scholarly journals Estimating Landscape Vulnerability to Soil Erosion by RUSLE Model Using GIS and Remote Sensing: A Case of Zariema watershed, Northern Ethiopia

2020 ◽  
Author(s):  
Yonas Hagos
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Steep Slope ◽  
Annual Rainfall ◽  
Northern Ethiopia ◽  
Rusle Model ◽  
Watershed Area ◽  
Factor C ◽  
Soil Loss Rate

Abstract Background:Zariema watershed located in the Tekeze basin Northern highlands of Ethiopia has been a subject to serious problem of soil erosion. Soil degradation due to soil erosion is one of the key environmental and socioeconomic case which threats soil nutrient depletion and food security in northern Ethiopian highlands. This study was conducted to estimate the soil loss rate and identify hotspot areas using RUSLE model in the Zariema watershed, Tekeze basin, Ethiopia.Methods:The rainfall – runoff erosivity(R) factor was determined from mean annual rainfall, soil erodibility(K) factor from soil map, Topographic factor (Ls) were generated from DEM, Crop management factor (C) and Conservation support practice factor(P) obtained from land use/land cover map. Finally, the factors were integrated with Arc GIS 10.3 tools to estimate soil loss rates and landscape vulnerability to soil erosion of the study watershed. Results:Annual Soil losses rates were estimated to be between 0 ton ha-1 year-1 in plain areas and 989 ton ha-1 year-1 in steep slope areas of the study watershed. The total annual soil loss from the entire watershed area of 2239.33Sq. Km was about 3,603,895.23 tons. About 31.41% of the study areas were affected through the soil loss hazard which is above acceptable soil loss rate 11 ton ha-1 year-1. The spatial hazard classification rate was 68.59% of the watershed area categorized as slight (0 – 11 ton ha-1 year-1), 8.03% moderate (12 – 18 ton ha-1 year-1), 7.64% high (19 – 30 ton ha-1 year-1), 6.65% very high (31 – 50 ton ha-1 year-1) and 9.09% severe (>51 ton ha-1 year-1). Conclusion:As a result, In the cultivation land around steep slope the soil loss rate was in sever condition. To mitigate the severity of the soil erosion in the identified prone area which accounts for about 31.41% of the total watershed area immediate action of soil and water conservation required.

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.

scholarly journals SPATIAL DISTRIBUTION OF SOIL LOSS IN UPPER DIDESSA WATERSHED, ETHIOPIA

2019 ◽  
Vol 4 (4) ◽  
pp. 434-443 ◽  
Author(s):  
Fayera Gudu Tufa ◽  
Tolera Abdissa Feyissa
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Agricultural Land ◽  
Nutrient Loss ◽  
Geographical Information ◽  
Water Supply Systems ◽  
Factor C ◽  
Soil Loss Rate

Soil erosion is dramatically increasing and accelerating in developing countries like Ethiopia. It has worrisome economic and environmental impacts and causes nutrient loss on agricultural land, sedimentation in rivers and reservoirs, clogged canals and other water supply systems. Determination of spatial distribution of soil loss rate in upper Didessa watershed is an important priority for prioritizing the area for watershed management practices in order to reduce soil erosion. The Revised Universal Soil Loss Equation (RUSLE) framed with geographical information system and remote sensing technique was used to estimate the mean annual soil loss in Upper Didessa Watershed, Ethiopia. Digital elevation model (DEM) with 30mx30m resolution was collected from Ministry of Water, Irrigation and Energy and used to delineate the watershed. Soil loss factors of the watershed like length and slope factor (LS), soil erodibility factor (K), cover management factor (C), support practicing factor (P) and rain fall erosivity factor (R) were evaluated and integrated in GIS to compute the annual soil loss rate of the watershed. The results of this work reveal that the annual rate of soil loss in the watershed is 5.23 t / ha / year. They also show that the central part of the watershed is an area prone to soil erosion. DISTRIBUIÇÃO ESPACIAL DA PERDA DO SOLO NA BACIA HIDROGRÁFICA SUPERIOR DIDESSA, ETIÓPIA ResumoA erosão do solo está aumentando e acelerando dramaticamente em países em desenvolvimento como a Etiópia. Tem impactos econômicos e ambientais preocupantes e causa perda de nutrientes em terras agrícolas, sedimentação em rios e reservatórios, entupimento de canais e outros sistemas de fornecimento de água. A determinação da distribuição espacial da taxa de perda de solo na bacia hidrográfica superior do Rio Didessa é uma prioridade importante para priorizar a área para práticas de manejo de bacias hidrográficas a fim de reduzir a erosão do solo. A Equação Universal de Perda de Solo Revisada (RUSLE), enquadrada com sistema de informação geográfica e técnica de sensoriamento remoto, foi usada para estimar a perda média anual de solo na Bacia do Alto Didessa, na Etiópia. O modelo digital de elevação (DEM) com resolução de 30mx30m foi coletado no Ministério da Água, Irrigação e Energia e utilizado para delinear a bacia hidrográfica. Os fatores de perda de solo da bacia hidrográfica, como comprimento e fator de inclinação (LS), fator de erodibilidade do solo (K), fator de manejo da cobertura (C), fator de prática de apoio (P) e fator de erosividade da chuva (R) foram avaliados e integrados no SIG para calcular a taxa anual de perda de solo da bacia hidrográfica. Os resultados deste trabalho revelam que taxa anual de perda de solo da bacia hidrográfica é de 5,23 t / ha / ano. Mostram ainda que a parte central da bacia hidrográfica é uma área propensa à erosão do solo. Palavras-chave: SIG. Perda de solo. RUSLE. Didessa superior da bacia hidrográfica.

scholarly journals Estimation of soil loss rate using the USLE model for Agewmariayam Watershed, northern Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Gebrehana Girmay ◽  
Awdenegest Moges ◽  
Alemayehu Muluneh
Keyword(s):  
Water Conservation ◽  
Soil Loss ◽  
Loss Rate ◽  
Sub Saharan Africa ◽  
Annual Rainfall ◽  
Rainfall Erosivity ◽  
Northern Ethiopia ◽  
Spatial Risk ◽  
Soil Loss Rate ◽  
Loss Rates

Abstract Background Soil erosion and nutrient depletion threaten food security and the sustainability of agricultural production in sub-Saharan Africa. Estimating soil loss and identifying hotspot areas support combating soil degradation. The aim of this paper is to estimate the soil loss rate and identify hotspot areas using USLE model in the Agewmariam watershed, northern Ethiopia. Methods Rainfall erosivity factor was determined from annual rainfall, soil erodibility factor from soil data, slope length and gradient factor were generated from DEM, cover factor and conservation practice factor obtained from land use cover map. Finally, the parameters were integrated with ArcGIS tools to estimate soil loss rates of the study watershed. Results Mean annual soil loss rates were estimated to be between 0 and 897 t ha−1 year−1 on flatter and steeper slopes, respectively. The total annual soil loss was 51,403.13 tons from the watershed and the annual soil loss rate of the study area was 25 t ha−1 year−1. More than 33% of the study areas were above tolerable soil loss rate (11 t ha−1 year−1). The spatial risk categorization rate was 67.2% severe (> 51 t ha−1 year−1), 5.4% very high (31–50 t ha−1 year−1), 5.8% high (19–30 t ha−1 year−1), 3.2% moderate (12–18 t ha−1 year−1) and 18.3% slight (0–11 t ha−1 year−1). Conclusion The results showed that the severity of erosion occurred on the steep slope cultivation, absence of conservation measures, and sparse nature of the vegetation cover. This area required immediate action of soil and water conservation which accounts for about 33.5% of the total watershed.

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 ◽  
Landsat 8 ◽  
Land Resources ◽  
Rusle Model ◽  
Model Based ◽  
Factor C ◽  
Significant Factors

The quantity of soil loss as a result of soil erosion is dramatically increasing in catchment where land resources management is very weak. In this paper, a RUSLE model-based soil loss quanti-fication technique is presented to estimate the annual soil loss and identify the severity of the erosion in the catchment. This study uses Fincha catchment in Abay river basin as the study area to quantify the annual soil loss by implementing Revised Universal Soil Loss Equation (RUSLE) model developed in ArcGIS version 10.4. 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 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. A model builder for the RUSLE model was developed and raster map calcula-tion algebra was applied in ArcGIS version 10.4 to quantify the total annual soil loss. 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. The information about the spatial variation of soil loss severity map generated in RUSLE model has a paramount role to alert land resources man-agers and all stakeholders in controlling the effects via 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.

scholarly journals Assessment of Current and Future Climate Change Impact on Soil Loss Rate of Agewmariam Watershed, Northern Ethiopia

2021 ◽  
Vol 14 ◽  
pp. 117862212199584
Author(s):  
Gebrehana Girmay ◽  
Awdenegest Moges ◽  
Alemayehu Muluneh
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Climate Change Impact ◽  
Soil Loss ◽  
Loss Rate ◽  
Future Climate Change ◽  
Northern Ethiopia ◽  
Rcp 8.5 ◽  
Change Impact ◽  
Soil Loss Rate

Soil erosion is 1 of the most important environmental problems that pose serious challenges to food security and the future development prospects of Ethiopia. Climate change influences soil erosion and is critical for the planning and management of soil and water resources. This study aimed to assess the current and future climate change impact on soil loss rate for the near future (2011-2040), middle future (2041-2070), and far future (2071-2100) periods relative to the reference period (1989-2018) in the Agewmariam watershed, Northern Ethiopia. The 20 models of Coupled Model Intercomparison Project phase 5 global climate models (GCMs) under Representative Concentration Pathway (RCP) 4.5 (intermediate scenario) and 8.5 (high emissions scenario) scenarios were used for climate projection. The statistical bias correction method was used to downscale GCMs. Universal Soil Loss Equation integrated with geographic information system was used to estimate soil loss. The results showed that the current average annual soil loss rate and the annual total soil loss on the study area were found to be 25 t ha−1 year−1 and 51 403.13 tons, respectively. The soil loss has increased by 3.0%, 4.7%, and 5.2% under RCP 4.5 scenarios and 6.0%, 9.52%, and 14.32% under RCP 8.5 scenarios in the 2020s, 2050s, and 2080s, respectively, from the current soil loss rate. Thus, the soil loss rate is expected to increase on all future periods (the 2020s, 2050s, and 2080s) under both scenarios (RCP 4.5 and RCP 8.5) due to the higher erosive power of the future intense rainfall. Thus, climate change will exacerbate the existing soil erosion problem and would need for vigorous new conservation policies and investments to mitigate the negative impacts of climate change on soil loss.

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

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.

Application of Erosion 2D Model for Erosion Studies in Makurdi Metropolis of Benue State, Nigeria

2011 ◽  
Vol 367 ◽  
pp. 815-825 ◽  
Author(s):  
M.O. Isikwue ◽  
T.G. Amile
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Physically Based Model ◽  
Cover Cropping ◽  
Physically Based ◽  
The City ◽  
Land Grading ◽  
2D Model ◽  
Soil Loss Rate

The equations of Erosion 2D Model (a physically based model) were transformed into a computer programme called EROSOFT and used to predict the rate of soil loss in Makurdi metropolis. The model has detachment, transport and deposition components. Four sites were chosen within the metropolis for this study. Soil samples were collected from the sites for laboratory analysis. Rainfall and runoff fluids were collected from the sites to determine their densities. Levelling instrument was used to detremine the channels slopes. The model predicted an average annual soil loss rate of 310kg m-2s-1 for the metropolis. The sensitivity analysis of the model indicates that straight slopes are more prone to soil erosion. The result of the model deviates slightly from established facts that, sandy soils are more erodible and hence prone to be easily detached. Nevertheless, the model shows that soil erosion is influenced by slope geometry and rainfall intensity. The study attributes the major causes of soil erosion in the city to urban runoff concentration and removal of vegetation, and therefore suggests the use of land grading, land forming and cover cropping as well as conservation structures like road side drains for the control of erosion in the metropolis.

GIS estimation of annual average soil loss rate from Hangar River watershed using RUSLE

2019 ◽  
Vol 11 (2) ◽  
pp. 529-539 ◽  
Author(s):  
Mahmud Mustefa ◽  
Fekadu Fufa ◽  
Wakjira Takala
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Study Finding ◽  
Mitigation Measures ◽  
Rainfall Erosivity ◽  
Vegetative Cover ◽  
Annual Average ◽  
Slope Length ◽  
Soil Loss Rate

Abstract Currently, soil erosion is the major environmental problem in the Blue Nile, Hangar watershed in particular. This study aimed to estimate the spatially distributed mean annual soil erosion and map the most vulnerable areas in Hangar watershed using the revised universal soil loss equation. In this model, rainfall erosivity (R-factor), soil erodibility (K-factor), slope steepness and slope length (LS-factor), vegetative cover (C-factor), and conservation practice (P-factor) were considered as the influencing factors. Maps of these factors were generated and integrated in ArcGIS and then the annual average soil erosion rate was determined. The result of the analysis showed that the amount of soil loss from the study area ranges from 1 to 500 tha−1 yr−1 with an average annual soil loss rate of 32 tha−1 yr−1. Considering contour ploughing with terracing as a fully developed watershed management, the resulting soil loss rate was reduced from 32 to 19.2 tha−1 yr−1. Hence, applying contour ploughing with terracing effectively reduces the vulnerability of the watershed by 40%. Based on the spatial vulnerability of the watershed, most critical soil erosion areas were situated in the steepest part of the watershed. The result of the study finding is helpful for stakeholders to take appropriate mitigation measures.

scholarly journals Assessment of Soil Loss Rates in Asreh Watershed (North Jordan Badia) Using RUSLE and GIS

2021 ◽  
Vol 12 (1) ◽  
pp. 10-16
Author(s):  
Saad M. AlAyyash ◽  
Keyword(s):  
Soil Loss ◽  
Loss Rate ◽  
Rainwater Harvesting ◽  
Annual Rainfall ◽  
Physical Factors ◽  
Rainfall Erosivity ◽  
Water Harvesting ◽  
Rainfall Runoff ◽  
Semi Arid ◽  
Soil Loss Rate

In arid lands, rainwater harvesting can play an important role in making more water available since most of the rainfall runoff evaporates. If rainwater can be collected, it will form a useful resource. Jordan is classified as one of the poorest countries regarding water resources with an arid and semi-arid climate. For these limited and vital sources of water, good estimation of rainfall runoff quantity and quality can enhance the sustainability of water harvesting projects. The hydrologic estimations of runoff quantities and qualities are essential, and several techniques to achieve that exist. Revised Universal Soil Loss Equation (RUSLE) is one of the widely used techniques to assess the soil erosion due to runoff, by assessing other physical factors that affect the soil loss. RUSLE combined five parameters to identify the soil loss rate: rainfall erosivity, topographic, soil erodibility, vegetation cover and management, and land management. Based on RUSLE results, areas are classified as a highly soil loss rate if the annual rates exceeded 20 tons per hectare. The Asreh watershed is a 196 km2 area that is mostly wasted land and receives an annual rainfall between 50 and 300 mm per year. The RUSLE equation inputs parameters for the study area are found and the equation is applied for the watershed. Results of RUSLE application on the Asreh watershed showed that the average annual soil loss rate is about 7.8 tons per hectare, about 73% of the area are classified as low soil loss rate with less than 10 tons per hectare per year, and only 13% of the area is classified as a high soil loss rate of more than 20 tons per hectare per year.

scholarly journals Impacts of land use/land cover and climate changes on soil erosion in Muga watershed, Upper Blue Nile basin (Abay), Ethiopia

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Tatek Belay ◽  
Daniel Ayalew Mengistu
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Climate Changes ◽  
Loss Rate ◽  
Land Use Land Cover ◽  
Nile Basin ◽  
Blue Nile Basin ◽  
The Future ◽  
Soil Loss Rate

Abstract Background Soil erosion is one of the major threats in the Ethiopian highlands. In this study, soil erosion in the Muga watershed of the Upper Blue Nile Basin (Abay) under historical and future climate and land use/land cover (LULC) change was assessed. Future LULC was predicted based on LULC map of 1985, 2002, and 2017. LULC maps of the historical periods were delineated from Landsat images, and future LULC was predicted using the CA–Markov chain model. Precipitation for the future period was projected from six regional circulation models. The RUSLE model was used to estimate the current and future soil erosion rate in Muga watershed. Results The average annual rate of soil erosion in the study area was increased from about 15 t ha−1 year−1 in 1985 to 19 t ha−1 year−1 in 2002, and 19.7 t ha−1 year−1 in 2017. Expansion of crop cultivation and loss of vegetation caused an increase in soil erosion. Unless proper measure is taken against the LULC changes, the rate of soil loss is expected to increase and reach about 20.7 t ha−1 year−1 in 2033. In the 2050s, soil loss is projected to increase by 9.6% and 11.3% under RCP4.5 and RCP8.5, respectively, compared with the baseline period. Thus, the soil loss rate is expected to increase under both scenarios due to the higher erosive power of the future intense rainfall. When both LULC and climate changes act together, the mean annual soil loss rate shows a rise of 13.2% and 15.7% in the future under RCP4.5 and RCP8.5, respectively, which is due to synergistic effects. Conclusions The results of this study can be useful for formulating proper land use planning and investments to mitigate the adverse effect of LULC on soil loss. Furthermore, climate change will exacerbate the existing soil erosion problem and would need for vigorous proper conservation policies and investments to mitigate the negative impacts of climate change on soil loss.

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