Soil Loss Rates Research Articles

Evaluation of potential sites for soil erosion risk in and around Yamuna River flood plain using RUSLE

In general, agricultural intensification and human intervention lead to the soil erosion problem. Remarkably, marginal alluvial plains of vast Indo-Gangetic plain consistently suffer a great peril of land degradation in and around the Yamuna-Chambal valley. This is probably due to the geologic evolution of the landscape. Geomorphology and the land forms developed in and around the studied countryside themselves indicate the erosional processes. However, quantification of erosion rates and mapping of most intense erosion areas in and around Agra, Firozabad and Etawah district of Uttar Pradesh have been carried out using geospatial technology. A Geographic Information System (GIS)-based Revised Universal Soil Loss Equation (RUSLE) model was used to analyse grid cell–based erosion rates by incorporating all the crucial factors, i.e. rainfall, slope, soil, length slope, cover management and practice management factors. An average annual soil loss rate of 445 t ha−1 year−1 was observed in the study area. Moreover, the intensity-based categorization reveals that 64% area is at high erosion risk. The Google Earth imagery along with Triangular Irregular Network (TIN) model presents the erosion-associated features and slope gradient of the Yamuna River watershed further validates the results obtained in the present study.

Soil, biochar, and nitrogen loss to runoff from loess soil amended with biochar under simulated rainfall

Biochar is known to improve soil physical properties, but its role in influencing soil erosion and nutrient losses, as well as biochar itself loss is poorly understood. The objectives of this study were to determine the magnitude of soil, biochar and nitrogen losses in runoff and quantify the degree of sediment enrichment with biochar and nitrogen in a soil amended with biochar. A loessial soil was amended with five rates of nitrogen-rich biochar [0, 1%, 3%, 5%, and 7% (w/w)] that had <0.25 mm particles and incubated for 8 months. A companion study compared three biochar particle sizes (<0.25, 0.25–1, and 1–2 mm) applied at 3% rate. A series of simulated rainfall events (90 mm h−1) were applied to the soil which was held in a box at a slope of 27%. The results showed that biochar addition of 1% or 3% reduced soil loss rates while the 7% biochar addition rate increased soil loss. Biochar loss rate was proportional to the biochar addition rate when the biochar particle size was <0.25 mm. Coarser biochar particles (1–2 mm) are retained in the soil better than the finer <0.25 mm biochar particles. Total nitrogen loss and sediment enrichment with nitrogen and biochar were also lowest with the coarse biochar particles (1–2 mm) addition. The finer biochar particle sizes (<0.25 mm) were more vulnerable to erosion losses and its application caused greater total nitrogen enrichment in sediment. When finer biochar particles (<0.25 mm) are used, 1% biochar application leads to the best results for soils with risks of erosion but 7% biochar increased the risk of soil, biochar, and total nitrogen losses. Our study overall shows that knowledge of the pros and cons of applying biochar should be carefully considered before providing biochar application recommendations as a soil supplement on loess hillslopes.

Estimation of Soil Erosion Using RUSLE Model and GIS: The Case of Satinskyi Catchment, Western Rwanda

The problem of soil erosion in Rwanda has been highlighted in previous studies. They have shown that half of the country’s farmland suffers moderate to severe erosion, with the highest soil loss rates found in the steeper and highly rainy northern and western highlands of the country. The purpose of this study was to estimate soil loss in Satinskyi, one of the catchments located in Ngororero District of Western Rwanda. This has been achieved using the Revised Universal Soil Loss Equation (RUSLE) model, which has been implemented in a Geographic Information Systems (GIS) environment. The methods consisted of preparing a set of input factor layers including Slope Length and Steepness (LS) factor, Rainfall Erosivity (R) factor, Soil Erodibility (K) factor, Support Practice (P) factor, and Land Surface Cover Management Factor (C) factor, for the model. The input factors have been integrated for soil loss estimates computation using RUSLE model, and this has enabled to quantitatively assess variations in the mean of the total estimated soil loss per annum in relation to topography and land-use patterns of the studied catchment. The findings showed that the average soil loss in Satinskyi catchment is estimated at 38.4 t/ha/year. It was however found that about 91% of the study area consists of areas with slope angle exceeding 15°, a situation which exposes the land to severe soil loss rates ranging between 31 t/ha/year and 41 t/ha/year. Apart from the steep slope, changes in land use also contribute to high rates of soil loss in the catchment.&#x0D; Keywords: Soil Erosion Estimation, GIS, RUSLE, Satinskyi Catchment, Rwanda

Cadastral Information and Erosion Modeling for Monitoring Gullies in Mpazi Catchment Area, Kigali City

Due to the lack of sediment load monitoring system, erosion model calibration is challenging in Rwanda. Based on the reports of parcels boundaries corrections from Rwanda Land Management and Use Authority, there are quite consistent losses of land due to gullies development in Mpazi River watershed. This study analysed the possibility of integrating cadastral information, erosion and hydrological modelling data for identifying potential gullies development in hilly urban area of Mpazi catchment. The orthophoto of 2008 coupled with ancillary data were used to delineate the shifts of parcel boundaries from 2012 to 2016. Hydrological modelling based on DEM was also applied to investigate geo-physical characteristics and potential gullies. The differential GPS was used to locate the potential gullies that were then uploaded into GIS. Gullies intersecting with rectified parcels boundary were measured with tape meter. The gully length was measured using hydrological modelling tools and GPS coordinates captured during the field verification. The results showed that gully system expanded from 7.5 to 20 meters while neighboring parcels shift was between 3 and 12.5 meters. The highest average rate of soil loss ranged between 100 and 150 tons/ha/year. The research findings from this study are salient for policy- and decision-makers who need to review the current land and environment policies and laws so that gully erosion can be assigned appropriate mitigation measures for ecologically sustainable management of hilly urban landscapes within Kigali City. More periodic data are required to feed the model and validating this approach brings the government institutions’ responsibility. The developed methodology has the potential to quantify the gully systems in urban context with scarce hydrological, soil and geomorphological data availability and where urban planning and environmental protection are constrained by limited financial and human resources.&#x0D; Keywords: Cadastral Maintenance Data, Erosion Modelling, Gully, Urban Areas

Soil erosion: An important indicator for the assessment of land degradation neutrality in Russia

This review of soil erosion (SE) studies in Russia focuses on two main tasks: (i) ensuring the completeness and reliability of SE data in Russia, a large country (17.1 million km2) with a variety of natural and socio-economic causes of land degradation, (ii) assessing the possibility of including a SE indicator among the indicators of land degradation neutrality (LDN). A wide range of statistical, remote sensing, mathematical modeling data, the results of scientific and field studies obtained at different levels were analyzed. It is asserted that in Russia the total area of eroded lands and those under erosion risk occupy more than 50% of all agricultural lands, whereas soil fertility of croplands decreased in Soviet time (from 1950s to 1980s) by 30–60% only due to water erosion. However, recent scientific studies indicate a decrease in erosion rate and in the area of eroded land during the last 30–40 years as a result of abandonment of arable land and subsequent overgrown with natural vegetation. The climate change resulting in decrease of the depth of soil freezing, flow of spring runoff also adds to the decrease of soil erosion. The SE indicator was suggested as an important complement to three global LDN indicators. At national and subnational level, it can be interpreted through such indices as “Rate of soil loss” (ton ha-1 yr-1) and “Total soil loss” (1000 tons, in certain area during selected time period). At local level the set of indices can be wider and site-specific, including those obtained through remote sensing data by using the classifier of thematic applications of remote sensing technologies; the example was tested at the local site.

Water erosion modeling by the Erosion Potential Method and the Revised Universal Soil Loss Equation: a comparative analysis

Water erosion is the principal degradation process of tropical soils, and its effects can be measured by modeling techniques. Erosion models provide a diagnosis of the soil loss intensity and can support the planning of soil conservation practices. Models with low data requirements, such as the Revised Universal Soil Loss Equation (RUSLE) and, more recently, the Erosion Potential Method (EPM), are mainly applied in Brazil. Thus, the objective of this work was to estimate water erosion soil-loss rates using the EPM and RUSLE models on a tropical subbasin, followed by a comparison of their outcomes. The models’ application considered soil physical parameters, edaphoclimatic conditions of the area, land use, and subbasin management practices. The accuracy of the methods was verified using total transported sediment and water discharge data. We compared the models using Pearson's correlation analyses, considering a 5% of significance. We found a predominance of moderate-intensity erosion with average soil loss of 1.17 and 1.46 Mg ha-1 year-1, measured by EPM and RUSLE, respectively. The EPM model underestimated soil losses by 15.27%, and RUSLE overestimated by 19.08%, indicating a higher percentage of areas with high erosion rates (4.60%). The models presented results with a different order of magnitude, but with significant correlations, indicating that both methods pointed out similar zones of intense and light-erosion rates.

Assessment of LULC Change and Its Impact on Soil Erosion Using GIS and Revised Universal Soil Loss Equation Model

Land use is one of the vital factors in estimating soil erosion over an area. Significant changes in spatio-temporal land use distribution might lead to water runoff which causes soil erosion events. It is important to assess the soil erosion risk for hydropower reservoir as part of sediment management activities. This study aims to assess the impact of land use and land cover (LULC) changes on soil erosion risk at Chenderoh catchment in Perak. LULC distribution within the study area was mapped for 2008, 2010 and 2015 by using land use maps obtained from Department of Agriculture, Malaysia. The soil loss rate was measured using the Revised Universal Soil Loss Equation (RUSLE) utilizing spatial data of rainfall factor, soil erodibility, topographical factor, conservation factor, and support practice factor. Average soil loss was calculated according to sub-catchment of Chenderoh, and it is found that the soil loss trend marginally increases from year 2008 to 2015. Based on soil erosion risk map results, it is found that conversion of forest land to agriculture is the main contributor to soil loss, which might be due to land clearance and agriculture practice activities.

Effects of native vegetation recovery on soil loss

Considering the economic and environmental damages caused by soil loss, it is clear the necessity of information about the effect that vegetation has on soil loss rate. The present paper uses the Revised Universal Soil Loss Equation with the objective of investigating soil loss under a native vegetation recovery (Atlantic Forest) and present conditions in the Guandu river basin, located in the Southwest portion of Brazil. It was identified that reforesting 8.11% of the basin, it would promote 28.73% reduction in the mean annual soil loss compared to the actual land use. Although the paper uses a particular vegetation recovery situation (areas protected by the Brazilian Forest Code), the intention here was to clarify the role that any native vegetation protection exercises on soil loss.

Soil erosion modelling using GIS and revised universal soil loss equation approach: a case study of Guna-Tana landscape, Northern Ethiopia

An attempt has been made in this study to quantify the soil loss rate in Guna-Tana Landscape, Ethiopia. A Digital Elevation Model (12 m by 12 m spatial resolution), rainfall data over 10 years, soil, and land cover/land use extracted were used as an input to calculate soil loss rates. GIS-based RUSLE factors were integrated and analyzed in the ArcGIS 10.3 plate form. The results showed that 12-monthly loss of soil in the study area ranges from zero in the lower, middle, upper, and steeper slope parts of the watershed to 4735 t/ha/year with a mean annual soil loss of 3627.5 t/ha/year. The overall annual soil loss in the study area is 14,335,517.8 tonnes. Approximately 681.21 ha of the area is within the extreme and very extreme erosion clusters which demand immediate controlling measures.

EVALUATION OF THE IMPACTS OF LAND USE AND LAND COVER CHANGES USING EROSION ASSESSMENT MODEL AT TIKUR WUHA WATERSHED

Rapid increases in population, forest clearing and continuing search for a farm land have induced pressure on natural resource. In order to reverse such kind of problem assessing the level of problem and finding solution at watershed level is necessary. The studies of land use land cover changes and their effects on soil erosion and runoff patterns at the watershed level are essential in water resource planning and management. This study provides an approach to identify the effects of land use land cover changes on runoff and sediment in Tikur wuha watershed. The changes in land use land cover were associated with growing demand of wood for fire, charcoal, construction materials, household furniture, pulp and paper industries, and expansion of farming and grazing land. The study was conducted the impacts of land use land cover changes, to identify the main cause erosion, to assess soil loss rate in different slope classes, agricultural activities and its effect on land resource by using erosion assessment model. USLE is important to predict the annual soil loss by using different parameters. The necessary data were generated from mean annual rainfall, previous study of the area, erosivity factor, erodibilty factor, topographic factor (LS), the cropping management factor, erosion control factor, both primary and secondary data as well as key informants interview, field observation, by distribution of structural survey questionnaire and field measurement. The result of the analysis showed that the amount of soil loss at Tikur wuha watershed is about 5.58 ton/ ha/yr. The study finding suggest that understanding of some of the socio- economic, institutional and biophysical factors that determine land cover change of the area would contribute to advice appropriate strategies to achieve the desired change in SWC process and to alleviate damage land cover change in the study area. In selecting priority intervention areas in the rehabilitation of land use land cover, strategies should considered the socio-economic and specific land characteristics as well as farmers preference.&#x0D;

Soil loss assessment in Sadiya Region, Assam, India using remote sensing and GIS

Objectives: This study focuses on identifying areas of intense soil erosion in Sadiya, a subdivision of Tinsukia district of Assam in India to facilitate appropriate implementation of soil management and conservation schemes in an administrative unit. Methods: A comprehensive methodology of Remote Sensing (RS) and Geographical Information System (GIS) is implemented with an empirical model called the Revised Universal Soil Loss Equation (RUSLE). RUSLE is the best model to assess soil loss creating different raster layers in GIS. Findings: This study estimates about 443865 tons of soil loss occurs in Sadiya region annually. The maximum rate of soil loss recorded in Sadiya region is 888.26 t ha-1 year-1 the average soil loss estimated for the region is 5.45 t ha-1 year-1. In addition, a final soil loss map is also created to show the zones of varied soil erosion rates/intensities. Applications/Improvements: The use of RS and GIS in soil loss estimation gives highly accurate result and can be used for extensive area with low cost. The study reveals that soil loss is a serious issue in the region where agriculture is the main economic activity. The outcome of the study may be used directly to address the hazard through management practices. Keywords: Soil erosion; Assam; remote sensing; GIS; soil loss estimation

A GIS-based assessment of the potential soil erosion and flood hazard zones in Ekiti State, Southwestern Nigeria using integrated RUSLE and HAND models

Soil loss estimation and flood hazard mapping cannot be overemphasized due to their environmental, economic and societal concern. Thus, the main objective of this study was to assess the potential soil erosion and flood hazards zones using Revised Universal Soil Loss Equation (RUSLE) and Hand Above Nearest Drainage (HAND) models, respectively for appropriate conservation and prevention measures in Ekiti State, Southwestern Nigeria. The result reveals annual soil erosion ranges from 0 to 889 t ha−1 year−1. The estimated total annual soil loss in the state was around 1.5 million tonnes, of this, 193223.3 tonnes which covers 7508 ha was lost at a rate much greater than the tolerable soil loss rate. Soil erosion vulnerability mapping was done using six (6) categories of soil loss severity from slight to very severe. Soil erosion rates varied from 0.21 t ha−1 year−1 in forests to 1.69 t ha−1 year−1 under bare soils. The very steep slope category had the highest soil erosion rate of 15.07 t ha−1 year−1 while the gentle slope regions had the least soil erosion rate of 0.39 t ha−1 year−1. About 23% of the area which covers 115847.58 ha was prone to high flood hazard whereas 15.69% (80932.30 ha) was moderately susceptible to flood risk. Approximately 15% of the area was susceptible to low flood hazard zone while 44.90% were vulnerable to very low flood occurrence. LULC has significant effect on the spatial pattern of soil loss in the study area. Potential soil loss risk zones were highly related to the degree and inclination of slope. The reported results can serve as preliminary information to determine erosion and flood hotspots in the study area and as input for policy decision for disasters prevention and conservation measures.

High-resolution monitoring of diffuse (sheet or interrill) erosion using structure-from-motion

Sheet erosion is common on agricultural lands, and understanding the dynamics of the erosive process as well as the quantification of soil loss is important for both soil scientists and managers. However, measuring rates of soil loss from sheet erosion has proved difficult due to requiring the detection of relatively small surface changes over extended areas. Consequently, such measurements have relied on the use of erosion plots, which have limited spatial coverage and have high operating costs. For measuring the larger erosion rates characteristic of rill and gully erosion, structure-from-motion (SfM) photogrammetry has been demonstrated to be a valuable tool. Here, we demonstrate the first direct validation of UAV-SfM measurements of sheet erosion using sediment collection data collected from erosion plots.Three erosion plots (12 m × 4 m) located at Lavras, Brazil, with bare soil exposed to natural rainfall from which event sediment and runoff was monitored, were mapped during two hydrological years (2016 and 2017), using a UAV equipped with a RGB camera. DEMs of difference (DoD) were calculated to detect spatial changes in the soil surface topography over time and to quantify the volumes of sediments lost or gained. Precision maps were generated to enable precision estimates for both DEMs to be propagated into the DoD as spatially variable vertical uncertainties.The point clouds generated from SfM gave mean errors of ~2.4 mm horizontally (xy) and ~1.9 mm vertically (z) on control and independent check points, and the level of detection (LoD) along the plots ranged from 1.4 mm to 7.4 mm. The soil loss values obtained by SfM were significantly (p < 0.001) correlated (r2 = 95.55%) with those derived from the sediment collection. These results open up the possibility to use SfM for erosion studies where channelized erosion is not the principal mechanism, offering a cost-effective method for gaining new insights into sheet, and interrill, erosion processes.

Analysis of the Soil Loss and Settlement of Silty Clay with Different Subclassifications

There is an ever-growing demand for the construction of silty clay stratum tunnels; therefore, effectively controlling the surface settlement caused by tunnel construction has become an important task. Since the physical indexes of silty clay greatly influence strength and deformation, based on the physical and mechanical indexes of 3192 groups in three areas, quantitative and determinative indexes for the subclassification of silty clay are proposed using K-means clustering and the tracking records of the actual project. Then, the soil loss and settlement of different subclassifications of silty clay are studied through the standard Gauss error function. Empirical formulas for calculating the width of the settlement trough and the soil loss rate are proposed. The dispersion of the settlement parameters with different subclassifications indicates that the soil properties of the silty clay strata vary greatly with subclassification, and the influence range of the surrounding soil disturbance caused by excavation also varies. In addition, the change in the soil loss rate with the propulsion of the tunnel face in the same monitoring section is discussed. For subgrade V, the increasing soil loss rate reaches a maximum when the tunnel face reaches the monitoring sections. For subgrades VI1 and VI2, this rate changes mainly during the timeframe spanning from 5 days before excavation to 5 days after excavation. A numerical simulation was also carried out to validate the applicability of the Peck formula for silty clay tunnels. The numerical prediction and field measured data show that when the cover-to-diameter ratio is between 1 and 3, it is reasonable to use the Peck formula to analyze the surface settlement of a silty clay tunnel. This paper can provide guidance based on experience for the subclassification of the soil surrounding rock and for the prediction of the ground surface settlement.

Evaluating Soil Loss Using Geographical Information System and Remote Sensing for Soil and Water Resource Conservation: The Case of Yisir Watershed, Northwestern Ethiopia

Soil erosion is more sensitive in the highlands of Ethiopia. The purpose of this study is estimating soil loss rate using RUSLE model with GIS and remote sensing to identify erosion potential areas for soil and water resources conservation plan and to prepare soil loss risk map. LANDSAT image of the study area and Digital Elevation Model from http://earthexplorer.usgs.gov as taken in 2017. Collected data were processed and analyzed using Arc GIS10.2 version. Total average annual soil loss from the 2,120.33ha was estimated at 7161.06tons. The lower soil loss rate was 2.5t/ha/yr on plantation and natural forest, the maximum value was 100.62tons/ha/yr in steep slope cultivated land and average soil loss was 50.31 tons/ha/yr. About 6.35% of the area is under extremely very severe soil erosion rate. Level soil bund, graded soil, stone or stone faced soil bund, fanyajju, cutoff- drain in the above part of the catchment, waterway along the slope, trenches on grazing land, check dam SWC measures at Quala got, integrated physical with biological measures like tree Lucerne, Vetiver grass are the recommended SWC measures. This approach can be applied in other basin or watershed for assessment of erosion risk potential using GIS and RS, and this can be used as a preliminary watershed planning tool for decision makers in Ethiopia like Woreda Agriculture and Natural Resources management Office. Keywords: Ethiopia, GIS, RUSLE, Soil and Water Resource, Yisir Watershed DOI: 10.7176/JRDM/66-02 Publication date: June 30th 2020

Identifying impacts of land use change on soil redistribution at different slope positions using magnetic susceptibility

Clear-cutting of Oak forests and intensive cultivation on the hilly regions of the Zagros Mountains has led to plausible threats on the natural ecosystem and catastrophic floods in western Iran. This study was conducted to explore the effects of clear-cutting of natural forests in different slope positions on some soil chemical and physical properties as well as quantification of soil redistribution using magnetic susceptibility. Two adjacent sites, including natural forest and cultivated lands, were selected and a total of six transects at three soil depths (0–10, 10–20, and 20–30 cm) and a total of seventy-two soil samples were examined. Soil properties such as particle size distributions, bulk density (ρb), calcium carbonate equivalent (CCE), soil organic matter (SOM), and magnetic susceptibility at low and high frequencies were measured. Results indicated that clear-cutting and cultivation for 50 years significantly (p < 0.05) increased ρb and CCE and reduced SOM and TN. Moreover, magnetic susceptibility at four slope positions was significantly (p < 0.05) lower compared with the natural forest. Using a simple proportional model to estimate the soil loss or gain and comparing the mean χlf in any given point confirmed a high rate of soil loss in cultivated sites. In the forest soils, low soil loss in shoulder position and high rate of deposition in footslope and backslope positions were obtained. In general, it is revealed that magnetic measures could provide valuable estimates of mid-term soil erosion and sedimentation in the hilly region following land use changes.

Erosion processes and features for a coarse-textured soil with different horizons: a laboratory simulation

Severe water erosion of coarse-textured soils, thereby exposing subsurface horizons at the surface, is a serious problem in southern China. Currently, there are few systematic studies on erosion processes and features as the various coarse-textured subsurface horizons are exposed. The main objective in this study was to investigate the effects of rainfall intensity and inflow rate on the runoff, soil loss, and erosion features of three horizons of a typical soil developed from granite (topsoil horizon, illuvial horizon, and parent material horizon) in the steeply sloped region. A series of laboratory simulation tests were conducted in a 0.8-m by 3-m flume using two combined rainfall and upslope inflow condition (90 mm h−1 plus 2 L min−1 and 120 mm h−1 plus 2.66 L min−1, respectively). Runoff coefficient and soil loss increased with the evolution of erosion phase from sheet erosion to rill advancement to rill maturity phase. Runoff generation increased as soil horizons with higher bulk density were exposed on the surface and as the rainfall-inflow rate increased. Additionally, rainfall-inflow rate and soil horizon had significant effects on soil loss rate, headward erosion rate, and rill density (p < 0.01). The hillslope roughness was dependent on the interaction of soil properties (clay content) and rainfall characteristics (rainfall intensity and duration). Despite the different hillslope roughness levels exhibited as result under the different rainfall-inflow treatments, the topsoil horizon always exhibited low soil loss. Moreover, as rainfall duration increased, coarse grains (quartz) were gradually enriched on the hillslope surface, which worked as “armoring” to protect the soil surface of interrill areas from further erosion, especially for the topsoil horizon. Due to the surface armoring, rill erosion was considered the main sediment source during the rill maturity phase. These results suggested that coarse grains could be an effective on-site soil conservation practice controlling soil erosion, which should be considered in future erosion prediction and bare land restoration in coarse-textured soils.

ASSESSMENT OF SOIL EROSION BY RUSLE MODEL USING GIS: A CASE STUDY OF CHEMORAH BASIN, ALGERIA

Soil erosion by water is one of the major sources of land degradation. Erosion contributes to the temporary or permanent lowering of the productive capacity of agricultural land and sedimentation of dams. The purpose of this study is to assess soil loss rate using a GIS/RUSLE approach at the Chemorah basin by focusing on two catchments, namely, Reboa and Soultez. The assessment of soil erosion aims thus to identify the lands more prone to erosion which are vital for erosion management process. RUSLE model supported by GIS software is to predict the spatial variability of erosion occurring in the Chemorah basin and its sub-basins. Five inputs such as rainfall erosivity, soil erodibility, slope and length of slope, plant cover and anti-erosion practices, are used in the model to compute the erosion loss rates. The mean annual soil loss in Chemorah river basin is estimated at 7.52 T/ha/year, and varying between 3.78 T/ha/year in Soultez catchment and 6.06 T/ha/year in Reboa sub-basin. The study shows that low erosion (≤ 7 T/ha/year) covers 52% and high to very high erosion (&gt; 7 T/ha/year) which does not exceed 23% of the Chemorah basin area. The results indicate that Reboa catchment faces the greatest risk of soil erosion compared to Soultez one, with contributions of 44 % and 32 % of their basin areas respectively. Use of the erosion factors’ information coupled with GIS/RUSLE program can help to design the appropriate land management to minimize soil erosion in the basin.

Identification of Soil Conservation Priority Area, in Jedeb River Watershed East Gojjam Zone, Amhara Region, Ethiopia

Soil erosion is a major environmental problem that threatens world food production; it can be described as the removal of organic as well as inorganic soil surface materials by wind and water. This (e present) study aims to identify the most erosion vulnerable sub-watersheds for planning appropriate conservation intervention and restoration measures in Jedeb watershed. Revised Universal Soil Loss Equation (RUSLE) integrated with satellite remote sensing (RS) and geographical information system (GIS) has been applied to calculate potential soil loss at sub-watershed level. The parameters of RUSLE model were estimated using remote sensing data and ArcGIS software. The rainfall erosivity R-factor was found from 3209.6 to 3896.69 MJ.mm/ (ha.h), soil erodibility K-factor varies from 0.1 to 0.25 t ha h/ (ha MJ mm), Topographic (LS factor) ranging from 0.19 to 6.7, C-factor varies 0.01 to 0.25 and support practice P-factors from 0.1 to 1. The total annual soil loss potential of the study area was found 1,383,158 t/ yr from the total watershed area of 29,633 ha. Average annual soil loss at sub-watersheds level was estimated from 29.275 to72.529 t/ha/year and mean annual soil loss of the entire watershed was 46t/ha/year. The study results indicated that potential soil erosion rate in the watershed was ranged into four priority categories from high to extremely severe. Three sub-watersheds covering 22.975% of the watershed shows very severe mean soil loss rate, two sub-watersheds was found severe mean soil rate which covered 19.014%, eight sub-watershed were existed under very high mean soil loss rate covers 47.59% and Three sub-watersheds were found in the high soil loss rate and covers 10.42%. Sever and extremely severe micro watersheds demand immediate attention in terms of management and planning perspective. Soil and water conservation structure was recommended and designed based on peak runoff rate, soil type, slope of the land, land use type and soil erosion hazard . Keywords : Soil Erosion; RUSLE; GIS; Soil Conservation; Jedeb watershed; Ethiopia DOI: 10.7176/JNSR/10-9-02 Publication date: May 31 st 2020

Sensitivity Analysis of Vegetation Coverage to Soil Loss Rate in Red Soil Region of South China

Vegetation is an important basic component of terrestrial ecosystem and one of the most sensitive factors affecting soil erosion. How to analyse the quantitative relationship between fractional vegetation cover (FVC) and soil erosion and determine the sensitive coverage of erosion is of great significance for guiding government departments to implement soil and water conservation policies. In this paper, through the variable-controlling mothed, the forest land, grassland and bare land in Changting County, a typical red soil region in southern China, were used as experimental areas to study the sensitivity of FVC change to soil erosion. The soil erosion amount was calculated by RUSLE model, and soil loss rate (rsl) were used to characterize soil erosion. The results show that when FVC changes from 0 to 0.8, the fitting curves rsl are in accordance with the logistic model distributions, with a high coefficient of determination R2, and the sensitivity of rsl is less sensitive in the range of 0∼0.05, it is most sensitive when FVC reaches a certain level, and there is basically no sensitivity when it reaches 0.7 or above; the fitting curves of rsl at different slope levels are similar to their overall distribution, which are consistent with the logistic models, and R2 is above 0.99, the curves of rsl at each slope level are different in the same FVC interval, for areas with poor vegetation coverage (0∼0.2) and high slope (>25°), the curve is less sensitive to terrain; rsl generally has higher sensitivity in the range of 0.2∼0.6 coverage; in areas above 0.6, the sensitivity decreases to zero.