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Rainfall-induced progressive soil erosion of compacted surface layer (SL) impedes the functioning of cover system (CS) of landfills with high expected design life (≈ 100 years). The existing soil erosion models are not tested extensively for compacted soil with cracks and vegetation. This study evaluated the efficacy of three popular soil erosion models for estimating the soil loss of compacted SL of CS, which is useful for annual maintenance. The interactive effect of rainfall, vegetation and desiccation cracks on erosion of compacted surface layer was investigated under the influence of both natural and simulated rainfall events for one year. Among all, the Morgan, Morgan and Finney (MMF) model was found to be effective in predicting soil erosion of compacted SL. However, the MMF model overestimated soil erosion when the vegetation cover exceeded 60%. The soil loss estimated from Revised Universal Soil Loss Equation (RUSLE) and Water Erosion Prediction Project (WEPP) models was poor for high rainfall intensity (100 mm/h). The RUSLE and WEPP model overestimated the soil erosion for low vegetation cover (≤ 3%) and underestimated for vegetation area > 3%. The mechanism of root reinforcement, strength due to root water uptake-induced soil suction and its effect on soil loss mitigation could not be adequately captured by the existing models for compacted SL. Further studies are needed to improve the existing erosion models for incorporating the effects of desiccation and vegetation on soil loss from the compacted SL.

In this study, the Water Erosion Prediction Project (WEPP) was used to model the soil sediment yield in four monocropping systems in Claveria, Misamis Oriental in Southern Philippines, as influenced by rainfall. The rainfall data were analyzed and inputted into the WEPP model, together with the soil, climate, and other relevant data in Claveria. The sensitivity analysis was performed using four corn monocropping systems (CMS), including no-till (NT), light till (LT), medium till (MT), and heavy till (HT), considering rill cover, effective hydraulic conductivities of the soil, increasing annual rainfall, and rainfall-runoff factors. The WEPP model indicated that soil sediment yield is highly sensitive to the type of tillage practice and the increased rainfall in Claveria. Claveria’s average annual rainfall is over 3000 mm with nine rainy months and three dry months. During the 13 years, the annual rainfall increased by 28%, which is equivalent to 68 mm/year. The average annual erosion rates increased by 114%, 85%, and 54% in LT, MT, and HT CMS, respectively. One management option to keep sediment yields to an acceptable level is to shift from HT or MT systems to NT or LT systems, which maintain high levels of residue cover on the soil.

In the current study, WEPP and EPM models were used to estimate the amount of soil erosion and sediment in the basin of Kangir. The required data for implementation of the WEPP model were prepared in six categories including soil, climate, management, slope, drainage and reservoir based on which we took the information needed to build soil and management files. Some information such as texture, cation exchange capacity, organic matter, sand content, effective hydraulic flow and critical shear stress was used. After production of all the layers, the WEPP model was implemented using the GEOWEPP software. In this software, erosion and sediment amounts were estimated by three methods: domain, watershed and flow path methods. In the Kangir River watershed, the sediment content was 7.64 t/ha/year, 6.13 t/ha/year and 11.87 t/ha/year. Thus, the two methods of domain 7.64 t/ha/year and flow path 11.83 t/ha/year were closer to the observed sediment 10.5. Based on the EPM model, the sedimentation coefficient of the Kangir basin was 0.81. The results of the research indicate the high erodibility rate of the watershed basin. The erosion-sensitive units were located in the western and southwestern regions of the basin. In the EPM model, the erosion rate (Z) was 0.6 indicating moderate to high erodibility rate in the watershed. Furthermore, the highest erosion rate was in the western and southwestern parts of the watershed. Finally, the results of estimating soil erosion and sediment production in the watershed of Kangir illustrated that the WEPP model has a more accurate estimation of soil erosion and sediment production, and in this model, the flow path method used to estimate the amount of soil erosion and sediment production was close to the observed sediment at the hydrometric station.

Accurate soil loss prediction at the regional scale is necessary for a better understanding of the soil erosion processes and conservation practices. This study aimed to calibrate the WEPP model for predicting soil loss under semi-arid region conditions in the northwest of Iran. Inter-rill and rill erosion were simulated at 59 points with three replications. Therefore, the ability of the regression equation in WEPP model and the derived regression and artificial neural network (ANN) models by Mirzaee et al. (2017) for predicting baseline soil erodibility parameters were evaluated to estimate soil loss. The results of the present study showed that the WEPP model that applied soil baseline erodibility predicted data by the regression equation in the WEPP model performed poorly in comparison to the derived aspatial models by Mirzaee et al. (2017). Additionally, the WEPP model that used soil baseline erodibility predicted data by the developed ANNs by Mirzaee et al. (2017) yielded the best results with the highest R2 (0.681) and the lowest RMSE (5.1 Mg ha−1) values for predicting soil loss rate. In general, the prediction map of soil erosion showed that soil erosion varied from 1.0 to 26.5 Mg ha−1.

Sedimentation has been causing both onsite and offsite damages around the world. In this context, watershed prioritization allows decision-makers to implement management strategies for reducing sediment yield. So, this study aimed to determine the subwatersheds that produce the maximum amount of sediment for reducing sedimentation in a watershed. We used GeoWEPP, Geo-spatial interface for Water Erosion Prediction Project (WEPP) model, to predict sediment yield in the watershed. In order to run GeoWEPP easily and reliably, the watershed was divided into 85 subwatersheds. Sediment yield was found to be 5.13 tons ha− year−for the whole watershed. In order to produce a sediment risk map in ArcGIS, values from 0 to 1 were assigned to the sediment yield values of each subwatershed by using min-max normalization method. The obtained values were divided into 5 risk classes. According to this map, 42% of the study area was subject to very low sediment risk, while 28%, 12%, 7%, and 11% of it were subject to low, moderate, high, and very high sediment risk. When the sediment yield amount of the risk classes was investigated, very high sediment risk class accounted for 54% of total sediment yield in the watershed. These results revealed that a small part of the watershed contributed a disproportionate amount of the total sediment yield. Consequently, the GeoWEPP-based prioritization approach can help decision-makers design and implement effective soil and water conservation practices to reduce sediment yield in the regions where human and financial resources are limited.

This study involves a loss of soil modeling in the catchment basin of Tessaoute upstream (Central High Atlas, Morocco), the integration of the universal soil loss equation in Wischmeier (USLE) in a Geographical Information System (GIS). The model allows a qualitative and quantitative assessment of water erosion. The various factors of water erosion (climate, topography, soil, land use and erosion control practices) were mapped, processed, sorted and merged in order to quantify the water erosion rate per unit area. The result is a quantitative map, spatial reference, with an average loss of about 15.44 t/ha/year by runoff sheet and rill. This allowed us to better understand the impact of each erosive factor, assess its contribution to soil loss and establish the decisive factors that control water erosion in the watershed in order of importance, slope, soil erodibility and vegetation cover.

Hirakud, the longest earthen dam in Asia on the river Mahanadi, has been affected by sedimentation problems which affect reservoir storage capacities and different reservoir operations. This article presents the hydrological modeling of the Mahanadi catchment up to Hirakud, located in the states of Chhattisgarh and Odisha in India, using the modified version of Soil and Water Assessment Tool (SWAT) with an interface of ArcView Geographic Information System software to predict soil erosion and sediment transport to the reservoir for improving its useful life. The data sources used in the study were: terrain data 90 m resolution of Shuttle Radar Topography Mission, Land Use and Land Cover derived from Landsat Enhanced Thematic Mapper Plus, soil map published by National Bureau of Soil Survey and Land Use Planning, India and meteorological data collected from India Meteorological Department, India. The study involves the analysis of sensitive parameters of the simulated data (discharge 15, sediment load 6); 5-year calibration and 3-year validation on daily basis to predict the discharge and sediment load. The sensitivity analysis was carried out using the Latin Hypercube and One-factor-At-a-Time. The results also show that the prediction of sediment yield is highly sensitive to the sizes of different sub-basins due to the sensitivity of topographic factors used in the Modified Universal Soil Loss Equation. The graphical as well as statistical results achieved in this study indicate that the model is capable to identify critical erosion-prone areas within the watershed on the scale of sub-watershed which helps the hydrologists to introduce effective management practices at the lowest cost. The study shows that about 34% area of total catchment falls under high or above soil erosion zones with combination of coarse loamy type of soil and agricultural type of land use and land cover condition. The results of this study also identify regions of high sediment yield and sediment delivery ratio. To enhance the SWAT model performance, it is recommended to use sub-daily data and to prioritize soil erosion at the Hydrological Response Units level for improvement of watershed management.

Evaluation of runoff and sediment load is the main problem that affects the performance of dams due to the reduction in the storage capacity of their reservoirs and their effect on dam efficiency and operation schedule. Hydrologic models are increasingly used for simulation of spatially varied hydrologic processes with the availability of spatially distributed data to understand and manage natural and activities that affect watershed systems if the continuous field measurements are not available. Soil and water conservation and also quantification of soil loss in watershed basins are a significant issue. In this study, the Soil and Water Assessment Tool (SWAT) and the Water Erosion Prediction Project (WEPP) are applied to estimate runoff volume and sediment load for Torogh dam reservoir area that is located in Kashafrood Watershed Basin in northeastern Iran. Simulated and observed runoff and sediment load are compared with these models. In the calibration period, the Nash–Sutcliffe coefficient (NSE) values for the SWAT and WEPP were 0.698 and 0.854 for runoff, and 0.667 and 0.832 for sediment load, respectively. In the validation period, the NSE values for SWAT and WEPP were 0.678 and 0.824 for runoff, and 0.809 and 0.816 for sediment load, respectively. The results indicate that both models gave reasonable results in comparison with measured values. Simulation with WEPP model was better than SWAT in some cases and with reasonable confidence could be used for soil loss quantification in the watershed basin of Torogh dam.

This study was taken up to investigate the effects of landscape patterns on the soil erosion processes in a mountain–basin watershed. The revised universal soil loss equation and sediment delivery distribution models were used to estimate the soil erosion processes. The landscape patterns include the landscape metrics at the landscape level, landscape composition and configuration indicators on the basis of source–sink landscape theory. In the study area, the grassland, bare land, farmland and construction land were the sediment-source landscape; the forest and shrub were the sediment-sink landscape. The correlation analysis results showed that the soil erosion processes were significantly associated with the landscape patterns of the study area. At the landscape level, fragmentation metric was positively correlated with soil erosion; diversity metric was negatively related to soil erosion and sediment yield at the sub-basin scale. Among the source–sink landscape composition and configuration indicators, the composition indicator was positively correlated with soil erosion rate and sediment yield. In the configuration landscape indices, the shape index was negatively correlated with soil erosion rate and sediment yield; the fragmentation index was positively correlated with soil erosion rate and negatively correlated with sediment delivery rate. These results indicated that the optimization measures, such as increase in the area, connectivity and regularity of sediment-sink landscape, or decrease in the proportion, connectivity and regularity of sediment-source landscape, were favorable for soil conservation. Furthermore, the landscape indicators based on the source–sink theory could provide more information for landscape pattern optimization to reduce soil erosion.

Landuse change significantly alters the hydrologic characteristics of the land surface within a watershed. In the present study, the impact of landuse change (2006-2016) on runoff and sediment yield has been assessed in Patiala-Ki-Rao watershed (5140 ha) located in Shivalik foot-hills, using remote sensing, geographical information system (GIS), and Water Erosion Prediction Project (WEPP) watershed model. The watershed has seven major landuse classes, namely agriculture, built-up, fallow land, forest, grass land, streams, and water bodies. The landuse change analysis indicated that the area under all the landuses decreased except built-up that increased by 372.27 ha (112.04%). Forest is the most affected landuse among all watershed landuses that shrinked by 194.90 ha followed by agriculture (64.57 ha), grass land (50.81 ha), streams (30.42 ha), fallow land (21.86 ha), and water bodies (9.72 ha). Runoff and sediment yield for the landuse of the years 2006 and 2016 were simulated by the WEPP model using two climate scenarios (2006 and 2016). The simulated runoff, sediment yield, and sediment delivery ratio increased by 18.62%, 48.04%, and 32.23% under Climate-2006 and 26.78%, 30.23%, and 16.09% under Climate-2016 due to change in landuse during a period of 10 years. This clearly indicates that landuse change in 10 years has greatly influenced the hydrology of the watershed and requires urgent land allocation policy in place for sustainable development in the area.

Soil erosion is a natural process causing grave land degradation problems. In Tunisia, soil erosion represents a serious environmental problem. Both man-made and natural phenomenon is reducing acres of agricultural land. The problem of soil erosion by water is very critical in Lebna watershed. In fact, Lebna is a town in the northeast of Tunisia and it seems high time to protect water and ground resources and to prevent the Lebna dam situated in the downstream from silting. In this context, the application of geographic RUSLE model using the techniques of geographic information system (GIS) and remote sensing has made it possible to assess the estimation of the soil erosion risk at the targeted watershed. This model is composed of several factors associated with climate, topography, soil and vegetation. The spatial distribution of annual average rate of soil loss resulting of this methodology shows an average of 24 ton/ha/year. Consequently, this method based on a combination of RUSLE as erosion model gave very similar results with bathymetric measures performed by Institute of Research for Development. It was about 29 ton/ha/year. Accordingly, Lebna watershed belongs to a zone of rather a steep erosive potential knowing that the maximum acceptable limit value of the erosive potential estimated is 12 ton/ha/year (Roose in Introduction a la gestion conservatoire de l’eau, de la biomasse et de la fertilite des sols (GCES). FAORome, 1994). The results have shown that Lebna watershed has a serious risk on soil erosion on sloping land. The highest values are mainly associated with the steep slopes, poor conservation practices, low vegetation cover and high rainfall. The final soil loss map can be thus a base to plan appropriate strategies for decision-makers to avoid soil erosion risks and consequently to lengthen dam life.

All characteristics of vegetation, runoff and sediment from 1960 to 2010 in the Xiliu Gully Watershed, which is a representative watershed in wind-water erosion crisscross region in the upper reaches of the Yellow River of China, have been analyzed in this study. Based on the remote sensing image data, and used multi-spectral interpretation method, the characteristics of vegetation variation in the Xiliu Gully Watershed have been analyzed. And the rules of precipitation, runoff and sediment’s changes have been illuminated by using mathematical statistics method. What′s more, the influence mechanism of vegetation on runoff and sediment has been discussed by using the data obtained from artificial rainfall simulation test. The results showed that the main vegetation type was given priority to low coverage, and the area of the low vegetation coverage type was reducing year by year. On the country, the area of the high vegetation coverage type was gradually increasing. In a word, vegetation conditions had got better improved since 2000 when the watershed management project started. The average annual precipitation of the river basin also got slightly increase in 2000–2010. The average annual runoff reduced by 37.5%, and the average annual sediment reduced by 73.9% in the same period. The results of artificial rainfall simulation tests showed that the improvement of vegetation coverage could increase not only soil infiltration but also vegetation evapotranspiration, and then made the rainfall-induced runoff production decrease. Vegetation root system could increases the resistance ability of soil to erosion, and vegetation aboveground part could reduce raindrop kinetic energy and splash soil erosion. Therefore, with the increase of vegetation coverage, the rainfall-induced sediment could decrease.

WOS: 000394371100002 Soil erosion is one of the major threats to the conservation of soil and water resources. For that reason, predictive erosion models are useful tools for evaluating soil erosion and developing soil erosion management plans. For this aim, the revised universal soil loss equation (RUSLE) function is a widely used erosion model. This research integrated the RUSLE with a geographic information system (GIS) to investigate the spatial distribution of annual soil loss potential in the Alaca catchment in north central Black Sea region, Turkey. The rainfall erosivity factor was developed from local annual precipitation data using a modified Fournier index; the topographic factor was developed from a digital elevation model; the land cover factor was generated from satellite imagery and forest inventory maps; and the soil organic carbon level and the erodibility factor were developed from systematically collected soil samples and the application of the geostatistical method, respectively. From the model, more than the half of the total study area as in the very low and low erosion risk classes (0-12 t ha(-1) year(-1)), whereas 4.4 % (723.6 h) of the total area was at high and very high erosion risk (35-150 and >150 t ha(-1) year(-1)), respectively. In addition, soil organic carbon density values were between 0.18 and 4.92 kg m(-2) across the catchment. Moreover, the distribution of soil organic carbon losses was closely correlated with the distribution of soil erosion risk classes in the study area. Soils and topographical properties of the watershed had a greater influence than land use/land-cover type on the magnitude of potential soil and soil organic carbon losses, because the erosivity factor did not change substantially in the study area.

In this work, a dynamic GIS modeling approach is presented that incorporates: a) geoinformatic techniques, b) 55-year historical meteorological data, and c) field measurements, in order to estimate soil erosion risk in intensively cultivated regions. The proposed GIS-based modeling approach includes the estimation of soil erosion rates due to surface water flow under current and future climate change scenarios A2 and B1 for the years 2030 and 2050. The soil erosion was estimated using the Universal Soil Loss Equation (USLE). The proposed soil erosion model was validated using field measurements at different sites of the study area. The results show that an extended part of the study area is under intense erosion with the mean annual loss to be 4.85 t/ha year−1. Moreover, an increase in rainfall intensity, especially for scenario B1, can generate a significant increase (32.44 %) in soil loss for the year 2030 and a much more (50.77 %) for the year 2050 in comparison with the current conditions. Regarding the scenario A2, a slight decrease (1.85 %) in soil loss was observed for the year 2030, while for 2050 the results show an adequate increase (7.31 %) in comparison with the present. All these approaches were implemented at one of the most productive agricultural areas of Crete in Greece dominated by olive and citrus crops.

Correct estimation of soil loss at catchment level helps the land and water resources planners to identify priority areas for soil conservation measures. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like landuse change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of Mandakini river basin, a hilly catchment in the state of Uttarakhand, India, to obtain future impact on soil erosion within the basin. The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies. Future soil erosion has shown increasing trend due to increasing rainfall which has been generated from the statistical-based downscaling method.

This study aims to verify the performances of Water Erosion Prediction Project (WEPP) rill erosion equation using loess material by investigating the variations of soil detachment rate with sediment load by rill flow, quantifying the response of soil detachment rate to sediment load, and comprehensively examining WEPP rill erosion equation, so as to provide scientific basis for the application of WEPP model on the loess plateau and to sufficiently understand the response of soil detachment rate to sediment load. The experiment was conducted in a rill flume with a soil-feeding hopper and was specifically designed to isolate the effect of sediment load on detachment rate. Loess material was collected from a typical hilly region of the Loess Plateau, Ansai, Shaanxi, China. The test soil was quantitatively fed into rill flow by a soil-feeding hopper to produce different sediment loads. Seven unit flow discharges (1.11, 1.56, 2.00, 2.44, 2.89, 3.33, and 3.78 × 10−3 m2 s−1) were combined with six slopes (10.51, 15.84, 21.26, 26.79, 32.49, and 38.39 %). The sediment transport capacity was measured for each combination. The detachment rate was measured for each combination under seven sediment loads, which were 0, 10, 25, 50, 75, 90, and 100 % of the sediment transport capacity. Soil detachment rate decreased with the increase of sediment load. Levels of sediment load in 0, 10, 25, 50, 75, 90, and 100 % reduced detachment rate in rates of 0, 18.93, 36.36, 56.28, 70.15, 83.42, and 92.19 %, respectively. The response relationship of detachment rate to sediment load by rill flow was described well by a negative linear equation (R 2 range from 0.8489 to 0.9982, P

Analysis of soil redistribution patterns in watershed areas provides information for understanding soil erosion and deposition for implementing management practices to improve agricultural land conditions and reduce sediment loads in river systems. This paper has demonstrated the use of Cesium-137 (137Cs) in estimating retrospective medium-term soil erosion rates in selected cassava cultivated areas in Pilar, a sub-watershed within the Inabanga watershed. To estimate erosion and deposition rates and elucidate the factors affecting the soil redistribution, samples were collected from a total of ninety-eight grid intersections representative of the local land use and slope gradients in the presence or absence of soil conservation practices. A proportional model was used to deduce soil redistribution rate estimates from 137Cs inventories measured from individual soil samples. Soil measurements of 137Cs activity-generated soil erosion rate gave values of 13.15 t ha−1 year−1 in cultivated areas practicing conservation measures and 22.23 t ha−1 year−1 in those with typical upland plantation, with the former corresponding to slight erosion case and the latter to moderate erosion case. The obtained values have provided an overview of the pattern of soil redistribution in the watershed area and reflect the impact of strategic soil erosion management being applied. Interestingly, in light of recent severe meteorological events befalling the region, e.g., super typhoon Haiyan and the 7.3 magnitude earthquake, the data obtained may serve as benchmark values for 137Cs activities against which changes in the soil movement and soil redistribution pattern along the watershed areas can be evaluated.

In this study, we address the characteristics of the spatial and temporal evolution of soil erosion in karstic mountainous area of Houzhai River Basin of southwest China. The study uses GIS, erodibility test results, actual surveys of soil types, a revised universal soil loss equation for estimating soil erosion in 1973, 1990, 2002, and 2013, and an analysis of the spatial and temporal distribution of the evolution law of soil erosion for almost 40 years. Results show the following: (1) The soil erosion modulus of the Houzhai River Basin exhibits a decrease from 222.72 t km−2 year−1 in 1973 to 103.82 t km−2 year−1 in 2013. (2) The intensity level of soil erosion changes across space. The most active area is mainly concentrated in the upstream peak cluster depression. Areas with a slope of 8°–25° account for 40.81 % of the total erosion contribution rate, indicating that these are the main areas where erosion occurs. (3) The global and universal classification standard of soil erosion shows that the Houzhai River Basin areas above 65 % do not undergo micro-erosion. The rocky desertification is a serious problem, which explains why grading standard soil erosion intensity is inapplicable to karst areas. (4) The average soil erosion modulus in the basin is generally low (i.e., below 1000 t km−2 year−1), which indicates strong karstification in the karst areas. This process can occur through subsurface pores, fissures, holes, and underground leakage phenomena, which underestimate the amount of soil erosion in the karst areas. A comprehensive analysis of a long time series reveals that soil erosion in the karst areas is a complex process which requires further detailed studies.

The Universal Soil Loss Equation (USLE) has been widely used to predict the long-term average annual soil loss associated with sheet and rill erosion caused by rainfall and runoff. Initially developed for agricultural purposes, it was later modified and extended for estimating soil loss on cut and fill slopes. In addition to this valuable equation, management of cut and fill slopes also requires a classification system in order to prioritize erosion control measures and maintenance operations based on estimated soil loss. Currently available erosion classifications (focused on soil productivity and sustainable agriculture) may not be relevant to transportation infrastructure slopes, in which soil loss rates are dramatically higher and primarily concern operational service conditions. Therefore, the objective of this study was to develop a classification system based on soil loss rates computed by the USLE model that can be valuable for management of cut and fill slopes. It was assumed that erosion classifications developed for agriculture could be used in cut and fill slopes as long as the ratio between respective soil loss rates was applied. It was found that the topographic factor, which accounts for the length and steepness of the slope, may explain most of the difference in respective soil loss rates. For typical values of the topographic factor, soil loss rates on cut and fill slopes were found to be roughly ten times greater than those on agriculture. Based on this finding, a new classification with six erosion levels was developed. Finally, validation analysis showed that the proposed classification successfully ranked soil loss rates reported in the literature into different categories.

The Water Erosion Prediction Project (WEPP) model is utilized to simulate the sediment and runoff processes. According to previous studies, WEPP model provides impressive results in watersheds of diverse climates and scales. It is also capable of modeling the sediment transportation processes and consequently predicting subsequent deposition sites. In this study, the geo-spatial interface for WEPP (GeoWEPP) was employed as a GIS framework to extract the data required from the ASTER Global Digital Elevation Model (ASTER-GDEM) dataset which was subsequently used as the model input. The case study was based on monthly data consisting of average sediment and runoff estimation from the Emameh sub-basin, in northern Iran. The model estimations were validated through field measurements. Two statistical measures of co-efficiency including the Nash–Sutcliffe Efficiency (NSE), and the coefficient of determination (R 2) were considered to evaluate how well the model predictions could explain the variability of observations in the field. The model performed favorably as corroborated by a reasonably high NSE of 0.99 and an R 2 value of 0.92 for sediment. In the case of runoff, the results were slightly inferior, but still acceptable with an NSE of 0.76 and R 2 value of 0.62.

Soil erosion is considered to be a serious problem for environmental sustainability. Healthy and stable soils are crucial for human well-being, providing important ecosystem functions and services. There is a need for a simple and practical approach which estimates and maps soil erosion risk that uses available information as input data to facilitate water and soil conservation. In this work, we developed a predictive approach to estimating the soil erosion risk of the Yanshan Reservoir catchment, which combines remote sensing information, geographic information system spatial analysis technology and a soil erosion risk assessment model. Three dominating factors affecting soil erosion were considered: vegetation coverage, topographic slope and land use. The soil erosion risk was divided into six levels: slight, light, moderate, intense, severe and extremely severe. The slight and light erosion risk accounted for about 83 % of the watershed and was prominent in cultivated land areas, while areas with relatively higher erosion risk were on steep slopes. This approach pointed to inappropriate land use and development as a source of increased risk of soil erosion of the Yanshan Reservoir catchment. Compared with field survey data, the soil erosion modeling approach was shown to have a high accuracy. Therefore, this model could be used to estimate and map soil erosion intensity and distribution at the catchment scale, and could provide useful information for managers and planners to make land management and conservation decisions.

Soil erosion by water is considered a major cause for land degradation in Jordan, where 0.14 cm of productive top soil is eroded annually. This investigation is intended to estimate the annual soil loss in Wadi Kerak watershed, and to examine the spatial patterns of soil loss and intensity, as an essential procedure for proper planning of conservation measures. To achieve these objectives, the revised universal soil loss equation (RUSLE) model has been applied in a geographical information system framework. After computing the RUSLE parameters (R, K, LS, C and P) soil erosion risk and intensity maps were generated, then integrated with physical factors (terrain units, elevation, slope, and land uses/cover) to explore the influence of these factors on the spatial patterns of soil erosion loss. The estimated potential annual average soil loss is 64 ton ha−1year−1, and the potential erosion rates from calculated class ranges from 0.0 to 790 ton ha−1year−1. Soil erosion risk assessment indicates that 54.5 % of the catchment is prone to high to extreme soil losses higher than 25 ton ha−1year−1. The lower and middle parts of the catchment suffer from high, severe, to extreme soil erosion. While 45.5 % of the basin still undergoes slight and moderate levels of soil loss of less than 25 ton ha−1year−1, yet 76.91 % of soil erosion occurred on four different terrain units, and 72.29 % of soil erosion occurred in zones less than 600 m in elevation, with 88 % present on areas of 0°–6°, 5°–15°, and 15°–25° slope categories. 32.6, 30.3, and 33.1 % of soil erosion occurred on rainfed mixed farming and irrigated areas, barren, and rangeland, respectively. The present results provide a vital database necessary to control soil erosion in order to ensure sustainable agriculture in the highland region of Jordan.

The aim of this study is to present continuous simulation efforts of soil and streambed erosion processes, as well as the comparison of computed sediment load values with field measurements. For this reason, a composite mathematical model, consisting of three submodels, is applied to the basin of Kosynthos River (district of Xanthi, Thrace, northeastern Greece): a rainfall-runoff submodel, a soil erosion submodel and a sediment transport submodel for streams. The rainfall-runoff submodel that is used for the computation of the surface runoff and the streamflow in the sub-basins, is the deterministic distributed hydrologic model HEC-HMS 3.5. For the estimate of soil erosion in a sub-basin, the model of Poesen (1985) is used, while for the estimate of sediment yield at the outlet of a sub-basin, and finally at the outlet of the whole basin, the stream sediment transport model of Yang and Stall (1976) is used. The statistic efficiency criteria utilized for the comparison between computed and measured sediment discharge values at the outlet of the whole basin, provide satisfactory values. Therefore, it is concluded that the continuous hydromorphologic modeling can be successfully applied to Kosynthos River basin.

Present study aimed at estimating soil erosion potential and identification of critical areas for soil conservation measures in an ungauged catchment situated in Aravalli hills of Udaipur district, Rajasthan (India). Also, impact of rainfall on soil erosion is evaluated. The soil erosion is estimated for 10 year period (2001–2010) by Universal Soil Loss Equation (USLE) model using Geographical information system (GIS) and remote sensing techniques for every 12 m × 12 m area. Thematic maps of six USLE model parameters, i.e., rainfall erosivity (R-factor), soil erodibility (K-factor), slope length (L-factor), slope steepness (S-factor), crop and management (C-factor), and support practice (P-factor), were prepared in GIS platform. The R-factor ranged from 1,522.93 to 10,225.88 MJ mm ha−1 h−1 year−1 in the years 2006 and 2008, respectively, when the annual rainfall was 984.3 and 572.2 mm, and number of rainy days were 58 and 47, respectively. The K-factor was highest for fine loam soil covering 56 % area, while the lowest value was for coarse loamy sand in 22 % area. The lowest value of the L-factor (0.736) was in accordance with the high slopes nearby catchment boundary; whereas the highest value (0.832) was for almost zero slopes in 34 % area nearby waterbodies. Opposite to the L-factor, the S-factor values were high (>4) for the higher slopes nearby catchment boundary and the lowest values for the zero slopes. The C-factor value in 170.36 km2 or 48.91 % of the area is 0.1 while the value is zero for waterbodies and builtup lands. The P-factor value in 250.36 km2 or 71.87 % of the area is 0.8. The mean annual soil erosion in the major portion of the catchment (231.13 km2 or 66.38 %) exceeds 10 t ha−1 year−1 indicating high to very severe soil erosion conditions prevailing in the catchment. It is apparent that vast quantities of the soil are getting eroded from the catchment, and the annual rainfall amount and rainfall intensity have the profound effect on the soil erosion potential. This study emphasizes that USLE model coupled with GIS and remote sensing techniques are promising and cost-effective tools for mapping critical areas of soil erosion in ungauged catchments especially in developing countries.

Sediment discharge is one of the main water quality concerns in integrated watershed management. A proper identification of sediment sources is therefore important to the success of watershed conservation programs. Since water quality monitoring data collected at the mouth of the watershed alone are typically not sufficient for identifying key sediment sources distributed in the watershed, hydrologic models can be applied to prioritize Best Management Practices (BMPs) implementation for sediment control in a watershed. In this paper, the Soil and Water Assessment Tool (SWAT) is applied to the South Tobacco Creek (STC) watershed in Canada to identify sediment sources and to estimate the spatial distribution of sediment yield from both upland and channel erosion processes. The model is calibrated and validated against observed flow and sediment data measured at fourteen edge-of-field and mainstream stations based on 20 years of land management data. Modeling results show that approximately 60 and 40 % of the sediment discharge at the mouth of the watershed are originated from channel erosion and upland erosion respectively. A high spatial and temporal variation of sediment yield is found in the watershed depending on climate, topography, land use, and soil conditions. These findings will be helpful for understanding the runoff and erosion processes and evaluating the cost-effectiveness of soil and water conservation programs at a watershed scale.

Soil erosion increasingly poses a great threat to human food security and environmental quality. It is necessary to implement the assessment of soil erosion so as to provide precautionary measures and relevant suggestions for soil conservation. In this paper, the soil erosion model, revised universal soil loss equation (RUSLE), was used to quantify the soil loss in a large mountainous area of Lower Jinsha River Basin. The analysis of the datasets by means of geographic information systems (GIS) together with RUSLE led to the estimation of soil erosion. Results show that the average annual soil erosion was estimated at 52.1 t ha−1 year−1 and the total annual soil loss was 4.5 × 108 t. The highest erosion was found along the main course of Jinsha River. Soil erosion was serious in the elevation zone between 1,675 and 2,153 m and slope zone with slopes between 15° and 35°. As for land use types, cropland and grassland contributed 84.1 % to total soil loss due to the large areas and higher erosion rates. The results can be used to advice the local government in prioritizing the areas of immediate conservation practices.

Studies on soil wind erosion began with single factors affecting soil wind erosion; with increasing quantities of data being accumulated, the wind erosion equation (WEQ), the revised wind erosion equation (RWEQ), the wind erosion prediction system (WEPS), and other soil wind erosion models have been successively established, and great advances have been achieved. Here we briefly review the soil wind erosion research course and analyze the advantages and disadvantages of the current soil wind erosion models. From the perspective of the dynamics of wind erosion, we classified the factors affecting soil wind erosion into three categories, namely, wind erosivity factors (WEF), soil antierodibility factors (SAF), and roughness interference factors (RIF). We proposed the concept of a standard plot of soil wind erosion to solve the problem of uncertainty of the soil wind erosion modulus on a spatial scale, and provided methods to set similarity conditions in wind tunnel simulation experiments and to convert the spatial scale of the wind erosion modulus from the standard plot to a large scale field. We also proposed a conceptual model on the basis of the dynamics of soil wind erosion with the theoretical basis that wind produces a shear force on the soil surface. This shear force is partitioned by barely erodible soil surfaces and roughness elements on the ground, and the amount of soil loss by wind should be calculated by comparing the shear force of the wind on barely erodible soil surfaces with the anti-erosion force of the surface soil. One advantage of this conceptual model is that the calculated soil wind erosion modulus is not subject to changes of spatial scale. Finally, we recommended continual improvement of the existing models while also establishing new models.

The purpose of this study was to investigate the spatial distribution of annual soil loss in the Danjiangkou Reservoir Region, China. Soil erosion was estimated by integrating the universal soil loss equation (USLE) model with GIS. The main factors affecting soil erosion including rainfall erosivity, soil erodibility, slope length and steepness, cover and management factor, and conservation supporting practice factor were determined from precipitation data, soil sample analysis, digital elevation model, land use and land cover, and empirical assessment, respectively. The results showed that the average annual soil erosion was 31.18 t hm−2 year−1, far above the soil loss tolerance maximum of 5.0 t hm−2 year−1 in the region. Regional soil erosion risk (SER) was estimated and categorized into five classes in terms of intensity (minimal, low, moderate, high, and intense), and 70.3 % of the total area was classified as minimal or low erosion risk. The soil erosion map was linked to land use and soil depth maps to explore the relationship between soil erosion and environmental factors and identify the areas of SER. The results can be used to advise the local people to prioritize critical areas for soil erosion prevention measures. The study also indicated that the USLE-GIS methodology allowed for relatively easy and cost-effective evaluation of SER with explicit spatial input.

In recent times, soil erosion interlocked with land use and land cover (LULC) changes has become one of the most important environmental issues in developing countries. Evaluation of this complex interaction between LULC change and soil erosion is indispensable in land use planning and conservation works. This paper analysed the impact of LULC change on soil erosion in the north-western highland Ethiopia over the period 1986–2016. Rib watershed, the area with dynamic LULC change and severe soil erosion problem, was selected as a case study site. Integrated approach that combined geospatial technologies with revised universal soil loss equation model was utilized to evaluate the spatio-temporal dynamics of soil loss over the study period. Pixel-based overlay of soil erosion intensity maps with LULC maps was carried out to understand the change in soil loss due to LULC change. Results showed that the annual soil loss in the study area varied from 0 to 236.5 t ha−1 year−1 (tons per hectare per year) in 1986 and 0–807 t ha−1 year−1 in 2016. The average annual soil loss for the entire watershed was estimated about 40 t ha−1 year−1 in 1986 comparing with 68 t ha−1 year−1 in 2016, a formidable increase. Soil erosion potential that was estimated to exceed the average soil loss tolerance level increased from 34.5% in 1986 to 66.8% in 2016. Expansion of agricultural land at the expense of grassland and shrubland was the most detrimental factor for severe soil erosion in the watershed. The most noticeable change in soil erosion intensity was observed from cropland with mean annual soil loss amount increased to 41.38 t ha−1 year−1 in 2016 from 26.60 in 1986. Moreover, the most successive erosion problems were detected in eastern, south-eastern and northern parts of the watershed. Therefore, the results of this study can help identify the soil erosion hot spots and conservation priority areas at local and regional levels.

This study was undertaken to evaluate land use change impact and management scenarios on annual average surface runoff (SR) and sediment yield (SY) using the GeoWEPP tool in the Lighvanchai watershed (located in northwestern Iran). Following a sensitivity analysis, the WEPP model was calibrated (2005–2007) and validated (2008–2010) against monthly observed SY and SR. The coefficient of determination (R 2), Nash–Sutcliffe efficiency (NSE), mean bias error (MBE), and root-mean-square error (RMSE) were applied to quantitatively evaluate the WEPP model. The results indicate a satisfactory model performance with R 2 > 0.80 and NSE > 0.60. Therefore, the model for current land use (scenario 1) was run for a 30-year time period (1982–2011). The annual average of SR and sediment load were predicted as 93,584 m3/year and 4340 ton/year, respectively. To reduce the annual average surface runoff and sediment yield at the watershed scale, the second scenario (alfalfa cultivation with suitable tillage) and the third scenario (grassland development) as two management scenarios of land use changes were defined by identifying the critical hillslopes. The rate of SR and sediment load in the second scenario were 42,096 m3/year and 429 ton/year, respectively. For the third scenario, the model predictions were 30,239 m3/year and 226 ton/year, respectively. Compared to the first scenario, the reduction rates in annual average of sediment load were about 90 and 94%, respectively. Moreover, for the second and third management scenarios, the reduction rates in annual average of SR were about 55 and 67%, respectively.

The objective of this paper is the assessment of soil erosion rate and its spatial distribution in Alqerdaha basin (West of Syria) with a surface area 217 km2. The study was conducted using Universal soil loss equation (USLE) model due to its modest data demand and easy comprehensible structure. Soil erosion affected by rainfall erosivity, soil erodibility, topography, vegetation, and conservation support practice factors. According to USLE model, soil erosion was modeled through the production of raster maps of previous factors and multiplied it using GIS and RS techniques. The results show that 12.9% of the study basin has a very low erosion of soil, 20.7% low erosion, 31.3% moderate erosion, 26.3% high erosion, and 8.8% a very high erosion. These results will be useful for soil conservation management and the planning of mitigation measures.

In this study, a Physiographic Soil Erosion–Deposition Model (PSED) is applied for better management of a watershed. The PSED model can effectively evaluate the key parameters of watershed management: surface runoff discharge, suspended sediment transport rate, quantity of soil erosion, and spatial distribution of soil erosion and deposition. A basin usually contains multiple watersheds. These watersheds may have complex topography and heterogeneous physiographic properties. The PSED model, containing a physiographic rainfall-runoff model and a basin scale erosion–deposition model, can simulate the physical mechanism of the entire erosion process based on a detailed calculation of bed-load transportation, surface soil entrainment, and the deposition mechanism. With the assistance of Geographic Information Systems (GIS), the PSED model can handle and analyze extremely large hydrologic and physiographic datasets and simulate the physical erosion process without the need for simplification. We verified the PSED model using three typhoon events and 40 rainfall events. The application of PSED to Chou-Shui River basin shows that the PSED model can accurately estimate discharge hydrographs, suspended sediment transport rates, and sediment yield. Additionally, we obtained reasonable quantities of soil erosion as well as the spatial distribution of soil erosion and deposition. The results show that the PSED model is capable of calculating spatially distributed soil erosion and suspended sediment transport rates for a basin with multiple watersheds even if these watersheds have complex topography and heterogeneous physiographic properties.

The relationships between precipitation, vegetation and erosion are important yet unresolved issues in the field of earth surface processes. Vegetation plays an important role in controlling soil erosion. Through field simulated rainfall experiments, we analyzed the characteristics, regulation of, and correlation among the slope rainfall-infiltration-runoff, erosion and sediment under different vegetation types. The results showed that the forest effectively improved soil structure, had stronger runoff and sediment regulation and was influenced less by rainfall intensity than those under other vegetative conditions. In addition, the efficiency and pattern of the regulation of runoff and sediment varied with vegetation types as did the mechanism of action. The soil and water conservation function of forest was water storage and sediment reduction by plant root systems to reduce erosion power, increase infiltration, decrease runoff and reduce flow speed. The function of grassland was direct sediment interception based on surface vegetation canopy for runoff and sediment regulation. The root contribution to runoff and sediment reduction was relatively greater than the shoot contribution under forest conditions, whereas, the effect of shoots and roots on soil loss was almost equivalent under grassland conditions. The different spatial structures of vegetation affected runoff and sediment regulation in different ways, and plant root systems were crucial for soil and water conservation. The cumulative sediment yield of the slopes increased as a statistically significant power function of cumulative runoff. The coefficient and curve shape of function were dependent on vegetation type, soil properties, rainfall intensity and surface roughness. The process of slope runoff and sediment was divided into development, active and stable stages. These stages correlated with each other to constitute a complete rainfall-runoff and erosion-sediment process, which exhibited their own features at each stage. This study furthers understanding of the relationships between vegetation, soil erosion and precipitation.

Hydrosedimentological modeling is a tool that can be used to understand better important processes occurring at the catchment scale, such as runoff and sediment yield. The aim of this study was to use the Limburg Soil Erosion Model (LISEM) to describe the runoff and sediment yield during rainfall–runoff events in a small rural catchment in southern Brazil. The study was conducted in the Lajeado Ferreira Creek catchment (drainage area of 1.19 km2) where intense land use has caused a negative impact on water resources. Thirteen rainfall–runoff events that occurred in 2010 and 2011, including high-magnitude events, were used to model hydrosedimentological processes. from the calibration and validation stages indicate that the model had a good performance when representing the hydrograph, including events with greater complexity. The use of a second soil layer in the model increased its efficiency, which is in accordance with the importance of subsurface flow in this catchment and its sensitivity to the physical properties of the soil, which are essential for controlling hydrosedimentological processes at the catchment scale. The simulation of sediment yield was overestimated by the model, constrained by the lack of sensitivity of the model to soil cohesion and the stability of soil aggregates. During the model calibration stage, these parameters had values different from those measured in the field. The LISEM model performed well in representing runoff for events of different magnitudes. The discretization of the physical–hydrologic properties in the soil profile enabled the evaluation of the effect of subsurface impediment layers on water infiltration and runoff. The simulation was less accurate for suspended sediment concentration than for runoff. This indicates the need for further studies to either identify other factors controlling erosion and sediment yield that have not been identified by the model, or identify if the representation of the physical parameters is inadequate, especially the values of soil cohesion and aggregate stability.

Accelerated soil erosion is a threat for the societies due to the loss of ecosystems services. Soil erosion and sediment delivery have been assessed in a small catchment of Central Spain with a new water body, the Pareja Limno-reservoir, located in its outlet. This limno-reservoir was created in 2006 with environmental and recreational purposes in the riverine zone of a large reservoir. Sedimentation risk is an issue of concern regarding limno-reservoirs environmental feasibility. Thus, the study of the soil erosion in the Pareja Limno-reservoir catchment and its sediment delivery seemed of the utmost importance. In this paper we establish an affordable and simple methodology to address it. A soil erosion and deposition monitoring network was installed in the Ompolveda River basin (≈88 km2), which flows into the Pareja Limno-reservoir. Results obtained were related with those from a sedimentation study previously carried out in the limno-reservoir. Gross hillslope erosion in the catchment was 6.0 Mg ha−1 year−1, which is in agreement with values reported for Mediterranean areas. After subtraction of the deposition measured, a soil loss of 1.2 Mg ha−1 year−1 was found in the catchment. Sediment delivery ratio (SDR) was estimated to be 3.8 %. SDR is low as a result of the low connectivity between the stream network and the limno-reservoir. Some local characteristics may also have a secondary influence in the low SDR value. Results obtained support the environmental feasibility of the Pareja Limno-reservoir from the sedimentation risk perspective. They also demonstrate that the methodology followed allows the assessment of soil loss and sediment delivery at a catchment scale, and the identification of areas where the erosion problems are most severe.

It is well known that soil erosion at the watershed scale is the result of interactions between various factors. Among these environmental factors, vegetation is the most important and plays a major role in the soil erosion process. The impact of fractional vegetation cover change (FVCC) on soil erosion in non-contributing areas is a heavily discussed topic. In this paper, the fractional vegetation cover (FVC) in 2002 and 2005 was calculated by using a backpropagation neural network based on remote sensing (RS) data. Then the impacts of FVCC on sediment loads at the outlets of two Miyun reservoir sub-basins were evaluated by integrating RS and geographic information system with statistical analysis. The Miyun reservoir basin (MRB) is characterized by hilly and mountainous topographies and seasonal rainy weather. The primary goal of this paper is to gain a better understanding of FVCC, its driving forces, and its impact on regional soil erosion. We discuss spatiotemporal variations in precipitation and soil erosion, identify which factors contribute to those variations, analyze the influences of FVCC on climate change and human activities and, finally, conclude that changes in FVC and climate regimes are primary factors for soil erosion in MRB. We also discuss how sediment loads may be used to quantitatively separate biophysical and anthropogenic influences and to identify critical thresholds that might have dramatic consequences for the watershed ecosystem. These findings should be quite helpful for sensible watershed development and management planning.

Soil erosion by water is one of the most widespread forms of soil degradation in Europe. There are many undesirable consequences of soil erosion due to water such as loss of water storage capacity in reservoirs and transfer of pollutants from farmland to water bodies. The objectives of this study were to calibrate and validate the Water Erosion Prediction Project watershed model (WEPP 2012.8) in the Bautzen dam catchment area with monthly and daily single events for runoff and sediment yield. This is to our knowledge the first study using WEPP in Germany. The catchment (310 km2) was subdivided into small sub-catchments with an area of

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km2. This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha−1 year−1 in 2002 and 70.58 ton ha−1 year−1 in 2010, while the estimated sediment yield was found to be 327.96 × 104 and 293.85 × 104 ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.

Soil erosion and sediment yield from catchments are key limitations to achieving sustainable land use and maintaining water quality in nature. One of the important aspects in protecting the watershed is evaluation of sediment produced by statistical methods. Controlling sediment loading in protecting the watershed requires knowledge of soil erosion and sedimentation. Sediment yield is usually not available as a direct measurement but is estimated using geospatial models. One of the geospatial models for estimating sediment yield at the basin scale is sediment delivery ratio (SDR). The present study investigates the spatial SDR model in determining the sediment yield rate considering climate and physical factors of basin in geographic information system environment. This new approach was developed and tested on the Amammeh catchments in Iran. The validation of the model was evaluated using the Nash Sutcliffe efficiency coefficient. The developed model is not only conceptually easy and well suited to the local data needs but also requires less parameter, which offers less uncertainty in its application while meeting the intended purpose. The model is developed based on local data. The results predict strong variations in SDR from 0 in to 70 % in the uplands of the Basin.

Identifying areas that are susceptible to soil erosion is crucial for water resource planning and management efforts. Furthermore, modeling has proven helpful in recognizing and monitoring high-risk areas at the watershed scale. The Water Erosion Prediction Project (WEPP) geospatial interface (GeoWEPP) software integrates GIS with the WEPP to analyze the spatial variation in soil loss, and it has been used as a modeling tool to determine the areas that are most prone to soil erosion and to evaluate best management practices for the Kasilian watershed in Iran. As much as 62.4% of the agronomic land in the Kasilian watershed is affected by a high magnitude of erosion (>5 t/ha). On the basis of this study, by using soybeans, high fertilization levels, and the drill-no-tillage system, reductions of erosion by almost 32.68-34.02% are perceivable in three critical subwatersheds that are located in the cultivated lands. Also, it is projected that reductions in the production of sediment in the range of about 36.7-47.1% are achievable by structural management within two critical, upland subwatersheds. So, by utilizing the best management strategies, sediment yield can be lowered and the conservation of soil and water is feasible at the watershed scale. These results objectively indicate that GeoWEPP can be efficaciously used for evaluating effective management practices for developing watershed conservation.

Land use changes extensively affect soil erosion, which is a great environmental concern. To evaluate the effect of land use change on soil erosion in fast economic developing areas, we studied land use changes of Guangdong, China, from 2002 to 2009 using remote sensing and estimated soil erosion using the Universal Soil Loss Equation. We calculated the areas and percentage of each land use type under different erosion intensity and analyzed soil erosion changes caused by transitions of land use types. In addition, the impact of land use change on soil erosion in different river catchments was studied. Our results show that forest and wasteland land conversions induce substantial soil erosion, while transition from wasteland to forest retards soil loss. This suggests that vegetation cover changes significantly influence soil erosion. Any conversion to wasteland causes soil erosion, whereas expansion of forests and orchards mitigates it. The most significant increase in soil erosion from 2002 to 2009 was found in the Beijiang catchment corresponding to the transition from forest/orchard to built-up and wasteland. Soil erosion in the Xijiang catchment accelerated in this period due to the enormous reduction in orchard land. In Hanjiang catchment, erosion was alleviated and vegetation coverage greatly expanded owing to considerable transitions from wasteland and cropland to orchards. Field investigations validated our estimations and proved the applicability of this method. Measures including protecting vegetation, strict control of mining as well as reasonable urban planning should be taken to prevent successive soil erosion.

This study evaluates erosivity, surface runoff generation, and soil erosion rates for Mamuaba catchment, sub-catchment of Gramame River basin (Brazil) by using the ArcView Soil and Water Assessment Tool (AvSWAT) model. Calibration and validation of the model was performed on monthly basis, and it could simulate surface runoff and soil erosion to a good level of accuracy. Daily rainfall data between 1969 and 1989 from six rain gauges were used, and the monthly rainfall erosivity of each station was computed for all the studied years. In order to evaluate the calibration and validation of the model, monthly runoff data between January 1978 and April 1982 from one runoff gauge were used as well. The estimated soil loss rates were also realistic when compared to what can be observed in the field and to results from previous studies around of catchment. The long-term average soil loss was estimated at 9.4 t ha(-1) year(-1); most of the area of the catchment (60%) was predicted to suffer from a low- to moderate-erosion risk (6 t ha(-1) year(-1)) and, in 20% of the catchment, the soil erosion was estimated to exceed12 t ha(-1) year(-1). Expectedly, estimated soil loss was significantly correlated with measured rainfall and simulated surface runoff. Based on the estimated soil loss rates, the catchment was divided into four priority categories (low, moderate, high and very high) for conservation intervention. The study demonstrates that the AvSWAT model provides a useful tool for soil erosion assessment from catchments and facilitates the planning for a sustainable land management in northeastern Brazil.

The RUSLE-3D (Revised Universal Soil Loss Equation-3D) model was implemented in geographic information system (GIS) for predicting the soil loss and the spatial patterns of soil erosion risk required for soil conservation planning. High resolution remote sensing data (IKONOS and IRS LISS-IV) were used to prepare land use/land cover and soil maps to derive the vegetation cover and the soil erodibility factor whereas Digital Elevation Model (DEM) was used to generate spatial topographic factor. Soil erodibility (K) factor in the sub-watershed ranged from 0.30 to 0.48. The sub-watershed is dominated by natural forest in the hilly landform and agricultural land in the piedmont and alluvial plains. Average soil loss was predicted to be lowest in very dense forest and highest in the open forest in the hilly landform. Agricultural land-1 and agriculture land-2 to have moderately high and low soil erosion risk, respectively. The study predicted that 15% area has ‘moderate’ to ‘moderately high’ and 26% area has high to very high risk of soil erosion in the sub-watershed.

Soil erosion induces land degradation and minimizes the water-holding capacity, resulting in poor environmental quality at a basin scale. This becomes more serious due to long-term anthropogenic pressure including over exploitation of natural resources and lack of sustainable development. In this study, an automated RUSLE-SY model was developed to identify the potential soil erosion and sediment yield zones in Tamiraparani sub-basin, South India. The input parameters required to execute the RUSLE-SY model are digital elevation model, study area boundary, land-use/land-cover data, soil data, annual rainfall data, near-infrared and red bands from satellite imagery. The entire set of data was geoprocessed with standard RUSLE and sediment yield equations for generating soil erosion and sediment yield map. The distribution of soil erosion and sediment yield in the study area was analyzed, and its impacts were discussed. The result reveals that the high soil erosion is noticed in the western part of the sub-basin (31.25 ton ha−1 year−1). Moreover, the sediment yield in this area contributes around 14.54 ton ha−1 year−1. The low level of soil erosion and sediment yield (~95 % of the area) reflects the climatic variability and topography of Tamiraparani sub-basin. The resulting RUSLE-SY model provides a robust and easy to use soil erosion and conservation management tool for efficient planning in similar environments.

Sedimentation is an important parameter to assess the life of a reservoir. Seventy-eight years ago, Cook was the first to identify mathematically, the three major factors affecting soil erosion in the catchment of a reservoir. As sedimentation is dependent on sediment yield and sediment yield depends on soil erosion, it is required to predict all three parameters to estimate the life of a reservoir. Since then many researchers carried their research dealing with soil erosion, sediment yield and sedimentation in various reservoirs for its practical significance. The aim of this article is to present a comprehensive state-of-the-art review of the important investigations on soil erosion, sediment yield and sedimentation in various reservoirs highlighting the governing mathematical background of these problems. 198 references are included in this review paper.

The study demonstrates the identification of site-specific watershed management technique using geospatial technology to enhance the groundwater potential of an area. The soil erosion prioritization evaluated using geoinformatics technique and drainage morphometric analysis highlights the utility of multiresources evaluation in sustainable watershed development. The superimposed thematic layers of land use/land cover, lithology, hydrogeomorphology, drainage, and lineament over the soil erosion variability map helped in suggesting the site-specific location of the water harvesting structures in Daltonganj watershed of Palamu, Jharkhand, India. The spatial variability of the various soil erosion zones indicated that 0.78 and 11.31 km2 are under very high and high soil erosion prone areas, respectively, whereas moderate areas of soil erosion comprised of 11.46 km2 within the Daltonganj watershed. The lower catchment region of the Daltonganj watershed was found to be most prone to very high soil erosion, whereas parts of the lower, middle, and upper catchment regions are significantly prone to high rate of soil erosion. The central regions, however, are low to moderately prone to soil erosion. The quantitative drainage morphometric analysis helped to understand the groundwater situation. The present study thus helped in locating suitable sites for water harvesting structures which include 9 check dams, 31 farm ponds, and 9 nala bunds in the watershed, which will help in efficiently monitoring the soil moisture conservation and groundwater recharge and put a check on soil erosion of the area.

Increasing rainfall intensity and frequency due to extreme climate change and haphazard land development are aggravating soil erosion problems in Korea. A quantitative estimate of the amount of sediment from the catchment is essential for soil and water conservation planning and management. Essential to catchment-scale soil erosion modeling is the ability to represent the fluvial transport system associated with the processes of detachment, transport, and deposition of soil particles due to rainfall and surface flow. This study applied a spatially distributed hydrologic model of rainfall–runoff–sediment yield simulation for flood events due to typhoons and then assessed the impact of topographic and climatic factors on erosion and deposition at a catchment scale. Measured versus predicted values of runoff and sediment discharge were acceptable in terms of applied model performance measures despite underestimation of simulated sediment loads near peak concentrations. Erosion occurred widely throughout the catchment, whereas deposition appeared near the channel network grid cells with a short hillslope flow path distance and gentle slope; the critical values of both topographic factors, providing only deposition, were observed at 3.5 (km) (hillslope flow path distance) and 0.2 (m/m) (local slope), respectively. In addition, spatially heterogeneous rainfall intensity, dependent on Thiessen polygons, led to spatially distinct net-erosion patterns; erosion increased gradually as rainfall amount increased, whereas deposition responded irregularly to variations in rainfall.

Soil erosion is one of the most serious land degradation problems and the primary environmental issue in Mediterranean regions. Estimation of soil erosion loss in these regions is often difficult due to the complex interplay of many factors such as climate, land uses, topography, and human activities. The purpose of this study is to apply the Soil and Water Assessment Tool (SWAT) model to predict surface runoff generation patterns and soil erosion hazard and to prioritize most degraded sub-catchment in order to adopt the appropriate management intervention. The study area is the Sarrath river catchment (1,491 km2), north of Tunisia. Based on the estimated soil loss rates, the catchment was divided into four priority categories for conservation intervention. Results showed that a larger part of the watershed (90 %) fell under low and moderate soil erosion risk and only 10 % of the watershed was vulnerable to soil erosion with an estimated sediment loss exceeding 10 t ha−1 year−1. Results indicated that spatial differences in erosion rates within the Sarrath catchment are mainly caused by differences in land cover type and gradient slope. Application of the SWAT model demonstrated that the model provides a useful tool to predict surface runoff and soil erosion hazard and can successfully be used for prioritization of vulnerable areas over semi-arid catchments.

The water erosion prediction project (WEPP) model is a popular water erosion prediction tool developed on the basis of the physical processes of water erosion. Although WEPP has been widely used around the world, its application in China is still insufficient. In this study, the performance of WEPP used to estimate the runoff and soil loss on purple soil (Calcaric Regosols in FAO taxonomy) sloping cropland was assessed with the data from runoff plots under simulated rainfall conditions. Based on measured soil properties, runoff and erosion parameters, namely effective hydraulic conductivity, inter-rill erodibility, rill erodibility, and critical shear stress were determined to be 2.68 mm h(-1), 5.54 x 10(6) kg s(-1) m(-4), 0.027 s m(-1) and 3.5 Pa, respectively, by using the recommended equations in the WEPP user manual. The simulated results were not good due to the low Nash efficiency of 0.41 for runoff and negative Nash efficiency for soil loss. After the four parameters were calibrated, WEPP performed better for soil loss prediction with a Nash efficiency of 0.76. The different results indicated that the equations recommended by WEPP to calculate parameters such as erodiblity and critical shear stress are not suitable for the purple soil areas, Sichuan Province, China. Although the predicted results can be accepted by optimizing the runoff and erosion parameters, more research related to the determination of erodibility and critical sheer stress must be conducted to improve the application of WEPP in the purple soil areas.

Watershed degradation due to soil erosion and sedimentation is considered to be one of the major environmental problems in Iran. In order to address the critical conditions of watershed degradation in arid and semiarid regions, a study based on the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model was carried out at Golestan watershed, northeast of Iran. The model information layers comprising nine effective factors in erosion and sedimentation at the watershed site were obtained by digitalization and spatial interpolation of the basic information data in a GIS program. These factors are geology, soil, climate, runoff, topography, land cover, land use, channel, and upland erosion. The source data for the model were obtained from available records on rainfall and river discharge and sediment, topography, land use, geology, and soil maps as well as field surveys and laboratory analysis. The results of the MPSIAC model indicated that 60.75 % (194.4 km2) and 54.97 % (175.9 km2) of the total watershed area were classified in the heavy sedimentation and erosion classes, and the total basin sediment yield and erosion were calculated as 4,171.1 and 17,813.4 m3 km−2 year−1, respectively. In the sensitivity analysis, it was found that the most sensitive parameters of the model in order of importance were topography (slope), land cover and use, runoff, and channel erosion (R2 = 0.92–0.94), while geology, climate (rainfall), soil, and upland erosion factors were found to have moderate effect to the model output (R2 = 0.74–0.59).