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The vulnerability of soil by wind erosion using the wind erosion equation (WEQ) in geographic information systems (GIS) was demonstrated on the cadastral area of Přísnotice, southeast of the Czech Republic. Raster layers were created for input factors of WEQ and potential soil loss by wind was calculated using the Raster Calculator. Subsequently, map outputs showing the potential vulnerability of soil to wind erosion were made. In the first variant, where the protective effect of the barriers was not taken into account, the wind erosion intensity reached 47.6 t.ha-1.year-1. In the second variant, where the protective effect of the barrier was assumed, the loss of soil was lower, the maximum value was 4.7 t.ha-1.year-1. The soil loss limit was exceeded, even in a situation where a relatively high protective barrier effect has been proposed. The advantage of determining of wind erosion vulnerability using ArcGIS is that it is possible to identify particular parts of soil blocks from the map outputs, which are the most vulnerable. Similarly, it is possible to design a windbreak network and simulate its protective effect using ArcGIS. [ABSTRACT FROM AUTHOR]

Abstract The adjustment of land use can alter the near soil surface characteristics and thus likely affects soil erodibility. However, few studies have been carried out to assess the variations in soil erodibility under different land uses on the Loess Plateau after many slope farmlands have been converted to green lands in the past several decades. This study was conducted to quantify comprehensively the effects of five typical land uses (cropland, orchard, grassland, shrubland and woodland) on soil erodibility based on soil cohesion (Coh), saturated conductivity (K s), the number of drop impact (NDI), the mean weight diameter of soil aggregates (MWD), soil penetration resistance (PR) and soil erodibility K factor from different aspects, as well as a comprehensive soil erodibility index (CSEI) produced by a weighted summation method. The results showed that Coh of grassland, K s of woodland, and MWD and NDI of shrubland were the maximum, while PR of woodland and K of shrubland were the minimum among five tested land uses. Soil erodibility (reflected by CSEI) of shrubland was the minimum, while cropland had the maximum CSEI. Compared to cropland, soil erodibility decreased by 15.5%, 53.0%, 77.2% and 59.6% for orchard, grassland, shrubland and woodland, respectively. The variation in soil erodibility under different land uses was closely related to near soil surface characteristics. Soil erodibility increased with soil bulk density, and decreased with biological soil crust thickness, organic matter content, plant litter density, and root density. The results are helpful for optimizing spatial planning and improving eco-environment on the Loess Plateau. Highlights • The adjustment of land use altered near soil surface characteristics greatly. • Soil erodibility decreased significantly with vegetation restoration. • Near soil surface characteristics affected soil erodibility significantly. [ABSTRACT FROM AUTHOR]

Abstract In Japan, moso-bamboo (Phyllostachys edulis (Carrière) J. Houz.), an invasive species, has spread into and replaced surrounding broadleaved and coniferous forests because of the inactive management of moso-bamboo forests. Some local governments in Japan have speculated about an increase in soil erosion caused by the replacement with moso-bamboo forests. To evaluate the impact of such replacement on soil erosion, the soil erosion rate in a moso-bamboo forest was compared with those in an evergreen broadleaved forest and a coniferous forest. We established three plots (width 1 m, length ca. 2 m) in each forest and measured overland flow and soil erosion in two continuous periods (Period I: July 26, 2012–April 26, 2013; Period II: April 26, 2013–July 17, 2014). In Period I, the soil erosion rate in the moso-bamboo forest (0.08–0.10 g m−2 mm−1) was not significantly higher than that in the broadleaved forest (0.27–0.55 g m−2 mm−1) and the coniferous forest (0.16–0.27 g m−2 mm−1). In Period II, we removed understory vegetation and litter from two of the three plots in each forest. In Period II, the plots with such removal had higher soil erosion rates than the control plots. The soil erosion rate for the removal plots of the moso-bamboo forest was less than half of those of the broadleaved and coniferous forests. Although rock fragment cover on the soil surface and shear strength of the topsoil did not differ significantly among the three forests, root density in the moso-bamboo forest was much greater than those in the broadleaved and coniferous forests. These results suggest that a large amount of roots in moso-bamboo forests could reduce soil erosion there. The findings of this study show that moso-bamboo forests have strong resistance against soil erosion, so the replacement of broadleaved and coniferous forests by moso-bamboo forests would not seem to imply an increase in soil erosion. Highlights • Soil erosion in a moso-bamboo forest was lower than in broadleaved and cedar forests. • Removal of floor coverage slightly increased soil erosion in the bamboo forest. • The removal dramatically increased soil erosion in the broadleaved and cedar forests. • Extremely dense roots of the bamboo forest could explain the relatively low erosion. • Expansion of moso-bamboo forests would not increase the risk of soil erosion. [ABSTRACT FROM AUTHOR]

Abstract The role of weeds in soil conservation in agroforestry systems has been largely ignored. We used the Land Use Change Impact Assessment (LUCIA) model to simulate the effects of weed management on erosion in rubber plantations (Hevea brasiliensis Muell. Arg). In order to quantify the impact of a dynamic, spatially explicit multi-layer plantation structure on erosion processes in agroforestry systems, we updated LUCIA's erosion module. Its new version simulates soil detachment due to rainfall and runoff, considering the separate effects of the tree canopy and surface cover on soil erosion. The updated LUCIA model was calibrated and validated based on an established rubber plantation experiment in Xishuangbanna, Southwest China, to evaluate the impact of different weeding strategies on soil loss. The model successfully represented the impact of the dynamic multi-layer structure on erosion and was able to predict well the effects of weed management on soil loss and runoff at the test site over 1 year, with a modelling efficiency (EF) of 0.5–0.96 and R2 of 0.64–0.92. Subsequently, we validated the ability of the model to simulate surface cover changes under rubber plantations of different age (up to 40 years). Simulation outputs for 4-, 12- and 18-year-old rubber plantations revealed satisfying to good results. However, the predicted change in surface cover for old rubber plantations (25- and 36-year) failed to meet the field trends. The model predicted the greatest erosion in the year when the rubber canopy started to close. During this period, weed growth was limited by light, while litter input from rubber was insufficient to provide good soil cover. Four weeding strategies ("clean-weeding", "twice-weeding", "once-weeding" and "no-weeding") were designed for scenario simulations. Based on the results of 20-year runs, we concluded that "once-weeding" and "no-weeding" both efficiently minimized soil loss during one rotation length. A high degree of surface and weed cover (over 95% and 60%) under "no-weeding" makes this management strategy with dense undergrowth hardly acceptable by local farmers due to reduced tree accessibility for tapping and increased potential danger through poisonous caterpillars. "Once-weeding", on the other hand, controlled overgrowth of understory vegetation by keeping weed cover below 50%. We therefore suggest "once-weeding" as an improved herbicide management strategy in rubber plantations, to meet ecological system service maintenance and to facilitate adoption in practice. Highlights • Forty-year erosion modelling in rubber plantations explains the effect of weeding. • A splash process is incorporated into erosion simulation in rubber plantations. • The updated model includes a multi-layer structure in agroforestry systems. • One herbicide application per year is recommended as a soil conservation measure. [ABSTRACT FROM AUTHOR]

Soil erodibility is an essential parameter used in soil erosion prediction. This study selected the Liangshan town watershed to quantify variation in the vertical zonality of rill erodibility (kr) in China's ecologically fragile Hengduan Mountains. Soil types comprised of yellow–brown (soil A), purple (soil B), and dry‐red (soil C) in a descending order of occurrence from the summit to the valley, which roughly corresponds to the vertical climate zone (i.e. cool‐high mountain, warm‐low mountain, and dry‐hot valley sections) of the study area. With elevation, vertical soil zonality varied in both soil organic matter (SOM) content and soil particle‐size fractions. A series of rill erosion‐based scour experiments were conducted, using water discharge rates of 100, 200, 300, 400, 500, and 600 mL min‐1. Additionally, detachment rates (Dr) were measured under three hydrological conditions (the drainage, saturation, and seepage treatments). Results show that both Dr and flow shear stress (Ʈ) values increased as discharge increased. As elevation increased, the kr values decreased, while the vertical zonality of critical shear stress (Ʈc) values showed no obvious variation. The highest kr values were observed during the seepage treatment, followed by the saturation treatment then drainage treatment, indicating that variation in vertical hydraulic gradients could significantly alter kr values. This study also found that land‐use types could also alter kr and Ʈc values. Further research, however, is necessary to better quantify the effects of subsurface hydrological conditions and land‐use types on kr under different soil zonalities in China's Hengduan Mountains. © 2018 John Wiley & Sons, Ltd. This study selected the Liangshan town watershed to quantify variation in the vertical zonality of rill erodibility (kr) in China's ecologically fragile Hengduan Mountains. As elevation increased, the kr values decreased. The highest kr values were observed during the seepage treatment, followed by the saturation treatment then drainage treatment, indicating that variation in vertical hydraulic gradients could significantly alter kr values. This study also found that land‐use types could also alter kr and Ʈc values. [ABSTRACT FROM AUTHOR]

The paper presents a spatial modeling approach of Soil erodibility (K factor)-which is a complex soil property-on conventional tillage (CoT) and no tillage (NOT) treatments of a Helianthus tuberosus crop using field measurements, soil laboratory analyses, GIS and determenistic models. A split-plot design with 4 treatments *3 replications of experimental field plots was used. Results of Anova statistical analysis (P-0.05) between K data groups revealed that the two tillage systems significantly differ (Sig. -0.008) and also the 4 treatments (A, B, C and D) were significantly different (Sig. -0.032). Final results showed that the best tillage system NOT and treatment C (No Tillage with Vegatation Cover) in hilly farmfields of Greece can be regarded as potential ecological good practices for the farmers, in order to reduse soil erodibility, erosion risk and preserve the soil environment and its valuable nutrients. [ABSTRACT FROM AUTHOR]

The erosion trend of soils is significantly associated with the physical and chemical soil properties. Wet soil aggregate stability (WAS) index is an important parameter in evaluating the erosion trends of soils. The processes of determining and preventing the soil erosion and taking measures against it are quite tiring and long-term. In recent years, estimation and modeling methods are applied to eliminate the wastages of time and effort that emerge us in the examination and investigation of soils. In this study, the soil properties which are measured routinely in semi-arid ecosystems and the predictability of wet soil aggregate stability were investigated by using artificial neural network and multiple linear regression (MLR) technique. For this purpose, 100 soil samples were obtained from 40 sample fields, and particle size distribution (sand, silt, clay), soil pH and organic matter analyses were performed. The soil properties which were selected based on the results of the statistical evaluations were used as independent variables. Accuracy of the predictions was evaluated by Mean Absolute Percentage Error (MAPE) and the root mean square error (RMSE) between the measured and predicted parameter values. The value of MAPE and RMSE derived by ANN model for WAS were 3.20 and 4.19 respectively. The corresponding values for MLR model were 13.10 and 8.32 respectively. Results showed that ANN with six neurons in hidden layer had better performance in predicting soil properties than MLR. [ABSTRACT FROM AUTHOR]

Highlights • One of the first studies that explores the suitability of Sentinel-1 and -2 data of the Copernicus mission in wildfire mapping. • Focus on retrieving information on burnt area, burn severity as well as in quantifying changes in soil erosion. • Results suggest that synergy of data has the potential of improving our ability to map parameters relevant to wildfire mapping. Abstract The present study explores the use of the recently launched Sentinel-1 and -2 data of the Copernicus mission in wildfire mapping with a particular focus on retrieving information on burnt area, burn severity as well as in quantifying soil erosion changes. As study area, the Sierra del Gata wildfire occurred in Spain during the summer of 2015 was selected. First, diverse image processing algorithms for burnt area extraction from Sentinel-2 data were evaluated. In the next step, burn severity maps were derived from Sentinel-2 data alone, and the synergy between Sentinel-2 & Sentinel-1 for this purpose was evaluated. Finally, the impact of the wildfire to soil erodibility estimates derived from the Revised Universal Soil Loss Equation (RUSLE) model implemented to the acquired Sentinel images was explored. In overall, the Support Vector Machines (SVMs) classifier obtained the most accurate burned area mapping, with a derived accuracy of 99.38%. An object-based SVMs classification using as input both optical and radar data was the most effective approach of delineating burn severity, achieving an overall accuracy of 92.97%. Soil erosion mapping predictions allowed quantifying the impact of wildfire to soil erosion at the studied site, suggesting the method could be potentially of a wider use. Our results contribute to the understanding of wildland fire dynamics in the context of the Mediterranean ecosystem, demonstrating the usefulness of Sentinels and of their derived products in wildfire mapping and assessment. [ABSTRACT FROM AUTHOR]

Abstract The recent launch of Sentinel missions offers a unique opportunity to assess the impacts of wildfires at higher spatial and spectral resolution provided by those Earth Observing (EO) systems. Herein, an assessment of the Sentinel-1 & 2 to map burnt areas has been conducted. Initially the use of Sentinel-2 solely was explored, and then in combination with Sentinel-1 and derived radiometric indices. As a case study, the large wildfire occurred in Pedrógão Grande, Portugal in 2017 was used. Burnt area estimates from the European Forest Fires Information System (EFFIS) were used as reference. Burnt area was delineated using the Maximum Likelihood (ML) and Support Vector Machines (SVMs) classifiers, and two multi-index methods. Following this, burn severity was assessed using SVMs and Artificial Neural Networks (ANNs), again for both standalone Sentinel-2 data and in combination with Sentinel-1 and spectral indices. Soil erosion predictions were evaluated using the Revised Universal Soil Loss Equation (RUSLE) model. The effect of the land cover derived from CORINE operational product was also evaluated across the burnt area and severity maps. SVMs produced the most accurate burnt area map, resulting a 94.8% overall accuracy and a Kappa coefficient of 0.90. SVMs also achieved the highest accuracy in burn severity levels estimation, with an overall accuracy of 77.9% and a kappa of 0.710. From an algorithmic perspective, implementation of the techniques applied herein, is based on EO imagery analysis provided nowadays globally at no cost. It is also robust and adaptable, being potentially integrated with other high EO data available. All in all, our study contributes to the understanding of Mediterranean landscape dynamics and corroborates the usefulness of Sentinels data in wildfire studies. Highlights • Assessment of the Sentinels 1 & 2 to map burnt areas, burn severity & soil erosion. • Case study one of the largest wildfires of 2017, in Portugal. • Results corroborate the usefulness of Sentinels in wildfire related studies. [ABSTRACT FROM AUTHOR]

Wind erosion and dust emissions are land surface processes that characterize drylands globally. Wind erosion depends on the relationship between erosivity and erodibility factors. Soil erodibility measures the relative potential for soils to be eroded by wind. In this study, soil erodibility was estimated from soil and vegetation data. Global soil texture data, a global soil database and a Normalized Difference Vegetation Index (NDVI) dataset were used to evaluate soil erodibility over Mongolia in terms of two parameters: wind erodible fraction of soil (a measure of erodibility related to soil properties) and threshold friction velocity. Threshold friction velocity was estimated using the frontal area of the roughness element that was calculated using NDVI-derived vegetation cover. A novel integrated soil erodibility map over Mongolia was developed using the two erodibility parameters and a soil classification map. The estimated wind erodible fraction of soil showed that erodibility is higher in the desert and the desert steppe regions. The estimated threshold friction velocity exhibited also a regional pattern. The threshold friction velocity was lower in the desert and desert steppe regions and higher in the forest area. The integrated soil erodibility map revealed widespread areas of high erodibility from the desert and desert steppe regions in the south to the sandy areas in the west. Low-erodibility areas extended from western to northern Mongolia, while medium-erodibility areas mostly covered the dry steppe regions and the desert steppe in the west. The integrated map will provide a useful climatological basis for studying dust emission processes and for developing practical dust risk assessment and early warning system applications. [ABSTRACT FROM AUTHOR]

The effects of vegetation restoration on soil erosion resistance of gully head, along a revegetation age gradient, remain poorly understood. Hence, we collected undisturbed soil samples from a slope farmland and four grasslands with different revegetation ages (3, 10, 18, 25 years) along gully heads. Then, these samples were used to obtain soil detachment rate of gully heads by the hydraulic flume experiment under five unit width flow discharges (2–6 m3 h). The results revealed that soil properties were significantly ameliorated and root density obviously increased in response to restoration age. Compared with farmland, soil detachment rate of revegetated gully heads decreased 35.5% to 66.5%, and the sensitivity of soil erosion of the gully heads to concentrated flow decreased with revegetation age. The soil detachment rate of gully heads was significantly related to the soil bulk density, soil disintegration rate, capillary porosity, saturated soil hydraulic conductivity, organic matter content and water stable aggregate. The roots of 0–0.5 and 0.5–1.0 mm had the highest benefit in reducing soil loss of gully head. After revegetation, soil erodibility of gully heads decreased 31.0% to 78.6%, and critical shear stress was improved by 1.2 to 4.0 times. The soil erodibility and critical shear stress would reach a stable state after an 18-years revegetation age. These results allow us to better evaluate soil vulnerability of gully heads to concentrated flow erosion and the efficiency of revegetation.

Rill detachment capacity is a key parameter in concentrated flow erosion. Rill erosion generally turns into gully erosion with severe environmental impacts. Changes in land use and human activities can have heavy effects in rill formation, particularly in forests subject to deforestation; soil morphology plays a significant role in these effects. However, literature reports few studies about rill detachment rates and their implications on soil quality in forest and deforested soils with different morphological characteristics. To fill these gaps, this study has evaluated the rill detachment capacity (Dc) and the main soil quality indicators in three areas (upper, middle and lower slope) of forest and deforested (for 10 years) hillslopes exposed to the north and south in Northern Iran. The variations of Dc have been measured on soil samples under laboratory conditions through a flume experiment at three slope gradients (12 to 19%) and five flow rates (0.22 to 0.67 L m−1 s−1) with four replications. The large and significant (p < 0.05) difference (about 70%) detected for Dc between forest and deforested hillslopes was associated to the higher organic matter content of forest areas; as a consequence, these areas also showed higher aggregate stability, porosity, root weight density, microbial respiration and available water. In the deforested hillslopes exposed to the south, the soil erodibility was higher by 12% compared to those exposed to the north. The differences in the monitored soil quality indicators were instead less noticeable and not always significant (p < 0.05). Conversely, Dc did not significantly change (p < 0.05) among the upper, middle and lower hillslope areas investigated in this study. Simple but accurate models to predict the rill detachment capacity, erodibility and critical shear stress of soils from indicators of soil quality or the unit stream power using regression equations are suggested. Overall, the results can support land planners in prioritizing the actions for soil conservation in deforested hillslopes exposed to the south as well as in the extensive application of the proposed equations in erosion prediction models.

Geodetic landmarks (GLs) are essential for obtaining precise height, horizontal coordinates, and the Earth's gravity field. This study aims to assess the soil susceptibility of GLs for past, present, and future scenarios, considering the projected anthropogenic effect from Coupled Model Intercomparison Project, Version 6 (CMIP6). Therefore, the soil loss estimations were made for all the GLs in the southern region of Santa Catarina state in Brazil using the Revised Soil Loss Equation (RUSLE). Our results showed average soil loss decreasing from 1985 to 2020. There was an increase in GLs in the null class (soil loss = 0 t/ha/year), mainly caused by urban growth. A decrease occurred in the low (0 t/ha/year < soil loss ≤10 t/ha/year), very severe (soil loss >200 t/ha/year), severe (50 t/ha/year < soil loss ≤200 t/ha/year), and moderate classes (10 t/ha/year < soil loss ≤50 t/ha/year). In addition, most future scenarios projected an increase in soil loss susceptibility, which also increased the GLs' susceptibility to soil loss from 2020 to 2100, albeit with lower values than the historical series. The soil loss remained stable in ssp126, slightly increased in ssp245 and ssp370, and increased in ssp585. The future scenarios only take into account changes in rainfall. Thus, the land cover change forecast would also be necessary for better analysis for future studies. Therefore, climate simulations can be used to understand the effects of climate change on soil erosion to support decision-making regarding GLs maintenance and the construction of new ones. • Soil erosion can affect the physical integrity of a geodetic network; • Landmarks can be destabilized and become useless; • Rainfall, soil types, relief, land use and land cover are important factors; • The RUSLE equation allows to determine soil loss in the past, present, and future; • Understanding future climate impacts can be important in preserving landmarks. [ABSTRACT FROM AUTHOR]

As a special kind of soil erosion that severely deteriorates the qualities of soil in granite regions, collapsing gully is widely distributed in the tropical and subtropical areas of South China. In particular, collapsing-gully erosion produces a large amount of sediment deposited on the plough layer of alluvial fan farmland and causes increase of desertification, great reduction of nutrients and rapid enhancement of erodibility in the soil. This study was designed to evaluate the effects of different land uses on the soil physic-chemical properties and erodibility of collapsing-gully alluvial fan. Our results show that the physical properties of soil in alluvial fan were greatly improved with smaller bulk density, increased soil porosity, strengthened water holding capacity and a higher particulate matter content. The chemical properties of soil were also significantly improved, including pH, cation exchange capacity, and the contents of organic matter, total and available nitrogen, potassium and phosphorus. All the land uses were proved to improve the soil properties, especially in the tea garden, vegetable land and paddy field. The results of correlation analyses among the properties demonstrate that the physical and chemical properties were significantly correlated, indicating that improving the soil physical properties is an effective method to increase the soil nutrient in the farmland of collapsing-gully alluvial fan. In addition, the application of land uses included grass land, eucalyptus forest land, vegetable land, tea garden, sweet potato land, and paddy field reduced the erodibility of the soil compare to bare land. The erodibility K values of soils in grass land, eucalyptus forest land, vegetable land, tea garden, sweet potato land, and paddy field were 14.43, 16.97, 45.45, 33.12, 18.94, and 34.01% lower than those of bare land, respectively. The results of multiple linear regression analysis show that the soil erodibility had a significant correlation with the physic-chemical properties, especially the soil texture and the content of organic matter. In conclusion, our results demonstrate that different land use patterns are effective to improve the quality of the soil in collapsing-gully alluvial fan, including the improvements of the soil structure, nutrients and anti-erosion ability. Our findings provide important implications for the soil improvement in the farmland of collapsing-gully alluvial fan.

Soil erodibility (K factor) is the most important tool for estimation the erosion. The aim of this study was to estimate the soil erodibility in Sanganeh area located in Naderi Kalat, Khorasan Razavi Province of northeastern Iran. The sediments load collected during the 17 rainfall events were measured at the end of 12 plots during 2009-2012. The K factor was calculated according to the USLE for each plot and rainfall event. The relationships between K factor and measured sediments load with soil attributes were studied. The results showed that calcium carbonate, SAR (sodium absorption ratio), silt, clay contents, and SI (structural stability index) were the most effective soil attributes for estimating the sediments load and OM (organic matter), sand, SI and calcium carbonate, silt, clay contents, and SI for K factor. The results of stepwise regression equations showed that the precision of regression equation derived from PCA for estimating the K factor and sediments load were more than ones derived from correlation test. According to the results of this research, it’s recommended that PCA be applied for determination the effective soil attributes for estimating the K factor in USLE and sediments load in studied area.

This study aimed to assess the ability of using visible and near-infrared reflectance (Vis–NIR) spectroscopy to quantify soil erodibility factor (K) rapidly in an ecologically restored watershed. To achieve this goal, we explored the performance and transferability of the developed spectral models in multiple land-use types: woodland, shrubland, terrace, and slope farmland (the first two types are natural land and the latter two are cultivated land). Subsequently, we developed an improved approach by combining spectral data with related topographic variables (i.e., elevation, watershed location, slope height, and normalized height) to estimate K. The results indicate that the calibrated spectral model using total samples could estimate K factor effectively (R2CV = 0.71, RMSECV = 0.0030 Mg h Mj−1 mm−1, and RPDCV = 1.84). When predicting K in the new samples, models performed well in natural land soils (R2P = 0.74, RPDP = 1.93) but failed in cultivated land soils (R2P = 0.24, RPDP = 0.99). Furthermore, the developed models showed low transferability between the natural and cultivated land datasets. The results also indicate that the combination of spectral data with topographic variables could slightly increase the accuracies of K estimation in total and natural land datasets but did not work for cultivated land samples. This study demonstrated that the Vis–NIR spectroscopy could be used as an effective method in predicting K. However, the predictability and transferability of the calibrated models were land-use type dependent. Our study also revealed that the coupling of spectrum and environmental variable is an effective improvement of K estimation in natural landscape region.

The Normalized Difference Vegetation Index (NDVI), has been increasingly used to capture spatiotemporal variations in cover factor (C) determination for erosion prediction on a larger landscape scale. However, NDVI-based C factor (Cndvi) estimation per se is sensitive to various biophysical variables, such as soil condition, topographic features, and vegetation phenology. As a result, Cndvi often results in incorrect values that affect the quality of soil erosion prediction. The aim of this study is to multi-temporally estimate Cndvi values and compare the values with those of literature values (Clit) in order to quantify discrepancies between C values obtained via NDVI and empirical-based methods. A further aim is to quantify the effect of biophysical variables such as slope shape, erodibility, and crop growth stage variation on Cndvi and soil erosion prediction on an agricultural landscape scale. Multi-temporal Landsat 7, Landsat 8, and Sentinel 2 data, from 2013 to 2016, were used in combination with high resolution agricultural land use data of the Integrated Administrative and Control System, from the Uckermark district of north-eastern Germany. Correlations between Cndvi and Clit improved in data from spring and summer seasons (up to r = 0.93); nonetheless, the Cndvi values were generally higher compared with Clit values. Consequently, modelling erosion using Cndvi resulted in two times higher rates than modelling with Clit. The Cndvi values were found to be sensitive to soil erodibility condition and slope shape of the landscape. Higher erodibility condition was associated with higher Cndvi values. Spring and summer taken images showed significant sensitivity to heterogeneous soil condition. The Cndvi estimation also showed varying sensitivity to slope shape variation; values on convex-shaped slopes were higher compared with flat slopes. Quantifying the sensitivity of Cndvi values to biophysical variables may help improve capturing spatiotemporal variability of C factor values in similar landscapes and conditions.

The relationships between surface runoffand soil erodibility are significant in water pollution and watershed management practices. Land use pattern, soil series and slope percentage are also major factors to develop the relationships. Daily rainfall data were collected and analyzed for variations in precipitation for calculating the surface runoff of these watersheds and surface runoff map was produced by GIS tools. Tew equation was utilized to predict soil erodibility of watershed soils.Results indicated that the weighted curve number varies from 82 to 85 and monthly runoff 23% to 30% among the five watersheds. Soil erodibility varies from 0.038 to 0.06 ton/ha (MJ.mm/ha/h). Linau-Telok-Local Alluvium, Malacca-Munchong, Munchong-Malacca-Serdang and Malacca-Munchong-Tavy are the dominant soil series of this region having the average soil erodibility of about 0.042 ton/ha (MJ.mm/ha/h). The main focus of this study is to provide the information of soil erodibility to reduce the water pollution of a watershed.

In this study we focused on the factors affecting final outputs of the USLE (Universal Soil Loss Equation) model. In doing so, we conducted soil particle size measurements in different institutions (University of Debrecen, University of Szeged and Geographical Institute, Research Centre for Astronomy and Earth Sciences of the Hungarian Academy of Sciences) with a variety of methodologies (laser, aerometer and pipette methods) on various soil materials (sandy, loamy and clay). Statistical analyses of the eight examined soil samples have been shown some significant and some non-significant differences among the particle size measurements. This paper is aimed at i) to ascertain whether these significant differences in particle size measurements cause significant differences in soil erodibility calculations; and ii) to assess the amount of soil loss calculated by these K factors. The results suggest that regardless of the relatively small percentage between the smallest and the greatest K factor values, the amount of soil loss can be fairly high, especially when erosion occurs on a longer or steeper slope. In the present case, when we compare simulations results, the amount of soil loss is more important than the difference in percentage between the minimum and maximum values. Because the percentage of the difference can remain the same between the simulations, while the amount of soil loss increases way beyond soil loss tolerance limits.

Land Use Land Cover (LULC) change analysis assists decision makers to ensure sustainable development and to understand the dynamics of our changing environment. During the past 15 years the study area has undergone many LULC changes due to rapid urban growth, poorly planned infrastructural development and a devastating earthquake event. This study was proposed to detect LULC changes and to investigate the major factors that have caused these changes. Steep topography, shallow soils and monsoonal climatic conditions tend to accelerate soil erosion that causes heavy sedimentation downstream. Therefore, erosion risk mapping was performed to prioritize the vulnerable areas for conservation efforts. For LULC change detection and analysis temporal Landsat satellite data captured by Thematic Mapper (TM) were employed. Maximum Likelihood (MLH) supervised classification algorithm was applied to classify the study area, whereas, Post Classification Comparison (PCC) approach was adopted to analyze the LULC changes. Soil erosion risk map was generated using four erosion controlling factors including rainfall, topography, soil erodibility and LULC. Results revealed that over a period of 11 years, a decrease has taken place in forest and low vegetation cover at a change rate of −02.70% and −02.60% respectively. On the other hand, built up and bare soil have increased at a rate of 01.00% and 04.20% respectively. The resultant erosion risk map shows that 59% of the area lies under low risk zone whereas 24%, 5% and 12% of the total area fall in medium, high and very high risk categories respectively.

Severe fire greatly increases soil erosion rates and overland-flow in forest land. Soil erosion prediction models are essential for estimating fire impacts and planning post-fire emergency responses. We evaluated the performance of a) the Revised Universal Soil Loss Equation (RUSLE), modified by inclusion of an alternative equation for the soil erodibility factor, and b) the Disturbed WEPP model, by comparing the soil loss predicted by the models and the soil loss measured in the first year after wildfire in 44 experimental field plots in NW Spain. The Disturbed WEPP has not previously been validated with field data for use in NW Spain; validation studies are also very scarce in other areas. We found that both models underestimated the erosion rates. The accuracy of the RUSLE model was low, even after inclusion of a modified soil erodibility factor accounting for high contents of soil organic matter. We conclude that neither model is suitable for predicting soil erosion in the first year after fire in NW Spain and suggest that soil burn severity should be given greater weighting in post-fire soil erosion modelling. [ABSTRACT FROM AUTHOR]

The effects of soil water content (SWC) and erodibility on available nutrient losses, as well as the influence of freeze-thaw on available nitrogen (AN) and phosphorus (AP) losses from loess soils have rarely been considered. We report on a series of laboratory simulation experiments conducted to determine SWC and soil erodibility effects on AN and AP losses under freeze-thaw conditions. Effect of freeze/thaw compared to unfrozen, two treatments were set (LS: Loess that unfrozen; FTS: Freeze-thawed a loess), and we studied five SWCs, between 10% and 30%, and we divided SWCs into two groups: lower water content areas (10% and 15%), higher water content areas (20%, 25%, and 30%). Overall, significant differences in runoff/sediment associated AN and AP concentrations of different SWCs for two treatments (p < 0.05) were noted, while the relationship between SWC and AN and AP loss show a quadratic function change trend (R 2  > 0.8). Largest runoff-associated AN and AP losses were found when the SWC was 30% and the largest sediment-associated AN and AP losses were found when the SWC was 10% in the two treatments. The soil erodibility factor ( K ) of the LS was less than that of the FTS when the SWC was low, and greater in a high water content area. The influence of runoff on sediment was positively linear. The absolute slope of the regression line between runoff rate and sediment yield rate is shown to be suitable as a soil erodibility indicator, while runoff-associated AN losses are mainly controlled by runoff rate, and are weakly affected by soil erodibility (p > 0.05). However, soil erodibility significantly influenced sediment-associated AP losses (p < 0.01), best described by a positive logarithmic relationship. Since the sediment-associated AP losses dominated the total AP losses for the two treatments, soil erodibility also exhibited a significant influence on total AP losses (p < 0.01). The freeze-thaw effect increased the total AN loss when the SWC was 15%, 20%, and 30%, and increased the total AP loss when it was 10% and 15%. The results of this study provide a better understanding of soil and available nutrient loss mechanisms under freeze-thaw conditions. [ABSTRACT FROM AUTHOR]

Somalia nation has been in the past classified as a volatile and of low economic value since 1990s when the government was deemed to have collapsed. Currently the independent Somalia is turning out to be one economic back bone of the Northern and Eastern parts of Africa in trade and agriculture. This paper focuses on the agricultural potential of Somalia using geospatial techniques through characterization. Climate is characterized and described, terrain models are derived, Soil analysis and hydrological assessment are also analyzed. Agroclimatic maps are developed to show suitable and unsuitable areas for agricultural production. The terrain of Somalia is more of a flat plain coupled with river basins that can be used as arable lands for agriculture. The ground water points can sustainably irrigate large number of parcels for crop production. Through GIS technology adopted for this particular work, two basins were mapped out to be possible agricultural potential areas: Juba and Shabelle. The assessment indicates that crop production can be achieved through irrigating of the arable plains and not relying so much on rain-fed agricultural systems. Agro-climatic zones of Somalia are delineated mainly due the amount of rainfall, temperature ranges and terrain patterns. With this study, farmers can be advised on which area to focus for crop production. The agricultural potential that lies in Somalia is so huge it could be named the future food basket of Africa, who knows? [ABSTRACT FROM AUTHOR]

Abstract: The soil factor is crucial in controlling and properly modeling the initiation and development of ephemeral gullies (EGs). Usually, EG initiation has been related to various soil properties (i.e. sealing, critical shear stress, moisture, texture, etc.); meanwhile, the total growth of each EG (erosion rate) has been linked with proper soil erodibility. But, despite the studies to determine the influence of soil erodibility on (ephemeral) gully erosion, a universal approach is still lacking. This is due to the complex relationship and interactions between soil properties and the erosive process. A feasible soil characterization of EG erosion prediction on a large scale should be based on simple, quick and inexpensive tests to perform. The objective of this study was to identify and assess the soil properties – easily and quickly to determine – which best reflect soil erodibility on EG erosion. Forty‐nine different physical–chemical soil properties that may participate in establishing soil erodibility were determined on agricultural soils affected by the formation of EGs in Spain and Italy. Experiments were conducted in the laboratory and in the field (in the vicinity of the erosion paths). Because of its importance in controlling EG erosion, five variables related to antecedent moisture prior to the event that generated the gullies and two properties related to landscape topography were obtained for each situation. The most relevant variables were detected using multivariate analysis. The results defined 13 key variables: water content before the initiation of EGs, organic matter content, cation exchange capacity, relative sealing index, two granulometric and organic matter indices, seal permeability, aggregates stability (three index), crust penetration resistance, shear strength and an erodibility index obtained from the Jet Test erosion apparatus. The latter is proposed as a useful technique to evaluate and predict soil loss caused by EG erosion. Copyright © 2018 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The intrinsic and extrinsic factors that control soil aggregate formation have been widely studied at the aggregate scale, but little is known about their roles in aggregate formation at different landscape scales. Here, a spatial analysis of soil aggregate stability and erodibility (K factors) was performed to understand the formation processes of aggregates at catchment scale. Spatial structures of the mean weight-diameter (MWD, mm), water-stable aggregates greater than 0.25 mm (WSA >0.25 , %) and K factors were investigated by using classical statistics, semivariograms, Local Indicators of Spatial Association (LISA), spatial interpretation, and spatial overlay in a small catchment of the Loess Plateau, China (LPC). The results showed that MWD and WSA >0.25 were significantly lower in farmland than in other land types, and were obviously higher in shrubland than in woodland, but it was the opposite case for K factors. Nugget/sill ratios C 0 /(C 0  + C) showed a very strong spatial dependence for MWD (9.13% at 0–10 cm and 19.49% at 10–20 cm soil layer) and WSA >0.25 (12.48% at 0–10 cm and 17.71% at 10–20 cm soil layer). These data and LISA results implied that the spatial variability of MWD, WSA >0.25 and K factors in the Zhifanggou catchment was mainly controlled by intrinsic factors such as parent materials, terrain attributes and soil types. Besides, the effects of extrinsic factors (land use and farming practice) could not be ignored, especially for K factors. Cross-validation results illustrated that ordinary kriging (OK) performed better than inverse distance weighting (IDW) for MWD and WSA >0.25 , but it was the opposite for K factors as a whole. Land-use type, topography, vegetation, and revegetation duration showed interactive effects on the spatial heterogeneity of soil aggregate stability and K factors. Spatial analysis showed great potential to be applied in the analysis of the influencing factors of soil aggregate stability at the small catchment scale. [ABSTRACT FROM AUTHOR]

Areas subjected to fire have a two-layer system (i.e., ash and soil), which brings enormous complexities to hydrogeomorphic processes. In addition, the combinations of variables from the ash and the soil characteristics result in several possible two-layer system contexts. Here, the interactions among ash and microaggregates (i.e., ash placed over fine soil microaggregates) and their effects on hydro-erosional processes are explored. The ash was produced by an experimental fire and collected from a field managed by a slash-and-burn agricultural system. The design of the experiment included a strategy for considering combinations in which each of the various factors of interest, i.e., ash and microaggregates, was present or absent. In addition, the study searched for interactions between the two factors when both were present. In total, 600 g m 2 of fine ash mixture (<0.250 mm), obtained from fire at different temperatures, and 90 g m 2 of microaggregates was placed over a small splash pan (0.135 m 2 ). Next, a rainfall of 56 mm h −1 lasting for 30 min was applied in four replicates for each treatment: 1) bare soil, 2) bare soil + microaggregates, 3) ash, and 4) ash + microaggregates. The interaction between the ash and soil microaggregates changed the soil hydrology dynamics, reducing soil moisture by 28% and surface runoff by 78%. The ash–microaggregates combination reduced soil loss by sheetwash by 20% and by rainsplash by 25%. Overall, the ash treatment increased soil loss by 47% compared to the case of bare soil. On the contrary, the ash–microaggregates interaction decreased soil loss by 26% compared to the ash treatment. [ABSTRACT FROM AUTHOR]

Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) are the models to compute the soil erosion loss, to estimate the accurate value of soil erosion that must be predicted several factors of its model. The land cover surface of topsoil is the important effect on the estimation of soil erosion loss. In this paper, the Euphrates watershed river of Iraq country will be adopted. This watershed includes seven provinces Najaf, Karbala, Al-Qadisiyyah, Dhi Qar, Al Muthanna, Babylon and Basrah of Iraq. The objective of present study was estimated the erodibility factor K for the watershed area. The K factor map was derived from the database of the UN-FAO (Food and Agriculture Organization of the United Nations 2007). This map of erodibility factor was prepared by ArcMap 10.2 software. It was estimated that K factor values of this watershed of study area range from 0.02276 to 0.00928. The K factor is depended on the percentage of topsoil content as sand, silt, clay and organic carbon. The large value of K factor for the topsoil type is Jc symbol (39% sand, 40% silt and 21% clay), while the soil erodibility factor is low for Qa-topsoil kind (92% sand, 3% silt, 4% clay and 1% organic carbon) because the silt of topsoil content is low compared with different other kinds. The big area of topsoil watershed type is Yk-type (63% sand, 18% silt, and 19% clay), it has been occupied about 47.2% of the whole watershed area. [ABSTRACT FROM AUTHOR]

Copyright of Ra'e Ga is the property of Ra'e Ga - O Espaco Geografico em Analise 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.)

This paper reports the results of jet tester experiments on soil samples of uniform properties which allow quantitative application of the new theory proposed in part 1 of these publications. This theory explores the possibly that a more adequate indicator of soil erodibility may be obtained by using the mass (and so volume) of soil eroded by the jet and the depth of scour penetration, rather than by using penetration depth alone, as assumed in the commonly-used data interpretation method. It is shown that scour geometry can be well described using a generalized form of the Gaussian function, defined by its standard deviation and maximum depth. Using a published expression for jet kinetic energy flux, the new theory divides this flux into that used to erode soil and the remainder which is dissipated in a variety of ways. Jet experiments on a specially-prepared uniform soil sample are reported which provide the key to determining the spatial variability in the profile resistance to erosion offered by field soils. This resistance is expressed in the work required to erode unit mass of soil, denoted as J (in J/kg). The paper also gives results obtained on the profile variation in J for jet tests carried out at riverine sites on the upper Brisbane River, Queensland, Australia. As expected in most natural soil profiles, the results show an increase in J with depth in the profile. The soil resistance (J) is compared to the traditional interpretation of soil erodibility, (kd). The graphical comparison of these two indicators illustrates the inverse type of relationship between them which is expected from their respective definitions, but this relationship is associated with significant scatter. Possible reasons for this scatter are given, together with comments on jet tester experience in a wide variety of soil types. [ABSTRACT FROM AUTHOR]

Abstract: Soil erosion is a serious problem world‐wide for the environment or humankind, exacerbating land degradation. However, little systematic knowledge is available about the erodibility of various types of soils at different erosional degradation levels, especially at the field scale. In this research, the spatiotemporal variations of the erodibility for 5 soil types (calcic luvisol, ferric luvisol, plinthic alisol, plinthic acrisol, and acric ferralsol) from temperate to tropical climate were investigated with field rainfall simulation experiments on prewetted bare fallow heavy‐textured soils (silty clay loam, silty clay, and clay) derived separately from loess deposits, quaternary red clays, and basalt. The experiments were performed in 3 erosion classes (noneroded, moderately eroded, and very severely eroded) and at 2 rainfall intensities (45 and 90 mm hr−1). Soil erodibility was represented by the K factor of the Revised Universal Soil Loss Equation. Soil erodibility was the lowest for the ferralsols among all the soil types and was significantly lower in the very severe than in the no or moderate erosion classes. Soil erodibility tended to be larger at the high than at the low rainfall intensity (p < .05) except for the very severely eroded luvisols, and their difference between rainfall intensities in the erodibility varied with rainfall duration. Soil erodibility could be well predicted by the combination of illite, dry aggregate stability, and amorphous aluminium oxides (adjusted R2 = .51, p < .001), and its temporal variations were significantly related with particle density, 1.4‐nm intergrade mineral, and capillary porosity (p < .05). Furthermore, soil properties selected to account for soil erodibility varied with rainfall intensity. The integrated data indicated that soil erodibility was mainly influenced by clay minerals at the region scale and soil degradation degree at the pedon scale. [ABSTRACT FROM AUTHOR]

Abstract: After slash‐and‐burn agriculture, topsoil becomes covered by ash layers of various colors. The different colored ashes have particular properties that may affect the hydro‐erosional processes on hillslopes in different ways. In the present study, the effects of black and gray ashes on the hydro‐erosional processes were examined in the context of slash‐and‐burn, and the soil erosion subprocesses responsible for soil loss were identified. Black and gray ashes were collected in the field after two slash‐and‐burn fires. The experiment was conducted in wettable, clay‐textured, brown oxisols. In the laboratory, the ash was spread carefully by hand over a plot of 0·14 m2. Simulated rainfall was discharged from a height of 6 m from the central plot for a period of 30 min with a rainfall intensity of 58 mm h−1. Gray ash reduced infiltration five times more than black ash and four times more than bare soil. The runoff coefficient showed black ash with minor runoff of ~7%, bare soil displayed intermediate runoff of ~12%, and gray ash exhibited the major runoff coefficient of 19%. Gray ash generated six and three and a half times more sediment than black ash and bare soil, respectively. This study determined that soil hydrology is affected more by ash cover than soil loss. Black ash protects against soil erosion and improves soil water infiltration; gray ash dramatically changes the topsoil hydrology and interill erosion processes; and bare soil and soil cover with different ash colors lose soil through different erosion subprocesses. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Copyright of Bulletin of the Faculty of Forestry, University of Banja Luka / Glasnik Šumarskog Fakulteta Univerziteta u Banjoj Luci is the property of University of Banja Luka, Faculty of Forestry 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.)

Detailed information pertaining to soil erosion is required to ensure eco-environment protection and economic development for Xinjiang Uygur Autonomous Region, and remote sensing and geographical information system technologies are adopted to obtain an accurate distribution of soil erosion. An improved estimation method for wind erosion is developed, which proves to be effective with an overall precision of 87.24%. The proposed model uses six critical factors: number of snow cover days, soil erodibility, aridity index, vegetation fraction, soil crust index, and wind field intensity. Results show that soil wind erosion is widely distributed throughout the Xinjiang Uygur Autonomous Region. The average erosion intensity is 0.50, which is determined to be a moderate erosion level. The wind erosion intensity increases from a slight level in the western part to a severe level in the mid-eastern part. The mean intensity of soil wind erosion for varying land use types is ranked in descending magnitude of barren or sparse vegetation, open shrubland, grassland, cropland, evergreen coniferous forest, and mixed forest. There are large differences in soil wind erosion intensities among soil types; grassland has severe wind erosion and Luvic Arenosols has the lowest erosion intensity. [ABSTRACT FROM AUTHOR]

Albania is known for having a considerable area of ultramafic soils, which are mainly located on the southeastern part of the country. The major part of this area is under intensive research aiming the recognition of status and its behavior above of all, and after, finding out the best ways and practices to improve the soil productivity. This is also, firstly, in fact, the broad aim of the research undertaken by our research team and presented in this article. Secondly, the more concrete aim is to determine, in real magnitudes, the capacity of these very specific soils to resist to erosion, which is a very widespread and dangerous phenomenon in the area where this type of soils occur naturally. That is why, the relationships existing between the erodibility index, K, and the textural factors, particularly clay and silt contents in ultramafic substrates (serpentines), is also at the centre of this study. The most typical ultramafic soils in Albania are considered to be the "ground" to determine these relationships. For each soil under consideration, the soil texture, organic matter, soil structure and soil permeability are determined experimentally. The above-mentioned measurements were used to calculate the erodibility factor for every single soil under consideration, by applying the Wischmeier equation. After, the erodibility factor, K, already determined, was considered, theoretically at least, as affected by the relative presence of clay and silt particles in soil. In order to determine this relationship quantitatively, which is believed to be a cause-effect relationship as well, the regression analysis was undertaken. The findings revealed interesting and specific relations between the erodibility factor and both: clay and silt contents, respectively. The very essential result was that the direction of dependency of soil erodibility on the clay content is the opposite of the direction of dependency of soil erodibility on the silt content. The increase of clay content in serpentines soils leads to a decrease of the soil erodibility; but the increase of silt content of the same type of soils leads to an increase of the soil erodibility. [ABSTRACT FROM AUTHOR]

Soil erosion poses a major threat to the sustainability of soil and water resources. Soil horizons differ in their properties due to pedogenic differentiation. Currently, limited research attempts have been made to assess the impact of the removal of topsoil horizons on the subsequent erosion process. The main objective in this study was to investigate the effects of erosion degree and rainfall intensity on erosion process and sediment transport mechanism. Field plot experiments were conducted on pre-wetted bare fallow Ultisols (derived from quaternary red clay) under four erosion degrees (no (E0), moderate (E1), severe (E2), and very severe (E3)) and two rainfall intensities (60 and 120 mm h −1 ). The erosion degrees were judged according to the outcrop of eluvium, illuvium (B1, B2) and parent material horizons. The simulated rainfall lasted one hour after runoff generation, and runoff and sediment were sampled at 3-min intervals to determine the runoff coefficient, sediment concentration, soil detachment rate and sediment effective size distribution. Runoff coefficient was negatively correlated with bulk density (r = −0.76, p < 0.05). Sediment concentration and soil detachment rate decreased with an increased erosion degree at the low rainfall intensity while they decreased in the order of E1 > E0 > E2 > E3 at the high rainfall intensity. Rainfall intensity and clay content played the negative and positive roles in the erosion process, respectively (Adj-R 2 > 0.80, p < 0.01). For E3, sediment transport was dominated by suspension/saltation (<0.1 mm) while for the other erosion degrees it was dominated by mechanisms of both suspension/saltation and rolling (2–0.5 mm). The average sediment size was positively correlated with silt content (r = 0.82, p < 0.05). The high variation of erosion process with erosion degree was intrinsically attributed to the difference in soil horizon nature (mainly soil texture and bulk density) and also influenced by rainfall intensity to varying extent, which should be considered in future erosion prediction. [ABSTRACT FROM AUTHOR]

Land-use change through degrading natural vegetation for agricultural production adversely affects many of soil properties particularly organic carbon content of soils. The native shrub land and grassland of Gaziantep-Adiyaman plateau that is an important pistachio growing eco-region have been cleared to convert into pistachio orchard for the last 50 to 60 years. In this study, the effects of conversion of natural vegetation into agricultural uses on soil erodibility have been investigated. Soil samples were collected from surface of agricultural fields and adjacent natural vegetation areas, and samples were analyzed for some soil erodibility indices such as dispersion ratio (DR), erosion ratio (ER), structural stability index (SSI), Henin's instability index ( I ), and aggregate size distribution after wet sieving (AggSD). According to the statistical evaluation, these two areas were found as different from each other in terms of erosion indices except for I index ( P < 0.001 for DR and ER or P < 0.01 for SSI). In addition, native shrub land and converted land to agriculture were found different in terms of AggSD in all aggregate size groups. As a contrary to expectations, correlation tests showed that there were no any interaction between soil organic carbon and measured erodibility indices in two areas. In addition, significant relationships were determined between measured variables and soil textural fractions as statistical. These obtaining findings were attributed to changing of textural component distribution and initial aggregate size distribution results from land-use change in the study area. Study results were explained about hierarchical aggregate formation mechanism. [ABSTRACT FROM AUTHOR]

• The impact of freeze–thaw effect (FT) on the soil erodibility of gully heads was quantified. • FT increased the comprehensive soil erodibility index (CSEI) of the gully heads by 26%. • The contribution of roots to the change in soil erodibility increased by 79% after FT. • Extreme low temperature and temperature change had the greatest impact on the CSEI. The soil erodibility of gully headwalls is a critical factor influencing gully erosion. In some cold regions, the soil of gully headwalls is subjected to a bidirectional freeze–thaw effect (FT), while the quantification of the influence of FT on the soil erodibility of gully heads is unclear. Therefore, five typical and representative gullies developed in farmlands (G F1 and G F2), along unpaved road (G R), in the woodland (G W) and in stabilized gully bed (G S) were selected to quantify the influence of FT on the soil erodibility of gully heads reflected by five soil erodibility parameters including the K factor (K), soil disintegration rate (SDR), mean weight diameter (MWD), soil shear strength (SS) and saturated soil hydraulic conductivity (SHC). A comprehensive soil erodibility index (CSEI) was constructed by combining the above five soil erodibility parameters. This study revealed that FT significantly affected the five soil erodibility parameters and CSEI , of which the K and SDR increased by 22.7 % and 52.3 %, respectively, but the MWD , SHC and SS decreased by 29.3 %, 30.4 % and 26.1 %, respectively. The change in soil erodibility of the gully heads was closely related to the soil and root properties, of which the contribution of roots to the change in soil erodibility of gully heads was increased by 78.5 % after FT on average. Furthermore, FT significantly increased the CSEI at depths of 0–50 cm in G F1 , G F2 and G R , and at depths of 0–80 cm in G w and G S. FT increased the CSEIs of the five gully heads by 20.1 %-37.3 %, with an average of 26.1 %. Evidently, the organic matter content (OMC), soil texture and temperature dominated the change in the CSEI , of which the extremely low temperature and temperature rangeability during freeze–thaw period exhibited the greatest impact on the soil erodibility of the gully heads. [ABSTRACT FROM AUTHOR]

It is generally acknowledged that soil erosion has become one of the greatest global threats to the human−environment system. Although the Revised Universal Soil Loss Equation (RUSLE) has been widely used for soil erosion estimation, the algorithm for calculating soil erodibility factor (K) in this equation remains limited, particularly in the context of China, which features highly diverse soil types. In order to address the problem, a modified algorithm describing the piecewise function of gravel content and relative soil erosion was used for the first time to modify the soil erodibility factor, because it has been proven that gravel content has an important effect on soil erosion. The Chaohu Lake Basin (CLB) in East China was used as an example to assess whether our proposal can improve the accuracy of soil erodibility calculation and soil erosion estimation compared with measured data. Results show that (1) taking gravel content into account helps to improve the calculation of soil erodibility and soil erosion estimation due to its protection to topsoil; (2) the overall soil erosion in the CLB was low (1.78 Mg·ha−1·year−1) the majority of which was slight erosion (accounting for 85.6%) and no extremely severe erosion; and (3) inappropriate land use such as steep slope reclamation and excessive vegetation destruction are the main reasons for soil erosion of the CLB. Our study will contribute to decision-makers to develop soil and water conservation policies.

This study investigates the effects of pumice excavation on runoff formation and soil erosion processes in a forested catchment in SW-Germany. The underlying questions are, if (a) backfilled soils have different properties concerning runoff generation and erodibility and if (b) clear-cutting prior to excavation triggers runoff and erosion. Four adjacent sub-areas were observed, which represented different pre- and post-excavation-stages. The basis of the investigation was a comprehensive field sampling that delivered the data for physical erosion modeling using the Water Erosion Prediction Project (WEPP). Modeling took place for standardized conditions (uniform slope geometry and/or uniform land management) and for actual slope geometry and land management. The results show that backfilled soils exhibited 53% increase of annual runoff and 70% increase of annual soil loss under standardized conditions. Storm runoff was increased by 6%, while storm soil loss was reduced by 9%. Land management changes also triggered shifts in annual runoff and soil erosion: Clear-cut (+1.796% runoff, +4.205% soil loss) and bare (+5.958% runoff, +21.055% soil loss) surfaces showed the most distinct changes when compared to undisturbed forest. While reforestation largely diminished post-excavation runoff and soil erosion, the standardized results statistically prove that soil erodibility and runoff generation remain increased after backfilling.

A data-driven model based on an adaptive neuro-fuzzy inference system (ANFIS) was tested for the estimation of suspended sediment concentrations within watersheds influenced by agriculture. ANFIS models were developed using different combinations of inputs such as precipitation, streamflow, surface runoff and the watershed vulnerability index. A multi-watershed ANFIS model was also developed combining the datasets from all studied watersheds. The best results were obtained from a combination of precipitation, streamflow and watershed vulnerability index as input variables. Nash-Sutcliffe coefficients were improved for the multi-watershed ANFIS compared to watershed-specific ANFIS models. The introduction of the erosion vulnerability index significantly improved the ability of the ANFIS model to estimate suspended sediment concentrations within the watersheds. Furthermore, the inclusion of this index opens the possibility of using the ANFIS model to investigate the impact of land-use changes on sediment delivery. [ABSTRACT FROM PUBLISHER]

Rainfall erosivity is the capability of rainfall to cause soil loss from hillslopes by water. Modern definitions of rainfall erosivity began with the development of the Universal Soil Loss Equation (USLE), where rainfall characteristics were statistically related to soil loss from thousands of plot-years of natural rainfall and runoff data. USLE erosivity combines the energy of the rainfall and the maximum continuous 30-min intensity in the event. Energy of rainfall is estimated as a function of the storm intensity through the rainfall event. The USLE erosivity has been used effectively for conservation planning purposes for more than 5 decades. When the USLE was replaced by the Revised Universal Soil Loss Equation (RUSLE), a new energy-intensity equation was adopted. The new equation was not extensively tested prior to adoption, leads to significant under-predictions of erosivity, and was later replaced in RUSLE2. The RUSLE energy-intensity equation is no longer recommended by the RUSLE and RUSLE2 development teams. RUSLE2 also introduced the concept of erosivity density, which resulted in significant improvements in the calculations and mapping of rainfall erosivity. Calculations of erosivity as a whole are entirely based on rainfall intensities, and erosivity is an empirically-based index. The science indicates that the direct role of kinetic energy of rainfall as the driver of hillslope erosion in all cases is not warranted by the overall evidence, because many times the kinetic energy of raindrops is not the driving force behind rill erosion. The USLE erosivity empirically explains much of the variance in the soil loss from natural rainfall erosion plots. [ABSTRACT FROM AUTHOR]