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 Estimation of annual soil erosion dynamics (2005 - 2015) in Pakistan using Revised Universal Soil Loss Equation (RUSLE)

2021 ◽  
Author(s):  
Hammad Gilani ◽  
Adeel Ahmad ◽  
Isma Younes ◽  
Sawaid Abbas
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Management Practices ◽  
Climatic Factors ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Conservation Practice ◽  
Administrative Units ◽  
Soil Loss Equation

Abrupt changes in climatic factors, exploitation of natural resources, and land degradation contribute to soil erosion. This study provides the first comprehensive analysis of annual soil erosion dynamics in Pakistan for 2005 and 2015 using publically available climatic, topographic, soil type, and land cover geospatial datasets at 1 km spatial resolution. A well-accepted and widely applied Revised Universal Soil Loss Equation (RUSLE) was implemented for the annual soil erosion estimations and mapping by incorporating six factors; rainfall erosivity (R), soil erodibility (K), slope-length (L), slope-steepness (S), cover management (C) and conservation practice (P). We used a cross tabular or change matrix method to assess the annual soil erosion (ton/ha/year) changes (2005-2015) in terms of areas and spatial distriburtions in four soil erosion classes; i.e. Low (<1), Medium (1–5], High (5-20], and Very high (>20). Major findings of this paper indicated that, at the national scale, an estimated annual soil erosion of 1.79 ± 11.52 ton/ha/year (mean ± standard deviation) was observed in 2005, which increased to 2.47 ±18.14 ton/ha/year in 2015. Among seven administrative units of Pakistan, in Azad Jammu & Kashmir, the average soil erosion doubled from 14.44 ± 35.70 ton/ha/year in 2005 to 28.03 ± 68.24 ton/ha/year in 2015. Spatially explicit and temporal annual analysis of soil erosion provided in this study is essential for various purposes, including the soil conservation and management practices, environmental impact assessment studies, among others.

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.

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.

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 New Insight on Soil Loss Estimation in the Northwestern Region of the Zagros Fold and Thrust Belt

2021 ◽  
Vol 10 (2) ◽  
pp. 59
Author(s):  
Arsalan Ahmed Othman ◽  
Ahmed K. Obaid ◽  
Diary Ali Mohammed Amin Al-Manmi ◽  
Ahmed F. Al-Maamar ◽  
Syed E. Hasan ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Landsat Imagery ◽  
Economic Problem ◽  
Mitigation Measures ◽  
Reliable Estimate ◽  
Thrust Belt ◽  
Slope Length ◽  
Fold And Thrust Belt ◽  
Basin Scale

Soil loss is one of the most important causes of land degradation. It is an inevitable environmental and socio-economic problem that exists in many physiographic regions of the world, which, besides other impacts, has a direct bearing on agricultural productivity. A reliable estimate of soil loss is critical for designing and implementing any mitigation measures. We applied the widely used Revised Universal Soil Loss Equation (RUSLE) in the Khabur River Basin (KhRB) within the NW part of the Zagros Fold and Thrust Belt (ZFTB). The areas such as the NW Zagros range, characterized by rugged topography, steep slope, high rainfall, and sparse vegetation, are most susceptible to soil erosion. We used the Digital Elevation Model (DEM) of the Shuttle Radar Topography Mission (SRTM), Tropical Rainfall Measuring Mission (TRMM), Harmonized World Soil Database (HWSD), and Landsat imagery to estimate annual soil loss using the RUSLE model. In addition, we estimated sediment yield (SY) at sub-basin scale, in the KhRB where a number of dams are planned, and where basic studies on soil erosion are lacking. Estimation of SY will be useful in mitigation of excessive sedimentation affecting dam performance and watershed management in this region. We determined the average annual soil loss and the SY in the KhRB to be 11.16 t.ha−1.y−1 and 57.79 t.ha−1.y−1, respectively. The rainfall and runoff erosivity (R factor), slope length (L factor), and slope steepness (S factor), are the three main factors controlling soil loss in the region. This is the first study to determine soil loss at the sub-basin scale along with identifying suitable locations for check dams to trap the sediment before it enters downstream reservoirs. The study provides valuable input data for design of the dams to prevent excessive siltation. This study also aims at offering a new approach in relating potential soil erosion to the actual erosion and hypsometric integrals.

scholarly journals ESTIMATION OF ANNUAL AVERAGE SOIL LOSS, BASED ON RUSLE MODEL IN KALLAR WATERSHED, BHAVANI BASIN, TAMIL NADU, INDIA

2015 ◽  
Vol II-2/W2 ◽  
pp. 207-214 ◽  
Author(s):  
S. Abdul Rahaman ◽  
S. Aruchamy ◽  
R. Jegankumar ◽  
S. Abdul Ajeez
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Tamil Nadu ◽  
Rainfall Erosivity ◽  
Storm Events ◽  
Rill Erosion ◽  
Slope Length ◽  
Conservation Practice ◽  
Erosion Risk ◽  
Wide Range

Soil erosion is a widespread environmental challenge faced in Kallar watershed nowadays. Erosion is defined as the movement of soil by water and wind, and it occurs in Kallar watershed under a wide range of land uses. Erosion by water can be dramatic during storm events, resulting in wash-outs and gullies. It can also be insidious, occurring as sheet and rill erosion during heavy rains. Most of the soil lost by water erosion is by the processes of sheet and rill erosion. Land degradation and subsequent soil erosion and sedimentation play a significant role in impairing water resources within sub watersheds, watersheds and basins. Using conventional methods to assess soil erosion risk is expensive and time consuming. A comprehensive methodology that integrates Remote sensing and Geographic Information Systems (GIS), coupled with the use of an empirical model (Revised Universal Soil Loss Equation- RUSLE) to assess risk, can identify and assess soil erosion potential and estimate the value of soil loss. GIS data layers including, rainfall erosivity (R), soil erodability (K), slope length and steepness (LS), cover management (C) and conservation practice (P) factors were computed to determine their effects on average annual soil loss in the study area. The final map of annual soil erosion shows a maximum soil loss of 398.58 t/ h<sup>-1</sup>/ y<sup>-1</sup>. Based on the result soil erosion was classified in to soil erosion severity map with five classes, very low, low, moderate, high and critical respectively. Further RUSLE factors has been broken into two categories, soil erosion susceptibility (A=RKLS), and soil erosion hazard (A=RKLSCP) have been computed. It is understood that functions of C and P are factors that can be controlled and thus can greatly reduce soil loss through management and conservational measures.

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

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.

A thousand-year erosional and sedimentation history in karst watersheds based on OSL dating and palynological techniques

2021 ◽  
Author(s):  
Zihao Cao ◽  
Qihua Ke ◽  
Keli Zhang ◽  
Zhuodong Zhang
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Loss Rate ◽  
Local Economic Development ◽  
Osl Dating ◽  
Dominant Factor ◽  
Rocky Desertification ◽  
Peak Cluster ◽  
The Past ◽  
Soil Loss Rate

&lt;p&gt;Rocky desertification is a serious environmental issue in karst regions that restricts food production and hinders local economic development. Generally, soil loss is known as a dominant factor driving rocky desertification. However, it is difficult to couple rocky desertification with the soil loss rate based on a database from short-term field plot observations. Hence, it is imperative to reconstruct the history of soil loss over long-term periods and to correlate the rocky desertification process with the soil loss rate. In karst regions, the most common geomorphic landforms are closed peak-cluster depressions. Researchers have shown that estimating soil loss from hillslopes based on a sediment deposition rate in a peak-cluster depression is possible. In this study, two typical peak-cluster depressions with different degrees of rocky desertification were selected, and sediment cores with lengths of 2 m were sampled from the depressions to determine pollen taxa, soil properties and sediments dating at different depths.The results showed that the burial ages of the sediments in the depressions were different in the time series. During the past millennium, soil loss in the LJWD watershed showed an overall decreasing and then increasing trend. While the change in soil erosion was more complex in the DJT watershed, high and low rates appeared alternately in the 748&amp;#177;100 &amp;#8211; 2018 period. The alluvial pollen analysis demonstrated that the soil erosion changes in both watersheds were closely related to human farming activities and vegetation landscape changes. The soil loss history over the past 1000 years was insufficient to reveal the evolution of rocky deserts in karst areas, indicating that the formation of rocky deserts should have occurred over a longer historical period. Overall, the optically stimulated luminescence (OSL) dating and palynological techniques were reliable in the investigation of local erosional history in karst regions.&lt;/p&gt;

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