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[Objective] The aims of this study are to assess the accuracy of soil erodibility K calculated by different methods in the key soil loss areas of Anhui Province, and to refine each calculation method based on the measured erodibility K. [Methods] The Nomo equation, modified Nomo equation, EPIC model, DG model and Torri model were utilized to estimate the soil erodibility K values. Based on monitoring data from runoff plots in Huoshan County, Guangde County, Yuexi County and She County, the actual erodibility factor K values were obtained to evaluate the effectiveness of each method. [Results] The soil erodibility K values in Huoshan County, Guangde County, Yuexi County and She County were 0.033~0.035, 0.018, 0.021 and 0.041 (thm² h)/(hm² MJ mm), respectively. The differences in soil erodibility K values derived from different methods were significant, with all methods greatly overestimating the K values. The overall ranking of the methods in terms of soil erodibility followed the order: K Torri> K Noma> KM-Nomo >K DG> K Epic. The methods of calculating K values for each were improved, in which the improved Nomo equation and the modified Nomo equation showed superior performance. [Conclusion] The improved Nomo equation and modified Nomo equation are recommended to apply in the key soil loss areas of Anhui Province. [ABSTRACT FROM AUTHOR]

Riverbank erosion is a significant and distinct problem in the floodplains of alluvial rivers in North East India. The Barak River has experienced an alarming increase in bank erosion rate over the last few decades, resulting in embankment breaches and biodiversity loss, but there is a dearth of field studies to evaluate riverbank fluvial erosion. This study aims to assess the river bank erosion and Vulnerability Assessment of the Barak River in India using an in-situ submerged Jet Erosion Test (JET). The riverbank erosion was estimated for a span of the riverbank on one side of the stream using the excess shear stress equation and impinging jet theory. Data was collected using a JET along the riverbank to determine the erodibility parameter of the bank soil. The results show that the spatial variation in erosion parameters of river banks varies significantly, which is dependent on the specific location. Annual bank erosion was computed using measured erodibility parameters and stage record data, which shows the bank erosion of the Barak River will occur in many places, particularly at the critical area. The measured bank erosion was compared with the observed satellite imagery map for the 2000–2020. This study shows that JET results should be used with caution; further, the findings can be helpful in planning river training and management strategies for vulnerable areas and may serve as a model for similar alluvial river studies. [ABSTRACT FROM AUTHOR]

Water erosion is one of the most extensive processes of soil and land degradation. This process significantly deteriorates the quality of ecosystem services provided. Studying the mechanism and consequences of this phenomenon will help develop strategies to mitigate its impact on the environment. One of the challenges in studying water erosion is the high cost of conducting field research over large areas. Another challenge is the limitation of existing models, which are often developed for specific regions. Our research aims to address these problems by adapting the widely used RUSLE2 model to local conditions. Beijing was chosen as the study area due to its rich information resources and extensive results from field measurements of soil water erosion. Calculations were performed using a raster data model, which included a slope angle model, slope length, soil erodibility, rainfall erosion potential factors from precipitation and snowmelt, land use types, and vegetation cover management factors. All data were taken from open sources. The average soil erosion in the studied area was 25 t · ha–1 per year. The discrepancy with other studies was less than 1%. The modified RUSLE2 model showed good results, correlating with other studies in this area. [ABSTRACT FROM AUTHOR]

The spatiotemporal variability of soil erosion in Crimea in the periods of 1958–1988 and 1989–2018 is estimated on the basis of RUSLE. The erosion rate varies from very slight to very high in the region. The most eroded areas are confined to the Southern Crimea mountains mainly corresponding to a combination of a high rainfall erosivity (R-factor) and relatively steep slopes (LS-factor). Soil loss in the first period slightly exceeded the similar value after 1989 approximately 13%, while the proportion of moderately to very highly eroded areas varied within the range of less than 1%. These changes are related to both the reduction of agricultural cultivated lands and the variability of soil erosion factors. The soil erosion formation is mainly due to the factors of rainfall erosivity, slope steepness, as well as the cover-management factor in Crimea. Based on the comparison of the actual suspended sediment yield in the gauges with the soil erosion values, most river areas are characterized by the accumulation of eroded material when no more than 50% of the washed-out products reach the gauges. [ABSTRACT FROM AUTHOR]

Soil erodibility (K) refers to the inherent ability of soil to withstand erosion. Accurate estimation and spatial prediction of K values are vital for assessing soil erosion and managing land resources. However, as most K-value estimation models are empirical, they suffer from significant extrapolation uncertainty, and traditional studies on spatial prediction focusing on individual empirical K values have neglected to explore the spatial pattern differences between various empirical models. This work proposed a universal framework for selecting an optimal soil-erodibility map using empirical models enhanced by machine learning. Specifically, three empirical models, namely, the erosion-productivity impact calculator model (K_EPIC), the Shirazi model (K_Shirazi), and the Torri model (K_Torri) were used to estimate K values. Random Forest (RF) and Gradient-Boosting Decision Tree (GBDT) algorithms were employed to develop prediction models, which led to the creation of three K-value maps. The spatial distribution of K values and associated environmental covariates were also investigated across varying empirical models. Results showed that RF achieved the highest accuracy, with R2 of K_EPIC, K_Shirazi, and K_Torri increasing by 46%, 34%, and 22%, respectively, compared to GBDT. And distinctions among environmental variables that shape the spatial patterns of empirical models have been identified. The K_EPIC and K_Shirazi are influenced by soil porosity and soil moisture. The K_Torri is more sensitive to soil moisture conditions and terrain location. More importantly, our study has highlighted disparities in the spatial patterns across the three K-value maps. Considering the data distribution, spatial distribution, and measured K values, the K_Torri model outperformed others in estimating soil erodibility in the plateau lake watershed. This study proposed a framework that aimed to create optimal soil-erodibility maps and offered a scientific and accurate K-value estimation method for the assessment of soil erosion. [ABSTRACT FROM AUTHOR]

Soil hydrology seriously affects the prevention of desertification in karst areas. However, water infiltration in the different soil layers of secondary forests and artificial forests in karst areas remains uncertain. This lack of clarity is also the factor that constrains local vegetation restoration. Therefore, monitoring and simulating the priority transport of soil moisture will help us understand the shallow soil moisture transport patterns after artificial vegetation restoration in the local area, providing a reference for more scientific restoration of the ecological environment and enhancement of carbon storage in karst areas. The integration of soil physical property assessments, computed tomography (CT) scanning, dye tracing studies, and HYDRUS-2D modeling was utilized to evaluate and contrast the attributes of soil macropores and the phenomenon of preferential flow across various forestland categories. This approach allowed for a comprehensive analysis of how the soil structure and water movement are influenced by different forest ecosystems and infiltration head simulations (5 mm, 15 mm, 35 mm, and 55 mm) to elucidate the dynamics of water movement across diverse soil types within karst regions, to identify the causes of water leakage due to preferential flow in secondary forests, and to understand the mechanisms of water conservation and reduction in artificial forests adopting a multifaceted approach. This study demonstrated that (1) the soil hydrological capacity of a plantation forest was 20% higher than a natural forest, which may be promoted by the clay content and distribution. (2) Afforestation-enhanced soils in karst regions demonstrate a significant capacity to mitigate the loss of clay particles during episodes of preferential flow and then improve the soil erosion resistance by about 5 times, which can effectively control desertification in karst area. (3) The uniform distribution of macropores in plantation forest soil was conducive to prevent water leakage more effectively than the secondary forest but was incapable of hindering the occurrence of preferential flow. The secondary forest had a very developed preferential flow phenomenon, and soil clay deposition occurred with an increase in depth. (4) Moreover, the results for preferential flow showed that the matrix flow depth did not increase with the increase in water quantity. Short-term and high-intensity heavy rainfall events facilitated the occurrence of preferential flow. Infiltration along the horizontal and vertical directions occurred simultaneously. These results could facilitate a further understanding of the contribution of the plantation to soil amelioration and the prevention of desertification in karst areas, and provide some suggestions for the sustainable development of forestry in karst areas where plantation restoration is an important ingredient. [ABSTRACT FROM AUTHOR]

Landslides caused by earthquakes bring about dramatic changes in soil erodibility. In order to understand the change characteristics of soil erodibility during a vegetation restoration period after the 5.12 Wenchuan earthquake, a non-landslide area, landslide area, and transition area in Leigu Town, Beichuan County were selected as research areas. Field soil sampling, geostatistics, and spatial interpolation were used to explore the spatiotemporal changes in soil physicochemical properties and soil erodibility during a natural restoration in 2013 (5 years after the earthquake) and in 2022 (14 years after the earthquake). The results showed that the comprehensive soil erodibility index (CSEI) was mainly composed of five soil factors, which were soil pH, soil total nitrogen (TN), mean weight diameter of soil aggregates (MWD), fractal dimension of soil water stable aggregates (D), and soil erodibility (Kepic). The CSEI of the landslide area was slightly lower than that of the non-landslide area. The CSEI was gradually increasing during the process of natural restoration after earthquake. From 2013 to 2022, the increase rates of the CSEI were 6.9%, 10.0%, and 41.5% for the landslide area, non-landslide area, and transition area, respectively. Along attitude segments, the spatial distribution of soil erodibility in 2022 is more uniform than that in 2013. The higher value of CSEI was located in the upper part of research areas. The spatial distribution of the CSEI in 2013 and 2022 appeared as a moderate autocorrelation. The variable ranges of CSEI in 2013 and 2022 were about 20 m. In the early stage of vegetation restoration, soil and water conservation engineering was recommended in the landslide area. [ABSTRACT FROM AUTHOR]

The Tiga Dam, a primary hydraulic structure in northern Nigeria, is subjected to intense hydrological stress during the rainy season, posing potential risks to its structural integrity. This study investigates the geotechnical properties and stability of the Tiga Dam in Kano State, Nigeria. Twelve soil samples from the downstream area were analyzed for specific gravity, grain size distribution, Atterberg limits, compaction parameters, permeability, and shear strength. The dam's stability was assessed using Plaxis 2D under various reservoir conditions. Soil erodibility was evaluated using the Revised Universal Soil Loss Equation (RUSLE), and a linear regression model with noise was developed to predict soil expansion rates. The results showed heterogeneous soil properties, with specific gravity ranging from 2.11 to 2.63 and permeability from 3.40 × 10−9 to 1.49 × 10−7 m/s. Stability analysis revealed factors of safety of 1.322, 1.006, 1.002, and 1.147 for high reservoir, rapid drawdown, slow drawdown, and low reservoir conditions, respectively. The RUSLE K factor ranged from 0.055 to 0.145, indicating low to moderate soil erodibility. The expansion rate model demonstrated high accuracy (R2 = 0.989) in predicting seasonal and long-term soil expansion trends, with peak rates increasing from 16.94 mm/month in 2010–2013 to 19.45 mm/month in 2017–2020. This comprehensive analysis provides crucial insights into the Tiga Dam's geotechnical behavior, highlighting potential vulnerabilities and the need for targeted management strategies to ensure long-term stability and safety. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Soil & Water Conservation (1009-2242) is the property of Institute of Soil & Water Conservation and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Global climate change and overgrazing are driving shifts in the plant composition of grassland communities, which may profoundly affect the function of grassland ecosystems in regulating runoff and soil erosion. Here, we examined the shift effects of normal hillslope alpine meadow to shrub and severely degraded meadow states on runoff and sediment generation under natural rainfall conditions, and determined the contributions of plant and soil properties changes to soil erodibility, runoff and sediment generation by in situ rainfall experiment and monitoring on the hillslope of Qinghai-Tibetan Plateau. The results showed that normal meadow shift into severely degraded meadow state, mean weight diameter, soil saturated hydraulic conductivity, soil cohesion and soil erodibility K-factor at the topsoil decreased by 70.3%, 73.1%, 80.3% and −13.1%, respectively, and when normal meadows shift into shrub meadow state, they reduced by 49.1%, −1.3%, 49.4%, and −8.3%, respectively. Runoff and soil loss significantly changed by - 40.0% and 177.8% when normal meadow shifted into a severely degraded meadow state, while runoff and soil loss significantly changed by + 65.0% and +77.8% when normal meadow shifted into a shrub meadow state. Our findings highlight that the two divergent shifts both increased soil loss compared to the normal hillslope alpine meadows. Overall, our results indicate that the divergent shifts of normal alpine meadows exacerbated soil erodibility and soil loss of hillslope alpine meadows. These results obtained here offer a novel perspective on the regulation of runoff and soil erosion in the alpine meadow ecosystem.

[Objective] To understand the variations in soil erodibility and nutrient content caused by different slope positions and land uses, and to discuss the influence of various factors on soil erodibility and nutrient status. [Methods] Soil and root samples were collected, and the Comprehensive Soil Erodibility Index (CSEI) and Comprehensive Soil Nutrient Index (CSNI) were calculated using a weighted sum method under different slope positions and land uses. [Results] (1) There were differences in both CSEI and CSNI among different slope positions. The highest value of CSEI was recorded on the slope crest (0.653) and the lowest value was at the bottom of the slope (0.275), while the highest value of CSNI was found on the slope crest (0.715) and the lowest value was at the top of the slope (0.341). (2) Differences in both CSEI and CSNI were observed among different land uses. The highest value of CSEI was observed in fallow land (0.617) and the lowest value was in forests (0.252), while the highest value of CSNI was found in forests (0.793) and the lowest value was in fallow land (0.322). (3) CSEI was significantly negatively correlated with clay content, sand content, root length density and aboveground biomass. It was also significantly positively correlated with silt content and soil bulk density. Soil bulk density had the greatest direct impact (0.26). CSNI was significantly positively correlated with clay content, sand content, root length density and aboveground biomass. It was also significantly negatively correlated with silt content and soil bulk density. Clay content had the greatest direct impact (0.45). There was a significant negative correlation between CSEI and CSNI. [Conclusion] Slope position significantly influences both CSEI and CSNI, emphasizing the importance of focusing on slope crests and mid-slopes in vegetation restoration efforts. Vegetation restoration in various geomorphic positions effectively reduces CSEI and enhances CSNI, with trees being more effective in controlling soil erosion.

Due to ongoing cultivation, the Teaching and Research Farm of Kwara State University in Malete has seen quick and accelerated erosion. Run-off-related soil loss is a significant and persistent ecological problem in the study area. Information on soil loss is essential for promoting agricultural production and natural resource management. The average annual soil loss was calculated and mapped in this study using remote sensing and GIS. The soil loss was computed using the Revised Universal Soil Loss (RUSLE) Model. Using a topographic map at a scale of 1:50,000, an aster digital elevation model (DEM) with a spatial resolution of 20 m, a digital soil map at a scale of 1: 250,000, rainfall data spanning 39 years (1981-2020), and other data, RUSLE's soil loss variables were calculated. The RUSLE parameters were investigated and incorporated using a raster calculator in the geoprocessing tools in the arc-GIS 10.1 environment to estimate and map the annual soil loss of the research region. The results show that the annual soil loss in the study region ranged from 48.553 to 1,476.606 t ha-1 year-1 , cover around 100 ha of land. Most of the soil erosion affected areas are spatially situated in block 2B and 3A part of the farm. These are areas where low Ferric Luvisols and high Ferric Luvisols with higher soil erodibility character (21- 33) values are dominant. Therefore, it was found that the main causes of soil erosion were slope gradient and length, followed by soil erodibility parameters. The study therefore recommended using sustainable soil and water conservation methods to address the problem of soil erosion in the study area.

Although black soil in northeast China undergoes severe erosion, the contribution of parent materials, mainly Quaternary loess and non-loess sediments, to soil erodibility remains unclear. Considering the inheritance of ferromagnetic materials by parent materials, changes in magnetic parameters can successfully determine soil erodibility on a regional scale with a close climatic background. Here, we analysed the magnetic indicators of 142 samples from the black soil horizon formed on loess and non-loess sediments, covering areas of severe and slight erosion in the region to determine the effects of parent materials on the erodibility of black soil in northeast China. Both low-frequency magnetic susceptibility and frequency magnetic susceptibility (χfd) were proportional to the decrease in erosion rate due to erosion-induced leaching of ferromagnetic materials, and the change in χfd was narrow for black soil with loess parent materials, corresponding to relatively low soil erodibility. Compared with loess, the addition of soil organic matter could stabilise soils against erosion, thereby inducing a decrease in the erodibility of black soil formed on loess. Additionally, sustainable soil management policies to protect black soil from further erosion are necessary and urgent under the pressure of maintaining high grain yields and preventing erosion in northeast China. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xinyang Normal University Natural Science Edition is the property of Journal of Xinyang Normal University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The mountainous and semi-mountainous nature of the relief on the territory of Botevgrad Valley (West Bulgaria) is a prerequisite for erosion processes with different intensity. The erosion is mostly hidden, in surface washing and removal of the fertile soil horizons. The degree of erosion in the area is low to moderate. The water erosion is represented as the annual average value of the amount of eroded soil through the Universal Soil Loss Equation (USLE) model integrated into the Geographical Information Systems (GIS). The estimated potential risk of water erosion on a main part (65.92%) of the land is very high. It was evaluated that potential risk can have values about 200 t/ha y eroded soil. The assessment of the estimated actual soil losses from water erosion in the Botevgrad Valley has a low actual risk (class 2). The estimated loss of eroded soil is about 3 t/ha y, which is typical for that region. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of Soil & Water Conservation is the property of Bulletin of Soil & Water Conservation Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Due to the climate change that has become evident especially in the last ten years, ecosystems such as forests and pastures in the Mediterranean climate zone have become even more vulnerable to degradation. High erosive precipitation increases the amount of erosion in these soils with increasing their erodibility. The aim of this study was to determine to what extent some polymers, such as polyacrylamide and polyvinylalcohol, can prevent runoff and soil loss from erosion pans where a pasture soil was placed. For this purpose, aggregates of soil samples <8 mm from the A horizon of a Chromic Haplustert were used. Polyacrylamide and polyvinylalcohol solutions at different doses (0, 3.5, 7.0 and 14.0 kg ha-1) were applied to the aggregates by spraying. Erosion pans with slopes of 9% and 15% were exposed to simulated rainfall produced by a drop former rainfall simulator for one hour. The simulation trial was planned as 2 replications according to the randomized plots trial design. During simulated rainfall, runoff water and sediment from pans were collected at 10-minute intervals. Transported soils were expressed as dry weight, and runoff waters were expressed as volumetric. According to the results obtained, the highest runoff occurred from a 15% inclined soil pan (11.06 mm) without polymer applied (control). After one hour of simulated rainfall, runoff did not occur from some pans with high-doses of applied polymer. The amount of soil transported from the control pan by runoff and by splashing to the sides is 362 and 4241 kg ha-1, respectively. The pan, in which the least soil is carried by splashing, was the one with a 9% slope and the highest dose of polyacrylamide (97 kg ha-1). Statistical results show that polyvinylalcohol was more successful than polyacrylamide in reducing soil and water losses especially on 15% slope. These results indicate that the application of polymer to pasture soils can be a valid way to combat erosion, but the treatments should be carried out by choosing the right dose, taking into account factors such as the slope of the land, the erodibility of the soil and the erosivity of rainfall. [ABSTRACT FROM AUTHOR]

Accommodating uncertainty stands as one of the most salient challenges in the development of soil erosion assessment tools. We presented a novel approach integrating the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model and Bayesian Belief Networks (BBNs) to assess soil erosion in a region of western Iran. The soil erosion status was reckoned based on the nine factors of MPSIAC. We utilized BBNs to produce a causal model for soil erosion, with output probabilities being validated through re-evaluation and sensitivity analysis. We identified erosion types, geological formations, run-off, soil erodibility, soil permeability, soil characteristics, and precipitation intensity as the main determinants of soil erosion. A significant, positive correlation existed between the erosion rate derived from MPSIAC and BBNs model in all land-use/covers over the work units. Overall, this study highlighted the potential of BBNs as a supportive tool for soil erosion prediction as well as a relatively simple and updatable soil erosion model for dealing with the diagnostic, scenario, and sensitivity analysis. Considering the increasing incidence of soil erosion, the BBNs model proposed in this study can be extended to a variety of ecosystems that are subject to soil erosion and changes in the probability of its causal factors.

The world's natural wetlands, which have important ecological functions, are being lost at an alarming rate. The erosion and deposition of soil on wetlands is a major cause of wetland conversion to agriculture. An urgent problem to be solved is how to slow down the erosion and deposition of wetlands resulting from land use. Land use patterns affect soil properties, thereby affecting soil aggregate stability and erodibility. Evaluating the effects of land use patterns on soil aggregate stability and erodibility in small watersheds of wetland ecosystems of karst plateau is of great importance. Thus, we compared the soil properties, aggregate stability indicators and soil erodibility of shrubland, grassland, artificial forest land and sloping farmland for evaluating the impact of various land use patterns on soil aggregate stability and erodibility in typical karst plateau wetland ecosystems. Our results showed that the mass fraction of soil aggregates > 0.25 mm was the main component in the four land uses, with greater variation in aggregates > 5 mm; overall, MWD, GMD and WSA0.25 were higher in grassland and shrubland than in sloping farmland and artificial forest land, while K values, PAD and SCAI showed the opposite trend. Correlation analysis showed that effective soil nutrients had a positive effect on soil aggregate stability. In conclusion, the stability of soil aggregates and resistance to soil erosion were strongest under the influence of shrubland. Our study showed that shrubland can better improve soil aggregate stability and erosion resistance, which may provide a guide for protecting and restoring karst plateau wetland ecosystems. [ABSTRACT FROM AUTHOR]

Soil erosion by water on agricultural hillslopes leads to numerous environmental problems including reservoir sedimentation, loss of agricultural land, declines in drinking water quality, and requires deep understanding of underlying physical processes for better mitigation. It is imperative to accurately predict soil erosion caused by overland flow processes so that soil conservation efforts can be undertaken proactively before large-scale sedimentation problems arise. Soil detachment is often described by the excess shear stress equation that contains two physical soil erodibility parameters, erodibility coefficient, and critical shear stress. These parameters are normally assumed to be constant but can change across varying soil texture classes as well as during surface runoff events due to changes in soil cohesion and potential dependency on soil moisture content. These changes may significantly affect soil erosion rates at the field and watershed scale. In this study, the erodibility parameters of three soil types (sandy loam, clay loam, and silty clay loam) were analyzed using a laboratory mini-Jet Erosion Test (JET) to determine the effect of soil sample infiltration and moisture condition. Results from the experiments depicted a dynamic relationship between the soil erodibility parameters and amount of infiltrated mass of water. Data analysis displayed that for soils of different texture critical shear stress exhibited local minimum with higher values for very dry and saturated soils, while erodibility coefficient tended to increase with the increase of mass of soil water. Utilizing these dynamic soil erodibility parameters did not result in a significant difference in soil erosion rates when compared to using the averaged soil erodibility parameters taken from the experiment but the range of potential erosion rates increases with the increase of applied sheer stress to soil surface. The erosion rates with the experiment-based coefficients were found to be higher than with the baseline WEPP-based coefficients. These results highlight the importance of evaluating the effect of intrastorm dependent factors during surface runoff events, such as antecedent soil moisture content, time to peak from the start of runoff, soil cohesion, etc., on soil erodibility parameters to accurately calculate erosion rates, especially for initially dry soils or during earlier stages of surface runoff when critical shear stresses were highly affected. Further assessment of such factors with JET or other laboratory and field tests is recommended. [ABSTRACT FROM AUTHOR]

Soil erosion is the main threat that causes land deterioration and is one of the ultimate problems of the twenty-first century. Our study aims to determine soil erosion at the Universiti Pertahanan Nasional Malaysia (UPNM) catchment using an integrated Geographic Information System (GIS) and remote sensing (RS) utilizing the Revised Universal Soil Loss Equation (RUSLE) model. The parameters for the model are soil erosivity (R), soil erodibility (K), slope length and steepness (LS), land cover (C), and practice of land management (P), which are prepared using the varied input datasets in the ArcGIS software. The final maps model was the nearest sampled, and the soil erosion rate was calculated using an algebra map in ArcGIS. The results show that the soil erosion at the catchment is spatially varied between 0 and 99.1 t ha-1 yr-1. The rate of soil erosion was lower than 2.3 t ha-1 yr-1, estimated to be about 43% of the UPNM area, i.e., the highest percent of soil erosion. Moreover, the highest soil erosion is 43.5 to 99.1 t ha-1 yr-1. Overall, the findings described the spatial pattern of soil eroded within the catchment. Thus, the proposed integrated model is useful for explaining the erosion process within the river and land system of a small area. [ABSTRACT FROM AUTHOR]

Purpose: collection, analysis and generalization of data on wind speed and the intensity of deflation processes in Rostov region, that helps assessing the quantitative side of soil loss depending on wind speed, weather conditions, terrain, tillage method and other factors, and development of wind corridors for the conditions of the region under consideration. Materials and methods. The research was carried out on chestnut soils, southern and ordinary chernozems of the agricultural enterprise “Rassvet” of Aksai district and the agricultural enterprise “Krasnoarmeyskoe” of Oryol district of Rostov region, and the results of other scientists, who have been conducting research in Rostov region since 1969, were analyzed and summarized. Wind speed was measured with anemometers at a height of 2 m above the soil level, and the soil mass moved by winds was determined by the Erosion bridge (pin method) and dust collectors of our own design. Methods of analysis and synthesis as a systematic approach to achieving the goal were used. Results. The wind direction and speed in Rostov region depend on the seasonal position of pressure centers: the Siberian maximum in winter and the Azores in summer. Over the 54 years of research from 1969 to 2023, dust storms and drifting snow were observed 11 times, i.e. once every five years. Mathematical processing of long-term research data made it possible to obtain dependencies for assessing the effect of wind speed on soil removal on average in 1 hour, to determine soil removal coefficients, to propose zoning of the region into five deflationary regions, to develop a map diagram of deflationary zones and wind corridors of Rostov region. Conclusions. The greatest soil losses in wind-impact directions were in 1969 up to 800–900 t/ha for a duration of 300 h, in 1972 – 170–200 t/ha for a duration of 96 h; in 1984, with a daytime wind speed of 10–14 m/s with gusts of up to 25–30 m/s for a duration of 142 h, soil losses amounted to 218 t/ha.

Landslides caused by earthquakes bring about dramatic changes in soil erodibility. In order to understand the change characteristics of soil erodibility during a vegetation restoration period after the 5.12 Wenchuan earthquake, a non-landslide area, landslide area, and transition area in Leigu Town, Beichuan County were selected as research areas. Field soil sampling, geostatistics, and spatial interpolation were used to explore the spatiotemporal changes in soil physicochemical properties and soil erodibility during a natural restoration in 2013 (5 years after the earthquake) and in 2022 (14 years after the earthquake). The results showed that the comprehensive soil erodibility index (CSEI) was mainly composed of five soil factors, which were soil pH, soil total nitrogen (TN), mean weight diameter of soil aggregates (MWD), fractal dimension of soil water stable aggregates (D), and soil erodibility (Kepic). The CSEI of the landslide area was slightly lower than that of the non-landslide area. The CSEI was gradually increasing during the process of natural restoration after earthquake. From 2013 to 2022, the increase rates of the CSEI were 6.9%, 10.0%, and 41.5% for the landslide area, non-landslide area, and transition area, respectively. Along attitude segments, the spatial distribution of soil erodibility in 2022 is more uniform than that in 2013. The higher value of CSEI was located in the upper part of research areas. The spatial distribution of the CSEI in 2013 and 2022 appeared as a moderate autocorrelation. The variable ranges of CSEI in 2013 and 2022 were about 20 m. In the early stage of vegetation restoration, soil and water conservation engineering was recommended in the landslide area.

Soil erodibility (K) refers to the inherent ability of soil to withstand erosion. Accurate estimation and spatial prediction of K values are vital for assessing soil erosion and managing land resources. However, as most K-value estimation models are empirical, they suffer from significant extrapolation uncertainty, and traditional studies on spatial prediction focusing on individual empirical K values have neglected to explore the spatial pattern differences between various empirical models. This work proposed a universal framework for selecting an optimal soil-erodibility map using empirical models enhanced by machine learning. Specifically, three empirical models, namely, the erosion-productivity impact calculator model (K_EPIC), the Shirazi model (K_Shirazi), and the Torri model (K_Torri) were used to estimate K values. Random Forest (RF) and Gradient-Boosting Decision Tree (GBDT) algorithms were employed to develop prediction models, which led to the creation of three K-value maps. The spatial distribution of K values and associated environmental covariates were also investigated across varying empirical models. Results showed that RF achieved the highest accuracy, with R2 of K_EPIC, K_Shirazi, and K_Torri increasing by 46%, 34%, and 22%, respectively, compared to GBDT. And distinctions among environmental variables that shape the spatial patterns of empirical models have been identified. The K_EPIC and K_Shirazi are influenced by soil porosity and soil moisture. The K_Torri is more sensitive to soil moisture conditions and terrain location. More importantly, our study has highlighted disparities in the spatial patterns across the three K-value maps. Considering the data distribution, spatial distribution, and measured K values, the K_Torri model outperformed others in estimating soil erodibility in the plateau lake watershed. This study proposed a framework that aimed to create optimal soil-erodibility maps and offered a scientific and accurate K-value estimation method for the assessment of soil erosion.

Soil hydrology seriously affects the prevention of desertification in karst areas. However, water infiltration in the different soil layers of secondary forests and artificial forests in karst areas remains uncertain. This lack of clarity is also the factor that constrains local vegetation restoration. Therefore, monitoring and simulating the priority transport of soil moisture will help us understand the shallow soil moisture transport patterns after artificial vegetation restoration in the local area, providing a reference for more scientific restoration of the ecological environment and enhancement of carbon storage in karst areas. The integration of soil physical property assessments, computed tomography (CT) scanning, dye tracing studies, and HYDRUS-2D modeling was utilized to evaluate and contrast the attributes of soil macropores and the phenomenon of preferential flow across various forestland categories. This approach allowed for a comprehensive analysis of how the soil structure and water movement are influenced by different forest ecosystems and infiltration head simulations (5 mm, 15 mm, 35 mm, and 55 mm) to elucidate the dynamics of water movement across diverse soil types within karst regions, to identify the causes of water leakage due to preferential flow in secondary forests, and to understand the mechanisms of water conservation and reduction in artificial forests adopting a multifaceted approach. This study demonstrated that (1) the soil hydrological capacity of a plantation forest was 20% higher than a natural forest, which may be promoted by the clay content and distribution. (2) Afforestation-enhanced soils in karst regions demonstrate a significant capacity to mitigate the loss of clay particles during episodes of preferential flow and then improve the soil erosion resistance by about 5 times, which can effectively control desertification in karst area. (3) The uniform distribution of macropores in plantation forest soil was conducive to prevent water leakage more effectively than the secondary forest but was incapable of hindering the occurrence of preferential flow. The secondary forest had a very developed preferential flow phenomenon, and soil clay deposition occurred with an increase in depth. (4) Moreover, the results for preferential flow showed that the matrix flow depth did not increase with the increase in water quantity. Short-term and high-intensity heavy rainfall events facilitated the occurrence of preferential flow. Infiltration along the horizontal and vertical directions occurred simultaneously. These results could facilitate a further understanding of the contribution of the plantation to soil amelioration and the prevention of desertification in karst areas, and provide some suggestions for the sustainable development of forestry in karst areas where plantation restoration is an important ingredient.

The Hulan River Basin is located in the black soil region of northeast China. This region is an important food-producing area and the susceptibility of black soil to erosion increases the risk of soil erosion, which is a serious environmental problem that affects agricultural productivity, water supply, and other important aspects of the region. In this paper, the changes in LULC (land use and land cover) in the basin between 2001 and 2020 were thoroughly analysed using GIS (geographic information system) and USLE (universal soil loss equation) models. The soil erosion risk in the Hulan River Basin between 2001 and 2020 was also studied and soil erosion hot spots were identified to target those that remained significant even under the implementation of soil conservation measures. Precipitation data were used to obtain the R factor distribution, LULC classification was adopted to assess the C factor distribution, soil data were employed to estimate the K factor distribution, DEM (Digital Elevation Model) data were used to generate an LS factor map, and slope and LULC data were considered to produce a P factor distribution map. These factors were based on the model parameters of the USLE. The findings of LULC change analysis over the last 20 years indicated that, while there have been nonobvious changes, agricultural land has continued to occupy the bulk of the area in the Hulan River Basin. The increase in areas used for human activities was the most notable trend. In 2001, the model-predicted soil erosion rate varied between 0 and 120 t/ha/yr, with an average of 4.63 t/ha/yr. By 2020, the estimated soil erosion rate varied between 0 and 193 t/ha/yr, with an average of 7.34 t/ha/yr. The Hulan River Basin was classified into five soil erosion risk categories. Most categories encompassed extremely low-risk levels and, over the past 20 years, the northeastern hilly regions of the basin have experienced the highest concentration of risk change areas. The northeastern hilly and mountainous regions comprised the risk change area and the regions that are most susceptible to erosion exhibited a high concentration of human production activities. In fact, the combined use of GIS and USLE modelling yielded erosion risk areas for mapping risk classes; these results could further assist local governments in improving soil conservation efforts. [ABSTRACT FROM AUTHOR]

In order to explore the influence of vegetation on homogeneity of surface particle size distribution (PSD) and heterogeneity of soil structure, observations, theory, and multifractal results were synthesized to highlight the evolution of the soil particle composition in the Jilantai Salt Lake Protection System (Jilantai system) after long‐term wind‐sand activities and its soil structure characteristics. From flowing sand dune to saline‐alkali wasteland areas, the mean grain size and surface particle sorting degree gradually increased and decreased, respectively, whereas the shape of the particle frequency curve gradually changed from extremely positive deviation to negative deviation, and the peak shape of the curve gradually changed from narrow to wide. Furthermore, the inhomogeneity of the soil particle composition gradually decreased, whereas the range of the soil PSD gradually increased, and the soil increasingly became fine‐grained. Therefore, the contents of clay and silt in shelterbelt soil increased by 16% and 18.36%, respectively, over 1986 levels. Additionally, clay and silt play a vital role in determining soil particle parameters such as standard deviation (SD), skewness (SKI), and monofractal (D), while vegetation factors are the main controlling factors of clay and silt. In conclusion, the Jilantai system could increase heterogeneity and homogeneity and decrease the concentration of soil PSD by changing the sedimentary environment, while this affect depends largely on the fractional vegetation cover, vegetation height, and light penetrating porosity. Moreover, the multifractal and particle parameters could describe the soil structure characteristics and sedimentary process, respectively, after long‐term wind‐sand activities. [ABSTRACT FROM AUTHOR]

[Objective] This study investigated the spatial distribution characteristics of soil erodibility K value in the valley of the Niyang River Basin in Tibet to provide references for reducing soil erosion risk in this region. [Method] A total of 122 sample plots were set up in the freeze-thaw erosion area (altitude> 4 200 m), the crisscross areas of freeze thaw and hydraulic erosion crisscross area (altitude 3 800-4 200 m) and the hydraulic erosion area (altitude<3 800 m) in the Niyang River Basin in southeastern Tibet. Basic physical and chemical properties of surface soil in the basin were measured and the EPIC model was used to calculate soil erodibility K value. The spatial distribution of K value in the valley was obtained u-sing the ordinary Kriging interpolation method. Finally, the correlations between soil erodibility K value and elevation and soil physical-chemical properties were analyzed. [Result] ➀ Physical and chemical properties of soil in the freeze-thaw erosion area, the crisscross area of freeze-thaw and hydraulic erosion and the hydraulic erosion area in the Niyang River Basin were significantly different. The freeze-thaw erosion area had the lowest soil volume quality and the highest soil porosity and contents of water, organic matter, silt and clay. ➁ The K values of soil erodibility in freeze-thaw erosion area, the crisscross area of freeze-thaw and hydraulic erosion and hydraulic erosion area were 0.263-0.431, 0.218-0.374 and 0.104-0.409 t ⋅ hm² ⋅ h/(MJ ⋅ mm ⋅ hm²) with average values of 0.349, 0.310 and 0.292 t ⋅ hm² ⋅ h/(MJ ⋅ mm ⋅ hm²) and medium variation coefficients of 11.7%, 12.7% and 21.5 %, respectively. The K values of soil erodibility factor in the Niyang River Basin decreased gradually from northwest to southeast. There were less low, medium, less high and high erodible soils in the basin without different main soil erosion types among areas. High erodible soils were mainly distributed in the freeze-thaw erosion areas, while less low and medium erodible soils were mainly distributed in the hydraulic erosion area and the freeze-thaw hydraulic erosion crisscross area. ➂ The soil erodibility K value had very significant correlation with elevation and soil physical and chemical properties (P< 0.01), with high correlation coefficients of -0.98, 0.99 and 0.62, respectively. [Conclusion] The spatial distribution characteristics of soil erodibility K value in the valley of Niyang River Basin in Tibet were investigated and the mechanical composition of soil was the main affecting factor. [ABSTRACT FROM AUTHOR]

The Tiga Dam, a primary hydraulic structure in northern Nigeria, is subjected to intense hydrological stress during the rainy season, posing potential risks to its structural integrity. This study investigates the geotechnical properties and stability of the Tiga Dam in Kano State, Nigeria. Twelve soil samples from the downstream area were analyzed for specific gravity, grain size distribution, Atterberg limits, compaction parameters, permeability, and shear strength. The dam’s stability was assessed using Plaxis 2D under various reservoir conditions. Soil erodibility was evaluated using the Revised Universal Soil Loss Equation (RUSLE), and a linear regression model with noise was developed to predict soil expansion rates. The results showed heterogeneous soil properties, with specific gravity ranging from 2.11 to 2.63 and permeability from 3.40 × 10−9 to 1.49 × 10−7 m/s. Stability analysis revealed factors of safety of 1.322, 1.006, 1.002, and 1.147 for high reservoir, rapid drawdown, slow drawdown, and low reservoir conditions, respectively. The RUSLE K factor ranged from 0.055 to 0.145, indicating low to moderate soil erodibility. The expansion rate model demonstrated high accuracy (R2 = 0.989) in predicting seasonal and long-term soil expansion trends, with peak rates increasing from 16.94 mm/month in 2010–2013 to 19.45 mm/month in 2017–2020. This comprehensive analysis provides crucial insights into the Tiga Dam’s geotechnical behavior, highlighting potential vulnerabilities and the need for targeted management strategies to ensure long-term stability and safety.

ABSTRACTSoil loss is one of the critical environmental problems caused by poor land use system, especially in developing countries. The loss of top soil through erosion in developing countries leads to loss of fertile soil which in turn increases the problem of food security. This study used the integration of the revised universal soil loss equation (RUSLE) model and geospatial techniques to assess the annual soil loss at Bore Guda watershed of Gibe River basin in southwestern parts of Ethiopia. To calculate the annual soil loss five factors, namely, rainfall erosivity, soil erodibility, topographic, cover management, and conservation practices were considered. The final soil loss severity classes were categorized into low, moderate, high, very high, and severe. The findings of the study revealed that the annual soil loss in the study area ranges from 0 to 775.784 ton/ha/year with average annual soil loss of 54.68 ton/ha/year. The results clearly showed that about 199.05 km2 (9.2%) and 872.63 km2 (41.29%) of the study area were identified as very high and severe soil loss, respectively. The results clearly showed that substantial areas categorized under severe erosion severity classes. Agricultural intensification caused by rapid population growth and high demand for more food is aggravating the problem of soil erosion. The increasing conversion due to agricultural intensification played a significant role in soil loss. The results of the study support decision makers, land administration, environmentalists, and others about the urgency of the situation and how to manage landscapes to minimize the severity of soil loss.

Mining activity always presents threats to soil and water pollution. As an extractive industry, it disturbs the ground and the biodiversity associated with soil and plants. Its operations have led to severe geological and environmental problems, including the depletion of land and water resources, geological dangers, and ecological landscape devastation that may have accelerated the desertification of mining areas. This case study analyzed the soil’s physical and chemical properties in a nickel laterite mine, including soil erodibility K factor, soil pH, and heavy metal accumulation, as a basis for establishing mine management protocol during and post-mining operations in Tubay, Agusan del Norte, Philippines. Results determined a slightly alkaline pH level. An estimate of soil erodibility ranging from 0.016 to 0.066 was determined using the USLE-K factor, with the highest erodibility at Mine 7, where % silt is high and % sand is lowest. X-ray fluorescence (XRF) spectroscopy was used to analyze soil samples. The findings show that Ni, Fe, Co, and Mn in the soil were above the WHO-permitted limits. The surface soil had mean values of 9,239 ppm for nickel, 302,618 ppm for iron, 639 ppm for cobalt, and 5,203 for manganese. Heavy metals in soil may be consumed by crops and pollute land and water.

Knowledge of the issue of water movement in the soil is the basis for agricultural activity, but also for many other sectors. One of the basic indicators that is evaluated in soil science is the rate of water infiltration into the soil. The article specifically states how soil texture and soil moisture affect the rate of water infiltration. The results show that changes in water infiltration can be significant and certain trends can be traced. The rate of water infiltration into the soil is most affected by the sand fraction (soil particles 0.05-2 mm). The higher the percentage of these soil particles in the soil, the lower the changes in infiltration rate depending on the degree of saturation. The article further evaluates soil moisture in relation to texture. The results were obtained at several research locations within the period 2014-2021 in the territory of the Czech Republic. The above findings are primarily applicable to the region of Central Europe or can be used as comparative values for regions in the rest of the world.

Riverbank erosion is a natural process of removal of earthen materials from the bank surface. The process of riverbank erosion that is induced naturally results in the formation of landforms such as valleys, canyons, and productive floodplains. However, riverbank erosion can also be considered a hazard when the process occurs at an alarming rate causing loss of land. The extent of erosion depends on many factors. One of the main factors responsible for riverbank erosion is the soil erodibility which is the resistance of soil to erosion. The aim of this study is to quantify the riverbank erosion rates and the potential magnitude of riverbank erosion in order to generate an empirical predictive model to estimate riverbank erosion from physical and geomorphic variables for rivers susceptible to riverbank erosion. Several models were trained using the Regression Learner application in MATLAB software. Models that include soil erodibility parameters perform better than the models without the soil erodibility parameters. The model with the highest accuracy was found to be Model 2, with Root Mean Square Error (RMSE) of 3.70E-08 and coefficient of determination, R2 of 0.55. The model produced in this study will be helpful to analyze and predict the effects of riverbank erosion and assist in the development of bank stabilization solution. ABSTRAK: Hakisan tebing sungai adalah proses semula jadi terhadap penyingkiran bahan tanah dari permukaan tebing. Proses hakisan tebing sungai yang terjadi secara semula jadi ini mengakibatkan pembentukan bentuk muka bumi seperti lembah, ngarai dan dataran banjir yang produktif. Bagaimanapun, hakisan tebing sungai juga boleh dianggap sebagai ancaman apabila proses berlaku pada kadar membimbangkan sehingga menyebabkan kehilangan tanah. Tahap hakisan bergantung pada banyak faktor. Salah satu faktor utama yang menyebabkan hakisan tebing sungai adalah kebolehhakisan tanah iaitu ketahanan tanah terhadap hakisan. Kajian ini bertujuan untuk mengukur kadar hakisan tebing sungai, mengkaji potensi magnitud hakisan tebing sungai dan menghasilkan model ramalan empirik bagi menganggarkan hakisan tebing sungai daripada pembolehubah fizikal dan geomorfik bagi sungai yang terdedah kepada hakisan tebing sungai. Beberapa model telah dilatih menggunakan aplikasi Regression Learner dalam perisian MATLAB. Dapatan menunjukkan model yang mengandungi parameter kebolehhakisan tanah adalah lebih baik berbanding model tanpa parameter kebolehhakisan tanah. Model 2 didapati mempunyai ketepatan tertinggi dengan ralat punca min kuasa dua (RMSE) sebanyak 3.70E-08 dan pekali penentuan, R2 sebanyak 0.55. Model dalam kajian ini dapat membantu dalam analisa berkaitan kesan hakisan tebing sungai dan penyelesaian kepada pembangunan kestabilan tebing.

Soil stoichiometric characteristics and aggregate stability are affected by vegetation restoration in degraded land. Yet, it is not known that how the aggregate stability is related to soil stoichiometric characteristics under different vegetation restorations. A 5-year in situ experiment was conducted to investigate the effects of vegetation restoration on the composition, stability and stoichiometric properties of soil aggregates. In the northwest part of Beijing, Bromus inermis Leyss. and Medicago sativa L. were planted in a typical area of desertification, and natural restoration was used as control. Boosted regression trees (BRTs) were applied to partition the factors that control aggregate stability. The results showed that the mean weight diameter (MWD) of soil water-stable aggregates under natural restoration (CK) and Medicago sativa L. sowing treatments (AF) was significantly higher than that under the restoration of the Bromus inermis Leyss. sowing treatments (SB). Compared with CK, AF significantly increased the geometric mean diameter (GMD) water stable aggregates, while SB showed the opposite result. AF significantly increased the proportion of soil aggregates >2 mm compared with CK. AF could improve the stability of soil aggregates by increasing the proportion of large aggregates. For the stoichiometric characteristics of the aggregates, AF increased significantly the value of C/P in 0.053−0.125 mm particle size aggregates in all soil layers. The MBC/MBN ratio aggregates at depths of 0–10 cm and 10–20 cm was also significantly increased in the treatment of AF. The BRTs indicated that stoichiometric ratio is the main factor driving the stability of soil aggregates rather than microbial community characteristics and soil nutrients. The C/P is the main driving factor affecting the MWD, in which the overall stoichiometric influence accounts for 46%, followed by the microbial influence of 36%. For the GMD, MBC/MBN is the main driving factor, and the stoichiometric influence accounts for 94%. Our findings indicate that AF is beneficial to the stability of deep soil aggregates, and their stoichiometric characteristics of soil are the key factors affecting the stability of soil aggregates.

Polyacrylamide (PAM) is a water-soluble polymer with strong cohesiveness and a strong water absorption capacity, and it has been widely used to modify soil structural stability. However, little information is available on the impact of PAM application on the aggregate-breaking process of purple soils in hilly areas of southwestern China. Therefore, the current study aimed to examine the influence of PAM application on the aggregate stability of purple soil in terms of different breakdown mechanisms at different hillslope locations. Three disruptive tests employing the Le Bissonnais method (FW, fast-wetting sieving; SW, slow-wetting sieving; and WS, wet-stirring sieving) were used to determine the mean weight diameter (MWD), geometric mean diameter (GMD), and mass fractal dimension (D) of the soil aggregates, and soil erodibility factor (K) was calculated as an index of soil anti-erodibility. Overall, the major aggregate-breaking mechanism for purple soils was the following: SW (differential swelling) > WS (mechanical breakdown) > FW (slaking). The content of water-stable aggregates (>0.25 mm) obviously rose after PAM application, with the most significant influences shown under FW. A significant difference in MWD was observed between PAM application and without polyacrylamide application (CK) under WS (p < 0.05). However, there was a significant difference in GMD between PAM and CK (p < 0.05) under FW and SW. In comparison with CK, D value in PAM under FW and SW was significantly reduced, mainly at the slope locations of 0 and 20 m. A descending order of FW, WS, and SW was found on the basis of K value at different slope locations. These findings contribute to improved understanding of proper application of soil amendments to control soil and water loss in purple soils. [ABSTRACT FROM AUTHOR]

Soil aggregate stability and soil erodibility (k) are crucial indicators of soil quality that exhibit high sensitivity to changes in soil function. Therefore, it is of great significance to explore the quantitative relationship between these indicators and soil quality for effective ecosystem monitoring and assessment. In this study, soil samples were collected from eight altitude gradients in a karst mountainous area; we analyzed 11 soil physical, chemical, and biological properties, and assessed soil quality using the minimum data set (MDS) method. The results revealed that soil aggregate stability, bulk density (BD), pH, and fungal community diversity exhibited a unimodal altitudinal pattern, whereas the soil organic carbon (SOC), total nitrogen (TN), and C:N ratio showed an increasing trend. Among the factors considered, SOC, BD, soil pH, mechanical composition, and fungal community diversity were found to explain the most variation in soil aggregate stability and soil erodibility (k). Principal component analysis (PCA) identified soil fungal community diversity, C:N ratio, coarse sand, and macro-aggregate (MA) content as highly weighted indicators for MDS. The integrated soil quality index (SQI) values, ranging from 0.30 to 0.62 across the eight altitude gradients, also exhibited a unimodal altitudinal pattern. The analysis indicated a significant linear relationship between the fractal dimension (D) and soil erodibility of the EPIC model (Kepic) with SQI, suggesting that D and Kepic can serve as alternative indicators for soil quality. These findings further enhance our understanding of the response of soil properties to altitude changes, and provide a novel method for assessing and monitoring soil quality in karst mountainous areas. [ABSTRACT FROM AUTHOR]

The world’s natural wetlands, which have important ecological functions, are being lost at an alarming rate. The erosion and deposition of soil on wetlands is a major cause of wetland conversion to agriculture. An urgent problem to be solved is how to slow down the erosion and deposition of wetlands resulting from land use. Land use patterns affect soil properties, thereby affecting soil aggregate stability and erodibility. Evaluating the effects of land use patterns on soil aggregate stability and erodibility in small watersheds of wetland ecosystems of karst plateau is of great importance. Thus, we compared the soil properties, aggregate stability indicators and soil erodibility of shrubland, grassland, artificial forest land and sloping farmland for evaluating the impact of various land use patterns on soil aggregate stability and erodibility in typical karst plateau wetland ecosystems. Our results showed that the mass fraction of soil aggregates > 0.25 mm was the main component in the four land uses, with greater variation in aggregates > 5 mm; overall, MWD, GMD and WSA0.25 were higher in grassland and shrubland than in sloping farmland and artificial forest land, while K values, PAD and SCAI showed the opposite trend. Correlation analysis showed that effective soil nutrients had a positive effect on soil aggregate stability. In conclusion, the stability of soil aggregates and resistance to soil erosion were strongest under the influence of shrubland. Our study showed that shrubland can better improve soil aggregate stability and erosion resistance, which may provide a guide for protecting and restoring karst plateau wetland ecosystems.

Soil erosion by water on agricultural hillslopes leads to numerous environmental problems including reservoir sedimentation, loss of agricultural land, declines in drinking water quality, and requires deep understanding of underlying physical processes for better mitigation. It is imperative to accurately predict soil erosion caused by overland flow processes so that soil conservation efforts can be undertaken proactively before large-scale sedimentation problems arise. Soil detachment is often described by the excess shear stress equation that contains two physical soil erodibility parameters, erodibility coefficient, and critical shear stress. These parameters are normally assumed to be constant but can change across varying soil texture classes as well as during surface runoff events due to changes in soil cohesion and potential dependency on soil moisture content. These changes may significantly affect soil erosion rates at the field and watershed scale. In this study, the erodibility parameters of three soil types (sandy loam, clay loam, and silty clay loam) were analyzed using a laboratory mini-Jet Erosion Test (JET) to determine the effect of soil sample infiltration and moisture condition. Results from the experiments depicted a dynamic relationship between the soil erodibility parameters and amount of infiltrated mass of water. Data analysis displayed that for soils of different texture critical shear stress exhibited local minimum with higher values for very dry and saturated soils, while erodibility coefficient tended to increase with the increase of mass of soil water. Utilizing these dynamic soil erodibility parameters did not result in a significant difference in soil erosion rates when compared to using the averaged soil erodibility parameters taken from the experiment but the range of potential erosion rates increases with the increase of applied sheer stress to soil surface. The erosion rates with the experiment-based coefficients were found to be higher than with the baseline WEPP-based coefficients. These results highlight the importance of evaluating the effect of intrastorm dependent factors during surface runoff events, such as antecedent soil moisture content, time to peak from the start of runoff, soil cohesion, etc., on soil erodibility parameters to accurately calculate erosion rates, especially for initially dry soils or during earlier stages of surface runoff when critical shear stresses were highly affected. Further assessment of such factors with JET or other laboratory and field tests is recommended.

Soil erodibility (K-Factor) is one of the fundamental parameters to estimate its rainfall erosion through mathematical models such as RUSLE. Carrying out an erodibility analysis at different pedological depths allows identifying what would be its susceptibility to erosion processes. Soil unit parcel data obtained by long-term field measurements are required, ensuring that the analyzed sections remain uncovered throughout observation period, investing large amounts of time and money. However, the lack of a good and extensive field database is the main limitation to apply this methodology. The objective of this work was to analyze the spatial distribution of soil erodibility in different pedological profiles, through the implementation of satellite data of soil characteristics. The methodology consisted in delimiting and analyzing the environmental characteristics of the Ecuadorian basins, obtaining the clay, silt, sand SOC contents of the analyzed depths, determining the K-Factor values and comparing them with environmental layers. Basins delimitation and environmental characteristics were extracted from regional literature; soil layer contents were obtained from SoilGrids; K-Factor calculation was made from soil characteristics using Software R and QGIS; results comparison against the elevation and land cover parameters were carried out using QGIS. The results allowed to identify very small variations between pedological profiles; determine that clay and silt are the most incident elements of K-Factor; identify that Crop and Grass are coverages that concentrate on the highest values of K-Factor as well as the highest areas. This allows the administrators of the territory to generate measures to reduce soil loss. [ABSTRACT FROM AUTHOR]

Mining activity always presents threats to soil and water pollution. As an extractive industry, it disturbs the ground and the biodiversity associated with soil and plants. Its operations have led to severe geological and environmental problems, including the depletion of land and water resources, geological dangers, and ecological landscape devastation that may have accelerated the desertification of mining areas. This case study analyzed the soil 's physical and chemical properties in a nickel laterite mine, including soil erodibility K factor, soil pH, and heavy metal accumulation, as a basis for establishing mine management protocol during and post-mining operations in Tubay, Agusan del Norte, Philippines. Results determined a slightly alkaline pH level. An estimate of soil erodibility ranging from 0.016 to 0.066 was determined using the USLEK factor, with the highest erodibility at Mine 7, where % silt is high and % sand is lowest. X-ray fluorescence (XRF) spectroscopy was used to analyze soil samples. The findings show that Ni, Fe, Co, and Mn in the soil were above the WHO-permitted limits. The surface soil had mean values of 9,239 ppm for nickel, 302,618 ppm for iron, 639 ppm for cobalt, and 5,203 for manganese. Heavy metals in soil may be consumed by crops and pollute land and water. [ABSTRACT FROM AUTHOR]

Tillage practices significantly influence soil nutrient retention, soil structure, and stability. However, the impact of tillage practices on soil stability and erosion resistance through the perturbation approach of soil structure remains unclear. This study aimed to establish universal principles across slope surface and soil profile scales. We evaluated the effects of various tillage practices, including conventional tillage (CT), soil compaction (CM), subsoil tillage (ST), no tillage (NT), and subsoil tillage and soil compaction (SCM) on soil stability and erosion resistance in China's red soil hilly region. Soil stability, erosion resistance, and other soil properties were quantified using field surveys and laboratory experiments. We discovered significant variations in soil aggregate stability (SAS), wet aggregate stability (WAS), soil mechanical stability (SMS), and soil erodibility (SE) among the five tillage methods. The K factor's average value indicated that the 0–40 cm soil layer was more erodible for CT (0.472) than for other methods, with NT (0.26) being the least erodible. NT (0.43) was the most effective treatment for reducing SE, while SCM (0.41) enhanced soil fertility, controlled SE, and mitigated machinery-induced soil compaction risks. CM (0.38) maintained soil stability without improving the soil nutrient storage, while ST (0.33) improved the soil stability such as alleviating the soil hardening caused by CM. The results provide reference parameter values for selecting appropriate tillage methods to decrease soil degradation and erosion while enhancing the soil productivity in a red soil hilly region. [ABSTRACT FROM AUTHOR]

Purpose : This study aims to clarify the spatial variability and characteristics of the distribution of soil properties and erodibility on a typical river alluvial and marine sedimentary plain in eastern China. Methods: We collected soil samples and measured the soil properties for 2955 sampling points in the study area. The spatial variation and distribution of the variables were analyzed using Moran's I, semivariogram, and sequential Gaussian simulation (SGS) methods, and a spatial risk analysis of soil erodibility (K factor) was performed based on 500 realizations of SGS. Results: The mean K factor, pH and sand, silt, clay, and organic matter contents were 0.0302 t·ha·h·ha−1·MJ−1·mm−1, 7.07 and 50.36, 30.05, 19.58%, and 27.62 g kg−1, respectively, all indicating moderate spatial variability. All variables were strongly globally autocorrelated (Moran's I > 0.3). The ratios of spatial structure indicated that all variables had moderate or moderately strong spatial dependence. The spatial distributions of the variables were strongly influenced by geography, with higher sand contents and pHs along the abandoned Yellow River, the eastern coastal area, and the alluvial area of the Yangtze River Delta. Silt, clay, and organic matter contents, however, had opposite spatial patterns. Areas at a high risk of soil erodibility were along the abandoned Yellow River, the eastern coast, and the southwest. The areas with probability of soil erodibility risk > 60, 80, and 90% accounted for 51.94, 33.45, and 24.34% of the study area, respectively. Conclusions: This study provides a methodological reference for research into spatial mapping and an empirical basis for agricultural management and erosion control that can be applied to other river alluvial and marine sedimentary plains. [ABSTRACT FROM AUTHOR]