Potential Soil Loss Estimation and Erosion-Prone Area Prioritization Using RUSLE, GIS, and Remote Sensing in Chereti Watershed, Northeastern Ethiopia

Soil erosion by water is the major form of land degradation in Chereti watershed, Northeastern Ethiopia. This problem is exacerbated by high rainfall after a long period of dry seasons, undulating topography, intensive cultivation, and lack of proper soil and water conservation measures. Hence, this study aimed to estimate the 23 years (1995-2018) average soil erosion rate of the watershed and to identify and prioritize erosion-vulnerable subwatersheds for conservation planning. The integration of the revised universal soil loss equation (RUSLE), geographic information system, and remote sensing was applied to estimate the long-term soil loss of the watershed. The RUSLE factors such as rainfall erosivity ( R), soil erodibility ( K), topography ( LS), cover and management ( C), and support and conservation practices ( P) factors were computed and overlayed to estimate the soil loss. The result showed that the annual soil loss rate of the watershed ranged up to 187.47 t ha−1 year−1 in steep slope areas with a mean annual soil loss of 38.7 t ha−1 year−1, and the entire watershed lost a total of about 487 057.7 tons of soil annually. About 57.9% of the annual watershed soil loss was generated from 5 subwatersheds which need prior intervention for the planning and implementation of soil conservation measures. The integrated use of RUSLE with GIS and remote sensing was found to be indispensable, less costly, and effective for the estimation of soil erosion, and prioritization of vulnerable subwatersheds for conservation planning.

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Remote Sensing and GIS-Based Soil Loss Assessment Using RUSLE Model -A Case Study of Bareli Watershed, Seoni District of Madhya Pradesh

Agropedology ◽

10.47114/j.agroped.2019.dec1 ◽

2019 ◽

Vol 29 (2) ◽

Author(s):

Sagar N. Ingle ◽

◽

M.S.S. Nagaraju ◽

Nirmal Kumar ◽

Nisha Sahu ◽

...

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Water Conservation ◽

Soil Loss ◽

Madhya Pradesh ◽

Soil And Water Conservation ◽

Rainfall Erosivity ◽

Rusle Model ◽

Conservation Measures ◽

Soil And Water

A quantitative assessment of soil loss was done using Revised Universal Soil Loss Equation (RUSLE) model, remote sensing and digital elevation model (DEM) in integrated raster based GIS in Bareli watershed, Seoni district of Madhya Pradesh. GIS data layers including rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed and integrated to compute average annual soil loss in the watershed. The watershed has been delineated into very low (<10 t ha-1yr-1), low (10–25 t ha-1yr-1), moderate (25–50 t ha-1yr-1), severe (50–100 t ha-1yr-1) and very severe (>100 t ha-1yr-1) soil erosion classes. The study indicated that 63.8% of TGA is under very low to low followed by 14.3% of TGA under moderate soil erosion class. The severe and very severe erosion classes constitute 21.9 % of TGA which warrant immediate attention for preparing strategies for soil and water conservation measures. Various soil and water conservation measures have been suggested based on landforms, soil, slope, land use and soil loss for sustainable management of land resources to improve the productivity of these lands.

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Application of RUSLE integrated with GIS and remote sensing techniques to assess soil erosion in Anambra State, South-Eastern Nigeria

Journal of Water and Climate Change ◽

10.2166/wcc.2020.222 ◽

2020 ◽

Vol 11 (S1) ◽

pp. 407-422 ◽

Cited By ~ 1

Author(s):

Fidelis Odedishemi Ajibade ◽

Nathaniel Azubuike Nwogwu ◽

Bashir Adelodun ◽

Taofeeq Sholagberu Abdulkadir ◽

Temitope Fausat Ajibade ◽

...

Keyword(s):

Remote Sensing ◽

Soil Erosion ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Erosivity ◽

Landsat 8 ◽

Gis And Remote Sensing ◽

Anambra State ◽

Remote Sensing Techniques ◽

Soil Loss Equation

Abstract Soil erosion and mass movement processes spread across Anambra State in Nigeria, therefore making management and conservation techniques expensive and difficult in execution across the entire state. This study employed the Revised Universal Soil Loss Equation (RUSLE) model with the integration of geographic information system (GIS) and remote sensing techniques to assess the risk of soil erosion and hotspots in the area. Remotely sensed data such as Landsat 8 imagery, Shuttle Radar Topography Mission (SRTM) imagery, Era-Interim coupled with world soil database were used as digital data sources for land use map, digital elevation model, rainfall and soil data, respectively, to generate the Universal Soil Loss Equation (USLE) parameters. The results indicated vulnerability levels in low, medium and high cover areas of 4,143.62 (91%), 332.29 (7%) and 84.06 (2%) km2, respectively, with a total soil loss between 0 and 181.237 ton/ha/yr (metric ton per hectare per year). This study revealed that high rainfall erosivity, steep and long slopes, and low vegetation cover were the main factors promoting soil loss in the area. Thus, the amount of soil loss in Anambra State is expected to increase with climate change and anthropogenic activities.

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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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Soil Erosion and Crop Productivity Loss in Palghar and Thane Districts of Maharashtra

Agropedology ◽

10.47114/j.agroped.2018.dec5 ◽

2019 ◽

Vol 28 (2) ◽

Author(s):

S. V. Shejale ◽

◽

S. B. Nandgude ◽

S. S. Salunkhe ◽

M. A. Phadtare ◽

...

Keyword(s):

Soil Erosion ◽

Water Conservation ◽

Soil Loss ◽

Productivity Loss ◽

Research Work ◽

Crop Productivity ◽

Soil And Water Conservation ◽

Conservation Practice ◽

Conservation Measures ◽

Soil And Water

Present research work was carried out on soil erosion and crop productivity loss in Palghar and Thane districts. The study also describes tolerable soil loss and relationship between top-soil loss and yield loss. The estimated average annual soil loss was 40.45 t ha-1yr-1 before adoption of the soil and water conservation measures (by USLE method) and estimated average tolerable soil loss was 9.36 t ha-1 yr-1, for Palghar district. Similarly, for Thane district the estimated average annual soil loss and tolerable soil loss were found to be 35.89 t ha-1 yr-1 and 9.61 t ha-1 yr-1, respectively for Thane district. The estimated average conservation practice factor (P) factors were obtained as 0.32 for Palghar district and 0.30 for Thane district to bring the soil loss below the tolerable limit. After adoption of soil and water conservation measures, the estimated soil loss were 9.02 t ha-1 yr-1 and 9.38 t ha-1 yr-1 for Palghar and Thane districts, respectively.

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The effect of natural infrastructure on water erosion mitigation in the Andes

10.5194/soil-2021-76 ◽

2021 ◽

Author(s):

Veerle Vanacker ◽

Armando Molina ◽

Miluska Rosas-Barturen ◽

Vivien Bonnesoeur ◽

Francisco Román-Dañobeytia ◽

...

Keyword(s):

Soil Erosion ◽

Water Conservation ◽

Soil Loss ◽

Southern Oscillation ◽

Soil And Water Conservation ◽

The Andes ◽

Conservation Measures ◽

Erosion Mitigation ◽

Soil And Water ◽

Loss Rates

Abstract. Soil erosion by water is affecting natural and anthropogenic environments through its impacts on water quality and availability, loss of soil nutrients, flood risk, sedimentation in rivers and streams, and damage to civil infrastructure. Sustainable management aims to avoid, reduce and reverse soil erosion and can provide multiple benefits for the environment, population, and livelihoods. We conducted a systematic review of 121 case studies from the Andes to answer the following questions: (1) Which erosion indicators allow us to assess the effectiveness of natural infrastructure? (2) What is the overall impact of working with natural infrastructure on on-site and off-site erosion mitigation? and (3) Which locations and types of studies are needed to fill critical gaps in knowledge and research? Three major categories of natural infrastructure were considered: protective vegetation, soil and water conservation measures, and adaptation measures that regulate the flow and transport of water. From the suite of physical, chemical and biological indicators commonly used in soil erosion research, two indicators were particularly relevant: soil organic carbon (SOC) of topsoil, and soil loss rates at the plot scale. In areas with protective vegetation and/or soil and water conservation measures, the SOC of topsoil is –on average– 1.3 to 2.8 times higher than in areas under traditional agriculture. Soil loss rates in areas with natural infrastructure were reported to be 38 % to 54 % lower than rates measured in untreated croplands. Further research is needed to evaluate whether the reported effectiveness holds during extreme events related to, for example, El Niño–Southern Oscillation.

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Natural infrastructure interventions and their effect on soil erosion mitigation in the Andes

10.5194/egusphere-egu21-11975 ◽

2021 ◽

Author(s):

Armando Molina ◽

Veerle Vanacker ◽

Miluska Rosas-Barturen ◽

Boris Ochoa-Tocachi ◽

Vivien Bonnesoeur ◽

...

Keyword(s):

Systematic Review ◽

Soil Erosion ◽

Water Conservation ◽

Soil Loss ◽

Soil And Water Conservation ◽

The Andes ◽

Conservation Measures ◽

Erosion Mitigation ◽

Andes Region ◽

Soil And Water

The Andes region is prone to soil erosion because of its steep topographic relief, high spatio-temporal variability in precipitation and heterogeneity in lithological strength. Soil erosion by water is affecting natural and anthropogenic environments through its impacts on water quality and availability, loss of soil nutrients, flood risk, sedimentation in rivers and streams, and damage to civil infrastructure. Sustainable land and water management, referred here as natural infrastructure interventions, aims to avoid, reduce and reverse soil erosion and can provide multiple benefits for the environment, population and livelihoods. In this study, we present a systematic review of peer-reviewed and grey literature involving more than 120 local case-studies from the Andes. Three major categories of natural infrastructure interventions were considered: protective vegetation, soil and water conservation measures, and adaptation measures that regulate the flow and transport of water. The analysis was designed to answer the following research questions: (1) Which soil erosion indicators allow us to assess the effectiveness of natural infrastructure interventions across the Andean range? (2) What is the overall impact of implementing natural infrastructure interventions for on-site and off-site erosion mitigation?The systematic review shows that the effectiveness of protective vegetation on soil erosion mitigation is the most commonly studied characteristic, accounting for more than half of the empirical studies. From the suite of physical, chemical and biological indicators that were commonly used in soil erosion research, our review identified two indicators to be particularly suitable for the analyses of the effectiveness of natural infrastructure interventions: soil organic carbon (SOC) of the topsoil, and soil loss rates at plot scale. The implementation of soil and water conservation measures in areas under traditional agriculture had positive effects on SOC (1.28 to 1.29 times higher SOC than in agricultural land). Soil loss rates were 54% lower when implementing SWC than on cropland. When implementing SWC in rangeland, the data indicated an increase in soil loss rate by 1.54 times. Untreated degraded land is reported to have significantly higher soil loss and specific sediment yield compared to cropland.The results of this systematic review allows to assess the overall effectiveness of commonly used natural infrastructure interventions, which can guide policy and decision making in the Andes. Similarly, the review identified critical gaps in knowledge that must be attended by more comprehensive research to consider the high spatiotemporal variability of the Andes region.

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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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Terrain Characterization and Soil Erosion Risk Assessment for Watershed Prioritization Using Remote Sensing and GIS (A case study of Nawagaon Maskara Rao Watershed, Saharanpur, India)

Forum Geografi ◽

10.23917/forgeo.v23i1.5001 ◽

2009 ◽

Vol 23 (1) ◽

pp. 86

Author(s):

Beny Harjadi

Keyword(s):

Remote Sensing ◽

Risk Assessment ◽

Land Use ◽

Soil Erosion ◽

Soil Conservation ◽

Soil Loss ◽

Remote Sensing And Gis ◽

Erosion Risk ◽

Soil Erosion Risk ◽

Conservation Measures

Soil erosion is crucial problem in India where more than 70% of land in degraded. This study is to establish conservation priorities of the sub watersheds across the entire terrain, and suggest suitable conservation measures. Soil conservation practices are not only from erosion data both qualitative SES (Soil Erosion Status) model and quantitative MMF (Morgan, Morgan and Finney) model erosion, but we have to consider LCC (Land Capability Classification) and LULC (Land Use Land Cover). Study demonstrated the use of RS (Remote Sensing) and GIS (Geographic Information System) in soil erosion risk assessment by deriving soil and vegetation parameters in the erosion models. Sub-watersheds were prioritized based on average soil loss and the area falls under various erosion risk classes for conservation planning. The annual rate of soil loss based on MMF model was classified into five soil erosion risk classes for soil conservation measures. From 11 sub watersheds, for the first priority of the watershed is catchment with the small area and the steep slope. Recommendation for steep areas (classes VI, VII, and VIII) land use allocation should be made to maintain forest functions.

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

10.20944/preprints202009.0082.v1 ◽

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.

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