scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

scholarly journals Assessment of Soil Erosion at Multiple Spatial Scales Following Land Use Changes in 1980-2017 in the Black Soil Region, (NE) China

2020 ◽  
Author(s):  
Haiyan Fang ◽  
Zemeng Fan
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Spatial Scales ◽  
Land Use Changes ◽  
Arable Land ◽  
Rainfall Erosivity ◽  
Erosion Rates ◽  
Soil Erosion Rate

Impact of land use and land cover (LULC) change on soil erosion is still imperfectly understood, especially in northeastern China (NEC). Based on the Revised Universal Loss Equation (RUSLE), the variability of soil erosion at different spatial scales following land use changes in1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 t ha-1 yr-1 with an average of 4.22 t ha-1 yr-1 in 1980-2017. The rates of soil erosion less than 1.41 t ha-1 yr-1 decreased from 1980 to 2010, and increased from 2010 to 2017, and opposite changing patterns occurred in higher erosion classes (i.e., above 5 t ha-1 yr-1). At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 t ha-1 yr-1, followed by Jilin Province, the east Inner Mongolia, and Heilongjing Province. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 t ha-1 yr-1. At a county scale, around 75% of the countries had soil erosion rate higher than its tolerance level. The county numbers with higher erosion rate increased in 1980-2010 and decreased in 2010- 2017, resulting from the sprawl and withdrawal of arable land. The results indicate that appropriate policies can control soil loss through limiting arable land sprawl in areas of unfavorable regions in the NEC.

scholarly journals Estimation of Soil Loss Using Remote Sensing And GIS-Based Universal Soil Loss Equation In Northern Catchment of Lake Tana Sub-Basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Author(s):  
Veera Narayana Balabathina ◽  
Raju RP ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Lake Tana ◽  
Erosion Risk ◽  
Priority Areas ◽  
Erosion Rates ◽  
The Mean ◽  
Soil Loss Equation

Abstract Background: Soil erosion, one of the major environmental challenges, is influenced by topography, climate, soil characteristics, and human activities and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. The present study attempts to estimate soil erosion risk in the Northern catchment of Lake Tana basin, situated in northwest part of Ethiopia, with available data through the application of the Universal Soil Loss Equation model integrated with Geographic Information System and remote sensing technologies to identify priority areas for controlling soil erosion. In addition, it analyzes the effect of land use and land cover, topography, erodibility, and drainage density on soil erosion potential of the catchment, and the possible relationships among them. Results: The results show that the mean annual soil loss of catchment is estimated at 37.89 ± 59.2 t ha−1yr−1 with a total annual soil loss of 1,705,370 tons. The topography (LS-factor), followed by the support practice (P-factor) and the soil erodibility (K-factor) were the most sensitive factors affecting soil erosion in the catchment. To identify high priority areas for management, the study area was subdivided into five major sub-basins and further categorized into five erosion classes based on erosion severity. The mean soil erosion rates of the Derma, Megech, Gumara, Garno, and Gabi Kura River sub-basins are 46.8, 40.98, 30.95, 30.04, and 29.66 t ha−1yr−1, respectively. About 58.9% of the area was found in very low erosion risk which extends from 0-1 t ha−1yr−1 and accounted only 1.1% of total soil loss, while 12.4% of the area was found to be under high and extreme erosion risk with erosion rates of 10 t ha−1yr−1 or more that contributes about 82.1% of total soil loss warrant high priority for reducing the risk of soil erosion. Conclusions: This study permits the understanding of the soil erosion process and the various factors that lead to the spatial variability of the risk in the catchment, and thus enhances the effectiveness of proposed conservation strategies for sustainable land management.

scholarly journals Soil erodibility indices under different land uses in Ri-Bhoi district of Meghalaya (India)

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Manish Olaniya ◽  
Pradip Kumar Bora ◽  
Susanta Das ◽  
Pukhrambam Helena Chanu
Keyword(s):  
Land Use ◽  
Organic Matter ◽  
Soil Erosion ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Soil Erodibility ◽  
Land Uses ◽  
Modified Clay ◽  
K Index ◽  
Soil Loss Equation

Abstract In absence of soil erosion plots for determination of erodibility index (K) for erosion models like Universal Soil Loss Equation (USLE) or Revised Universal Soil Loss Equation (RUSLE) to estimate soil erosion, empirical relations are used. In the present study, soil erodibility index was determined for entire Ri-bhoi district of Meghalaya based on soil physical and chemical properties through empirical relationship and presented in a map form. Dominant land uses of the district were identified through geo-spatial tools which were viz. agriculture, forest, jhum land and wasteland. Soil samples from surface depth (01–15 cm) were collected from areas of different dominant land uses. Twenty five sampling points were selected under each land use type and geo-coded them on the base map of Ri-bhoi district. Apart from K-index, Clay Ratio, Modified Clay Ratio and Critical Soil Organic Matter were also determined for understanding the effect of primary soil particles on erodibility. In agriculture land use system K-index values were found in the range of 0.08–0.41 with an average of 0.25 ± 0.02. In case of jhum, forest and wasteland these were in the range of 0.08–0.42 with an average of 0.20 ± 0.01; 0.09–0.40 with an average of 0.22 ± 0.02, and 0.10–0.34 with an average value of 0.23 ± 0.02, respectively. Clay ratio (2.74) and Modified clay ratio (2.41) were observed to be higher in forest LUS, lower clay ratio (1.97) and modified clay ratio (1.81) were found in the wasteland indicating erosion susceptibility in forested area. The values of Critical Level of Organic Matter (CLOM) for the district ranged from 4.72 to 16.56. Out of 100 samples, only one sample had CLOM value less than 5 and rest 99 samples had values more than 5 indicating that the soils of the district had moderate to stable soil structure and offer resistance to erosion. All the indices values of geo-coded points were then interpolated in the Arc-GIS environment to produce land use based maps for Ri-bhoi district of Meghalaya. As K-index is a quantitative parameter which is used in models, the index can be then interpolated for estimation of soil erosion through USLE or RUSLE for any given situation.

scholarly journals Assessment of Soil Erosion by the RUSLE Model Using Remote Sensing and GIS: A Case Study of Jilin Province of China

2020 ◽  
Author(s):  
Ping ZHOU ◽  
Yajin GE ◽  
Yue JIANG ◽  
Yanan XIE ◽  
Zhiwen SI ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Food Production ◽  
Erosion Rate ◽  
Slope Angle ◽  
Jilin Province ◽  
Rusle Model ◽  
Soil Erosion Rate

The accurate assessment and monitoring of soil erosion is of great significance for guiding food production and ensuring ecological security, and it is a current research hotspot. In this paper, remote sensing and geographic information systems (GISs) are combined with the Revised Universal Soil Loss Equation (RUSLE model) to carry out research on soil erosion monitoring and make a quantitative evaluation. According to five factors, including rainfall erosivity, soil erodibility, topography, vegetation cover, crop management and water and soil conservation measures, the distribution of the soil erosion rate in Jilin Province in 2019 was mapped, and the soil erosion rate was divided into 5 levels according to the degree of erosion, including very slight, slight, moderate, severe and extremely severe erosion. Based on the segmented S-slope factor model and the unique topographical features of the study area, the relationships among the soil erosion rate, erosion risk level, erosion area, erosion amount and slope angle (θ) were systematically analysed, and a slope angle of 15° was identified as the threshold for soil erosion on sloped farmland in Jilin Province. The total soil erosion in Jilin Province was 402.14×106 t in 2019, the average soil erosion rate was 21.6 t·ha-1·a-1, and the average soil loss thickness was 1.6 mm·a-1; these values were far greater than the soil erosion rate risk threshold of 10 t ·Ha-1·a-1. Thus, the province has a strong level of soil erosion. We conclude that soil degradation is accelerating, and food production and the ecological environment will face severe challenges. It is suggested that soil erosion control should be carried out according to different types and slopes of land, with an emphasis on the management of forestland and farmland because forestland and farmland are currently the first types of land to be managed in Jilin Province. This paper aims to explore a timely, fast, efficient and convenient soil erosion monitoring and evaluation method and provide effective monitoring tools for agricultural water and soil conservation, ecological safety management and stable food production in Jilin Province and similar black soil areas.

scholarly journals Assessment of Soil Erosion at Multiple Spatial Scales Following Land Use Changes in 1980–2017 in the Black Soil Region, (NE) China

2020 ◽  
Vol 17 (20) ◽  
pp. 7378
Author(s):  
Haiyan Fang ◽  
Zemeng Fan
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Erosion Rate ◽  
Spatial Scales ◽  
Land Use Changes ◽  
Arable Land ◽  
Black Soil ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Black Soil Region

Impact of land use and land cover change on soil erosion is still imperfectly understood, especially in northeastern China where severe soil erosion has occurred since the 1950s. It is important to identify temporal changes of soil erosion for the black soil region at different spatial scales. In the present study, potential soil erosion in northeastern China was estimated based on the Revised Universal Loss Equation by integrating satellite images, and the variability of soil erosion at different spatial scales following land use changes in 1980, 1990, 2000, 2010, and 2017 was analyzed. The regionally spatial patterns of soil loss coincided with the topography, rainfall erosivity, soil erodibility, and use patterns, and around 45% of soil loss came from arable land. Regionally, soil erosion rates increased from 1980 to 2010 and decreased from 2010 to 2017, ranging from 3.91 to 4.45 Mg ha−1 yr−1 with an average of 4.22 Mg ha−1 yr−1 in 1980–2017. Areas with a rate of soil erosion less than 1.41 Mg ha−1 yr−1 decreased from 1980 to 2010 and increased from 2010 to 2017, and the opposite changing patterns occurred in higher erosion classes. Arable land continuously increased at the expense of forest in the high-elevation and steep-slope areas from 1980 to 2010, and decreased from 2010 to 2017, resulting in increased areas with erosion rates higher than 7.05 Mg ha−1 yr−1. At a provincial scale, Liaoning Province experienced the highest soil erosion rate of 9.43 Mg ha−1 yr−1, followed by Jilin Province, the eastern Inner Mongolia Autonomous Region, and Heilongjiang Province. At a county scale, around 75% of the counties had a soil erosion rate higher than the tolerance level. The county numbers with higher erosion rate increased in 1980–2010 and decreased in 2010–2017, resulting from the sprawl and withdrawal of arable land.

scholarly journals Quantitative Assessment of Soil Erosion Based on CSLE and the 2010 National Soil Erosion Survey at Regional Scale in Yunnan Province of China

2019 ◽  
Vol 11 (12) ◽  
pp. 3252 ◽  
Author(s):  
Guokun Chen ◽  
Zengxiang Zhang ◽  
Qiankun Guo ◽  
Xiao Wang ◽  
Qingke Wen
Keyword(s):  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Erosion Rate ◽  
Mountainous Areas ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Total Soil ◽  
Conservation Measures ◽  
Soil Conservation Measures

Regional soil loss assessment is the critical method of incorporating soil erosion into decision-making associated with land resources management and soil conservation planning. However, data availability has limited its application for mountainous areas. To obtain a clear understanding of soil erosion in Yunnan, a pixel-based estimation was employed to quantify soil erosion rate and the benefits of soil conservation measures based on Chinese Soil Loss Equation (CSLE) and data collected in the national soil erosion survey. Results showed that 38.77% of the land was being eroded at an erosion rate higher than the soil loss tolerance, the average soil erosion rate was found to be 12.46 t∙ha−1∙yr−1, resulting in a total soil loss of 0.47 Gt annually. Higher erosion rates mostly occurred in the downstream areas of the major rivers as compared to upstream areas, especially for the southwest agricultural regions. Rain-fed cropland suffered the most severe soil erosion, with a mean erosion rate of 47.69 t∙ha−1∙yr−1 and an erosion ratio of 64.24%. Lands with a permanent cover (forest, shrub, and grassland) were mostly characterized by erosion rates an order of magnitude lower than those from rain-fed cropland, except for erosion from sparse woods, which was noticeable and should not be underestimated. Soil loss from arable land, woodland and grassland accounted for 52.24%, 35.65% and 11.71% of the total soil loss, respectively. We also found significant regional differences in erosion rates and a close relationship between erosion and soil conservation measures adopted. The CSLE estimates did not compare well with qualitative estimates from the National Soil Erosion Database of China (NSED-C) and only 47.77% of the territory fell within the same erosion intensity for the two approaches. However, the CSLE estimates were consistent with the results from a national survey and local assessments under experimental plots. By advocating of soil conservation measures and converting slope cropland into grass/forest and terraced field, policy interventions during 2006–2010 have reduced soil erosion on rain-fed cropland by 20% in soil erosion rate and 32% in total soil loss compared to the local assessments. The quantitative CSLE method provides a reliable estimation, due to the consideration of erosion control measures and is potentially transferable to other mountainous areas as a robust approach for rapid assessment of sheet and rill erosion.

scholarly journals Soil erosion by snow gliding – a first quantification attempt in a subalpine area in Switzerland

2014 ◽  
Vol 18 (9) ◽  
pp. 3763-3775 ◽  
Author(s):  
K. Meusburger ◽  
G. Leitinger ◽  
L. Mabit ◽  
M. H. Mueller ◽  
A. Walter ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Sediment Yield ◽  
Soil Loss ◽  
Water Erosion ◽  
Erosion Rates ◽  
The Difference ◽  
Snow Gliding

Abstract. Snow processes might be one important driver of soil erosion in Alpine grasslands and thus the unknown variable when erosion modelling is attempted. The aim of this study is to assess the importance of snow gliding as a soil erosion agent for four different land use/land cover types in a subalpine area in Switzerland. We used three different approaches to estimate soil erosion rates: sediment yield measurements in snow glide depositions, the fallout radionuclide 137Cs and modelling with the Revised Universal Soil Loss Equation (RUSLE). RUSLE permits the evaluation of soil loss by water erosion, the 137Cs method integrates soil loss due to all erosion agents involved, and the measurement of snow glide deposition sediment yield can be directly related to snow-glide-induced erosion. Further, cumulative snow glide distance was measured for the sites in the winter of 2009/2010 and modelled for the surrounding area and long-term average winter precipitation (1959–2010) with the spatial snow glide model (SSGM). Measured snow glide distance confirmed the presence of snow gliding and ranged from 2 to 189 cm, with lower values on the north-facing slopes. We observed a reduction of snow glide distance with increasing surface roughness of the vegetation, which is an important information with respect to conservation planning and expected and ongoing land use changes in the Alps. Snow glide erosion estimated from the snow glide depositions was highly variable with values ranging from 0.03 to 22.9 t ha−1 yr−1 in the winter of 2012/2013. For sites affected by snow glide deposition, a mean erosion rate of 8.4 t ha−1 yr−1 was found. The difference in long-term erosion rates determined with RUSLE and 137Cs confirms the constant influence of snow-glide-induced erosion, since a large difference (lower proportion of water erosion compared to total net erosion) was observed for sites with high snow glide rates and vice versa. Moreover, the difference between RUSLE and 137Cs erosion rates was related to the measured snow glide distance (R2 = 0.64; p < 0.005) and to the snow deposition sediment yields (R2 = 0.39; p = 0.13). The SSGM reproduced the relative difference of the measured snow glide values under different land uses and land cover types. The resulting map highlighted the relevance of snow gliding for large parts of the investigated area. Based on these results, we conclude that snow gliding appears to be a crucial and non-negligible process impacting soil erosion patterns and magnitude in subalpine areas with similar topographic and climatic conditions.

scholarly journals Impacts of oak deforestation and rainfed cultivation on soil redistribution processes across hillslopes using 137Cs techniques

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Shamsollah Ayoubi ◽  
Nafiseh Sadeghi ◽  
Farideh Abbaszadeh Afshar ◽  
Mohammad Reza Abdi ◽  
Mojtaba Zeraatpisheh ◽  
...  
Keyword(s):  
Land Use ◽  
Magnetic Susceptibility ◽  
Soil Erosion ◽  
Erosion Rate ◽  
Land Use Changes ◽  
Soil Samples ◽  
Natural Forest ◽  
Oak Forests ◽  
Erosion Rates ◽  
Rainfed Farming

Abstract Background As one of the main components of land-use change, deforestation is considered the greatest threat to global environmental diversity with possible irreversible environmental consequences. Specifically, one example could be the impacts of land-use changes from oak forests into agricultural ecosystems, which may have detrimental impacts on soil mobilization across hillslopes. However, to date, scarce studies are assessing these impacts at different slope positions and soil depths, shedding light on key geomorphological processes. Methods In this research, the Caesium-137 (137Cs) technique was applied to evaluate soil redistribution and soil erosion rates due to the effects of these above-mentioned land-use changes. To achieve this goal, we select a representative area in the Lordegan district, central Iran. 137Cs depth distribution profiles were established in four different hillslope positions after converting natural oak forests to rainfed farming. In each hillslope, soil samples from three depths (0–10, 10–20, and 20–50 cm) and in four different slope positions (summit, shoulder, backslope, and footslope) were taken in three transects of about 20 m away from each other. The activity of 137Cs was determined in all the soil samples (72 soil samples) by a gamma spectrometer. In addition, some physicochemical properties and the magnetic susceptibility (MS) of soil samples were measured. Results Erosion rates reached 51.1 t·ha− 1·yr− 1 in rainfed farming, whereas in the natural forest, the erosion rate was 9.3 t·ha− 1·yr− 1. Magnetic susceptibility was considerably lower in the cultivated land (χhf = 43.5 × 10− 8 m3·kg− 1) than in the natural forest (χhf = 55.1 × 10− 8 m3·kg− 1). The lower soil erosion rate in the natural forest land indicated significantly higher MS in all landform positions except at the summit one, compared to that in the rainfed farming land. The shoulder and summit positions were the most erodible hillslope positions in the natural forest and rainfed farming, respectively. Conclusions We concluded that land-use change and hillslope positions played a key role in eroding the surface soils in this area. Moreover, land management can influence soil erosion intensity and may both mitigate and amplify soil loss.

scholarly journals Assessment of Soil Erosion Vulnerability in the Heavily Populated and Ecologically Fragile Communities in Motozintla De Mendoza, Chiapas, Mexico

2017 ◽  
Author(s):  
Selene B. González-Morales ◽  
Alex Mayer ◽  
Neptalí Ramírez-Marcial
Keyword(s):  
Soil Erosion ◽  
Erosion Rate ◽  
Negative Response ◽  
Attitudes And Practices ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Kap Survey ◽  
Level Of Knowledge ◽  
Steep Slopes ◽  
Knowledge Attitudes And Practices

Abstract. The physical aspects and knowledge of soil erosion in six communities in rural Chiapas, Mexico were assessed. Average erosion rates estimated with the RUSLE model ranged from 200 to 1,200 ha−1 yr−1. Most erosion rates are relatively high due to steep slopes, sandy soils and bare land cover. The lowest rates occur where corn is cultivated for much of the year and slopes are relatively low. The results of a knowledge, attitudes and practices (KAP) survey showed that two-thirds of respondents believed that the major cause of soil erosion was hurricanes or rainfall and only 14 % of respondents identified human activities as causes of erosion. Forty-two percent of respondents indicated that the responsibility for solving soil erosion problems lies with government, as opposed to 26 % indicating that the community is responsible. More than half of respondents believed that reforestation is a viable option for reducing soil erosion, but only a third of respondents were currently applying reforestation practices and another one-third indicated that they were not following any conservation practices. The KAP results were used to assess the overall level of knowledge and interest in soil erosion problems and their solutions by compiling negative responses. The community of Barrio Vicente Guerrero may be most vulnerable to soil erosion, since it had the highest average negative response and the second highest soil erosion rate. However, Poblado Cambil had the highest estimated soil erosion rate and a relatively low average negative response rate, suggesting that soil conservation efforts should be prioritized for this community. We conclude that as long as the economic and productive needs of the communities are not solved simultaneously, the risk of soil erosion will increase in the future, which threatens the survival of these communities.

scholarly journals Estimation of Soil Erosion using USLE and GIS

2019 ◽  
Vol 8 (2) ◽  
pp. 3936-3939
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Environmental Problem ◽  
Gis Technique ◽  
Economic Imbalances ◽  
Factor C ◽  
Soil Loss Equation

Soil erosion is one of the most serious environmental problem which must be taken in to consideration to prevent economic imbalances in nature. Soil erosion not only affect the agricultural productivity but also increases level of sedimentation. The study was carried out to determine the soil erosion for the watershed which is located in Godavari middle sub basin, Nanded district, Maharashtra state (India). The universal soil loss equation (USLE) and Geographic information system (GIS) technique was used to determine soil erosion. Present study revealed that, the study area is under moderate erosion with an average soil loss 7.233 tones/ha/yr. Where as minimum and maximum erosion rate observed as 5.39 tones/ha/yr to 10.27 tones/ha/yr respectively. The various maps of USLE factors prepared in QGIS environment. Statistically significant relationship obtained between soil loss and cover management factor (C). It was observed that C factor more influences in soil loss than any other factor.

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