Soil Erosion Research Methods

Erosion by water on agricultural areas has been studied by USDA (SCS, ARS, FS, NRCS) since the 1930‘s, initially consisting of natural runoff plots at numerous locations in the country that provided data that culminated in the development of the Universal Soil Loss Equation (USLE) in 1965 in Agriculture Handbook 282 (Wischmeier and Smith, 1965). Rainfall simulation equipment developed by ARS scientists located at Purdue University during the early 1960‘s was used to supplement the natural rainfall plot data and provided the ability to rapidly study soil erosion processes in more controlled laboratory and field experiments. The USLE update in Agriculture Handbook 537 (Wischmeier and Smith, 1978) contained a soil erodibility nomograph, developed from the results of extensive field rainfall simulation studies across the Midwest U.S. Transitions to process-based soil erosion modeling approaches in the 1980‘s-1990‘s relied upon laboratory and field rainfall simulation experiments to study processes and develop parameterization approaches for sensitive model input parameters. The Water Erosion Prediction Project (WEPP) model solves differential equations down a slope profile, that compute changes in sediment load and detachment/deposition at discrete points (Flanagan and Nearing, 1995; Flanagan et al., 2001). Unfortunately, most data available for validation of process-based hillslope interrill/rill erosion is from natural runoff plots (USLE database) or other natural or simulated rainfall studies where soil (sediment) loss was only measured at the plot end. Newer experimental measurement techniques, equipment, and approaches are needed to allow examination of changes in sediment detachment/deposition/loads with very fine spatial resolution down a hillslope and down a rill channel. The current modeling techniques also assume either uniformly spaced rill channels down a slope profile (default is 1-m spacing), or alternately simulations can be conducted where all surface flow is assumed to be distributed at a uniform shallow depth across the entire flow width. However, in real world situations the soil conditions, landscape complexities and increases in slope lengths can result in situations where no evident rilling occurs, rill spacings change with increasing slope lengths, or surface flows converge or diverge which may result in channelized rill flows changing to broader sheet flows. These complex surface flow situations need to be accounted for in any new water erosion prediction technologies, as they can greatly affect soil detachment and deposition processes. Additionally, subsurface hydrology effects also need to be better accounted for in any new technologies. Current erosion prediction models poorly account for water moving within the soil, and how saturation conditions can weaken the soil surface and make it more susceptible to detachment. A comprehensive understanding of how subsurface water moves and can converge in fields (and may emerge to the surface) is needed in new modeling approaches that can also be linked to initiation and development of ephemeral gullies. Additionally, better understanding and modeling of the effects of subsurface drainage and controlled drainage systems on hydrology and soil erosion is required. This also highlights the needs to move to erosion prediction systems that truly represent the landscape and fields as 2-D/3-D surfaces. Current prediction technologies are largely limited to estimating soil erosion processes at points down a line to represent a rectangular area. Long-term temporal effects of various practices on soil health and soil hydrology and erosion also should be accounted for in new erosion models. Currently, baseline soil erodibility is assumed to be a constant value for a particular soil and cropping system as a function of soil texture, organic matter, and other properties. However, fields that are in long-term pasture, or long-term no-till row crop management systems along with the use of cover crops may substantially change soil organic matter, soil structure, infiltration characteristics, and erodibilities that are not currently reflected in USDA models. This presentation will explore these and other areas of research needed.

Erosion by water on agricultural areas has been studied by USDA (SCS, ARS, FS, NRCS) since the 1930‘s, initially consisting of natural runoff plots at numerous locations in the country that provided data that culminated in the development of the Universal Soil Loss Equation (USLE) in 1965 in Agriculture Handbook 282 (Wischmeier and Smith, 1965). Rainfall simulation equipment developed by ARS scientists located at Purdue University during the early 1960‘s was used to supplement the natural rainfall plot data and provided the ability to rapidly study soil erosion processes in more controlled laboratory and field experiments. The USLE update in Agriculture Handbook 537 (Wischmeier and Smith, 1978) contained a soil erodibility nomograph, developed from the results of extensive field rainfall simulation studies across the Midwest U.S. Transitions to process-based soil erosion modeling approaches in the 1980‘s-1990‘s relied upon laboratory and field rainfall simulation experiments to study processes and develop parameterization approaches for sensitive model input parameters. The Water Erosion Prediction Project (WEPP) model solves differential equations down a slope profile, that compute changes in sediment load and detachment/deposition at discrete points (Flanagan and Nearing, 1995; Flanagan et al., 2001). Unfortunately, most data available for validation of process-based hillslope interrill/rill erosion is from natural runoff plots (USLE database) or other natural or simulated rainfall studies where soil (sediment) loss was only measured at the plot end. Newer experimental measurement techniques, equipment, and approaches are needed to allow examination of changes in sediment detachment/deposition/loads with very fine spatial resolution down a hillslope and down a rill channel. The current modeling techniques also assume either uniformly spaced rill channels down a slope profile (default is 1-m spacing), or alternately simulations can be conducted where all surface flow is assumed to be distributed at a uniform shallow depth across the entire flow width. However, in real world situations the soil conditions, landscape complexities and increases in slope lengths can result in situations where no evident rilling occurs, rill spacings change with increasing slope lengths, or surface flows converge or diverge which may result in channelized rill flows changing to broader sheet flows. These complex surface flow situations need to be accounted for in any new water erosion prediction technologies, as they can greatly affect soil detachment and deposition processes. Additionally, subsurface hydrology effects also need to be better accounted for in any new technologies. Current erosion prediction models poorly account for water moving within the soil, and how saturation conditions can weaken the soil surface and make it more susceptible to detachment. A comprehensive understanding of how subsurface water moves and can converge in fields (and may emerge to the surface) is needed in new modeling approaches that can also be linked to initiation and development of ephemeral gullies. Additionally, better understanding and modeling of the effects of subsurface drainage and controlled drainage systems on hydrology and soil erosion is required. This also highlights the needs to move to erosion prediction systems that truly represent the landscape and fields as 2-D/3-D surfaces. Current prediction technologies are largely limited to estimating soil erosion processes at points down a line to represent a rectangular area. Long-term temporal effects of various practices on soil health and soil hydrology and erosion also should be accounted for in new erosion models. Currently, baseline soil erodibility is assumed to be a constant value for a particular soil and cropping system as a function of soil texture, organic matter, and other properties. However, fields that are in long-term pasture, or long-term no-till row crop management systems along with the use of cover crops may substantially change soil organic matter, soil structure, infiltration characteristics, and erodibilities that are not currently reflected in USDA models. This presentation will explore these and other areas of research needed.

1.1 Plot-scale experimental studies: structure, equipment, hydrologic monitoring Plot-scale experimental studies are generally part of broader research projects aimed at improving the understanding of interrelations between processes involving hydrological, climatic and biological factors (Wainwright et al., 2000). Recently, these studies have become multidisciplinary, integrating fields such as hydrology, ecology and geomorphology. In a global environmental change and degradation context, plot-scale studies may provide information about runoff mechanisms, soil erosion and vegetation dynamics processes that result from these changes (Abrahams et al., 1995; Parsons et al., 1996). Furthermore, plotscale studies may focus on water fluxes and sediment transport processes at controlled conditions using rainfall simulation (Wainwright et al., 2000; Rickson, 2001). It is important to note that process control generally involves simplifying a complex system that is highly variable in time and space (Wainwright et al., 2000; Abrahams et al., 1998; Parsons et al., 1998). However, plot-scale studies have the advantage of allowing for detailed process monitoring at small scale, providing a basic description of the most relevant aspects (Michaelides et al., 2009). Plot-scale studies are also useful in providing experimental data involving rainfall, surface runoff and soil erosion. These data are used as reference in modeling conception, calibration and validation. However, there can be considerable variability in soil erosion processes, as well as limitations of models atempting to simulate these complexities (Nearing, 2004). For example, in a study using 40 cultivated plots in the United States the experimental data coefficient of variation ranged between 18-91%. In addition, this variation was found to decrease with increasing rainfall erosive power (Wendt et al., 1986). Ruttimann et al. (1995) found that soil loss varied up to 173% between replicates under the same treatment. In general, the capacity of the model in representing local physical system can be tested by comparing observed and simulated model data, using regression analysis. Regression coefficient values from several studies demonstrate that model efficiency increases as erosion variability decreases, such as when mean annual soil loss data are used (Nearing, 1998; Risse et al., 1993; Zhang et al., 1996). The USLE-Universal Soil Loss Erosion (Wischmeyer & Smith, 1978) soil erosion model was originally conceived by using statistical

Physically based soil erosion and sediment yield models revisited

چکیده تغییر غیر اصولی کاربری اراضی به ویژه اکوسیستم های طبیعی، عموما تأثیر قابل توجهی را بر ویژگیهای فیزیکی، شیمیایی و بیولوژیکی خاکها و در پی آن میزان روان آب و فرسایش خاک می گذارد. بررسی تغییرات روان آب و فرسایش خاک در پی تغییر خصوصیات خاک و شناخت متغیرهای مؤثر خاک بر وقوع آن می تواند در بهبود توصیه های مدیریتی و کمی نمودن تغییرات روان آب و فرسایش خاک مفید واقع شود. لذا این پژوهش به منظور بررسی روان آب و فرسایش خاک در خاک های تحت پوشش اراضی جنگلی و مقایسه آن با اراضی زراعی و باغ که منتج از تغییر کاربری جنگل بوده و همچنین شناسایی فاکتورهای مؤثر در روان آب و فرسایش خاک از بین متغیرهای کمی خاک در محدوده شهرستان ساری صورت گرفته است. سپس در هر یک از کاربری ها، مبادرت به اندازه گیری میزان روان آب و فرسایش خاک طی انجام شبیه سازی باران با شدت ثابت 2 میلی متر بر دقیقه، مدت زمان 15 دقیقه و نمونه برداری خاک در 15 تکرار شد. نتایج حاصله نشان داد که بیشترین و کمترین میزان روان آب به ترتیب در کاربری جنگل و باغ ایجاد شده است. همچنین مقدار فرسایش خاک در اراضی زراعی و باغ به ترتیب 76/1 و 36/1 برابر کاربری جنگل اندازه گیری شد. طبق نتایج ماتریس همبستگی درصد سیلت، رطوبت قبلی و وزن مخصوص ظاهری خاک دارای همبستگی معنی دار مثبت و درصد شن و ماده آلی دارای همبستگی معنی دار منفی با میزان روان آب می باشند. همچنین متغیرهای رس، شن و ماده آلی خاک به صورت ارتباط منفی و درصد سیلت و رطوبت قبلی خاک دارای همبستگی معنی دار مثبت با میزان فرسایش شناخته شدند. واژه های کلیدی: باران ساز، تغییر کاربری، روان آب، فرسایش خاک

Abstract. Soil erosion in Alpine areas is mainly related to extreme topographic and weather conditions. Although different methods of assessing soil erosion exist, the knowledge of erosive forces of the snow cover needs more investigation in order to allow soil erosion modeling in areas where the snow lays on the ground for several months. This study aims to assess whether the RUSLE (Revised Universal Soil Loss Equation) empirical prediction model, which gives an estimation of water erosion in t ha yr−1 obtained from a combination of five factors (rainfall erosivity, soil erodibility, topography, soil cover, protection practices) can be applied to mountain areas by introducing a winter factor (W), which should account for the soil erosion occurring in winter time by the snow cover. The W factor is calculated from the ratio of Ceasium-137 (137Cs) to RUSLE erosion rates. Ceasium-137 is another possible way of assessing soil erosion rates in the field. In contrast to RUSLE, it not only provides water-induced erosion but integrates all erosion agents involved. Thus, we hypothesize that in mountain areas the difference between the two approaches is related to the soil erosion by snow. In this study we compared 137Cs-based measurement of soil redistribution and soil loss estimated with RUSLE in a mountain slope affected by avalanches, in order to assess the relative importance of winter erosion processes such as snow gliding and full-depth avalanches. Three subareas were considered: DS, avalanche defense structures, RA, release area, and TA, track area, characterized by different prevalent winter processes. The RUSLE estimates and the 137Cs redistribution gave significantly different results. The resulting ranges of W evidenced relevant differences in the role of winter erosion in the considered subareas, and the application of an avalanche simulation model corroborated these findings. Thus, the higher rates obtained with the 137Cs method confirmed the relevant role of winter soil erosion. Despite the limited sample size (11 points), the inclusion of a W factor in RUSLE seems promising for the improvement of soil erosion estimates in Alpine environments affected by snow movements.

Soil erosion is one of the most critical environmental hazards of recent times. It broadly affects to agricultural land and reservoir sedimentation and its consequences are very harmful. In agricultural land, soil erosion affects the fertility of soil and its composition, crop production, soil quality and land quality, yield and crop quality, infiltration rate and water holding capacity, organic matter and plant nutrient and groundwater regimes. In reservoir sedimentation process the consequences of soil erosion process are reduction of the reservoir capacity, life of reservoir, water supply, power generation etc. Based on these two aspects, an attempt has been made to the present study utilizing Revised Universal Soil Loss Equation (RUSLE) has been used in integration with remote sensing and GIS techniques to assess the spatial pattern of annual rate of soil erosion, average annual soil erosion rate and erosion prone areas in the MAN catchment. The RUSLE considers several factors such as rainfall, soil erodibility, slope length and steepness, land use and land cover and erosion control practice for soil erosion prediction. In the present study, it is found that average annual soil erosion rate for the MAN catchment is 13.01-tons/ha/year, which is higher than that of adopted and recommended values for the project. It has been found that 53% area of the MAN catchment has negligible soil erosion rate (less than 2-tons/ha/year). Its spatial distribution found on flat land of upper MAN catchment. It has been detected that 26% area of MAN catchment has moderate to extremely severe soil erosion rate (greater than 10-tons/ha/year). Its spatial distribution has been found on undulated topography of the middle MAN catchment. It is proposed to treat this area by catchment area treatment activity.

Scale effect in USLE and WEPP application for soil erosion computation from three Sicilian basins

Soil erosion by water is one of the most important land degradation processes in Mediterranean environments. This process is strongly linked to problems of flooding and channel management. This article reviews existing knowledge on these topics and defines research gaps. In the framework of environmental change studies it is important to consider soil erosion at various spatial and temporal scales. Most field measurements and modelling efforts have hitherto concentrated on water erosion processes operating at the runoff plot scale. Soil erosion processes operating at other spatial scales have received much less attention in the literature. Yet, there are indications that gully and channel erosion are probably the dominant sediment sources in a variety of Mediterranean environments. Beside water erosion, other erosion processes operating within catchments, such as tillage erosion, land reshaping for land preparation (e.g., terracing) or soil quarrying can have significant impacts on soil profile truncation. Land use changes strongly affect the intensity of these processes. The conditions, position and connectivity of the runoff and sediment generating areas within catchments have a profound effect on flood characteristics within the main channels but the dynamics are not well understood. Some research has taken place into meteorological conditions producing catastrophic flooding and into development of hydrological models using catchment variables. Much less is known of the properties and effects of flood waves within channels, partly because of lack of records of these infrequent events. It is not only water but also sediment which causes destruction in floods, yet sediment is frequently ignored in channel management. The extreme conditions associated with floods in the region, the variability of flows and of flood zones, the mobility of the channels and the high sediment loads create particular challenges for channel management. Trends in land use and channel management are tending to exacerbate these problems. From this review it can be concluded that there is still an important need for process-based understanding and modelling of key soil erosion processes operating at a range of scales: i.e., from plots over hillslopes, catchments to regions. In particular, more research is needed on the linkages between upland areas which produce large volumes of runoff and sediment and channels on the other hand. Such linkages are through gullies and sedimentation zones. Monitoring and experi mental data on key soil erosion and channel processes operating within Mediterranean landscapes are crucial for the improvement of soil erosion and channel models for a range of scales. In particular, long-term monitoring of soil erosion processes and stream channel changes seems to be essential to observe the effects of infrequent torrential rain events on severe erosion, flooding and stream channel changes as well as on the transient response of Mediterranean landscapes to changes in land use and climate. Systematic collation of historical evidence of changes would be valuable. Implications of land and water use need to be examined in detail. A wide range of alternative strategies and techniques of channel and basin management must be explored and modelled. A holistic approach to management of the fluvial system is recommended.

AimThe relationship between erosion and biodiversity is reciprocal. Soil organisms can both reduce soil loss, by improving porosity, and increase it, by diminishing soil stability as a result of their mixing activities. Simultaneously, soil runoff has ecological impacts on belowground communities. Despite clear research into interactions, soil erosion models do not consider biodiversity in their estimates and soil ecology has poorly investigated the effects of erosion. In order to start filling in these research gaps, we present a novel biological factor and introduce it into a well‐known soil erosion model (the revised universal soil loss equation). Furthermore, we propose insights to advance soil erosion ecology.LocationPan‐European.Time periodSimulation of present‐day conditions.Major taxa studiedEarthworms.MethodsWe present three pathways to fill in current knowledge gaps in soil biodiversity and erosion studies: (a) introducing a biological factor into soil erosion models; (b) developing plot‐scale experiments to clarify and quantify the positive/negative effects of soil organisms on erosion; (c) promoting ecological studies to assess both short‐ and long‐term effects of soil erosion on soil biota.ResultsWe develop a biological factor to be included in soil erosion modelling. Thanks to available data on earthworm diversity (richness and abundance), we generate an “earthworm factor”, incorporate it into a model of soil erosion and produce the first pan‐European maps of it.Main conclusionsNew estimates of soil loss can be generated by including biological factors in soil erosion models. At the same time, the effects of soil loss on belowground diversity require further investigation. Available data and technologies make both processes possible. We think that it is time to commit to fostering the fundamental, although complex, relationship between soil biodiversity and erosion.

Soil erosion is considered a very critical environmental issue that has repercussions for almost every aspect of the world. In developing countries, such as India, soil erosion continues to be a major limitation. A prediction and assessment of erosion prone areas is of utmost importance for soil fertility and water management. Recent technological advancements have provided useful models through which remotely-sensed data for a large scale area can be analyzed and interpreted. This study aims to adopt an erosion model that is unique to the physiography, biological and climatic conditions of the Indian Himalayan Region. The Revised Universal Soil Loss Equation (RUSLE) model estimates the average annual soil loss A in tonnes ha-1 year-1. Recognizing the conditions of the region, the RUSLE developed by Renard et al., (1997) was applied in conjunction with Geographic Information System (GIS) for estimating soil loss. All parameters of the model were thoroughly studied, starting from reviews and research papers on soil erosion assessment at national and catchment levels. The study follows the RUSLE soil model in estimating the rate of soil erosion at state and district level. The model was developed around coarse resolution data requirements, with practicality in providing annual soil loss rate for a large study area. It provides a means to describe specific districts that are vulnerable to soil erosion, rendering immediate action for soil conservation practices. To determine the spatial distribution of average annual soil erosion within the study area, cell-based parameters of the RUSLE were multiplied in the specified 500m x 500m spatial resolution using the raster calculator function in ArcGIS 10.0 software. The spatial pattern of soil erosion indicates that maximum erosion takes place in the north, north-western and eastern regions of the study area while the areas with low erosion rates are located in the eastern-most part of the study area. Keywords: Soil erosion, Remote sensing, Geographic information system, Soil erodibility

Scaling effects on sediment yield in the upper Yangtze River are investigated through constructing relationships between the specific sediment yield(SSY) and drainage area and factors influencing soil erosion based on data of drainage basins upstream of 268 hydrological stations.The factors influencing soil erosion used in the study are those in the Revised Universal Soil Loss Equation(RUSLE) and are calculated from DEM,rainfall,landuse,soil type data banks for the upper Yangtze River.Results show that there is a negative power relationship between SSY and the drainage area of all the gauged drainage basins in the upper Yangtze River and this relationship can be ascribed to the changes in rainfall erosivity factor R and soil erodibility factor K in RUSLE with the drainage area.Between the drainage area of 104-1.58×105km2 exists an abrupt decline of SSY with the increase of drainage area and it is a main component of the overall decreasing trend of SSY with the drainage area.In the regression relationship of SSY with the drainage area and all RUSLE factors,SSY is positively and exponentially related with the drainage area,revealing that deposition of eroded sediment occurs in a short distance in the upper Yangtze River.The relationships of SSY with the drainage area and RUSLE factors of the drainage basins of the main first-order tributaries of the upper Yangtze River are also constructed and analyzed.The results show different relationships for different tributaries because of different reasons.The scaling effects on sediment yield and causes for changes in SSY with the drainage area in the Jingsha basin are similar to those in the whole upper Yangtze River.The causes for changes in SSY with the drainage area in the Min-Tuo(Minjiang-Tuojiang) basin are also associated to the changes in factors R and K with the drainage area,but SSY is negatively related with the drainage area in the multiple regression relationship between SSY and the drainage area and factors in RUSLE due to sediment deposition in the lower reaches of the tributary.In the Jialing basin,the main factors for the occurrence of the positive relationship between SSY and the drainage area are the slope length and steepness factor LS and support practice factor P,and the positive relationship between SSY and the drainage area also keeps in the multiple regression between SSY and factors in RUSLE and the drainage area.There is not a significant regression relationship between SSY and the drainage area in the Wu-Chishui-Heng(Wujiang-Chishui-Hengjiang) basins due to intensive human activities.

A model of soil erosion and sediment transport on hillslopes is used to illustrate the role of process understanding in determining dominant processes as a function of spatial scale. Erosion and sediment yield from hillslopes are primarily determined by surface runoff, topography, vegetative canopy cover, ground surface cover, soil erodibility, and sediment properties. In areas where winter processes (snow, snowmelt, soil frost, etc.) are important, erosion and sediment yield also determined by these factors. The Hillslope Erosion Model (HEM) incorporates these factors in simulating erosion and sediment yield. The world's largest rainfall simulator database for arid and semiarid areas and data from small hillslope-scale watersheds are used to calibrate and validate the spatially distributed, processed-based HEM. Spatially distributed estimates of sediment transport and yield along hillslopes from the HEM are used with an understanding of dominant processes as a function of spatial scale as the scientific basis to determine stability of slopes at plot to hillslope scales. Interrill processes of raindrop splash and thin sheetflow transport are diffusive. Concentrated flow (rill erosion) processes are advective. Spatial loci of transition from diffusive to advective processes are inherently zones of landscape instability and channel formation. The HEM is used to define these areas of instability on hillslopes. Stability criteria for hillslopes are in turn used as criteria for geomorphic designs. Field data taken on a mine rehabilitation site in Queensland, Australia and at the Yakima Training Center in Washington State were used to extend the erosion model to disturbed site rehabilitation problems. These example applications from natural and designed slopes are used to illustrate model predictions and their applications in scaling and geomorphic designs.

This research explores the use of the revised universal soil loss equation (RUSLE) process and remote sensing (RS) and geographic information system (GIS) techniques to estimate soil erosion in Kundapura taluk, Udupi, Karnataka. The average annual predicted soil loss ranges between 292.16 and 41044.92 t yr-1. The loss of soil <292.16 t yr-1 near coastal areas has been recorded, and 1741.86 t yr-1 was found intensely plantation (mainly areca nut plantation and paddy field) area and degraded forest area. Soil erosion rate was predicted moderately high (4802.34 t yr-1) for agriculture and slope areas, which needs proper soil conservation measures to reduce erosion. The high, very high, and extreme rate (10601.16-41044.92 t yr-1) of soil erosion was found in the dense forest because of moderate slope value and the high slope length and steepness factor. The computed sediment yield (2010-2018) values range from 137.29- 504.65 t yr-1. In the coming years, huge man-made interventions in the Western Ghats region can significantly increase soil erosion. Also, most soil erosion changes happen at the micro-level and need much-localized study for specific regions. The study area belongs to the coastal region of Kundapura, which faces more soil erosion problems. This research may be helpful to understand and quantify soil erodibility rate. This study effectively proves the important role of RS and GIS in understanding geological processes and that the RULSE method can effectively be used for erosion mapping.

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.