Influence Soil Erosion Research Articles

Quantitative Evaluation of Soil Erosion in Loess Hilly Area of Western Henan Based on Sampling Approach

The terrain in the loess hilly area of western Henan is fragmented, with steep slopes and weak soil erosion resistance. The substantial soil erosion in this region results in plenty of problems, including decreased soil productivity and ecological degradation. These problems significantly hinder the social and economic development in the region. Soil conservation planning and ecological development require accurate soil erosion surveys. However, the studies of spatio-temporal patterns, evolution, and the driving force of soil erosion in this region are insufficient. Therefore, based on a multi-stage, unequal probability, systematic area sampling method and field investigation, the soil erosion of the loess hilly area of western Henan was quantitatively evaluated by the Chinese Soil Loss Equation (CSLE) in 2022. The impact forces of soil erosion were analyzed by means of a geographic detector and multiple linear regression analysis, and the key driving factors of the spatio-temporal evolution of soil erosion in this region were revealed. The results were as follows. (1) The average soil erosion rate of the loess hilly area in western Henan in 2022 was 5.94 t⋅ha−1⋅a−1, with a percentage of soil erosion area of 29.10%. (2) High soil erosion rates mainly appeared in the west of Shangjie, Xingyang, and Jiyuan, which are related to the development of production and construction projects in these areas. The areas with a high percentage of soil erosion area were in the north (Xinan and Yima), west (Lushi), and southeast (Songxian and Ruyang) of the study area. Moreover, areas with the most erosion were found in forest land, cultivated land, and areas with a slope above 25°. (3) At the landscape level, the number and density of patches of all land types, except orchard land, increased significantly, and the boundary perimeter, landscape pattern segmentation, and degree of fragmentation increased. (4) The geographical detector and multiple linear regression analysis indicated that the driving forces of soil erosion are mainly topographic and climatic (slope length, elevation, precipitation, and temperature). Soil erosion was significantly influenced by the density of landscape patches. These maps and factors influencing soil erosion can serve as valuable sources of information for regional soil conservation plans and ecological environment improvements.

Regulatory mechanism of soil and water conservation measures on understorey erosion in a subtropical hilly region

Vegetation restoration affects soil erosion by altering near soil-surface characteristics and hydrodynamic mechanisms. However, the regulatory mechanisms of vegetation restoration in reducing soil erosion under forests are not fully clear. Five soil and water conservation measures (SWCM) with different vegetation structures and characteristics were used in the pure forest of Pinus massoniana which included the grass and shrub, grass, grass and shrub + level furrow, grass, shrub and trees and grass + fish-scale pits, to analyze the impact of vegetation restoration on near soil-surface characteristics and soil erosion. The data were analyzed using Structural Equation Modeling (SEM) to find the key indicators affecting soil erosion under forest. The findings revealed that, as opposed to the control plots (CK), there were significant alterations in the near soil-surface attribute following the application of SWCM. These changes were characterized by an increase in soil porosity, soil water content, soil nutrient content, root biomass, litter, and vegetation cover, and a decrease in soil compaction, disintegration coefficient, and bulk density, with the most significant improvement occurring in 0–10 cm soil layer. The SWCM significantly reduced soil erosion, with runoff and soil loss reduction ranging from 60.46 % to 74.09 % and 67.62 % to 79.99 %, respectively. Structural equation models revealed the influence of SWCM on soil erosion. Specifically, soil water content and litter had a favourable influence on reducing soil erosion, root biomass had a direct positive impact on soil erosion, and vegetation cover directly leads to a reduction in soil erosion. Soil physical properties primarily influenced soil erosion through their effect on vegetation cover. Combining bioengineering and vegetation measures is superior at enhancing soil structure, improving nutrient content, and decreasing soil erosion compared to single vegetation measures. It is recommended to combine bioengineering with vegetation strategies to effectively curb understory forest erosion and enhance soil quality in pine forests.

Evaluation of soil erosion in the Changhua River Basin on Hainan Island based on the Chinese soil loss equation model

Soil erosion is one of the most serious ecological and environmental problems facing southern China. The Changhua River Basin on Hainan Island is affected by soil erosion, which is causing the soil environment to become more fragile. Compared with the Revised Soil Erosion Equation (RUSLE), the Chinese Soil Loss Equation (CSLE) is based on a large amount of Chinese local data and research results, which more accurately reflect the actual situation of soil erosion in China and therefore have better accuracy and applicability in the Chinese region. By combining GIS and RS technologies, this study establishes the CSLE model of the Changhua River Basin, quantifies the soil erosion data via image elements from 2020 to 2022 using the spatial interpolation method, classifies the erosion intensity, and analyzes the spatial and temporal change characteristics of soil erosion. The statistical results show that, during the period from 2020 to 2022, the area of slight erosion in the Changhua River Basin increased by 553.25 km2, with a rate of change of 15.83 %, and the areas of mild erosion, moderate erosion, intense erosion, very intense erosion, and severe erosion decreased by 446.42 km2, 64.4 km2, 25.73 km2, 11.25 km2, and 5.45 km2, respectively, with rates of change of −31.05 %, −30.08 %, −36.58 %, −18.02 %, and −13.85 %, respectively. Slight erosion is defined as soil erosion less than the permissible soil loss and is not regarded as soil erosion, and the other erosion intensities showed a yearly decreasing trend, indicating that the soil erosion control was effective during this three-year period. In the work of soil and water conservation, it is especially necessary to determine the main factors influencing soil erosion and predict the areas that may be prone to such erosion. Therefore, on the basis of establishing a characteristic model using land use type, slope and soil type, and through superposition analysis, we obtained the spatial and temporal change characteristics of soil erosion. The research results are as follows: (1) slight erosion is mainly concentrated in forested areas, and forested land has a better capacity for soil and water conservation; (2) mild, moderate, and strong erosion mainly occur in cultivated areas and areas with a slope of 0–5°; (3) areas of built land and areas with a slope of 8°–15° are more prone to intense erosion, although they cover a smaller area; (4) when the slope is greater than 15°, the overlap range with the forest area is larger and the slope is no longer the main factor leading to soil erosion. Thus, it can be seen that forest land significantly reduces the impact of soil erosion. (5) among the different soil types, Technosol, Ferralsol and Fluvisol all have less than 55 per cent uneroded area and are generally less erosion-resistant, while Lixisol and Acrisol are relatively more susceptible to a high degree of erosion hazard (Extremely strong erosion, severe erosion).

Soil erodibility and hillslope erosion processes affected by vegetation restoration duration

Restoring vegetation is an effective way to control regional erosion as well as reduce soil erodibility. However, it is not clear how the vegetation restoration duration affects soil erodibility and how it further influences soil erosion processes. Therefore, the soil physicochemical properties and comprehensive soil erodibility index (CSEI) at five sampling sites with 3, 20, 55, 80 and 100 years of vegetation restoration were investigated in this study. A simulated rainfall with intensities of 60, 90, and 120 mm h−1 was conducted on three slopes with gradients of 10°, 20°, and 30° by using rare earth element oxides (Ho2O3 and Sm2O3) as tracers to quantify interrill and rill erosion. The results revealed a decreasing trend in both the CSEI and sediment concentration with increasing vegetation restoration duration. Compared to that at the site with 3 years of vegetation restoration, the CSEI at the sites with 20, 55, 80, and 100 years of restoration was reduced by 35.2 %, 39.7 %, 92.8 %, and 67.1 %, respectively. Interrill erosion dominated the hillslope erosion processes and contributed more than 76.9 % to the total erosion amount. By comparing the measured and estimated erosion rates using the equations provided by the Water Erosion Prediction Project (WEPP), significant prediction errors were found. Therefore, relationships among the CSEI, slope gradient and rainfall intensity were established for interrill and rill erosion rate estimation in vegetation restoration areas. This study provides a theoretical basis for evaluating the soil and water conservation benefits of vegetation restoration and for improving soil erosion prediction models within the context of vegetation restoration.

A 44-year balanced fertilizer application affected rill erosion resistance by changing humus, aggregates, and polyvalent cation

Fertilizer application can affect the physicochemical properties of soil, such as the contents of large aggregates, humus, and exchangeable cations, thereby influencing soil erosion resistance. However, the rill erosion resistance and its key influencing factors of soil following long-term balanced fertilizer application remains unclear. This study aimed to analyze the change in rill erosion resistance following 44 years of balanced fertilizer application (No changes in the type of fertilizer) to non-calcareous soils and establish a Partial Least Squares Regression (PLSR) model of rill erodibility (kd) and soil critical shear stress (τc) to changes in the physical and chemical properties of the soil. Five treatments were designed: (1) CK (no fertilizer applied), (2) N (nitrogen), (3) NP (nitrogen plus phosphorus), (4) NK (nitrogen plus potassium), and (5) NPK (nitrogen, phosphorus, and potassium). Compared to CK, the N, NP, NK, and NPK application significantly increased τc by 49.6, 96.7, 73.6, and 36.2 %, respectively. Whereas, kd increased significantly only in the NPK treatment group. The optimal partial least squares regression model showed that mean weight diameter (MWD) had the greatest positive influence on soil critical shear stress, followed by fulvic acid (FA) content, whereas water-dissolved substances had a negative influence. Long-term balanced fertilizer application can increase MWD and τc by combining micro-aggregates and humus into large aggregates. Ca2+ content had the greatest positive effect on kd. Compared with that of CK, exchangeable Ca2+ content increased significantly with NP and NPK application (7.9 and 34.3 %, respectively). Ca2+ can increase kd by binding to the polar functional groups in FA to promote the shedding of hydration shells in large aggregates. Among all treatments, the NP treatment showed the best performance for reducing kd and increasing τc. This study could contribute to the understanding of the rill erosion process and modeling in non-calcareous soils and offer a reference for agricultural erosion control treatments.

Unveiling the threshold in forest patch shapes to soil retention ecosystem services

Soil erosion is a critical process that leads to landscape degradation, compromising soil fertility and ecosystem functions. Forest ecosystems, with their intricate characteristics, play a pivotal role in mitigating soil erosion and providing soil retention ecosystem services (SRES). This study explores the impact of forest patch thresholds and critical points on soil erosion rates, focusing on 401 catchments in Poland using generalised additive models to identify thresholds and critical points in forest patches.Landscape metrics were applied to measure landscape structure, including shape, fractal dimension, contiguity, related circumscribing circles, and perimeter-area ratio indexes. These metrics, along with slope, rainfall, organic carbon content, water content, and clay ratio variables, were considered dependent variables in the models. The developed models have demonstrated reliable performance in estimating soil erosion rates, with a significant deviation explained from 80.5 to 81.1 for coniferous forest patches, 79.1 to 80.1 for broad-leave forest patches, and 80.9 to 81.4 for mixed forest patches at p < 0.05.In broad-leaved forests, three thresholds are identified in the shape index, which influence soil erosion rates in a complex manner. For coniferous forests, thresholds in the perimeter area ratio, related circumscribing circles, and contiguity indexes exhibit nonlinear relationships with soil erosion rates. Mixed forests show two thresholds in the related circumscribing circle and one in the fractal dimension index, affecting soil erosion rates differently.This research contributes significantly to understanding the interplay between forest patch shapes and soil erosion rates, providing decision support for land use planning. The identified thresholds and critical points offer valuable tools to enhance sustainable landscape functionality, emphasizing the importance of considering forest landscape structure in preserving soil retention ecosystem services.

Responses of soil microbial biomass carbon and microbial entropy to soil properties in typical sloping croplands of China under erosion conditions

Soil microbial biomass carbon (MBC) and microbial entropy play a crucial role in the carbon cycle of terrestrial ecosystems, while their responses to soil properties in typical sloping croplands under the impact of soil erosion remain poorly understood due to the complexity of the soil erosion process. In this study, we selected typical sloping croplands with different erosion levels for the four severely eroded soil types (black, loess, purple, and red soil) in China to assess the key controls of MBC and microbial entropy under the influence of soil erosion. The results showed that soil erosion significantly reduced the MBC content but increased the microbial entropy of sloping croplands in black soil region (BS) (22 %, 43.6 %), purple soil region (PS) (25.5 %, 26.2 %) and red soil region (RS) (28.9 %, 21.9 %), but not in loess soil region (LS). The soil physicochemical properties had significantly positive and negative correlations on the MBC and microbial entropy, respectively. The MBC and microbial entropy of these sloping croplands had different dominant drivers under soil erosion. Overall, our results revealed that changes in MBC and microbial entropy directly depended on the fundamental properties of the soil and soil erosion could indirectly affect the MBC and microbial entropy by directly affecting the physicochemical properties of soil. Thus, the impact of soil erosion on sloping croplands and the associated responses following changes in MBC and microbial entropy provide fresh insights into predicting the effects of soil erosion on carbon stability.

Plutonium isotopes can be used to model soil erosion in Kenya

Climate change poses an immediate threat to tropical soils with changes in rainfall patterns resulting in accelerated land degradation processes. To ensure the future sustainability of arable land, it is essential to improve our understanding of the factors that influence soil erosion processes. This work aimed to evaluate patterns of soil erosion using the activity of plutonium isotopes (Pu) at sites with different land use and clearance scale in the Winam Gulf catchment of Lake Victoria in Kenya. Erosion rates were modelled at potential erosive sites using the MODERN model to understand small-scale erosion processes and the effect of different management practices. The lowest soil redistribution rates for arable land were 0.10 Mg ha−1 yr−1 showing overall deposition, resulting from community-led bottom-up mitigation practices. In contrast erosion rates of 8.93 Mg ha−1 yr−1 were found in areas where steep terraces have been formed. This demonstrates the significance of community-led participation in effectively managing land degradation processes. Another key factor identified in the acceleration of soil erosion rates was the clearance of land with an increased rate of erosion over three years reported (0.45 to 0.82 Mg ha−1 yr−1) underlining the importance vegetation cover plays in limiting soil erosion processes. This novel application of fallout plutonium as a tracer, highlights its potential to inform the understanding of how soil erosion processes respond to land management, which will better support implementation of effective mitigation strategies.Graphical abstractModelling of soil erosion and deposition patterns using the MODERN model to calculate the depth of soil loss/gain.

Variation in soil erosion rate under typical land uses and vertical zones in an agricultural catchment of the Daliangshan region, Southwest China

AbstractThe Daliangshan region (DLS) is characterized by significant vertical differentiation in human activity and land use owing to the high elevation gradient, which may affect the soil erosion pattern in the vertical direction. However, the spatial variability of soil erosion rates along a hillslope at the catchment scale remains poorly understood. In this study, we used the cesium‐137 tracer technique to estimate soil erosion rates under different land uses and vertical zones from a small agricultural catchment, the Luowugou catchment in the DLS. Ten plots comprising four typical vertical zones (valley, low mountain, middle mountain and sub‐alpine) and five land‐use types (sloping farmland, grassland, abandoned farmland, forest land and horizontal terrace) were selected. In addition, two parallel downslope transects were built in each plot, and soil samples were collected at 3–7 m intervals along these transects. The results indicated that the soil erosion rates on sloping farmland (4.82 kg·m−2·y−1) and grassland (4.09 kg·m−2·y−1) were significantly higher than those on abandoned farmland (0.91 kg·m−2·y−1) and forest land (0.80 kg·m−2·y−1). In contrast, the horizontal terrace showed net deposition, with a deposition rate of 0.62 kg·m−2·y−1. The erosion rates varied across different zones, with the low mountain zone having the highest erosion rate (5.65 kg·m−2·y−1), followed by the middle mountain (2.96 kg·m−2·y−1) and subalpine (1.46 kg·m−2·y−1) zones, and the valley zone having the lowest erosion rate (1.28 kg·m−2·y−1). Furthermore, there were significant correlations (P &lt; 0.05) between the soil erosion rates from different vertical zones and the proportion of sloping farmland, implying that sloping farmland plays a dominant role in shaping soil erosion along a vertical gradient. These comparisons suggest that the highest soil erosion rate occurred in the low mountain zone, indicating that the steeply sloping farmlands, resulting from migration from high‐altitude areas, have intensified soil erosion in the vertical zone. These findings highlight the role of agricultural activities originating from sloping farmlands in influencing soil erosion across different vertical zones, which has important implications for mitigating soil erosion and optimizing agricultural layout in the region.

A New Attempt to Estimate Underground Soil Leakage through High-Density, Fixed-Point Monitoring in a Typical Karst Rocky Desertification Region

Understanding soil loss pathways in karst regions is crucial for erosion control. Combining high-density measurements of grid points with runoff plot monitoring, we attempt to use a new indirect method to study the characteristics of soil loss in karst rocky desertification areas of Salaxi Town, Guizhou province. One cycle year monitoring data of 12640 grid points were applied in the soil loss analysis. This study identifies underground leakage as the primary pathway of soil loss, with an mean soil leakage of 21.51 kg in potential areas, accounting for 83.12%, and an average leakage of 22.69 kg in in mild karst rocky desertification areas accounting for 81.48%. Mixed vegetation types (forest, shrub, and grass) were better at preventing surface soil loss but increased underground leakage compared to single vegetation types. The rainy season significantly influences soil erosion, accounting for 67.88% of total loss, with slight variations among different karst rocky desertification grades and vegetation types. Mean underground leakage rates during the rainy and dry seasons are 63.34% and 36.66%, respectively. Although this method still has certain limitations, it plays a positive role in revealing the mechanism of soil erosion processes in karst regions.

Exploring the relationship between soil erosion and hydraulic parameters on slopes with clipped herbaceous vegetation through Bayesian network modeling

AbstractClipping management, which alters vegetation conditions by removing aboveground vegetation while preserving the underground root system, directly impacts hydrological processes and flow dynamics, ultimately affecting soil erosion processes. This study conducted field experiments (2 × 6 m) encompassing four clipping intensities (with vegetation coverage of 70%, 50%, 25%, and 0%), three rainfall intensities (60, 90, and 120 mm·h−1), and three slope gradients (10°, 20°, and 30°). The results showed that clipping treatments significantly reduced the Darcy–Weisbach resistance coefficient (f). Elevated levels of clipping intensity, rainfall intensity, and slope gradient led to increased flow velocity (v), Reynolds number (Re), and stream power (ω). The shear stress (τ) exhibited an upward trend with rising slope and rainfall intensity, with no significant difference in the effect of clipping intensity. Variation partitioning analysis demonstrated that the influence of steep slopes amplified the effects of rainfall intensity while diminishing the impact of clipping intensity on v values. Critically, the Bayesian network model suggested that, in comparison to the influence of raindrop splashing, soil detachment and transportation by runoff were the predominant driving mechanisms for erosion on slopes with clipped vegetation. Rainfall intensity and clipping intensity were found to raise the runoff depth and enhance the v value, which ultimately influenced soil erosion. Overall, these results contribute to an improved comprehension of the hydraulic dynamics of soil erosion on slopes with clipped vegetation and provide invaluable perspectives for developing effective clipping management strategies to ensure sustainable land utilization and judicious water resource governance.

Simulation of topographic effects on soil erosion and deposition in a small watershed of loess hilly region

AbstractTopography plays a critical role in soil migration and redistribution, but few studies have been conducted to quantify its effects on sediment deposition. In this study, we established a physical simulation and analysis framework to investigate the erosional and depositional impacts of two‐dimensional slope terrain, specifically applied to Xiannangou small watershed in the loess hilly region. The results showed that the slope gradient, slope length, and slope shape have significantly influence the distribution of soil erosion and deposition. The magnitude of the erosion/deposition rate (Yr) determines the relative intensity of slope erosion and deposition, where Yr &lt; 0 indicates erosion and Yr &gt; 0 signifies deposition. The erosion rate on straight slope exhibited a positive correlation with slope length, while the erosion/deposition rate on concave and convex slopes exhibited fluctuations with slope length. Soil erosion predominantly occurred along the main flow line and the middle slope, aligning with the observed distribution of gully and slope erosion in the field. The sediment deposition was primarily concentrated on the lower slope or the lowest outlet of the basin, notably in gullies and gentle slopes where the terrain slows, especially during transition from steep to gradual slopes. These results can effectively predict the relative erosion/sedimentation rate of two‐dimensional slopes, significantly contributing to a comprehensive understanding of how topography influences soil erosion and deposition. This study thoroughly considers the role of sediment deposition in the soil erosion process, providing a more accurate reflection of soil erosion/deposition in small watersheds. It addresses the existing deficiency in sediment consideration within soil erosion evaluation and supports the enhancement of soil erosion model.

Spatiotemporal Variation in Wind Erosion in Tarim River Basin from 2010 to 2018

The Tarim River Basin, China’s largest inland river basin, is renowned for its ecological fragility characterized by concurrent greening and desertification processes. Soil wind erosion emerges as a critical factor impacting the natural ecosystem of this region. This study employs a soil wind erosion model tailored to cultivated land, grassland, and desert terrains to analyze the multitemporal characteristics of and spatial variations in soil wind erosion across nine subbasins within the Tarim River Basin, utilizing observed data from 2010, 2015, and 2018. Additionally, this study investigates the influence of various factors, particularly wind speed, on the soil wind erosion dynamics. Following established standards of soil erosion classification, the intensity levels of soil erosion are assessed for each calculation grid within the study area alongside an analysis of the environmental factors influencing soil erosion. Findings indicate that approximately 38.79% of the total study area experiences soil wind erosion, with the Qarqan River Basin exhibiting the highest erosion modulus and the Aksu River Basin registering the lowest. Light and moderate erosion predominates in the Tarim River Basin, with an overall decreasing trend observed over the study period. Notably, the Qiemo River Basin, Dina River Basin, and Kaidu Kongque River Basin display relatively higher proportions of eroded area compared to their total subbasin area. Furthermore, this study underscores the substantial influence of the annual average wind speed on soil erosion within the study area, advocating for prioritizing soil and water conservation programs, particularly in the downstream regions of the Tarim River Basin, to mitigate future environmental degradation.

Spatiotemporal Variability in Rainfall Erosivity and Its Teleconnection with Atmospheric Circulation Indices in China

Rainfall erosivity (RE) is a critical factor influencing soil erosion, and soil erosion is closely related to land ecosystem health and long-term sustainable utilization. To ensure regional stable food supply and ecological balance, it is crucial to study the spatiotemporal distribution and influencing factors of RE. This study focuses on China and its three natural regions using daily precipitation data from 611 stations from 1960 to 2020. The study analyses the spatiotemporal changes in RE. Rainfall events were classified as moderate, large, and heavy based on rainfall intensity. The RE contribution from different rainfall levels to the total RE was analyzed, and the key climatic drivers closely linked to RE were identified using random forest. The results demonstrate that (1) on a national scale, RE shows a significant increasing trend, marked by an 81.67 MJ·mm·ha−1·h−1/decade. In the subregions, the Eastern Monsoon Region (EMR) and Qinghai–Tibet Plateau Region (QTR) show a significant increasing trend, with a greater change rate in EMR of 108.54 MJ·mm·ha−1·h−1/decade, and the Northwest Arid Region (NAR) shows a nonsignificant upwards trend. (2) The average RE increases northwest–southeast nationwide, ranging from 60.15 MJ·mm·ha−1·h−1 to 31,418.52 MJ·mm·ha−1·h−1. The RE contribution generated by different rainfall levels to the total RE exhibits spatial variations. The dominant types show that EMR is influenced by heavy RE, NAR is dominated by large RE, and QTR is affected by moderate RE. (3) The REs are associated with teleconnection indices, but the impact of these indices varies in different regions. The Western Hemisphere Warm Pool has the greatest impact on the EMR, while the North Atlantic Oscillation and Atlantic Multidecadal Oscillation are the factors influencing RE in NAR and QTR, respectively. (4) On a national scale, for every 1 mm increase in annual total rainfall, the RE increased by 8.54 MJ·mm·ha−1·h−1, a sensitivity of 8.54 MJ·mm·ha−1·h−1/mm. For the three subregions, there are differences in the sensitivity of RE to changes in annual precipitation. The highest sensitivity is found in EMR, at 8.71 MJ·mm·ha−1·h−1/mm, which is greater than the sensitivity indices in NAR (6.19 MJ·mm·ha−1·h−1/mm) and QTR (3.60 MJ·mm·ha−1·h−1/mm). This study can provide theoretical references for future regional soil erosion prediction and sustainable agricultural development in China.

Mapping of soil erosion susceptibility using advanced machine learning models at Nghe An, Vietnam

Abstract Soil Erosion Susceptibility Mapping (SESM) is one of the practical approaches for managing and mitigating soil erosion. This study applied four Machine Learning (ML) models, namely the Multilayer Perceptron (MLP) classifier, AdaBoost, Ridge classifier, and Gradient Boosting classifier to perform SESM in a region of Nghe An province, Vietnam. The development of these models incorporated seven factors influencing soil erosion: slope degree, slope aspect, curvature, elevation, Normalized Difference Vegetation Index (NDVI), rainfall, and soil type. These factors were determined based on 685 identified soil erosion locations. According to SHapley Additive exPlanations (SHAP) analysis, soil type emerged as the most significant factor influencing soil erosion. Among all the developed models, the Gradient Boosting classifier demonstrated the highest prediction power, followed by the MLP classifier, Ridge classifier, and AdaBoost, respectively. Therefore, the Gradient Boosting classifier is recommended for accurate SESM in other regions too, taking into account the local geo-environmental factors.

Exploring driving factors of soil erosion using a Multiscale GWR model: a case study at Central Citarum Watershed, West Java, Indonesia

To address challenges in soil erosion management and ecological rehabilitation, understanding the determinants of soil erosion is crucial. This research aims to achieve two primary objectives: (1) delineating the spatial patterns of soil erosion within the designated region and (2) identifying the influential factors using the Multiscale Geographical Weighted Regression (MGWR) methodology. The methodological framework involved the creation of grid datasets, with soil erosion as the response variable and a combination of physical and socioeconomic attributes as predictors. We extracted 550 data points from raster datasets, specifically centered on village locations, using the ‘extract multi-value to point’ tool in ArcGIS. The R Studio environment was utilized to select the relevant factors influencing soil erosion. The geographical detector technique was applied to determine the explanatory power of each determinant concerning the spatial patterns of soil erosion. Subsequently, data from the Ordinary Least Squares (OLS) model underwent MGWR analysis. The findings reveal that the Central Citarum Watershed experiences an estimated annual soil erosion of 23.16 million tons, averaging 102.01 tons per hectare. The analysis identified LS (slope length and gradient) and CP (vegetative cover and supportive practices) as the primary variables influencing the spatial variability of soil erosion. Notably, the MGWR model demonstrated enhanced explanatory capacity and effectiveness compared to both the OLS and Geographically Weighted Regression (GWR) methodologies.

Soil erosion prediction using Markov and CA-Markov chains methods and remote sensing drought indicators

Climate change and reduced rainfall in the past decade have resulted in an alarming increase in soil erosion within arid and semi-arid regions, including southern Iran. Given the significance of this issue, our research aimed to predict soil erosion in the southwest of Fars province, Iran, by utilizing climatic indicators and remote sensing. To determine the key indicators of drought influencing soil erosion, the principal component analysis (PCA) method was employed. Subsequently, Markov chains and Cellular Automata Markov chain (CA-Markov) were utilized to forecast soil erosion and drought conditions in 2040. The findings revealed a steady rise in drought frequency within the region from 2000 to 2020. Notably, meteorological indices and meteorological drought exhibited strong correlations with the Standard Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Index (SPI) (RSPEI = 0.98 and RSPI = 0.97). The correlation analysis between soil erodibility indices and drought identified Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) as significantly linked to erosion rates. The soil erosion predictions using Markov and CA-Markov chains in 2040 indicated that approximately 38% of the region faces erosion risk based on the NDVI index, while around 47% face risk based on the EVI index. Moreover, the southern and eastern regions are projected to experience increased erosion due to the combination of low rainfall and high drought in the upcoming years. These results underscore the profound impact of drought on critical soil properties, including soil moisture, texture, and the adhesion of soil particles. Consequently, drought-induced soil erosion may lead to greater wastage and ecological repercussions. By leveraging remote sensing drought indicators and their influence on soil erosion, effective land management practices can be implemented to prevent soil erosion and mitigate its adverse effects on the ecological potential of watersheds.

Lithology‐mediated soil erodibility characteristics after vegetation restoration in the karst region of Southwest China

AbstractEcological restoration projects have significantly increased global vegetation cover and reduced soil erosion. However, it is very challenging to clarify the complex soil erosion mechanisms of limestone and dolomite in the southwest karst region and to identify the key factors affecting erosion. The study site has a subtropical monsoon climate with precipitation concentrated during the rainy season from May to September. In this study, four plantation restoration measures with a recovery time of approximately 16 years were selected, which included arbor forest, orchard, grassland, and cropland (control). Soil physical–chemical properties and soil erodibility K values were used to evaluate the soil erosion characteristics. The results showed that both limestone and dolomite exhibited lower soil bulk density as well as higher capillary porosity, and soil water‐stable aggregates after revegetation. The limestone and dolomite K values were reduced by 12%–15% and 15%–17%, respectively. However, the K value of limestone was 17.9% higher than that of dolomite, indicating that dolomite exhibited a higher stability. Through redundancy analysis and structural equation modeling, revegetation was found to reduce soil erosion by influencing the soil particle composition. The silt was the key factor influencing soil erosion, accounting for 84.4% and 78.2% of the variation in the limestone and dolomite K values, respectively. These findings suggest that vegetation restoration enhances soil erosion resistance; however, the effectiveness of restoration is controlled by the lithology in the southwest karst region. These findings provide a reference for soil and water management and vegetation restoration.

A new method for disentangling the coupling effect of slaking and mechanical breakdown on aggregate stability: Validation on splash erosion

Aggregate breakdown strongly influences soil erosion process, during which slaking and mechanical breakdown are two dominant breakdown mechanisms. Despite of many methods on aggregate stability, there is a paucity of satisfactory one to disentangle how these two mechanisms interact in aggregate breakdown. Herein, on the basis of Le Bissonnais method (1996) including three treatments (i.e., fast wetting (FW), stirring after pre-wetting (WS), and slow wetting (SW)), a new treatment of water-stirring after fast wetting (SF) was proposed in order to evaluate the coupling effect of slaking and mechanical breakdown on aggregate stability. The coupling effect of slaking and mechanical breakdown was larger to a varying extent than their individual effects, and its difference with slaking showed a unimodal variation with increased aggregate stability. This new method can partition the unique and shared effects of these two breakdown mechanisms; the shared effect (0–77%) decreased logarithmically with increased aggregate stability; the unique effect of slaking (16–52%) showed a unimodal variation and much larger than that of mechanical breakdown (0–17%). As validated by previously published splash erosion data over a wide range of soils (including various soil types, land uses, textures and parent materials), the proposed aggregate stability indices in this new method showed better performance in predicting splash erosion compared to existing ones (e.g., RSI×RMI and RSI/RMI). Collectively, this new method facilitates a systematic understanding on aggregate breakdown mechanisms and exhibits great superiority in aggregate stability measurement and erosion prediction.

Rainfall erosivity in the Republic of North Macedonia: Fournier index approach

Rainfall erosivity is a crucial factor influencing soil erosion, which results from the detachment, transportation, and deposition of soil particles caused by rainfall and runoff. Rainfall erosivity assessment is a fundamental process aimed at quantifying the erosive power of rainfall events in a given region. The paper provides an overview of rainfall erosivity assessment in several heterogeneous regions of the Republic of North Macedonia based on rainfall data from meteorological stations characterized by different climatic and geographical conditions. Having into consideration that rainfall erosivity can be quantified by using various indices, this study uses two common ones: Fournier Index (FI) and the Modified Fournier Index (MFI) based on monthly and annual precipitation totals for the period 1951-2020. The results imply that in general, the studied stations belong to a low class of erosivity. It is found that FI has greater sensitivity and provides more details, also showing years with high and even very high rainfall erosivity while MFI gives more information for moderate rainfall erosivity.