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

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.

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

Environmental Sciences Proceedings ◽

10.3390/ecas2021-10348 ◽

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.

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

10.20944/preprints202011.0435.v1 ◽

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.

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Impact of Land Cover Change Due to Armed Conflicts on Soil Erosion in the Basin of the Northern Al-Kabeer River in Syria Using the RUSLE Model

Water ◽

10.3390/w12123323 ◽

2020 ◽

Vol 12 (12) ◽

pp. 3323

Author(s):

Hussein Almohamad

Keyword(s):

Soil Erosion ◽

Land Cover ◽

Land Cover Change ◽

Forest Fires ◽

Armed Conflict ◽

Soil Loss ◽

Erosion Rate ◽

Armed Conflicts ◽

Rusle Model ◽

Soil Erosion Rate

Due to armed conflicts, the sudden changes in land cover are among the most drastic and recurring shocks on an international scale, and thus, have become a major source of threat to soil and water conservation. Throughout this analysis, the impact of land cover change on spatio-temporal variations of soil erosion from 2009/2010 to 2018/2019 was investigated using the Revised Universal Soil Loss Equation (RUSLE) model. The goal was to identify the characteristics and variations of soil erosion under armed conflicts in the basin of the Northern Al-Kabeer river in Syria. The soil erosion rate is 4 t ha−1 year−1 with a standard deviation of 6.4 t ha−1 year−1. In addition, the spatial distribution of erosion classes was estimated. Only about 10.1% of the basin is subject to a tolerable soil erosion rate and 79.9% of the study area experienced erosion at different levels. The soil erosion area of regions with no changes was 10%. The results revealed an increase in soil erosion until 2013/2014 and a decrease during the period from 20013/2014 to 2018/2019. This increase is a result of forest fires under armed conflict, particularly toward the steeper slopes. Coniferous forest as well as transitional woodland and scrub are the dominant land cover types in the upper part of the basin, for which the average post-fire soil loss rates (caused by factor C) were 200% to 800% higher than in the pre-fire situation. In the period from 2013/2014 to 2019/2020, soil erosion was mitigated due to a ceasefire that was agreed upon after 2016, resulting in decreased human pressures on soils in contested areas. By comparing 2009/2010 (before war) with 2018/2019 (at the end of the war stage), it can be concluded that the change in C factors slowed down the deterioration trend of soil erosion and reduced the average soil erosion rate in more than half of the basin by about 10–75%. The area concerned is located in the western part of the basin and is relatively far from the centers of armed conflicts. In contrast, the areas with increased soil erosion by about 60–400% are situated in the northeast and east, with shorter distances to armed conflict centers. These findings can be explained by forest fires, after which the burned forests were turned into agricultural land or refugee camps and road areas. Understanding the complex biophysical and socio-economic interactions of exposure to land loss is a key to guarantee regional environmental protection and to conserve the ecological quality of soil and forest systems.

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Influence of DEM resolution on the RUSLE model: Case of abandoned quarries in Settat province (Morocco)

E3S Web of Conferences ◽

10.1051/e3sconf/202131404004 ◽

2021 ◽

Vol 314 ◽

pp. 04004

Author(s):

Nabil Aouichaty ◽

Yassine Bouslihim ◽

Said Hilali ◽

Abdeljalil Zouhri ◽

Yahya Koulali

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Erosion Rate ◽

Loss Rate ◽

Model Case ◽

Rusle Model ◽

Topographic Slope ◽

Soil Erosion Rate ◽

The Impact ◽

Soil Loss Rate

Topographic slope information is one of the critical variables, which governs soil erosion. This topographic slope can be derived from the Digital Elevation Model (DEM). Significant discrepancies are found in the estimation of soil erosion using different DEMs of different resolutions. In the present study, the Revised Universal Soil Loss Equation (RUSLE) was used for soils in the Settat province (Morocco) to assess the risk of water erosion caused by abandoned quarries. The soil erosion rate was divided into five classes to illustrate the erosion rate variability using two DEMs (30m and 90m). The impact of topography on erosion was determined by calculating the value of the LS factors. In this case, the values obtained vary between 0 - 120.623 for ASTER DEM (30m) and 0 - 10.225 for DEM SRTM (90m). The results also show that most quarries have a soil loss rate that varies between 0 t/ha/year and 8.1 t/ha/year for ASTER DEM (30 m). However, for DEM SRTM (90 m), the soil loss rate is zero. This suggests that RUSLE model users should use high-resolution input data for a close representation of reality and capture the maximum results with reasonable accuracy.

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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

ENVIRONMENTAL SYSTEMS RESEARCH ◽

10.1186/s40068-020-00203-3 ◽

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.

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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)

European Scientific Journal ESJ ◽

10.19044/esj.2018.v14n3p524 ◽

2018 ◽

Vol 14 (3) ◽

pp. 524 ◽

Cited By ~ 2

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).

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Sensitivity Assessment of Spatial Resolution Difference in DEM for Soil Erosion Estimation Based on UAV Observations: An Experiment on Agriculture Terraces in the Middle Hill of Nepal

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10010028 ◽

2021 ◽

Vol 10 (1) ◽

pp. 28

Author(s):

Chhabi Lal Chidi ◽

Wei Zhao ◽

Suresh Chaudhary ◽

Donghong Xiong ◽

Yanhong Wu

Keyword(s):

High Resolution ◽

Soil Erosion ◽

Environmental Sustainability ◽

Erosion Rate ◽

Slope Gradient ◽

Slope Length ◽

Dem Resolution ◽

Gradient Slope ◽

Soil Erosion Rate ◽

Sensitivity Assessment

Soil erosion in the agricultural area of a hill slope is a fundamental issue for crop productivity and environmental sustainability. Building terrace is a very popular way to control soil erosion, and accurate assessment of the soil erosion rate is important for sustainable agriculture and environmental management. Currently, many soil erosion estimations are mainly based on the freely available medium or coarse resolution digital elevation model (DEM) data that neglect micro topographic modification of the agriculture terraces. The development of unmanned aerial vehicle (UAV) technology enables the development of high-resolution (centimeter level) DEM to present accurate topographic features. To demonstrate the sensitivity of soil erosion estimates to DEM resolution at this high-resolution level, this study tries to evaluate soil erosion estimation in the Middle Hill agriculture terraces in Nepal based on UAV derived high-resolution (5 × 5 cm) DEM data and make a comparative study for the estimates by using the DEM data aggregated into different spatial resolutions (5 × 5 cm to 10 × 10 m). Firstly, slope gradient, slope length, and topographic factors were calculated at different resolutions. Then, the revised universal soil loss estimation (RUSLE) model was applied to estimate soil erosion rates with the derived LS factor at different resolutions. The results indicated that there was higher change rate in slope gradient, slope length, LS factor, and soil erosion rate when using DEM data with resolution from 5 × 5 cm to 2 × 2 m than using coarser DEM data. A power trend line was effectively used to present the relationship between soil erosion rate and DEM resolution. The findings indicated that soil erosion estimates are highly sensitive to DEM resolution (from 5 × 5 cm to 2 × 2 m), and the changes become relatively stable from 2 × 2 m. The use of DEM data with pixel size larger than 2 × 2 m cannot detect the micro topography. With the insights about the influencing mechanism of DEM resolution on soil erosion estimates, this study provides important suggestions for appropriate DEM data selection that should be investigated first for accurate soil erosion estimation.

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The overshadow of the human evolvement process in the dynamics of soil drift of an agricultural watershed in Nilgiri Hills, India

Soil and Water Research ◽

10.17221/105/2020-swr ◽

2021 ◽

Author(s):

Sangeetha Ramakrishnan ◽

Ambujam Neelakanda Pillai Kanniperumal

Keyword(s):

Soil Erosion ◽

Soil Loss ◽

Agricultural Watershed ◽

Rainfall Erosivity ◽

Landsat Images ◽

Slope Length ◽

Data Format ◽

Conservation Practice ◽

Soil Erosion Rate ◽

Agricultural Planning

The Nilgiri Biosphere, being one of the critical catchments, a small agricultural watershed of Udhagamandalam has been analysed to show the need to improve the agriculture by reducing the soil erosion. For this study, the land use and land cover classification was undertaken using Landsat images to highlight the changes that have occurred between 1981 and 2019. The Revised Universal Soil Loss Equation (RUSLE) method and the Geographic Information System (GIS) was used in this study to determine the soil erosion vulnerability of Sillahalla watershed in the Nilgiri Hills in Tamilnadu. This study will help to promote the economic development of the watershed with proper agricultural planning and erosion management. This study focuses on the estimation of the average annual soil loss and to classify the spatial distribution of the soil loss as a map with the RUSLE method and GIS. To estimate the average annual soil loss of the study area, GIS layers of the RUSLE factors like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C) and conservation practice (P) were computed in a raster data format. The total soil loss and average annual soil loss of the study area for 1981–1990,1991–2000, 2001–2010, 2011–2019 were found to be 0.2, 0.254, 0.3, 0.35 million t/year and 31.33, 37.78, 46.7, 51.89 t/ha/year, respectively. The soil erosion rate is classified into different classes as per the FAO guidelines and this severity classification map was prepared to identify the vulnerable areas.

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Geospatial Assessment of Soil Erosion Intensity and Sediment Yield Using the Revised Universal Soil Loss Equation (RUSLE) Model

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9060356 ◽

2020 ◽

Vol 9 (6) ◽

pp. 356 ◽

Cited By ~ 3

Author(s):

Ahsen Maqsoom ◽

Bilal Aslam ◽

Usman Hassan ◽

Zaheer Abbas Kazmi ◽

Mahmoud Sodangi ◽

...

Keyword(s):

Soil Erosion ◽

Sediment Yield ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Rusle Model ◽

High Severity ◽

Quantitative Mapping ◽

Severity Class ◽

Very High ◽

Soil Loss Equation

Land degradation caused by soil erosion is considered among the most severe problems of the 21stcentury. It poses serious threats to soil fertility, food availability, human health, and the world ecosystem. The purpose of the study is to make a quantitative mapping of soil loss in the Chitral district, Pakistan. For the estimation of soil loss in the study area, the Revised Universal Soil Loss Equation (RUSLE) model was used in combination with Remote Sensing (RS) and Geographic Information System (GIS). Topographical features of the study area show that the area is more vulnerable to soil loss, having the highest average annual soil loss of 78 ton/ha/year. Maps generated in the study show that the area has the highest sediment yield of 258 tons/ha/year and higher average annual soil loss of 450 tons/ha/year. The very high severity class represents 8%, 16% under high, 21% under moderate, 12% under low, and 13% under very low soil loss in the Chitral district. The above study is helpful to researchers and planners for better planning to control the loss of soil in the high severity zones. Plantation of trees and structures should be built like check dams, which effectively control the soil erosion process.

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