, a significant positive linear relationship (r(2) = 0.722, p < 0.05) was observed between the proportion of cropland area and the occurrence of high-level GER. Although the primary risk levels were categorized as low and very low, the proportion of high-risk levels exceeded the existing gully coverage (0.34%-3.69%). These findings highlight the substantial potential for gully erosion and underscore the necessity for intensified efforts in the prevention and control of gully erosion within the black soil region of Northeast China. (c) 2024 International Research and Training Center on Erosion and Sedimentation, China Water and Power Press, and China Institute of Water Resources and Hydropower Research. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY- NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

To reduce the potential threat of soil loss due to ephemeral gullies, it is crucial to adopt Best Management Practices (BMPs) that prevent damage to landscapes by reducing sediments load. The current research evaluated the impact of five BMPs, including cover crops, grassed waterways, no-till, conservation tillage, and riparian buffer strips for reduction of sediment load from sheet/rill, and ephemeral gully erosion in an agricultural watershed in Southern Ontario, Canada. The study aimed to automatically calibrate AnnAGNPS using genetic algorithm and the most sensitive parameters of the model identified using a combination of Latin Hypercube Sampling (LHS) and One-At-a-Time (OAT) approach. It also utilized the calibrated model to simulate the effectiveness of BMPs in reducing the average seasonal and annual sediment loads from both sources of erosion (sheet/rill, and ephemeral gully) to determine the most effective practices. Riparian buffer strips were consistently successful in decreasing average seasonal sediment load of sheet/rill erosion, with an average reduction efficiency of 72 % in Spring, 64 % in Summer, 65 % in Fall, and 76 % in Winter. In terms of reducing average seasonal sediment load from ephemeral gully erosion, grassed waterways proved to be the most effective BMPs. They showed efficiency of 90 % in Spring; 83 % in Summer; 79 % in Fall; and 75 % in Winter. Considering the average annual sediment load, riparian buffer strips were consistently successful in decreasing average annual sediment load of sheet/rill erosion, with 69% reduction efficiency. Similarly, grassed waterways were the most effective BMPs for reducing average annual sediment load of ephemeral gully erosion, with an efficiency of 81 %. Additionally, grassed waterways were found to be the most efficient BMPs for reducing average annual total sediment load with reduction efficiency of 71 %. These results demonstrate the importance of implementing effective BMPs to address ephemeral gully erosion in watersheds where ephemeral gullies are the main source of erosion.

Gully erosion is a significant natural hazard and a form of soil erosion. This research aims to predict gully formation in the Kalshour basin, Sabzevar, Iran. Employing the Information Gain Ratio (IGR) index, we identified 13 key factors out of 22 for modeling, with elevation emerging as the most influential factor in gully formation. The study evaluated the performance of individual machine learning algorithms and ensemble algorithms, including the Functional Tree (FT) as the main classifier, Bagging (Bagg), AdaBoost (Ada), Rotation Forest (RoF), and Random Subspace (RSS). Using a data set of 400 gully and non-gully points obtained through field investigations (70% for training and 30% for testing), the RoF model achieved an area under the curev (AUC) value of 0.99, indicating its high predictive ability for gully-susceptible areas. Other algorithms also performed well (Ada: 0.90, FT: 0.92, RSS: 0.94, Bagg: 0.95). However, the RoF algorithm with the functional tree as the main classifier (RoF_FT) demonstrated the highest ability in gully classification and susceptibility mapping, enhancing the functional tree's performance. In addition to AUC, the RoF_FT model achieved an F1 score of 0.89 and an MCC of 0.78 on the validation set, indicating a high balance between precision and recall, and a strong correlation between predicted and actual classes, respectively. Similarly, other models showed robust performance with high F1 scores and MCC values, but the RoF_FT model consistently outperformed them, underscoring its robustness and reliability. The resulting gully erosion-susceptibility map can be valuable for decision-makers and local managers in soil conservation and minimizing damages. Implementing proactive measures based on these findings can contribute to sustainable land management practices in the Kalshour basin.Recommendations Gully erosion threat: Gully erosion poses a significant threat to soil, with far-reaching environmental consequences. Predictive modeling: This research focuses on predicting gully formation in the Kalshour basin, Sabzevar, Iran, using advanced machine learning algorithms. Key findings for decision-makers: The study evaluates the performance of various machine learning algorithms and ensemble algorithms, with the Functional Tree serving as the main classifier. This not only enhances our ability to predict gully formation but also provides a valuable tool for decision-makers and local managers in soil conservation. Impact on sustainable land management: By offering a gully erosion-susceptibility map, the research empowers decision-makers to implement proactive measures, minimizing damage and contributing to sustainable land management practices. Interdisciplinary approach: The study's combination of geospatial analysis, machine learning, and soil conservation aligns with the journal's mission to advance understanding in environmental modeling.

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.

Gully erosion damages land resources and endangers human productivity and life, making it a key issue in global research on soil erosion nowadays. Gully headcut retreat (GHR) is the main form of gully erosion. Tiny concave features can be found in many retreating gully heads worldwide, and they are referred to as niche terrain in this study. To investigate the association between niche terrain and GHR, relevant research was reviewed on niches and stability analysis of gully heads with niches was modelled and analysed. Studies have shown that not all niches worldwide are identical due to regional differences in internal material-external environmental conditions. Special soil properties, joints, and cracks are the internal material conditions that lead to the formation of niche. External conditions include climate conditions, vegetation conditions, and topography. Water is the driving force for the formation of niche, while vegetation and topography are key factors. Niches can be regarded as the initial stage of GHR in areas where gully erosion is intense. In general, GHR is a composite cyclical process dominated by hydraulic erosion in the early stage and gravitational erosion in the late stage, including niche formation, inward concave formation, free face formation, overhanging soil collapse, and niche reformation. In this study, a model of gully head stability is applied, and it is found that the stability-based factor of safety decreases exponentially with increasing niche height and crack depth, increases exponentially with increasing niche angle, and decreases quadratically with increasing catchment slope. Summarizing the common characteristics of niche terrains worldwide can facilitate the study of the evolution of gully erosion globally. Niches can be regarded as the initial stage of gully head retreat. The mechanism of niches varies with regional internal material-external environmental conditions. Gully head retreat is a composite cycle process dominated by early hydraulic erosion and later gravity erosion. image

Erosion is an ongoing environmental problem that leads to soil loss and damages ecosystems downstream of agriculture. Increasingly frequent heavy precipitation causes single erosion events with potentially high erosion rates owing to gully erosion. In this study, analyses of croplands affected by heavy precipitation and linear erosion indicate that erosion occurs only on sparsely vegetated fields with land cover <= 25% and that slope gradient and length are significant factors for the occurrence of linear erosion tracks. Existing erosion models are not calibrated to the conditions of heavy precipitation and linear erosion, namely high precipitation intensities and long and steep croplands. In this study, natural linear erosion was analyzed using an unmanned aerial vehicle and erosion volumes were determined for 32 rills and gullies of different sizes. Comparisons with the RUSLE2 and EROSION-3D model values showed an underestimation of linear erosion in both models. Therefore, calibration data for erosion models used for heavy precipitation conditions must be adapted. The data obtained in this study meet the required criteria.