Soil Loss Estimation based on RUSLE along the Central Hunter Valley Region,NSW, Australia

Soil erosion by water has been a major problem since man introduced agriculture in the landscape. Soil erosion is a common hazard which is steadily increasing as a result of human activities in many parts of the world. Hunter Valley of NSW is located in subtropical eastern Australia. The region is known for its diversity in landscape that includes wide floodplains, extensive estuarine wetlands, undulating country, escarpments and rugged sandstone gorges. The region is also well known for wine production. The Hunter Valley has a long history of soil erosion following the European settlement 150 years ago. Currently there have been renewed human activities in the south central part of the region for coal mining, leading to clearance of vegetation and disturbance of soil. The present study addresses the issue of soil erosion in a part of Hunter Region by employing the Revised Universal Soil Loss Equation (RUSLE, Renard et al., 1977) model. The results indicate that the average annual soil loss from the area is 0.7 kg/m²/year, which is well beyond the tolerance limit of the soil. Statistical relationships between soil loss and each parameter of the RUSLE equation were obtained and it was found that C factor has significant influence on the average soil loss in the area. An overall picture that emerges out of the study is that the region is continuing to suffer as a result of disturbance in natural environment from the historical times till present.     

Soil erosion prediction using the Revised Universal Soil Loss Equation (RUSLE) in a GIS framework,Chania, Northwestern Crete,Greece

Soil erosion is a growing problem in southern Greece and particularly in the island of Crete, the biggest Greek island with great agricultural activity. Soil erosion not only decreases agricultural productivity, but also reduces the water availability. In the current study, an effort to predict potential annual soil loss has been conducted. For the prediction, the Revised Universal Soil Loss Equation (RUSLE) has been adopted in a Geographical Information System framework. The RUSLE factors were calculated (in the form of raster layers) for the nine major watersheds which cover the northern part of the Chania Prefecture. The R-factor was calculated from monthly and annual precipitation data. The K-factor was estimated using soil maps available from the Soil Geographical Data Base of Europe at a scale of 1:1,000,000. The LS-factor was calculated from a 30-m digital elevation model. The C-factor was calculated using Remote Sensing techniques. The P-factor in absence of data was set to 1. The results show that an extended part of the area is undergoing severe erosion. The mean annual soil loss is predicted up to ∼200 (t/ha year⁻¹) for some watersheds showing extended erosion and demanding the attention of local administrators.     

Mapping soil erosion susceptibility using remote sensing and GIS: a case of the Upper Nam Wa Watershed,Nan Province,Thailand

Land degradation is still a very common problem in the mountains of Asia because of inappropriate land use practice in steep topography. Many studies have been carried out to map shifting cultivation and areas susceptible to soil erosion. Mostly, estimated soil loss is taken as the basis to classify the level of soil loss susceptibility of area. Factors that influence soil erosion are: rainfall erosivity, soil erodibility, slope length and steepness, crop management and conservation practices. Thus the reliability of estimated soil loss is based on how accurately the different factors were estimated or prepared. As each and every small pixel of our earth surface is different from one area to another, the manner in which the study area was discretized into smaller homogenous sizes and how the most accurate and efficient technique were adopted to estimate the soil loss are very important. The purpose of this study is to produce erosion susceptibility maps for an area that has suffered because of shifting cultivation located in the mountainous regions of Northern Thailand. For this purpose, an integrated approach using RS and GIS-based methods is proposed. Data from the Upper Nam Wa Watershed, a mountainous area of the Northern Thailand were used. An Earth Resources Data Analysis System (ERDAS) imagine image processor has been used for the digital analysis of satellite data and topographical analysis of the contour data for deriving the land use/land cover and the topographical data of the watershed, respectively. ARCInfo and ARCView have been used for carrying out geographical data analysis. The watershed was discretized into hydrologically, topographically, and geographically homogeneous grid cells to capture the watershed heterogeneity. The soil erosion in each cell was calculated using the universal soil loss equation (USLE) by carefully determining its various parameters and classifying the watershed into different levels of soil erosion severity. Results show that during the time of this study most of the areas under shifting cultivation fell in the highest severity class of susceptibility.     

Soil loss tolerance limits: an environmental management tool

Soil loss tolerance is defined as the maximum acceptable level of soil loss from an area which will allow a high level of productivity to be maintained. Furthermore the criteria which determines soil loss tolerance limits are discussed, and two methods currently in use in Southern Africa, i.e. those proposed by the Department of Agricultural Technical Services (DATS) and Skidmore are discussed. It is concluded that for various reasons the latter approach is more acceptable, and that it is imperative that a different T-value be determined for each soil series.Application of the principle of soil loss tolerance in the Tugela River Basin reveals that various areas are subjected to severe stress. Maps indicating areas with soil loss of more than 10 t/ha/yr; areas with a soil loss higher than its allocated soil loss tolerance limits; and soil loss as a percentage of its T-values are included. These maps reveal startling facts, and emphasize the need for swift action in order to combat the problem of soil erosion in the area.The conclusion is drawn that the technique by which soil loss tolerance limits are determied could be applied to large areas, and its representation on large scale maps could be very useful in environmental planning and management.     

Calibrating a rainfall erosivity assessment model at regional scale in Mediterranean area

A simplified regression model is here calibrated on the basis of rainfall data records of Sicily (southern Italy), in order to show the model reliability in assessing the R-factor of the Universal Soil Loss Equation and its revised version (RUSLE) and to provide an estimate of long-term rainfall erosivity at medium-regional scale. The proposed model is a rearrangement of a former simplified model, formulated for the Italian environment, grouping three easily available rainfall variables on various time scales, which has been shown to be more successful than others in reproducing the rainfall erosive power over different locations of Italy. A geostatistical interpolation procedure is then applied for generating the regional long-term erosivity map with associated standard error. Areas with severe erosive rainfalls (from 2,000 up to more than 6,000 MJ mm ha⁻¹ h⁻¹) are pointed out which will correspond to areas suffering from severe soil erosion. Solving the problem of calculating the R-factor value in the RUSLE equation by means of such a simplified model here formulated will allow to predict the related soil loss. Moreover, given the availability of long time-series of concerned rainfall data, it will be possible to analyse the variability of rainfall erosivity within the last 50 years, and to investigate the application of RUSLE or similar soil erosion models with forecasting purposes of soil erosion risk.     

Soil erosion monitoring and its implication in a limestone land suffering from rocky desertification in the Huajiang Canyon, Guizhou, Southwest China

Over the past decades, the vast limestone mountain areas in southwestern China have suffered greatly from karst rocky desertification (KRD), which is a unique type of desertification caused by irrational land-use practices and has drawn increasing attention of international academic community. Characterizing soil erosion in this region is the key to understanding the escalating KRD problem and finding solution to it. The authors applied leveling method to study soil erosion process in the Huajiang Karst Canyon area between 1999 and 2003, and tried to relate it to KRD expansion. The monitoring data indicate that soil in the study area was losing at an alarming rate, which is much higher than soil formation rate and has already resulted in severe KRD problem. Soil loss under different land-use conditions varied greatly during the monitoring period. The highest soil erosion rate occurred in bare and newly abandoned cropland, followed by sparse grass land, forest land, and dense grass land. In addition, soil erosion could be significantly different under different micro-topographic conditions. Because soil erosion rate in the studied karst mountain areas is surprisingly high, it is urgent to take quick actions to fight against the ongoing KRD problems in Southwest China before an irreversible situation occurs. However, the traditional way to combat KRD by abandoning current cropland needs to be carefully reconsidered, since a bare newly abandoned cropland may suffer more from rapid soil loss than before.     

Estimation of soil erosion using RUSLE in a GIS framework: a case study in the Buyukcekmece Lake watershed,northwest Turkey

This study was aimed at predicting soil erosion risk in the Buyukcekmece Lake watershed located in the western part of Istanbul, Turkey, by using Revised Universal Soil Loss Equation (RUSLE) model in a GIS framework. The factors used in RUSLE were computed by using different data obtained or produced from meteorological station, soil surveys, topographic maps, and satellite images. The RUSLE factors were represented by raster layers in a GIS environment and then multiplied together to estimate the soil erosion rate in the study area using spatial analyst tool of ArcGIS 9.3. In the study, soil loss rate below 1 t/ha/year was defined as low erosion, while those >10 t/ha/year were defined as severe erosion. The values between low and severe erosion were further classified as slight, moderate, and high erosion areas. The study provided a reliable prediction of soil erosion rates and delineation of erosion-prone areas within the watershed. As the study revealed, soil erosion risk is low in more than half of the study area (54%) with soil loss <1 t/ha/year. Around one-fifth of the study area (19%) has slight erosion risk with values between 1 and 3 t/ha/year. Only 11% of the study area was found to be under high erosion risk with soil loss between 5 and 10 t/ha/year. The severe erosion risk is seen only in 5% of the study area with soil loss more than 10 t/ha/year. As the study revealed, nearly half of the Buyukcekmece Lake watershed requires implementation of effective soil conservation measures to reduce soil erosion risk.     

桂江流域土壤侵蚀估算及其时空特征分析

桂江流域的水土流失现状研究对珠江三角洲的水生态安全有重要的现实意义。采用修正的通用土壤流失方程（RUSLE）估算了桂江流域的土壤侵蚀模数与年侵蚀总量,分析流域内土壤侵蚀的时空分布特征,探讨了影响该区域土壤侵蚀强度的自然与人文因素。结果表明,桂江流域51.8%的地表都在发生不同程度的土壤侵蚀。从全流域平均土壤侵蚀强度来看,属于中度侵蚀。从土壤侵蚀面积来看,约85%的地表处于微度、轻度与中度侵蚀。4-6月的全流域平均土壤侵蚀强度最大,侵蚀总量也是最大的。流域的土壤侵蚀主要发生在高程在30~600m的低山丘陵-高地地貌区内的林地与耕地中。流域内岩溶区的土壤侵蚀强度随着石漠化程度从无到中度逐渐增加,轻、中度石漠化区的土壤侵蚀强度达到强度侵蚀等级。      

Identification and prioritization of sub-watersheds for land and water management using InVEST SDR model: Rmelriver basin,Tunisia

Tunisia presents many favorable conditions for the outbreak of water erosion because of its climatic and physical characteristics. This phenomenon represents a serious threat to the natural resources of soil and water. The aim of the present study is to identify the most vulnerable areas in order to help managers implement an effective management program. Thematic layers and parameters were integrated in the InVEST (Integrated Valuation of Environmental Services and Trade-offs) SDR (Sediment Delivery Ratio). Soil loss and sediment yield were calculated by the model and compared to observed data. The Rmel river basin was divided into 17 sub-watersheds using the dam axis as the main outlet. Results reveal that approximately 60% of the basin presents soil loss more than 5 ton/ha/year. Soil erosion map demonstrates that soil erosion risk increases with increased slope gradient, especially in agricultural lands. Sub-catchment prioritizations have been fixed based on soil erosion risk. Results show that sub-catchment 16 presents the highest soil loss with a value of 65 ton/ha/year. Sub-catchment presenting high soil erosion risk needs to give a high priority in conservation planning.     

Estimation of spatial patterns of soil erosion using remote sensing and GIS: a case study of Indravati catchment

Soil erosion is a serious environmental problem in Indravati catchment. It carries the highest amount of sediments compared with other catchments in India. This catchment spreading an area of 41,285 km² is drained by river Indravati, which is one of the northern tributaries of the river Godavari in its lower reach. In the present study, USLE is used to estimate potential soil erosion from river Indravati catchment. Both magnitude and spatial distribution of potential soil erosion in the catchment is determined. The derived soil loss map from USLE model is classified into six categories ranging from slight to very severe risk depending on the calculated soil erosion amount. The soil erosion map is linked to elevation and slope maps to identify the area for conservation practice in order to reduce the soil loss. From the model output predictions, it is found that average erosion rate predicted is 18.00 tons/ha/year and sediment yield at the out let of the catchment is 22.30 Million tons per annum. The predicted sediment yield verified with the observed data.     

Soil erosion prediction at the basin scale using the revised universal soil loss equation (RUSLE) in a catchment of Sicily (southern Italy)

Soil erosion by water is a serious problem in southern Italy, particularly in Sicily which is one of the Italian administrative regions prone to desertification. Soil erosion not only affects soil quality, in terms of agricultural productivity, but also reduces the availability of water in reservoirs. This study was conducted in the Comunelli catchment in south-central Sicily, to predict potential annual soil loss using the revised universal soil loss equation (RUSLE) and to test the reliability of this methodology to predict reservoirs siltation. The RUSLE factors were calculated for the catchment using survey data and rain gauge measurement data. The R-factor was calculated from daily, monthly and annual precipitation data. The K-factor was calculated from soil samples collected in May and November 2004. The LS topographic factor was calculated from a 20 m digital elevation model. The C- and P-factors, in absence of detailed data, were set to 1. The results were compared with those obtained from another soil loss estimation method based on ¹³⁷Cs and with the soil loss estimated from the sediment volume stored in the Comunelli reservoir between 1968 and 2004.     

Regional soil erosion risk mapping using RUSLE,GIS, and remote sensing: a case study in Miyun Watershed,North China

This paper applied the Revised Universal Soil Loss Equation (RUSLE), remote-sensing technique, and geographic information system (GIS) to map the soil erosion risk in Miyun Watershed, North China. 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 a back propagation (BP) neural network method of Landsat ETM+ data with a correlation coefficient (r) of 0.929 to the field collected data, and a digital elevation model (DEM) with a spatial resolution of 30 m was derived from topographical map at the scale of 1:50,000 to develop the LS factor map. P factor map was assumed as 1 for the watershed because only a very small area has conservation practices. By integrating the six factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the upper watershed of Miyun reservoir was obtained by the RUSLE model. The results showed that the annual average soil loss for the upper watershed of Miyun reservoir was 9.86 t ha⁻¹ ya⁻¹ in 2005, and the area of 47.5 km² (0.3%) experiences extremely severe erosion risk, which needs suitable conservation measures to be adopted on a priority basis. The spatial distribution of erosion risk classes was 66.88% very low, 21.90% low, 6.19% moderate, 2.90% severe, and 1.84% very severe. Among all counties and cities in the study area, Huairou County is in the extremely severe level of soil erosion risk, about 39.6% of land suffer from soil erosion, while Guyuan County in the very low level of soil erosion risk suffered from 17.79% of soil erosion in 2005. Therefore, the areas which are in the extremely severe level of soil erosion risk need immediate attention from soil conservation point of view.     

Tolerable versus actual soil erosion rates in Europe

Erosion is a major threat to soil resources in Europe, and may impair their ability to deliver a range of ecosystem goods and services. This is reflected by the European Commission's Thematic Strategy for Soil Protection, which recommends an indicator-based approach for monitoring soil erosion. Defined baseline and threshold values are essential for the evaluation of soil monitoring data. Therefore, accurate spatial data on both soil loss and soil genesis are required, especially in the light of predicted changes in climate patterns, notably frequency, seasonal distribution and intensity of precipitation. Rates of soil loss are reported that have been measured, modelled or inferred for most types of soil erosion in a variety of landscapes, by studies across the spectrum of the Earth sciences. Natural rates of soil formation can be used as a basis for setting tolerable soil erosion rates, with soil formation consisting of mineral weathering as well as dust deposition. This paper reviews the concept of tolerable soil erosion and summarises current knowledge on rates of soil formation, which are then compared to rates of soil erosion by known erosion types, for assessment of soil erosion monitoring at the European scale.A modified definition of tolerable soil erosion is proposed as ‘any actual soil erosion rate at which a deterioration or loss of one or more soil functions does not occur,’ actual soil erosion being ‘the total amount of soil lost by all recognised erosion types.’ Even when including dust deposition in soil formation rates, the upper limit of tolerable soil erosion, as equal to soil formation, is ca. 1.4 t ha^− 1 yr^− 1 while the lower limit is ca. 0.3 t ha^− 1 yr^− 1, for conditions prevalent in Europe. Scope for spatio-temporal differentiation of tolerable soil erosion rates below this upper limit is suggested by considering (components of) relevant soil functions. Reported rates of actual soil erosion vary much more than those for soil formation. Actual soil erosion rates for tilled, arable land in Europe are, on average, 3 to 40 times greater than the upper limit of tolerable soil erosion, accepting substantial spatio-temporal variation. This paper comprehensively reviews tolerable and actual soil erosion in Europe and highlights the scientific areas where more research is needed for successful implementation of an effective European soil monitoring system.     

Wind erodibility in eastern Ningxia Province, China

Many methods have been used to study wind erosion, a common phenomenon in arid and semi-arid regions. This paper documents a 2006 field study in which sediment samplers and steel pins were used to measure soil erosion, and sand drift potential was used to estimate wind erosion and transport in the eastern part of Ningxia Province, China. Wind energy in the study area was found to be moderate and sediments were transported from northwest to southeast. Sediment transport differed depending on the surface type: sediment transport was greatest in areas of shifting dunes, with cultivated land, semi-fixed dunes, and fixed dunes showing progressively less transport. Sediment transport was lowest in shrubland areas. The depth of erosion was 66 in cultivated areas, 33 in shifting dunes, 28 in semi-fixed dunes, 20 in fixed dunes, and 3 mm in shrublands. The extensive erosion of sediment in cultivated lands and the resultant decrease in surface height results in serious degradation and loss of soil fertility.     

Conditional simulation of USLE/RUSLE soil erodibility factor by geostatistics in a Mediterranean Catchment,Turkey

Soil erosion is a major environmental problem that threatens the sustainability and productivity of agricultural areas. Assessment and mapping of soil erosion are extremely important in the management and conservation of natural resources. The universal soil loss equation (USLE/RUSLE) is an erosion model that predicts soil loss as a function of soil erodibility (K-factor), as well as topographic, rainfall, cover, and management factors. The traditional approach assumes that one soil erodibility value represents the entire area of each soil series. Therefore, that approach does not account for spatial variability of soil series. This study was carried out to evaluate the use of the sequential Gaussian simulation (SGS) for mapping soil erodibility factor of the USLE/RUSLE methodology. Five hundred and forty-four surface soil samples (0–20 cm) were collected from the study area to determine the soil erodibility. A simulation procedure was carried out on 300 realizations, and histogram and semivariogram of the simulation were compared to the observed values. The results showed that the summary statistics, histogram, and semivariogram of the simulation results were close to the observed values. In contrary to the traditional approach and kriging, 95% confidence interval of the simulated realizations was formed in order to determine uncertainty standard deviation map, and the uncertainty was explained numerically. The SGS produced a more reliable soil erodibility map and it can be more successfully used for monitoring and improving effective strategies to prevent erosion hazards especially to improve site specific management plans.     

Multi-temporal annual soil loss risk mapping employing Revised Universal Soil Loss Equation (RUSLE) model in Nun Nadi Watershed, Uttrakhand (India)

The present comparative study is multi-temporal in nature. The Revised Universal Soil Loss Equation (RUSLE), remote sensing, and GIS were used to model the soil loss estimation for soil conservation and vegetation rehabilitation in Nun Nadi watershed for the years 2000 and 2009. The estimated mean soil loss for the year 2000 and 2009 is 3,283.11 and 1,419.39 Mg?ha^?1 year^?1, respectively. The study finds that about 80 % area has low or least risk of erosion and about 7 % is exposed to high or very high risk which indicates the improvement in terms of soil loss if we compare the data of both the time periods. The findings show that the rainfall, LULC change, and elevation are the main responsible factors for the soil loss in Nun Nadi watershed. Conservation measures have been adopted; however, the problem still remains serious and demands urgent attention.     

Modeling soil erosion using RUSLE and GIS in a watershed occupied by rural settlement in the Brazilian Cerrado

The installation of a rural settlement complex in the watershed stream Indaiá has promoted changes in land-use and vegetation cover dynamics; however, the effects of intensive agriculture and cattle farming in rural settlements on soil loss rates are not well known. Predictive models implemented in geographic information systems have proven to be effective tools for estimating erosive processes. The erosion predictive model Revised Universal Soil Loss Equation (RUSLE) is a useful tool for analyzing, establishing and managing soil erosion. RUSLE has been widely used to estimate annual averages of soil loss, by both interrill and rill erosion, worldwide. Therefore, the aim of this work was to estimate the soil loss in the watershed stream Indaiá, using the RUSLE model and geoprocessing techniques. To estimate soil loss, the following factors were spatialized: erosivity (R), erodibility (K), topography (LS), land-use and management (C) and conservation practices (P); the annual soil loss values were calculated using the RUSLE model equation. The estimated value of soil loss in the hydrographic basin ranged from 0 to 4082.16 Mg ha^?1 year^?1 and had an average value of 47.81 Mg ha^?1 year^?1. These results have demonstrated that 68.16 % of the study area showed little or no soil loss based on the Food and Agriculture Organization’s (FAO 1980) classification. When comparing the average value of soil loss obtained using the RUSLE model with the Natural Potential for Erosion, a 16-fold reduction in soil was found, which highlighted the fact that vegetation cover (C factor) has a greater influence than other factors (R, K and LS) on soil loss prediction attenuation. These results lead to the conclusion that soil loss occurs by different methods in each settlement in the basin and that erosive processes modeled by geoprocessing have the potential to contribute to an orderly land management process.     

Soil erosion and management recommendations at three State Vehicular Recreation areas,California

Off-road vehicle (ORV) impact on the landscape includes the destruction of protective vegetative cover, soil compaction, and increased runoff followed by increased erosion. An investigation of three State Vehicular Recreation Areas (SVRAs) in arid regions of California have documented 10-to 25-fold increases in sediment yield relative to nearby undisturbed basins. Soil texture and slope length are the dominant factors controlling soil erodibility in these areas. Organic carbon content of the soil exposed in hillclimb gullies was comparable to C horizon values of undisturbed soil profiles demonstrating a significant (70%) loss of soil fertility due to accelerated erosion. Soil erosion can be minimized and lifespan of these recreational areas prolonged by initiating and enforcing some critical management policies, including careful control over location and length of hillclimb, rotating use areas such that rehabilitation or revegetation is feasible, and seasonal use restrictions.     

Spatial variability of soil properties in relation to land use and topography in a typical small watershed of the black soil region,northeastern China

Soil degradation resulted from unreasonable land use and erosion has been a serious problem in the black soil region of northeastern China. This paper seeks to understand the relationships between topsoil properties and topography and land use for land management targeting at improving soil quality in this region. A total of 292 soil samples and 81 volumetric rings were taken from a typical small watershed of the region in June 2005 for examining total carbon (TC), total nitrogen (TN), soil texture (classified into gravel, sand, silt, and clay), and bulk density (ρ _b), respectively. Spatial variability of these soil properties was evaluated with classical statistics and geostatistics methods. The results of classical statistics indicated that TC, TN, sand, silt, clay content, and ρ _b were moderate variables while gravel had great variability. Soil properties were mainly correlated to slope position, elevation and land types. Geostatistical analyses showed that the spatial autocorrelation for TC, TN, and silt was weak, strong for clay and moderate for and ρ _b sand, respectively. The spatial variations of soil properties are affected comprehensively by topographic factors, land use, erosion, and erosion control in this watershed. Past erosion, however, is the most important component to induce change of soil properties. In this small watershed, current soil and water conservation measures play an important role in controlling soil loss. But the restoration of soil properties was unsatisfactory. Comparing with untilled soil of this region, TC, TN, silt content are excessively low; whereas ρ _b, sand and clay content are excessively high; gravel appears at most sampling locations. It is necessary for improving soil properties to protect forest and grassland and change cultivation system of farmlands.     

Integration of geospatial technologies with RUSLE for analysis of land use/cover change impact on soil erosion: case study in Rib watershed,north-western highland Ethiopia

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.