scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection: A Case of Fincha Catchment, Ethiopia

2021 ◽  
Vol 14 ◽  
pp. 117862212110462
Author(s):  
Meseret Wagari ◽  
Habtamu Tamiru
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Physical Factors ◽  
Rainfall Erosivity ◽  
Rusle Model ◽  
Raster Calculator ◽  
Gis Environment ◽  
Elevation Model ◽  
The Individual ◽  
P Factor

In this study, Revised Universal Soil Loss Equation (RUSLE) model and Geographic Information System (GIS) platforms were successfully applied to quantify the annual soil loss for the protection of soil erosion in Fincha catchment, Ethiopia. The key physical factors such as rainfall erosivity ( R-factor), soil erodibility ( K-factor), topographic condition (LS-factor), cover management ( C-factor), and support practice ( P-factor) were prepared in GIS environment from rainfall, soil, Digital Elevation Model (DEM), Land use/Land cover (LULC) respectively. The RUSLE equation was used in raster calculator of ArcGIS spatial tool analyst. The individual map of the derived factors was multiplied in the raster calculator and an average annual soil loss ranges from 0.0 to 76.5 t ha−1 yr−1 was estimated. The estimated annual soil loss was categorized based on the qualitative and quantitative classifications as Very Low (0–15 t ha−1 yr−1), Low (15–45 t ha−1 yr−1), Moderate (45–75 t ha−1 yr−1), and High (>75 t ha−1 yr−1). It was found from the generated soil erosion severity map that about 45% of the catchment area was vulnerable to the erosion with an annual soil loss of (>75 t ha−1 yr−1), and this demonstrates that the erosion reduction actions are immediately required to ensure the sustainable soil resources in the study area. The soil erosion severity map generated based on RUSLE model and GIS platforms have a paramount role to alert all stakeholders in controlling the effects of the erosion. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss protection practices.

scholarly journals RUSLE Model Based Annual Soil Loss Quantification for Soil Erosion Protection in Fincha Catchment, Abay River Basin, Ethiopia.

2021 ◽  
Author(s):  
Habtamu Tamiru ◽  
Meseret Wagari
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Factor C ◽  
Significant Factors

Abstract Background: The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. The annual dramatic increment of the depletion of very important soil nutrients exposes the residents of this catchment to high expenses of money to use artificial fertilizers to increase the yield. This paper was conducted in Fincha Catchment where the soil is highly vulnerable to erosion, however, where such studies are not undertaken. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss, where such studies are not undertaken, by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. Results: Digital Elevation Model (12.5 x 12.5), LANDSAT 8 of Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS), Annual Rainfall of 10 stations (2010-2019) and soil maps of the catchment were used as input parameters to generate the significant factors. Rainfall erosivity factor (R), soil erodibility factor (K), cover and management factor (C), slope length and steepness factor (LS) and support practice factor (P) were used as soil loss quantification significant factors. It was found that the quantified average annual soil loss ranges from 0.0 to 76.5 t ha-1 yr-1 was obtained in the catchment. The area coverage of soil erosion severity with 55%, 35% and 10% as low to moderate, high and very high respectively were identified. Conclusion: Finally, it was concluded that having information about the spatial variability of soil loss severity map generated in the RUSLE model has a paramount role to alert land resources managers and all stakeholders in controlling the effects via the implementation of both structural and non-structural mitigations. The results of the RUSLE model can also be further considered along with the catchment for practical soil loss quantification that can help for protection practices.

SOIL EROSION MAPPING OF WATERSHED IN MIRZAPUR DISTRICT USING RUSLE MODEL IN GIS ENVIRONMENT

2016 ◽  
Vol 4 (3) ◽  
pp. 56 ◽  
Author(s):  
Deepanshu Agarwal ◽  
Kunal Tongaria ◽  
Siddhartha Pathak ◽  
Anurag Ohri ◽  
Medha Jha
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Uttar Pradesh ◽  
Rainfall Erosivity ◽  
Agricultural Activity ◽  
Preparation Methods ◽  
Rusle Model ◽  
Calculation Of Parameters ◽  
Erosion Prediction ◽  
Factor C

Soil erosion is one of the serious issues threatening the environment. It is a growing problem especially in areas of agricultural activity where soil erosion not only leads to de-creased agricultural productivity but also reduces water availability. This leads to drastic degradation of the agricultural lands. So there is a need to take up conservation and management measures which can be applied to check further soil erosion. Universal Soil Loss Equation (USLE) is the most popular empirically based model used globally for erosion prediction and control. Remote sensing and GIS techniques have become valuable tools for the digitization of the input data and genereation of maps. In the present study, RUSLE model has been adopted to estimate the soil erosion in the Khajuri watershed of Uttar Pradesh, India. This model involves calculation of parameters including runoff-rainfall erosivity factor (R), soil erodability Factor (K), topographic factor  (LS), cropping management factor (C), and support practice factor (P). Layer wise thematic maps of each of these factors were generated using GIS platform using various data sources and data preparation methods. The results of the study indicate that the annual average soil loss within the watershed is about  t/ha/yr (metric ton per hectare per year).

Identification of Soil Erosion Prone Areas of Madhya Pradesh using USLE/ RUSLE

2021 ◽  
Vol 58 (02) ◽  
pp. 177-191
Author(s):  
Ashwini Suryawanshi ◽  
Anupam Kumar Nema ◽  
Rahul Kumar Jaiswal ◽  
Sukant Jain ◽  
Saswat Kumar Kar
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Madhya Pradesh ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Rusle Model ◽  
Percentage Area ◽  
Support Practice Factor ◽  
Factor C ◽  
Soil Loss Equation

Soil erosion is caused due to the dynamic action of erosive agents, mainly water, and is a major threat to the environment. Primary aim of the present study was to study the soil loss dynamics, and identify the environmental hotspots in Madhya Pradesh to aid decision-makers to plan and prioritize appropriate conservation measures. Universal Soil Loss Equation (USLE) and Revised Universal Soil Loss Equation (RUSLE) models were applied for erosion rate estimation by generating thematic maps of R (Rainfall erosivity factor), K (Soil erodibility factor), LS (Topographic factor), C (Cover and management factor), and P (Support practice factor) factors by using several input parameters in QGIS software. Subsequently, the different classes of soil erosion and percentage area under these classes were identified. The average annual soil erosion for the entire state as obtained from the USLE and RUSLE model were 5.80 t.ha-1.yr-1 and 6.64 t.ha-1.yr-1, respectively. The areas under severe risk were 1.09 % and 1.80 %, and very severe risk areas were 1.57 % and 1.83 % as estimated by USLE and RUSLE model, respectively. As compared to RUSLE model, USLE model underestimated rate of soil erosion for most river basins of the state as well as for the entire state

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

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
R. V Byizigiro ◽  
G Rwanyiziri ◽  
M. Mugabowindekwe ◽  
C. Kagoyire ◽  
M. Biryabarema
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Surface ◽  
Soil Loss ◽  
Slope Angle ◽  
Rainfall Erosivity ◽  
Land Use Patterns ◽  
Rusle Model ◽  
Factor C ◽  
Loss Rates

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

scholarly journals ASSESSMENT OF SOIL EROSION BY RUSLE MODEL IN THE MELLEGUE WATERSHED, NORTHEAST OF ALGERIA

2020 ◽  
Vol 4 (1) ◽  
pp. 15-22
Author(s):  
Kamel Khanchoul ◽  
Kaouther Selmi ◽  
Kaddour Benmarce
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Agricultural Land ◽  
Anthropogenic Activities ◽  
Plant Cover ◽  
Rainfall Erosivity ◽  
Process Data ◽  
Rusle Model ◽  
Basin Area ◽  
Very High

In Algeria, soil erosion has experienced a spectacular extension, it is therefore imperative to assess the effects of this phenomenon. The purpose of this study is to assess soil loss rate using a GIS/USLE approach at the Mellegue watershed, northeast of Algeria. Geographic Information System techniques have been adopted to process data obtained at the study watershed, of reasonable spatial mapping, for the application of the RUSLE model. The model is a multiplication of the five erosion factors, namely rainfall erosivity, soil erodibility, slope and length of slope, plant cover and anti-erosion practices. Each of these factors has been expressed as a thematic map. The resulting soil loss map, with mean erosion rate of 20.40 T/ha/year, shows very low erosion (≤ 7 T/ha/year) which covers 64.60% of the total area of the basin, and very high erosion (> 60 T/ha/year) which does not exceed 4.80% of the basin area. The results indicate that Chabro and downstream Mellegue sub-watersheds face the greatest risk of soil erosion compared to Meskiana sub-basin, with contributions of 14.20 % and 12.90 % of their basin areas respectively. This is mainly due to natural factors and anthropogenic activities without appropriate conservation practices of agricultural land.

scholarly journals Soil erosion vulnerability in the verde river basin, southern minas gerais

2014 ◽  
Vol 38 (3) ◽  
pp. 262-269 ◽  
Author(s):  
Vinícius Augusto de Oliveira ◽  
Carlos Rogério de Mello ◽  
Matheus Fonseca Durães ◽  
Antônio Marciano da Silva
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Minas Gerais ◽  
Annual Rainfall ◽  
Southeastern Brazil ◽  
Rainfall Erosivity ◽  
Verde River ◽  
Gis Environment ◽  
Elevation Model ◽  
Very High

Soil erosion is one of the most significant environmental degradation processes. Mapping and assessment of soil erosion vulnerability is an important tool for planning and management of the natural resources. The objective of the present study was to apply the Revised Universal Soil Loss Equation (RUSLE) using GIS tools to the Verde River Basin (VRB), southern Minas Gerais, in order to assess soil erosion vulnerability. A annual rainfall erosivity map was derived from the geographical model adjusted for Southeastern Brazil, calculating an annual value for each pixel. The maps of soil erodibility (K), topographic factor (LS), and use and management of soils (C) were developed from soils and their uses map and the digital elevation model (DEM) developed for the basin. In a GIS environment, the layers of the factors were combined to create the soil erosion vulnerability map according to RUSLE. The results showed that, in general, the soils of the VRB present a very high vulnerability to water erosion, with 58.68% of soil losses classified as "High" and "Extremely High" classes. In the headwater region of VRB, the predominant classes were "Very High" and "Extremely High" where there is predominance of Cambisols associated with extensive pastures. Furthermore, the integration of RUSLE/GIS showed an efficient tool for spatial characterization of soil erosion vulnerability in this important basin of the Minas Gerais state.

Estimation of Soil Erosion in Three Northern Regions of Ghana Using RUSLE in GIS Environment

2021 ◽  
Vol 12 (2) ◽  
pp. 1-19
Author(s):  
Eliasu Salifu ◽  
Wilson Agyei Agyare ◽  
Nicholas Kyei-Baffour ◽  
Gift Dumedah
Keyword(s):  
Soil Erosion ◽  
Northern Region ◽  
Rainfall Erosivity ◽  
Erosion Rates ◽  
North East ◽  
The North ◽  
Soil Erosion Rate ◽  
Reduction Effect ◽  
Gis Environment ◽  
P Factor

Soil erosion is a global problem with severe consequences, which has become a widespread environmental challenge in the northern parts of Ghana in recent times. This research integrated RUSLE into GIS to estimate the annual soil erosion rates for the Northern, North-East, and Savannah Regions of Ghana. A soil erosion map was generated with an annual soil erosion rate of 4.0 t ha−1y−1 for the Northern Region, 5.0 t ha−1y−1 for the North-East Region, and 7.0 t ha−1y−1 for the Savannah Region. Relatively higher erosion rates were observed in the Tatale Sangule and Kpandai districts of the Northern Region, with rainfall erosivity being the main driving factor. There was a landuse/cover erosion reduction effect of 66% in the Northern Region, 70% in the Northeast Region, and 58% in the Savannah Region. The cover management (C) factor was overwhelmingly the main erosion-reducing factor in erosion control as opposed to land conservation (P) factor.

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

2020 ◽  
Vol 4 (2) ◽  
pp. 70-78
Author(s):  
Khanchoul K. ◽  
Balla F. ◽  
Othmani O.
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Agricultural Land ◽  
Plant Cover ◽  
Rainfall Erosivity ◽  
Productive Capacity ◽  
Rusle Model ◽  
Erosion Loss ◽  
Gis Software ◽  
Soil Erosion By Water

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

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

Agropedology ◽  
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.

scholarly journals Soil Loss Estimation for Conservation Planning in the Welmel Watershed of the Genale Dawa Basin, Ethiopia

Agronomy ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 777 ◽  
Author(s):  
Yared Mesfin Tessema ◽  
Justyna Jasińska ◽  
Lemma Tiki Yadeta ◽  
Marcin Świtoniak ◽  
Radosław Puchałka ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Land Management ◽  
Water Conservation ◽  
Soil Loss ◽  
Management Practices ◽  
Rainfall Erosivity ◽  
Sustainable Livelihood ◽  
Digital Elevation ◽  
Elevation Model ◽  
Agricultural Yields

As a form of environmental degradation, soil degradation directly or indirectly affects many lives through decreased agricultural yields, increased flooding and habitat loss. Soil loss has been increasing in most parts of the world and is most pronounced in tropical developing countries where there is poor or zero soil and water conservation (SWC) planning and management activities. Identifying areas prone to soil erosion has also been inadequate, having not been informed by dedicated scientific studies. This is true of the poorly understood watershed of Welmel in the Oromia region of Ethiopia, where most livelihoods heavily rely upon agriculture. To plan effective SWC management techniques, a solid knowledge of spatial variations across different climate, land use and soil erosion is essential. This study has aimed at identifying potential areas needing SWC practices through conducting a spatial modeling of soil erosion within the Welmel watershed’s Genale Dawa basin using a geographic information system (GIS), remote sensing (RS), multiple factors as land uses and climate. The Welmel catchment is located in southeastern Ethiopia and extends between 5°0′0″ N–7°45′00″ N and 39°0′0″ E–41°15′0″ E. The revised universal soil loss equation (RUSLE), which was previously adapted to Ethiopian conditions, was used to estimate potential soil loss. It used information on interpolated rainfall erosivity (R), soil erodibility (K), vegetation cover (C) and topography (LS) from a digital elevation model (DEM) and that of conservation practices (P) from satellite images. The study demonstrates that the RUSLE using GIS and RS considering different climates and land management practices provides a great advantage in that it allows one to spatially analyze multilayer data in order to identify soil erosion-prone areas and thereby develop the most appropriate watershed management strategy. The mean soil loss was determined to be 31 tons ha−1 year−1 and it varied between 0 and 169 tons ha−1 year−1. About 79% of the watershed lies within the tolerable level of 11 tons ha−1 year−1. However, the remaining 21% has a high soil truncation trait, mainly due to its steeper slope and use as cultivated land. Our study identifies cultivated and deforested areas of the watershed as the potential SWC practice demanding areas. Thus, the application of RUSEL using GIS across different land management practices and climate zones is a potential tool for identifying SWC demanding sites. This remains helpful in efforts towards sustainable land management practices for the sustainable livelihood of the local human population.

Sign in / Sign up

Export Citation Format

Share Document