Using Universal Soil Loss Equation Research Articles

The Study of Erosion on Varoious Land Use in Paluh Besar Sub Watershed Using Geographic Information System

Erosion could be a sign of natural resources damage. It’s important to prevent the erosion that had to predict in each land cover to sustainability of natural resources. This study aimed to predict the erosion value in each land cover unit using Universal Soil Loss Equation (USLE) Method with Geographic Information System. The study showed that the highest erosion occurs in residential area which valued 138.11 ton/ha/year and the lowest occur in pond that valued 0.3 ton/ha/year. The highest erosion hazard level occur in residential area that classify moderate (III) and the lowest erosion hazard level is pond that classify low hazard level (I).

Towards multi-model soil erosion modelling: An evaluation of the erosion potential method (EPM) for global soil erosion assessments

Soil erosion is expected to increase in the future due to climate change. Soil erosion models are useful tools that can be used by decision makers and other stakeholders to deal with soil erosion problems or the implementation of soil protection measures. Most of the modelling applications are using Universal Soil Loss Equation (USLE)-type models. In this study, we evaluate the applicability of the Erosion Potential Model (EPM) and its modified version (mEPM) for the estimation of the gross and net erosion rates at a global scale. The sensitivity analysis shows that the model results have the highest variability due to the soil protection (land cover) coefficient followed by the soil erodibility parameter. The models’ evaluations indicate that that the EPM cannot be applied to cold regions while the mEPM overcomes this issue. The erosion rates based on the EPM were 1.5–2.5 times larger than the ones obtained from the mEPM. Increasing the number of catchment properties as inputs to the model may help in improving the performance of the tested EPM and mEPM. Moreover, a comparison of net soil losses by mEPM with long-term suspended sediment yield data for 116 catchments located around the globe indicates a median bias of less than 10%, although the bias for around 1/3 of catchments was above 100%. Furthermore, a direct comparison with other soil erosion models such as USLE-type models is not possible since the EPM and mEPM do take into consideration other processes such as soil slumps and gully erosion and not just sheet and rill erosion. Therefore, as expected, the gross erosion rates by the EPM and mEPM are higher compared to the USLE-type models. Hence, the mEPM, despite its limitations, could be regarded as an interesting approach for the describing erosion processes around the globe and should be further tested using small- and medium-sized catchments from various climate zones.

Rainfall erosivity estimation models for the Tibetan Plateau

Many models have been developed internationally to estimate rainfall erosivity. However, the effectiveness of these pre-existing models has not been verified for the Tibetan Plateau with large spatiotemporal heterogeneity of rainfall due to lack of high-temporal resolution rainfall data. The purpose of this study was to develop models to accurately estimate daily and semi-monthly rainfall erosivity values in the Tibetan Plateau. We used one-minute resolution rainfall data from 1,182 weather stations to develop rainfall erosivity models over the Tibetan Plateau for the first time. The particle swarm optimization (PSO) method was performed to determine the newly developed model parameters. The newly developed models were compared with three internationally common existing models (exponentially seasonal1Exponentially seasonal model denoted Richardson model (1983) that was revised as R =αP1.7265 by Xie et al. (2016).1, cosine2Cosine model denoted Yu and Rosewell model (1996) that was revised as R=0.26861+0.5412cosπ6M-7π6P1.7265 by Xie et al. (2016).2, and exponentially semi-month3Exponentially semi-month model denoted Zhang model (2002) that was expressed as R=α∑j=1mPjβ,α= 21.586β- 7.1891 and β=0.8363+18.177Pd12+24.455Py12.3) to evaluate their effectiveness. Our results showed that (1) the three existing models all overestimated the values of mean annual rainfall erosivity in the Tibetan Plateau because limited rainfall data in the area were used to develop these models; (2) the new models greatly reduced computational error values of mean annual rainfall erosivity (the symmetric mean absolute percentage error (SMAPE) of ≤ 23%), relative to the three existing models (SMAPE of ≥ 40%); (3) the new semi-monthly models (SMAPE of 17.7 – 29.2%) generally outperformed the new daily models (SMAPE of 17.9 – 30.7%) because of their better ability to estimate the values of extreme rainfall erosivity. It is advisable to use the semi-monthly model rather than daily model to compute rainfall erosivity when using universal soil loss equation (USLE) and its derived models to calculate soil erosion. That will benefit to reduce the time-scale conversion errors between event-based and daily data when lacking high-temporal resolution data and using daily rainfall data to analyze the influence of rainfall on soil erosion.

Impacts of soil conservation techniques on soil erodibility on an Alfisol

Soil erosion is a serious challenge for sustainable crop production. Alfisols in Nigeria are easily prone to soil degradations which have significantly reduced soil productivity, crop yield and increased cost of production. The use of soil conservation measures are vital interventions for sustainable crop production against the effects of erosion. The impacts of soil conservation on erodibility of an Alfisol was investigated in a tropical alfisol in Southwestern Nigeria. The study utilized four-soil conservation measures - Irvingia wombulu, Irvingia garbonensis, paddock and Cynodon plectostachyus was established on 20.4 ha land for 25 years, and replicated thrice based on land area. Empirical soil erodibility factor using Universal Soil Loss Equation (USLE) and Water Erosion Prediction Project (WEPP) erodibility factor models was determined. Analysis of variance analysis was done using R statistics to ascertain response patterns of the soil conservation measures to erodibility. Correlation was conducted for the conformity and relationship between erodibility models and soil properties. I. garbonensis soil conservation measure gave the least erodibility factor (K = 0.07), among paddock (K = 0.09), I. wombulu (K = 0.11) and C. plectostachyus with the highest erodibility factor (K = 0.17), indicating that I. garbonensis has the highest potential for soil conservation. Soil conservation measures significantly (p ≤ 0.05) influenced soil properties. Wischmeier and Mannering's USLE erodibility and WEPP's rill and inter-rill erodibility were not significantly (p ≥ 0.05) different across the soil conservation measures. Elswaify and Dangler's USLE erodibility correlated best with Wischmeier and Mannering USLE erodibility (r = 1.00) and WEPP's rill (r = 0.8) and inter-rill (r = 0.8) erodibility. Sand, silt, organic carbon, available phosphorus and aggregate stability significantly (p ≤ 0.05) correlated with USLE erodibility factor. Elswaify and Dangler USLE erodibility gave higher precision in erodibility determination of the soils. I. garbonensis was more efficient in reducing soil erosion, indicating that it is the best soil conservation measure for sustainable agriculture in alfisols in the tropics.

Estimation of slope length gradient (LS) factor for the sub-watershed areas of Juri River in Tripura

The slope length gradient (LS) factor expresses the effect of topography, i.e., combining effects of slope length (L) and slope steepness (S) on rate of soil erosion. The longer the slope length, greater is the amount of cumulative runoff and similarly steeper the slope of the land the higher is the velocities of the runoff that contributes erosion. The LS factor is the most important parameter for estimation of soil loss and soil management using Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE). A precise inventory and assessment of vulnerable areas includes the formulation of correct soil management for property development. Juri is a peri-urban watershed situated in Tripura, India, having high undulating topography, which leads to increase soil erosion and land slide problem. Therefore, it has become essential to quantify the LS factor to understand the characteristics of the topographic factor, which will help the researchers for estimation of soil erosion and preparation of management plan. The present study focused to evaluate the LS factor for the sub-watershed areas of Juri River of Tripura. Two methods namely (1) suggested by Moore and Burch (1986) and (2) proposed by Wischmeier and Smith (1978) were used to calculate the LS factor. Both the methods use Digital Elevation Model (DEM) in spatial domain to estimate the LS factor. The LS factor of the study area ranges from 0 to 982.71 by method-1 and 0.66 to 285.58 by method-2. The study indicates that, the method-2 is more apposite than method-1 because it gives LS factor value, which distributed uniformly in spatial domain; whereas method-1 resulted highest LS factor value along the flow direction and it had almost same value of LS factor in the remaining areas. This study will help for prediction of soil erosion and preparation of management plan by reducing the slope length of the study area. This findings and the methodology employed can be widely used in similar mountainous to hilly watersheds around the world for calculation of soil loss.

Susceptibility to Soil Erosion and Risk Assessment at Hilly Farms Using Geospatial Techniques

Soil erosion is a serious environmental challenge which persistently diminishes available land resources globally.The impact of soil erosion is more severeat hilly regions where various techniques are deployed to evaluateits risk levels. However, the traditional approach of estimating the magnitude of erosion is tedious, costly, and considerably time consuming. This study was intended to assess the risk associated with soil erosion at hilly areas of Cameron Highlands through geospatial means. The Digital Elevation Model (DEM) with 5m resolution from Interferometric Synthetic Aperture Radar (IfSAR) was utilized to generate the slope inthe highlands. Soil erosion rates was estimated using Universal Soil Loss Equation (USLE), while information about land use and cover were sourced from relevant government agencies. Inversed Distance Weighted (IDW) method of spatial interpolation was applied to predict the values of unknown pixels. The analysis shows that, there is 217.5 km2of the highlands which is greater than 45-degreeaccounted for about 30.5% of the total land area. Moreover, erosion risk assessment indicated that 66.3%, 11.4%, 11.7% and 10.8% are respectively classified as very low, law, moderate and high susceptible to soil erosion. In general, the risk of soil erosion is relatively low and could be attributed to den sevegetation coverage within the study watershed despite the steep slopes where it was found to be at very high risk to soil erosion susceptibility. However, there is need to deploy best management practices to reduce the effect of soil disturbances at hilly areas and prevent excessive soil loss in future.

Estimation of sediment yield based on correlation between potential land erosion using Universal Soil Loss Equation (USLE) and actual sediment load using Schaffernak Method in Situ Gintung Dam

Sediment yield is eroded soil that transported from a place to a measurement point, for example in a reservoir. Sediment in the reservoir is a problem that can reduce the performance of the reservoir, so it needs to be assess regularly. One of many ways to assess is to calculate the potential of sediment that enters the reservoir. The research objective is to calculate the potential of sediment that enters the reservoir at Situ Gintung Dam using two methods, the Universal Soil Loss Equation (USLE) and Schaffernak methods. The USLE method calculate sediment that comes from land erosion of a watershed, but the potential land erosion that occurred is not necessarily create actual sediment load at the river bed so it needs to be correlated with the results of the actual sediment load. The actual sediment load can be calculated using Schaffernak method. The results of that obtain from each method will analysed to confirm the representativeness of the potential land erosion in Situ Gintung Dam. Percent of potential land erosion that transform into the sediment in the water body can be calculated by the value of Schaffernack method.

GIS Based Universal Soil Erosion Estimation in District Chakwal Punjab, Pakistan

Soil erosion is a serious environmental problem faced by district Chakwal. Unpredictable short term and high intensity rainfall, improper cultivation and deforestation have accelerated the soil erosion in the district. The agricultural productivity of the study area can be enhanced by understanding, estimating and controlling the root causes of soil erosion. This study was undertaken to estimate and spatially represent the rate of average annual soil erosion in Chakwal using GIS/RS techniques. The soil erosion was estimated using Universal Soil Loss Equation (USLE) model. To find out parameters of USLE, ASTER GDEM of 30 m resolution was used to estimate slope length and elevation of the study area. Landsat 8 satellite imagery of year 2019, was used to prepare land use map using supervised classification. Soil map with texture and geomorphology was used to identify soils of study area and rainfall data of last 7 years was also studied. Finally, the soil loss has been computed using raster calculator of ArcGIS 10.2 software. The average annual soil loss was predicted up to 268,619 tons/acre/year, of which maximum soil erosion was occurring near the steep slopes and river channels. It is necessary to adapt sustainable land management practices to reduce the risk of further soil erosion, by adopting rainwater harvesting and choosing right crops for suitable soil types.

Estimation of Soil Loss from Watershed for Identifying High Risk Erosion Zones Using GIS

Soil loss from watersheds significantly influences the fertility soils and natural environment and hence it is a serious concern across the globe. Soil conservation is the top priority in watershed management though it is impractical to completely control soil erosion from all parts of watershed and hence achieve soil conservation. As controlling soil erosion in watersheds at micro level is difficult, broad measures which are economical and feasible are recommended for soil conservation. In order to plan suitable conservation techniques, it is essential to prioritize watersheds based on vulnerability to soil erosion. For identifying suitable soil conservation methods, it is necessary to consider critical erosion zones, threats to lives and property, socio-economic constraints and local challenges. Assessment of soil erosion is very important for arriving at the prioritization of watersheds for soil conservation. This paper reports the findings of the study carried out on Janagoan Mandal in Warangal District with hell of GIS techniques. Estimation of soil loss from the watershed is estimated using Universal Soil Loss Equation (USLE). Using the data available with various agencies, average annual erosion is estimated by developing GIS maps for six major watershed parameters. The watershed has been divided into sub watersheds and prioritization study is carried out considering factors that influence soil erosion. Using GIS tool and Universal Soil Loss Equation (USLE), the soil loss from the watershed is estimated and high risk zones are demarked. Soil loss from 80% of the watershed area is in the range of 0 - 200 tons/ha/year, while the high risk zones of erosion are about 12% of the area. Watershed management practices are recommended to reduce the soil loss from the high risk zones.

Identification of critical erosion prone areas in Temengor Reservoir Basin using Universal Soil Loss Equation (USLE) and Geographic Information System (GIS)

In this study, the Geographic Information System (GIS) was integrated with the Universal Soil Loss Equation (USLE) model to identify the risk of erosion at 360,000 ha in the Temengor Reservoir Basin. GIS was utilized as a tool for generating, manipulating and spatializing data from government agencies for sediment yield modelling and offering spatial input data to the erosion model. Meanwhile, USLE was used to predict the spatial distribution of the sediment yield on the grid basis. The five main parameters used in this study were the rainfall erosivity factor (R), topographic factor (LS), soil erodibility factor (K), crop management factor (C) and practice support factor (P). The R factor was calculated based on the annual rainfall data of the study area. The soil survey data was used to generate the K value and Digital Improvement Model (DEM) of the study area was used to generate LS factor. The values of C and P factors were derived from the land use map. After generating all parameters, analysis was performed to estimate the soil erosion using USLE model with spatial information analysis approach. It was discovered that the average annual soil loss in the study area was 8 t ha-1 year-1 and only 4% of the total area was under extreme erosion risk.

ANALISIS KEKRITISAN LAHAN UNTUK PERENCANAAN REHABILITASI LAHAN DAS SOLO BAGIAN HULU (Analyses of degraded land for rehabilitation planning in upper Solo Watershed)

Water erosion is one of the causes of degraded land and a decrease in land productivity. Improvement of degraded land needs to detect sources of erosion and vulnerability level of the degraded land. The research was conducted to predict the vulnerability of soil erosion and distribution of degraded land in order to support the implementation programme of Land Rehabilitation and Soil Conservation. The research was conducted in upper Solo Watershed. Soil erosion was predicted using Universal Soil Loss Equation (USLE). The analysis of Land Capability Class was undertaken to determine the suitability of current landuse with its capability. Analysis of critical land was based on the regulations of the Directorate General of Watershed Management and Social Forestry (BPDAS-PS) Nomor 4/V-SET/2013. The data used were DEM (Digital Elevation Model) Aster (30 m x 30 m), map of the Regional Physical Planning Program for Transmigration (RePPProT) scale 1: 250,000, map of forest area (1: 50,000) from BPKH (Forest Zone Determination Center), land cover map from BPKH (1: 50,000), Google Earth imagery, rainfall data from 93 rain stations and field surveys. The results show that the upper Solo Watershed is dominated by land categorized as potentially degraded (54%), followed by slightly degraded (35%), while land which is classified as degraded occupied 7% of the total watershed. The dominant land capability is categorized as V th class and limited by soil erosion (89%). Dry land agriculture areas were found at land capability VI th and VII th which should not utilized for agricultural activities. Implementation of agroforestry and teracing are alternatives to prevent further land degradation and to improve the current condition.

Reservoir Sedimentation Volume Changing Analysis of Pangsar Soedirman Dam Through USLE Based Rainfall Characteristics

Penelitian ini dimaksudkan untuk menganalisis pengaruh karakteristik curah hujan di daerah tangkapan air Waduk Pangsar Sudirman terhadap peningkatan sedimentasi Waduk. Penelitian dilakukan menggunakan formula USLE dengan faktor curah hujan (erosivitas) di DTA Waduk Pangsar Soedirman sebagai penentu. Data laju sedimentasi waduk tahun 1989-2010 digunakan sebagai verifikasi hasil analisis. Hasil penelitian menunjukkan DTA Waduk Pangsar Soedirman memiliki curah hujan tahunan rata-rata sebesar 3.900 mm/tahun. Karakteristik curah hujan ini menyebabkan potensi kejadian erosi dan sedimentasi cukup besar. Volume sedimen di Waduk Pangsar Soedirman sejak tahun 1989 hingga 2010, mencapai 92,77 juta m3 atau sekitar 60 % dari volume dead storage dengan volume inflow rata-rata sedimen mencapai 4,2 juta m3/tahun.

GIS Based Assessment of Soil Erosion Using Universal Soil Loss Equation (USLE) in Wular Catchment of Kashmir

The Universal Soil Loss Equation (USLE) has been assessed in the present study using Remote Sensing and GIS in order to estimate the potential Soil Loss at watershed level in Wular Catchment. Wular Catchment has an area of 1200.36 km 2 and lies between 34 o 12′24″ and 34 o 36′26″ N latitude and 74 o 26′41″ and 74 o 56′02″E longitude. Its altitudinal range is from 1580 meters near Wular Lake to about 4500 meters in Harmukh range. Maps of the R, K, LS, C and P factors were derived from the precipitation data, soil map, digital elevation model (DEM), land use and field survey respectively. It emerges from the study that about 6% of the area has severe erosion with a soil loss more than 900 t ha −1 yr −1 . The watersheds of 1EE2a, 1EM2a and 1EE1c have the highest percentage share of 19.91%, 17.30% and 14.88% respectively under severe erosion. This is the most susceptible zone to soil erosion primarily due to very steep slope gradient and slope length. The study clearly demonstrates the importance of vegetation cover for watershed management. The Study has proposed soil and water conservation measures in accordance with the spatial distribution of soil loss in the Catchment. Keywords: USLE; Soil Loss; Wular Catchment; Soil Erosion; Rainfall; Erosivity Cite this Article Zahoor-ul-Hassan, M. Imran Malik, T.A. Kanth. GIS Based Assessment of Soil Erosion Using Universal Soil Loss Equation (USLE) in Wular Catchment of Kashmir. Journal of Remote Sensing & GIS . 2017; 8(3): 56–66p.

GIS environmental information analysis of the Darro River basin as the key for the management and hydrological forest restoration

This article presents analyses of soil and environmental information for the Darro River basin (Granada-Spain) preliminary to its hydrological and forestry restoration. These analyses were carried out using a geographical information system (GIS) and employing a new procedure that adapts hydrological forest-restoration methods. The complete analysis encompasses morphological conditions, soil and climate characteristics as well as vegetation and land use. The study investigates soil erosion in the basin by using Universal Soil Loss Equation (USLE) and by mapping erosion fragility units. The results are presented in a set of maps and their analysis, providing the starting point for river basin management and the hydrological and forestry-restoration project that was approved at the end of 2015. The presence of soft substrates (e.g. gravel and sand) indicates that the area is susceptible to erosion, particularly the areas that are dominated by human activity and have little soil protection. Finally, land use and vegetation cover were identified as key factors in the soil erosion in the basin. According to the results, river authorities have included several measures in the restoration project aimed at reducing the erosion and helping to recover the environmental value of this river basin and to include it in recreation possibilities for the community of Granada. The presented analytical approach, designed by the authors, would be useful as a tool for environmental restoration in other small Mediterranean river basins.

Assessing soil erosion using USLE model and MODIS data in the Guangdong, China

In this study, soil erosion in the Guangdong, China during 2012 was quantitatively assessed using Universal Soil Loss Equation (USLE). The parameters of the model were calculated using GIS and MODIS data. The spatial distribution of the average annual soil loss on grid basis was mapped. The estimated average annual soil erosion in Guangdong in 2012 is about 2294.47t/ (km2.a). Four high sensitive area of soil erosion in Guangdong in 2012 was found. The key factors of these four high sensitive areas of soil erosion were significantly contributed to the land cover types, rainfall and Economic development and human activities.

Spatial assessment of soil erosion in Alqerdaha basin (Syria)

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.

Soil Loss Prediction on Mobile Platform Using Universal Soil-Loss Equation (USLE) Model

Indirect method for soil loss predictions are plentiful, one of which is Universal soil-loss equation (USLE) model. Available technology in mobile applications prompted the authors to develop a tool for calculating soil loss for many land types by transforming the USLE model into smart mobile application. The application is designed by using simple language for calculating each and every factor and lastly summing up the results. Factors that are involved in the calculation of soil loss are namely erosivity, erodibility, slope steepness, length of slope, land cover and conservation measures. The program will also be able to give its judgment for each of the prediction of soil loss rates for each and every possible land uses ranging from very light to very heavy. The application is believed to be useful for land users, students, farmers, planners, companies and government officers. It is shown by conducting usability testing using usability model, which is designed for mobile application. The results showed from 120 respondents that the usability of the system in this study was in “very good” classification, for three characteristics (ease of use, user satisfaction, and learnability). Only attractiveness characteristic that falls into “good” classification.

Estimation of Soil Loss in Three Agro-climatic Zones of Belagavi District, Karnataka Using USLE and GIS

Estimating soil loss using Universal Soil Loss Equation (ULSE) and geographical information system (GIS) was attempted in three agro-climatic zones of Belagavi district in north Karnataka. The study area included one micro-watershed in each agro-climatic zone viz., Yadawad in northern dry zone (zone 3), Hukkeri in northern transitional zone (zone 8) and Khanapur in hilly zone (zone 9). Slope gradient map was prepared from SRTM-DEM and the R, K and LS factors in USLE were determined from the established equations. Information on conservation was obtained from field survey. Using a grid-based approach, soil loss map was prepared in GIS environment. The predicted soil loss varied among the agro-climatic zones. The soil loss was very low to low (< 10 t ha−1) in the entire Yadawad micro-watershed area, whereas, it was moderately high to high (15–40 t ha−1) in 32% of Hukkeri and 19% of Khanapur micro-watersheds due to slope and land use characteristics. Despite heavy rainfall in Khanapur watershed, the soil loss risk was more for Hukkeri watershed suggesting that factors other than rainfall played an important role in rendering the soil loss.

Identification of Critical Erosion Prone Areas using Remote Sensing and GIS: A Case Study of Sarada River Basin

Background/Objectives: Developed an integrated soil erosion model utilizing RS and GIS approach and mapped for prioritization of critical soil erosion prone areas in a watershed. Methods/Statistical Analysis: The geomorphologic parameters of the watershed have been extracted using Arc-GIS software. In order to evaluate effectively for the soil erosion prone areas, the selected basin has been divided into 143 micro-watershed basins. The micro basins were analyzed using Universal Soil Loss Equation (USLE) soil loss based on annual basis has been assessed for the entire basin. Findings: The soil erosion estimation in a river basin has significant impact on reduction of the reservoir capacities on downstream side if they are situated at the downstream side. In the present study, the soil erosion has been estimated and identified for soil erosion based on their classification. Accordingly, the selected basin has five main categories of soil loss varying from 5 ton per ha per year to more than 80 ton per ha per year. The results obtained based on the present findings, it can be inferred that the Sarada basin has 12.12% area is prone for soil loss of more than 80 ton per ha per year which is under very severe erosion class, 40-80 ton per ha per year under severe class, 11.95% under very high class and 3.10% under high class and 27.78% under moderate class apart from 36.37% under not affected areas for soil erosion. Remote Sensing (RS) technology and Geographic Information System (GIS) were utilized to create and spatially establish the data and maps were generated for soil erosion modeling in the selected region. Applications/Improvements: In the present study, soil erosion has been estimated and critical prone areas for soil loss in a watershed basin that have been generated using RS and GIS.

Soil Erosion Assessment of the Poyang Lake Basin, China: Using USLE, GIS and Remote Sensing

Soil erosion is one of the most critical eco-environmental issues in the Poyang Lake basin, China. The purpose of this study is to discover the spatial pattern of soil erosion, and predict soil loss and sediment yield, and evaluate soil loss impacts on main reservoirs by using Universal Soil Loss Equation (USLE), GIS and Remote Sensing (RS). Firstly, five erosion factors including rainfall erosivity (R), soil erodibility (K), topographic factor (LS), cover and management factor(C), and conservation supporting practice factor (P) were calculated and analyzed, respectively. Secondly, annual soil erosion and its spatial distribution were evaluated, and sediment yield was subsequently predicted. Next, soil erosion was classified into five erosion categories according to Industry Standard of Water Resources of China. Then, the relationship among soil erosion, landform and land use and land cover (LULC) were analyzed. Finally, the influence of soil erosion on main reservoirs in the basin were assessed. The result showed that: 28.3% of the total watershed area appears soil loss; the average annual soil loss amount is approximate 2.7 × 107 t; soil erosion modulus ranged from 0 to 394.8 t/ha/y, with a mean value of 1.82 t/ha/y. 71.7% of the watershed area are undergoing minimal erosion, primarily appear in surrounding the lake area, both sides of river valley and plains of five main rivers; 24.1% of the watershed area are undergoing low erosion, mainly found in the west, east, central hilly and mountain areas; 3.4% of the watershed area was observed moderate soil erosion; 0.83% of the watershed area are undergoing high, very high and extreme soil erosion, which located in the northeastern and northwestern corner, and the upstream of the Ganjiang river and Fuhe river sub-watershed. Low and moderate soil erosion most frequently occurred at the plains and hills zone in this basin. Soil loss happens on needleleaved forest, rainfed croplands and shrub land use type are greater than that of other LULC types; soil erosion modulus descends on the different land use types, orderly by bare lands, grass lands, shrub lands, rainfed croplands, needleleaved forest, spares vegetation, broadleaved deciduous forest, artificial surface, irrigated croplands and water bodies. Present main reservoirs are undergoing a big threat from the upstream sediment load, especially as the Qiyi, Da’ao, Qixing and Tuolin reservoir.