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 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 Soil erosion assessment of a Himalayan river basin using TRMM data

2015 ◽  
Vol 366 ◽  
pp. 200-200 ◽  
Author(s):  
A. Pandey ◽  
S. K. Mishra ◽  
A. K. Gautam ◽  
D. Kumar
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Daily Rainfall ◽  
Point Of View ◽  
Rainfall Erosivity ◽  
Severe Erosion ◽  
Basin Area ◽  
Very High ◽  
Himalayan River

Abstract. In this study, an attempt has been made to assess the soil erosion of a Himalayan river basin, the Karnali basin, Nepal, using rainfall erosivity (R-factor) derived from satellite-based rainfall estimates (TRMM-3B42 V7). Average annual sediment yield was estimated using the well-known Universal Soil Loss Equation (USLE). The eight-year annual average rainfall erosivity factor (R) for the Karnali River basin was found to be 2620.84 MJ mm ha−1 h−1 year−1. Using intensity–erosivity relationships and eight years of the TRMM daily rainfall dataset (1998–2005), average annual soil erosion was also estimated for Karnali River basin. The minimum and maximum values of the rainfall erosivity factor were 1108.7 and 4868.49 MJ mm ha−1 h−1 year−1, respectively, during the assessment period. The average annual soil loss of the Karnali River basin was found to be 38.17 t ha−1 year−1. Finally, the basin area was categorized according to the following scale of erosion severity classes: Slight (0 to 5 t ha−1 year−1), Moderate (5 to 10 t ha−1 year−1), High (10 to 20 t ha−1 year−1), Very High (20 to 40 t ha−1 year−1), Severe (40 to 80 t ha−1 year−1) and Very Severe (>80 t ha−1 year−1). About 30.86% of the river basin area was found to be in the slight erosion class. The areas covered by the moderate, high, very high, severe and very severe erosion potential zones were 13.09%, 6.36%, 11.09%, 22.02% and 16.64% respectively. The study revealed that approximately 69% of the Karnali River basin needs immediate attention from a soil conservation point of view.

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 Application of Revised Universal Soil Loss Equation (Rusle) Model to Assess Soil Erosion in “Kalu Ganga” River Basin in Sri Lanka

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
D. L. D. Panditharathne ◽  
N. S. Abeysingha ◽  
K. G. S. Nirmanee ◽  
Ananda Mallawatantri
Keyword(s):  
Land Use ◽  
Sri Lanka ◽  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Management Practices ◽  
Agricultural Land ◽  
Universal Soil Loss Equation ◽  
Rusle Model ◽  
Soil Loss Equation

Soil erosion is one of the main forms of land degradation. Erosion contributes to loss of agricultural land productivity and ecological and esthetic values of natural environment, and it impairs the production of safe drinking water and hydroenergy production. Thus, assessment of soil erosion and identifying the lands more prone to erosion are vital for erosion management process. Revised Universal Soil Loss Equation (Rusle) model supported by a GIS system was used to assess the spatial variability of erosion occurring at Kalu Ganga river basin in Sri Lanka. Digital Elevation Model (30 × 30 m), twenty years’ rainfall data measured at 11 rain gauge stations across the basin, land use and soil maps, and published literature were used as inputs to the model. The average annual soil loss in Kalu Ganga river basin varied from 0 to 134 t ha−1 year−1 and mean annual soil loss was estimated at 0.63 t ha−1 year−1. Based on erosion estimates, the basin landscape was divided into four different erosion severity classes: very low, low, moderate, and high. About 1.68% of the areas (4714 ha) in the river basin were identified with moderate to high erosion severity (>5 t ha−1 year−1) class which urgently need measures to control soil erosion. Lands with moderate to high soil erosion classes were mostly found in Bulathsinghala, Kuruwita, and Rathnapura divisional secretarial divisions. Use of the erosion severity information coupled with basin wide individual RUSLE parameters can help to design the appropriate land use management practices and improved management based on the observations to minimize soil erosion in the basin.

scholarly journals Geospatial Analysis of Soil Erosion Susceptibility and Causative Factors in Anambra State, South East, Nigeria

2021 ◽  
pp. 5-32
Author(s):  
Romanus Udegbunam Ayadiuno ◽  
Dominic Chukwuka Ndulue ◽  
Chinemelu Cosmas Ndichie ◽  
Arinze Tagbo Mozie ◽  
Philip O. Phil-Eze ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Soil Loss ◽  
Vegetation Index ◽  
Anthropogenic Activities ◽  
Rainfall Erosivity ◽  
Anambra State ◽  
Causative Factors

Land degradation is a function of soil erosion leading to soil loss and reduction in crop productivity as well as other socio-economic activities. The menace of soil erosion is challenging due to diverse factors including advertent and inadvertent anthropogenic activities. This study looks at soil erosion susceptibility and causative factors in Anambra State, both static and dynamic with the intent of identifying them, investigating spatial variability of soil loss, relate erodibility to soil properties and causative factors to soil erosion. Eight (8) prominent causative factors (CFs), were identified. These causative factors (CFs) were analyzed using ArcGIS 10.2. Sixty (60) soil samples were extracted randomly, analyzed, and tested. The study identified CFs such as Drainage Density, Erosion Density, Lineament Density, Slope Length, Land Surface Temperature, and Rainfall Erosivity, which contribute to Soil Erodibility (K - Factor). Land Surface Temperature, Soil Moisture Index, Rainfall Erosivity, and Normalized Difference Vegetation Index contributed to the loss of 8.97 ton/ha/yr, 9.1288 ton/ha/yr, 1,1134.7 ton/ha/yr, and 0.245 ton/ha/yr respectively to erosion in Anambra State. Conclusively, the dynamic causative factors influence soil susceptibility and trigger erosion in the State.

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).

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.

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 Estimation of soil erosion using USLE and GIS in the locality of Tzicatlacoyan, Puebla, México

2019 ◽  
Vol 15 (No. 1) ◽  
pp. 9-17
Author(s):  
Erika María López-García ◽  
Edgardo Torres-Trejo ◽  
Lucia López-Reyes ◽  
Ángel David Flores-Domínguez ◽  
Ricardo Darío Peña-Moreno ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Soil Loss ◽  
Agricultural Land ◽  
Anthropogenic Activities ◽  
Low Risk ◽  
Average Annual Rate ◽  
Erosion Risk ◽  
Extreme Risk ◽  
Natural Grasslands

Deforestation and conversion of natural grasslands to agricultural land constitute two of the main threats to soil and water conservation, causing erosion, and likely, desertification. The objective of this study was to estimate the erosion of the soil in the locality of Tzicatlacoyan, applying the Universal Soil Loss Equation (USLE) through Geographic Information Systems (GIS). The results indicated that Tzicatlacoyan faces risk of soil erosion with an average annual rate of 117.18 t/ha∙year, due to natural factors and anthropogenic activities such as the use of agricultural land without appropriate conservation practices. Four classes of soil erosion risk were identified, according to the rate of erosion (A) in t/ha∙year: extreme risk (114 ≥ A ≤ 234.36), severe risk (59 ≥ A < 114), moderate risk (23 ≥ A < 59), and low risk (A < 23). Most of the area (180.96 km2, 64.83%) was characterised by the low risk of erosion, while a small part (11.64 km2, 4.17%) of the study area showed extreme risk. The results indicated that 13.33% of the territory of Tzicatlacoyan present values of soil loss exceeding tolerable. The assessment of the soil erosion using the USLE model and GIS might allow land users to make better decisions about the use and conservation of the soil and the ecosystem, adding scientific criteria to their traditional knowledge.

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