Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques

Soil conservation planning often requires estimates of the spatial distribution of soil erosion at a catchment or regional scale. This paper applied the Revised Universal Soil Loss Equation (RUSLE) to investigate the spatial distribution of annual soil loss over the upper basin of Miyun reservoir in China. Among the soil erosion factors, which are rainfall erosivity (R), soil erodibility (K), slope length (L), slope steepness (S), vegetation cover (C), and support practice factor (P), the vegetative cover or C factor, which represents the effects of vegetation canopy and ground covers in reducing soil loss, has been one of the most difficult to estimate over broad geographic areas. In this paper, the C factor was estimated based on back propagation neural network and the results were compared with the values measured in the field. The correlation coefficient (r) obtained was 0.929. Then the C factor and the other factors were used as the input to RUSLE model. By integrating the six factor maps in geographical information system (GIS) through pixel-based computing, the spatial distribution of soil loss over the upper basin of Miyun reservoir was obtained. The results showed that the annual average soil loss for the upper basin of Miyun reservoir was 9.86 t ha(-1) ya(-1) in 2005, and the area of 46.61 km(2) (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 66.9% very low, 21.89% low, 6.18% moderate, 2.89% severe, and 1.84% very severe. Thus, by using RUSLE in a GIS environment, the spatial distribution of water erosion can be obtained and the regions which susceptible to water erosion and need immediate soil conservation planning and application over the upper watershed of Miyun reservoir in China can be identified.     

Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete

Due to inappropriate agricultural management practices, soil erosion is becoming one of the most dangerous forms of soil degradation in many olive farming areas in the Mediterranean region, leading to significant decrease of soil fertility and yield. In order to prevent further soil degradation, proper measures are necessary to be locally implemented. In this perspective, an increase in the spatial accuracy of remote sensing datasets and advanced image analysis are significant tools necessary and efficient for mapping soil erosion risk on a fine scale. In this study, the Revised Universal Soil Loss Equation (RUSLE) was implemented in the spatial domain using GIS, while a very high resolution satellite image, namely a QuickBird image, was used for deriving cover management (C) and support practice (P) factors, in order to map the risk of soil erosion in Kolymvari, a typical olive farming area in the island of Crete, Greece. The results comprised a risk map of soil erosion when P factor was taken uniform (conventional approach) and a risk map when P factor was quantified site-specifically using object-oriented image analysis. The results showed that the QuickBird image was necessary in order to achieve site-specificity of the P factor and therefore to support fine scale mapping of soil erosion risk in an olive cultivation area, such as the one of Kolymvari in Crete. Increasing the accuracy of the QB image classification will further improve the resulted soil erosion mapping.     

Use of USLE/GIS Methodology for Predicting Soil Loss in a Semiarid Agricultural Watershed

The Universal Soil Loss Equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices in agricultural watersheds by the effective integration of the GIS-based procedures to estimate the factor values in a grid cell basis. This study was performed in the Kazan Watershed located in the central Anatolia, Turkey, to predict soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Rain erosivity (R), soil erodibility (K), and cover management factor (C) values of the model were calculated from erosivity map, soil map, and land use map of Turkey, respectively. R values were site-specifically corrected using DEM and climatic data. The topographical and hydrological effects on the soil loss were characterized by LS factor evaluated by the flow accumulation tool using DEM and watershed delineation techniques. From resulting soil loss map of the watershed, the magnitude of the soil erosion was estimated in terms of the different soil units and land uses and the most erosion-prone areas where irreversible soil losses occurred were reasonably located in the Kazan watershed. This could be very useful for deciding restoration practices to control the soil erosion of the sites to be severely influenced.     

10-Daily soil erosion modelling over sub-Saharan Africa

Soil erosion is considered to be one of the greatest environmental problems of sub-Saharan Africa. This paper investigates the advantages and disadvantages of modelling soil erosion at the continental scale and suggests an operational methodology for mapping and quantifying 10-daily water runoff and soil erosion over this scale using remote sensing data in a geographical information system framework. An attempt is made to compare the estimates of this study with general data on the severity of soil erosion over Africa and with measured rates of soil loss at different locations over the continent. The results show that the measured and estimated rates of erosion are in some areas very similar and in general within the same order of magnitude. The importance and the potential of using the soil erosion estimates with simple models and easily accessible free data for various continental-scale environmental applications are also demonstrated.     

The use of spatial empirical models to estimate soil erosion in arid ecosystems

The central objective of this project was to utilize geographical information systems and remote sensing to compare soil erosion models, including Modified Pacific South-west Inter Agency Committee (MPSIAC), Erosion Potential Method (EPM), and Revised Universal Soil Loss Equation (RUSLE), and to determine their applicability for arid regions such as Kuwait. The northern portion of Umm Nigga, containing both coastal and desert ecosystems, falls within the boundaries of the de-militarized zone (DMZ) adjacent to Iraq and has been fenced off to restrict public access since 1994. Results showed that the MPSIAC and EPM models were similar in spatial distribution of erosion, though the MPSIAC had a more realistic spatial distribution of erosion and presented finer level details. The RUSLE presented unrealistic results. We then predicted the amount of soil loss between coastal and desert areas and fenced and unfenced sites for each model. In the MPSIAC and EPM models, soil loss was different between fenced and unfenced sites at the desert areas, which was higher at the unfenced due to the low vegetation cover. The overall results implied that vegetation cover played an important role in reducing soil erosion and that fencing is much more important in the desert ecosystems to protect against human activities such as overgrazing. We conclude that the MPSIAC model is best for predicting soil erosion for arid regions such as Kuwait. We also recommend the integration of field-based experiments with lab-based spatial analysis and modeling in future research.     

Load estimation and source apportionment of nonpoint source nitrogen and phosphorus based on integrated application of SLURP model, ECM, and RUSLE: a case study in the Jinjiang River, China

The nonpoint source (NPS) pollution is difficult to manage and control due to its complicated generation and formation. Load estimation and source apportionment are an important and necessary process for efficient NPS control. Here, an integrated application of semi-distributed land use-based runoff process (SLURP) model, export coefficients model (ECM), and revise universal soil loss equation (RUSLE) for the load estimation and source apportionment of nitrogen and phosphorus was proposed. The Jinjiang River (China) was chosen for the evaluation of the method proposed here. The chosen watershed was divided into 27 subbasins. After which, the SLURP model was used to calculate land use runoff and to estimate loads of dissolved nitrogen and phosphorus, and ECM was applied to estimate dissolved loads from livestock and rural domestic sewage. Next, the RUSLE was employed for load estimation of adsorbed nitrogen and phosphorus. The results showed that the 12,029.06 t?a^?1 pollution loads of total NPS nitrogen (TN) mainly originated from dissolved nitrogen (96.24 %). The major sources of TN were land use runoff, which accounted for 45.97 % of the total, followed by livestock (32.43 %) and rural domestic sewage (17.83 %). For total NPS phosphorous (TP), its pollution loads were 570.82 t?a^?1 and made up of dissolved and adsorbed phosphorous with 66.29 and 33.71 % respectively. Soil erosion, land use runoff, rural domestic sewage, and livestock were the main sources of phosphorus with contribution ratios of 33.71, 45.73, 14.32, and 6.24 % respectively. Therefore, land use runoff, livestock, and soil erosion were identified as the main pollution sources to influence loads of NPS nitrogen and phosphorus in the Jinjiang River and should be controlled first. The method developed here provided a helpful guideline for conducting NPS pollution management in similar watershed.     

Identification of effective best management practices in sediment yield diminution using GeoWEPP: the Kasilian watershed case study

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.     

Assessment of the redistribution of soil carbon using a new index—a case study in the Haihe River Basin,North China

Soil carbon redistribution is an important process in the terrestrial carbon cycle. This study describes a new index, soil carbon redistribution (SCR) index, that can be used to assess long-term soil carbon redistribution at a large watershed scale. The new index is based on the theoretical preconditions that soil carbon redistribution is mainly controlled by vegetation type, precipitation, topography/slope, and soil carbon concentration. The Haihe River Basin served as an example for this analysis. The SCR index was calculated, and a GIS-based map shows its spatial patterns. The results suggested that soil carbon was usually prone to being carried away from mountainous regions with natural vegetation, while it was prone to deposition in the plain and plateau regions with cultivated vegetation. The methods in the paper offer a tool that can be used to quantify the potential risk where soil carbon is prone to being carried away and deposited in a large watershed.     

Check dam sediments: an important indicator of the effects of environmental changes on soil erosion in the Loess Plateau in China

Check dam sediments document the process of soil erosion for a watershed. The main objectives of this research are as follows: first, to determine whether the sediments trapped in check dams can provide useful information about local erosion and the environment, and second, to obtain the extent to which they can be stratigraphically interpreted and correlated to the land use history of an area controlled by check dams. Particle size and the concentration of ¹³⁷Cs in sediments are the indicators used to study the effects of environmental changes on soil erosion in the Loess Plateau, China. A total of 216 soil samples were collected from four sediment profile cores at the Yangjuangou watershed check dam constructed in 1955 and fully silted with sediments by 1965. The results indicated that ¹³⁷Cs dating and sediment particle size can characterize the sediment deposition process. Silt makes up more than 50 % of the sediment; both the clay and silt sediment fractions decrease gradually in the upstream direction. The sediment profiles are characterized by three depositional layers. These layers suggest changes in the land use. The top layer showed tillage disturbance, with moderate sediments and new soil mixed from 0 to 20 cm. A transition stage from wetlands (characterized by vegetation such as bulrush) to cropland is inferred from sediments at depths of 20–85 cm. Below 85 cm, sedimentary layering is obvious and there is no tillage disturbance. At the downstream site, A0, the average rate of sediment deposition from 1958 to 1963 was approximately 6,125.4 t year^?1 km^?2. Because of their high time resolution, check dam sediments indicate the effects of environmental changes on soil erosion, and they can provide a multiyear record of the soil erosion evolution at the local scale in the middle reaches of the Yellow River.     

An experimental method to verify soil conservation by check dams on the Loess Plateau, China

A successful experiment with a physical model requires necessary conditions of similarity. This study presents an experimental method with a semi-scale physical model. The model is used to monitor and verify soil conservation by check dams in a small watershed on the Loess Plateau of China. During experiments, the model–prototype ratio of geomorphic variables was kept constant under each rainfall event. Consequently, experimental data are available for verification of soil erosion processes in the field and for predicting soil loss in a model watershed with check dams. Thus, it can predict the amount of soil loss in a catchment. This study also mentions four criteria: similarities of watershed geometry, grain size and bare land, Froude number (Fr) for rainfall event, and soil erosion in downscaled models. The efficacy of the proposed method was confirmed using these criteria in two different downscaled model experiments. The B-Model, a large scale model, simulates watershed prototype. The two small scale models, D_a and D_b, have different erosion rates, but are the same size. These two models simulate hydraulic processes in the B-Model. Experiment results show that while soil loss in the small scale models was converted by multiplying the soil loss scale number, it was very close to that of the B-Model. Obviously, with a semi-scale physical model, experiments are available to verify and predict soil loss in a small watershed area with check dam system on the Loess Plateau, China.     

An assessment to prioritise the critical erosion-prone sub-watersheds for soil conservation in the Gumti basin of Tripura,North-East India

Erosion-induced land degradation problem has emerged as a serious environmental issue across the world. Assessment of this problem through modelling can generate valuable quantitative information for the planners to identify priority areas for proper soil conservation measures. The Gumti River basin of Tripura falls under humid tropical climate and experiences soil erosion for a prolonged period which has turned into a major environmental issue. Increased sediment supply through top soil erosion is one of the major reasons for reduced navigability of this river. Thus, the present study is an attempt to prioritize the sub-watersheds of the Gumti basin by estimating soil loss through the USLE (Universal Soil Loss Equation) model. For that purpose, five parameters of the USLE model were processed, computed and overlaid in a GIS environment. The result shows that potential mean annual soil loss of the Gumti basin ranges between 0.03 and 114.08 t ha^?1 year^?1. The resultant values of soil loss were classified into five categories considering the minimum and maximum values. It has been identified that low, moderate, high, very high and severe soil loss categories occupy 68.71, 8.94, 5.86, 5.02 and 11.47% of the basin respectively. Moreover, it has been recognised that sub-watersheds like SW7, SW8, SW12, SW21, SW24 and SW29 fall under very high priority class for which mitigation measures are essential. Therefore, the present study recommends mitigation measures through terrace cultivation, as an alternative of shifting cultivation in the hilly areas and through construction of check dams at the appropriate sites of the erosion prone sub-watersheds. Moreover, proper afforestation programmes that have been implemented successfully in other parts of Tripura through the Japan International Cooperation Agency, Joint Forest Management, and National Afforestation Programme should be initiated in the highly erosion-prone areas of the Gumti River basin.     

Soil erosion and sediment fluxes analysis: a watershed study of the Ni Reservoir,Spotsylvania County,VA, USA

Anthropogenic forces that alter the physical landscape are known to cause significant soil erosion, which has negative impact on surface water bodies, such as rivers, lakes/reservoirs, and coastal zones, and thus sediment control has become one of the central aspects of catchment management planning. The revised universal soil loss equation empirical model, erosion pins, and isotopic sediment core analyses were used to evaluate watershed erosion, stream bank erosion, and reservoir sediment accumulation rates for Ni Reservoir, in central Virginia. Land-use and land cover seems to be dominant control in watershed soil erosion, with barren land and human-disturbed areas contributing the most sediment, and forest and herbaceous areas contributing the least. Results show a 7 % increase in human development from 2001 (14 %) to 2009 (21.6 %), corresponding to an increase in soil loss of 0.82 Mg ha^-1 year^-1 in the same time period. ²¹⁰Pb-based sediment accumulation rates at three locations in Ni Reservoir were 1.020, 0.364, and 0.543 g cm^-2 year^-1 respectively, indicating that sediment accumulation and distribution in the reservoir is influenced by reservoir configuration and significant contributions from bedload. All three locations indicate an increase in modern sediment accumulation rates. Erosion pin results show variability in stream bank erosion with values ranging from 4.7 to 11.3 cm year^-1. These results indicate that urban growth and the decline in vegetative cover has increased sediment fluxes from the watershed and poses a significant threat to the long-term sustainability of the Ni Reservoir as urbanization continues to increase.     

An evaluation of grid size uncertainty in empirical soil loss modeling with digital elevation models

This paper presents a study on the effect of topographic variability on grid-based empirical estimation of soil erosion and sediment transport with raster geographic information systems (GIS). An original digital elevation model (DEM) of 10 m resolution for a case watershed is resampled to six realizations of greater grid sizes for a comparative examination. The Universal Soil Loss Equation (USLE) and a distance-based sediment delivery equation are applied to the watershed to calculate soil loss from each cell and total sediment transport to streams, respectively. The results suggest that the selection of the DEM gird size has considerable influence on the soil loss estimation with the empirical models. The estimate of total soil loss from the watershed decreases significantly with the increasing DEM cell size as the spatial variability is reduced by the cell aggregation. The empirical modeling approach is a useful tool for qualitative assessment of soil erosion, provided that spatial variability can be adequately represented by applied DEMs. However, discretion is suggested for its applications to quantitative estimation of soil loss concerning the sensitivity to the grid size selection.     

土壤侵蚀的环境磁学监测方法

依据土壤、沉积物磁性理论,河流或湖泊的悬移物和沉积物记载了其产地的磁信息,根据它们的磁性参数可以追踪其来源及分布范围;根据表土磁性增强现象,可以采用土壤剖面磁性变化方法来判断土壤侵蚀程度;另外,应用“磁性示踪剂”也是研究土壤侵蚀的有效手段。文章就这方面的国内外研究进展情况加以阐述,并对该方法的优缺点及发展前景提出看法。     

A multi-level assessment methodology for determining the potential for groundwater contamination by pesticides

A multi-level pesticide assessment methodology has been developed to permit regulatory personnel to undertake a variety of assessments on the potential for pesticide used in agricultural areas to contaminate the groundwater regime at an increasingly detailed geographical scale of investigation. A multi-level approach accounts for a variety of assessment objectives and detail required in the assessment, the restrictions on the availability and accuracy of data, the time available to undertake the assessment, and the expertise of the decision maker. The level 1: regional scale is designed to prioritize districts having a potentially high risk for groundwater contamination from the application of a specific pesticide for a particular crop. The level 2: local scale is used to identify critical areas for groundwater contamination, at a soil polygon scale, within a district. A level 3: soil profile scale allows the user to evaluate specific factors influencing pesticide leaching and persistence, and to determine the extent and timing of leaching, through the simulation of the migration of a pesticide within a soil profile. Because of the scale of investigation, limited amount of data required, and qualitative nature of the assessment results, the level 1 and level 2 assessment are designed primarily for quick and broad guidance related to management practices. A level 3 assessment is more complex, requires considerably more data and expertise on the part of the user, and hence is designed to verify the potential for contamination identified during the level 1 or 2 assessment. The system combines environmental modelling, geographical information systems, extensive databases, data management systems, expert systems, and pesticide assessment models, to form an environmental information system for assessing the potential for pesticides to contaminate groundwater.     

Land degradation assessment by geo-spatially modeling different soil erodibility equations in a semi-arid catchment

Land degradation by soil erosion is one of the most serious problems and environmental issues in many ecosystems of arid and semi-arid regions. Especially, the disturbed areas have greater soil detachability and transportability capacity. Evaluation of land degradation in terms of soil erodibility, by using geostatistical modeling, is vital to protect and reclaim susceptible areas. Soil erodibility, described as the ability of soils to resist erosion, can be measured either directly under natural or simulated rainfall conditions, or indirectly estimated by empirical regression models. This study compares three empirical equations used to determine the soil erodibility factor of revised universal soil loss equation prediction technology based on their geospatial performances in the semi-arid catchment of the Saraykoy II Irrigation Dam located in Cankiri, Turkey. A total of 311 geo-referenced soil samples were collected with irregular intervals from the top soil layer (0-10?cm). Geostatistical analysis was performed with the point values of each equation to determine its spatial pattern. Results showed that equations that used soil organic matter in combination with the soil particle size better agreed with the variations in land use and topography of the catchment than the one using only the particle size distribution. It is recommended that the equations which dynamically integrate soil intrinsic properties with land use, topography, and its influences on the local microclimates, could be successfully used to geospatially determine sites highly susceptible to water erosion, and therefore, to select the agricultural and bio-engineering control measures needed.     

Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed,China

The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate–nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.     

Assessing regional environmental quality by integrated use of remote sensing,GIS, and spatial multi-criteria evaluation for prioritization of environmental restoration

This study was an attempt to analyse the regional environmental quality with the application of remote sensing, geographical information system, and spatial multiple criteria decision analysis and, to project a quantitative method applicable to identify the status of the regional environment of the study area. Using spatial multi-criteria evaluation (SMCE) approach with expert knowledge in this study, an integrated regional environmental quality index (REQI) was computed and classified into five levels of regional environment quality viz. worse, poor, moderate, good, and very good. During the process, a set of spatial criteria were selected (here, 15 criterions) together with the degree of importance of criteria in sustainability of the regional environment. Integrated remote sensing and GIS technique and models were applied to generate the necessary factors (criterions) maps for the SMCE approach. The ranking, along with expected value method, was used to standardize the factors and on the other hand, an analytical hierarchy process (AHP) was applied for calculating factor weights. The entire process was executed in the integrated land and water information system (ILWIS) software tool that supports SMCE. The analysis showed that the overall regional environmental quality of the area was at moderate level and was partly determined by elevation. Areas under worse and poor quality of environment indicated that the regional environmental status showed decline in these parts of the county. The study also revealed that the human activities, vegetation condition, soil erosion, topography, climate, and soil conditions have serious influence on the regional environment condition of the area. Considering the regional characteristics of environmental quality, priority, and practical needs for environmental restoration, the study area was further regionalized into four priority areas which may serve as base areas of decision making for the recovery, rebuilding, and protection of the environment.     

Exploring the Relationship Between Hydrologic Parameters and Nutrient Loads Using Digital Elevation Model and GIS – A Case Study from Sugarcreek Headwaters, Ohio, U.S.A.

Ohio is typical among the Midwestern and Eastern United States with high levels of water pollutants, the main sources being from agriculture. In this study, we used a digital elevation model in conjunction with hydrological indices to determine the role of landscape complexity affecting the spatial and temporal variation in pollutant levels, in one of the most impaired headwater streams in Ohio. More than eighty five percent of the study area is dominated by agriculture. Spatial distribution of slope (S), altitude and wetness index along with other watershed parameters such as flow direction, flow accumulation, stream networks, flow stream orders and erosion index were used within a Geographic Information Systems framework to quantify variation in nitrate and phosphate loads to headwater streams. Stream monitoring data for nutrient loads were used to correlate the observed spatial and temporal patterns with hydrological parameters using multiple linear regressions. Results from the wetness index calculated from a digital elevation model suggested a range of 0.10–16.39, with more than 35% having values less than 4.0. A Revised Universal Soil Loss Equation (RUSLE) predicted soil loss in the range of 0.01–4.0 t/ha/yr. Nitrate nitrogen levels in the study area paralleled precipitation patterns over time, with higher nitrate levels corresponding to high precipitation. Atmospheric deposition through precipitation could explain approximately 35% of total nitrate levels observed in streams. Among the different topographic variables and hydrological indices, results from the step-wise multiple regression suggested the following best predictors, (1) elevation range and upstream flow length for nitrate, (2) flow direction and upstream flow length for ammonia-nitrogen and slope, and (3) elevation range for phosphate levels. Differences in the landscape models observed for nitrate, phosphate and ammonia-nitrogen in the surface waters were attributed partly to differences in the chemical activity and source strengths of the different forms of these nutrients through agricultural management practices. The results identify geomorphologic and landscape characteristics that influence pollutant levels in the study area.     

Effect of land use land cover change on soil erosion potential in an agricultural watershed

Universal soil loss equation (USLE) was used in conjunction with a geographic information system to determine the influence of land use and land cover change (LUCC) on soil erosion potential of a reservoir catchment during the period 1989 to 2004. Results showed that the mean soil erosion potential of the watershed was increased slightly from 12.11 t ha^???1 year^???1 in the year 1989 to 13.21 t ha^???1 year^???1 in the year 2004. Spatial analysis revealed that the disappearance of forest patches from relatively flat areas, increased in wasteland in steep slope, and intensification of cultivation practice in relatively more erosion-prone soil were the main factors contributing toward the increased soil erosion potential of the watershed during the study period. Results indicated that transition of other land use land cover (LUC) categories to cropland was the most detrimental to watershed in terms of soil loss while forest acted as the most effective barrier to soil loss. A p value of 0.5503 obtained for two-tailed paired t test between the mean erosion potential of microwatersheds in 1989 and 2004 also indicated towards a moderate change in soil erosion potential of the watershed over the studied period. This study revealed that the spatial location of LUC parcels with respect to terrain and associated soil properties should be an important consideration in soil erosion assessment process.