scholarly journals Soil Erosion Estimation Using RUSLE Modeling and Geospatial Tool: Case Study of Kathmandu District, Nepal

2020 ◽  
Vol 17 ◽  
pp. 118-134
Author(s):  
Roshan Dahal
Keyword(s):  
Soil Erosion ◽  
Spatial Data ◽  
Soil Loss ◽  
Erosion Rate ◽  
Slope Length ◽  
Erosion Rates ◽  
High Erosion Rate ◽  
Time Savings ◽  
Data Screening

Revised Universal Soil Loss Equation (RUSLE) model is applied in this study to evaluate the risk of erosion in Kathmandu district. The calculation of erosion requires certain data from various sources available in different formats and scales. Geographic Information System (GIS) was used which allowed considerable time savings in the processing of spatial data, screening the effects of each factor affecting soil erosion. Among various erosion factors, topography, rainfall, soil properties, and soil conservation practices were used for the study. Average soil loss was calculated by multiplying these factors. Final results of soil erosion rates were separated into six classes based on erosion severity, in which 2.18% of land (> 80Mg ha-1yr-1), followed by 2.85% of land (40-80 Mg ha-1yr-1), 5.56% of land (20-40 Mg ha-1yr-1), 8.73% of land (10-20 Mg ha-1yr-1), 10.53% of land (5-10 Mg ha-1yr-1) and 70.14% of land (0-5 Mg ha-1yr-1), falls under very severe, severe, very high, moderate and low severity zone respectively. Area having high slope length (LS) factor has high erosion rate. In Dakshinkali, Nagarjun and Budanilkantha area, there is high erosion rate. From the result, spatial distribution of soil erosion across Kathmandu district, can be applied for management and controlling the erosion.

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 Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India

2021 ◽  
Vol 8 (1) ◽  
pp. 26
Author(s):  
Manti Patil ◽  
Radheshyam Patel ◽  
Arnab Saha
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Crop Production ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Reservoir Sedimentation ◽  
Reservoir Water ◽  
Slope Length ◽  
Soil Erosion Rate

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.

scholarly journals Modelisation Du Risque D’érosion Hydrique Par L’équation Universelle Des Pertes En Terre Dans Le Rif Occidental: Cas Du Bassin Versant De Moulay Bouchta (Maroc)

2018 ◽  
Vol 14 (3) ◽  
pp. 524 ◽  
Author(s):  
Anis Zouagui ◽  
Mohamed Sabir ◽  
Mustapha Naimi ◽  
Mohamed Chikhaoui ◽  
Moncef Benmansour
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Land Development ◽  
Principal Component ◽  
Slope Length ◽  
Increased Risk ◽  
Effect Of Support ◽  
Soil Losses

Soil erosion causes many environmental and socio-economic problems: loss of biodiversity, decrease in the productivity of agricultural land, siltation of dams and increased risk of flooding. It is therefore essential to establish a detailed evaluation of this process before any spatial planning. To evaluate the effects of soil erosion spatially and quantitatively in order to face this phenomenon, and propose the best conservation and land development strategies, the Universal Soil Loss Equation (USLE) coupled with a geographic information system (GIS) is applied. This model is a multiplication of the five erosion factors: the erosivity of the rain, the erodibility of the soil, the inclination and the slope length, the vegetation cover and the anti-erosion practices. The study area is the Moulay Bouchta watershed (7 889 ha), which is located in the western part of the Rif Mountains, is characterized by a complex and contrasting landscape. The resulting soil loss map shows an average erosion rate of 39.5 (t/ha/yr), 87% of the basin has an erosion rate above the tolerance threshold for soil loss (7 (t/ha/yr)). Soil losses per subbasin range from 16.2 to 81.4 (t/ha/yr). The amount of eroded soil is estimated at 311,591 (t/yr), corresponding to a specific degradation of 12.1 (t/ha/yr). In the absence of any erosion control, 25% of the soil losses would reach the new dam located a little upstream of the basin outlet, reducing its water mobilization capacity to 59,625 (m3/yr). The application of Principal Component Analysis (PCA) to soil erosion factors shows a significant influence of topographic factor (LS) on soil erosion process, followed by the effect of support practices (P), then by soil erodibility (K).

scholarly journals Quantification of water related soil erosion in the transboundary basin of the Bia (West Africa)

2021 ◽  
Vol 384 ◽  
pp. 107-112
Author(s):  
N'diaye Edwige Hermann Meledje ◽  
Kouakou Lazare Kouassi ◽  
Yao Alexis N'Go
Keyword(s):  
Soil Erosion ◽  
West Africa ◽  
Vegetation Cover ◽  
Soil Loss ◽  
Catchment Area ◽  
Erosion Rate ◽  
Random Variable ◽  
Erosion Rates ◽  
Transboundary Basin ◽  
Large Heterogeneity

Abstract. In view of the complexity of the phenomenon of water related soil erosion in the Bia catchment area, linked to a large heterogeneity of soils, to a very scattered and in some places non-existent vegetation cover, and to a poorly distributed precipitation in both space and time, a mapping test of the “specific erosion” random variable is undertaken. The mapping of the intensity of the erosion hazard was carried out using the Universal Soil Loss Model (USLE). The map shows that the basin is generally characterized by relatively moderate erosion rates with an average erosion rate of 16 t/ha/year.

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 Soil loss estimation and severity mapping using RUSLE model and GIS: a case study in Megech Watershed, Ethiopia

2022 ◽  
Author(s):  
Legese Abebaw Getu ◽  
Attila Nagy ◽  
Hailu Kendie Addis
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Risk Category ◽  
Model Parameters ◽  
Main Concern ◽  
Slope Length ◽  
Rusle Model ◽  
Soil Erosion Rate ◽  
Very High

Abstract AbstractBackground: Soil erosion is the most serious problem that affects economic development, food security, and ecosystem services which is the main concern in Ethiopia. This study focused on quantifying soil erosion rate and severity mapping of the Megech watershed for effective planning and decision-making processes to implement protection measures. The RUSLE model integrated with ArcGIS software was used to conduct the present study. The six RUSLE model parameters: erosivity, erodibility, slope length and steepness, cover management, and erosion control practices were used as input parameters to predict the average annual soil loss and identify erosion hotspots in the watershed. Results: The RUSLE estimated 1,399,210 tons yr-1 total soil loss from the watershed with a mean annual soil loss of 32.84 tons ha-1yr-1. The soil erosion rate was varied from 0.08 to greater than 500 tons ha-1yr-1. A severity map with seven severity classes was created for 27 sub-watersheds: low (below 10), moderate (10-20), high (20-30), very high (30-35), severe (35-40), very severe (40-45) and extremely severe (above 45) in which the values are in tons ha-1yr-1. The area coverage was 6.5%, 11.1%, 8.7%, 22%, 30.9%, 13.4%, and 7.4% for low, moderate, high, very high, severe, very severe, and extremely severe erosion classes respectively. Conclusion: About 82 % of the watershed was found in more than the high-risk category which reflects the need for immediate land management action. This paper could be important for decision-makers to prioritize critical erosion hotspot areas for comprehensive and sustainable management of the watershed.

scholarly journals Soil Erosion Assessment Using the RUSLE Model and Geospatial Techniques (Remote Sensing and GIS) in South-Central Niger (Maradi Region)

Water ◽  
2021 ◽  
Vol 13 (24) ◽  
pp. 3511
Author(s):  
Mohamed Adou Sidi Almouctar ◽  
Yiping Wu ◽  
Fubo Zhao ◽  
Jacqueline Fifame Dossou
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Management Strategies ◽  
Equation Model ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Erosion Rates ◽  
South Central ◽  
Input Variables

A systematic method, incorporating the revised universal soil loss equation model (RUSLE), remote sensing, and the geographic information system (GIS), was used to estimate soil erosion potential and potential area in the Maradi region of south-central Niger. The spatial trend of seasonal soil erosion was obtained by integrating remote sensing environmental variables into a grid-based GIS method. RUSLE is the most commonly used method for estimating soil erosion, and its input variables, such as rainfall erosivity, soil erodibility, slope length and steepness, cover management, and conservation practices, vary greatly over space. These factors were calculated to determine their influence on average soil erosion in the region. An estimated potential mean annual soil loss of 472.4 t/ac/year, based on RUSLE, was determined for the study area. The potential erosion rates varied from 14.8 to 944.9 t/ac/year. The most eroded areas were identified in central and west-southern areas, with erosion rates ranging from 237.1 to 944.9 t/ac/year. The spatial erosion maps can serve as a useful reference for deriving land planning and management strategies and provide the opportunity to develop a decision plan for soil erosion prevention and control in south-central Niger.

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 Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia

2013 ◽  
Vol 18 (1) ◽  
pp. 81 ◽  
Author(s):  
. Aflizar ◽  
Roni Afrizal ◽  
Tsugiyuki Masunaga
Keyword(s):  
Soil Erosion ◽  
Soil Conservation ◽  
Soil Loss ◽  
Rainfall Erosivity ◽  
Conservation Practices ◽  
Slope Length ◽  
R Factor ◽  
K Factor ◽  
West Sumatra

Quantitative evaluation of soil erosion rate is an important basic to investigate and improve land use system, which has not been sufficiently conducted in Indonesia.  The Universal Soil Loss Equation (USLE) and Erosion Three Dimension (E3D) in Surfer were used to identify characteristic of dominant erosion factors in Sumani Watershed in West Sumatra, Indonesia using data soil survey and monitoring sediment yield in outlet watershed.  Climatology data from three stations were used to calculate Rainfall erosivity (R) factor. As many as101 sampling sites were used to investigate soil erodibility (K-factor) with physico-chemical laboratory analysis. Digital elevation model (DEM) of Sumani Watershed was used to calculate slope length and Steepness (LS-factor). Landsat TM imagery and field survey were used to determine crop management (C-factor) and conservation practices (P-factor). Calculating soil loss and map of USLE factor were determined by Kriging method in Surfer 9. Sumani Watershed had erosion hazard in criteria as: severe to extreme severe (26.23%), moderate (24.59%) and very low to low (49.18%).  Annual average soil loss for Sumani watershed was 76.70 Mg ha-1 y-1 in 2011. Upland area was designated as having a severe to extreme severe erosion hazard compared to lowland which was designated  as having very less to moderate.  On the other land, soil eroded from upland were deposited in lowland. These results were verified by comparing one year’s sediment yield observation on the outlet of the watershed. Land use (C-factor), rainfall erosivity (R- factor), soil erodibility (K-factor), slope length and steepness (LS-factor) were dominant factors that affected soil erosion. Traditional soil conservation practices were applied by farmer for a long time such as terrace in Sawah.  The USLE model in Surfer was used to identify specific regions susceptible to soil erosion by water and was also applied to identify suitable sites to conduct soil conservation planning in Sumani Watershed.[How to Cite : Aflizar, R Afrizal, T Masunaga. 2013. Assessment Erosion 3D Hazard with USLE and Surfer Tool: A Case Study of Sumani Watershed in West Sumatra Indonesia. J Trop Soils, 18 (1): 81-92. doi: 10.5400/jts.2013.18.1.81][Permalink/DOI: www.dx.doi.org/10.5400/jts.2013.18.1.81]

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