Soil Erosion and Sediment Yield Modelling in the Pra River Basin of Ghana using the Revised Universal Soil Loss Equation (RUSLE) (original) (raw)
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Spatial distribution of soil erosion and sediment yield in the Pra River Basin
SN Applied Sciences
This study demonstrates the application of Revised Universal Soil Loss Equation (RUSLE) and Sediment Distributed Delivery (SEDD) models integrated with Geographic Information System (GIS) to estimate gross soil loss and the sediment delivery of the Pra River Basin in Ghana. Digital Elevation Model, land use map, rainfall data and soil map were input to the model to display the spatial distribution of soil erosion and sediment in the basin. The model estimated an annual soil erosion of 1.28 × 10 6 t/year and an average sediment yield of 2.70 t/ha/year in the basin. Results showed that about 21.3% of the basin is susceptible to severe and very severe erosion. The model results showed that soil erosion rate varied with land use types. It also showed that the Lower Ofin sub-basin has the highest erosion rate. The study demonstrates that the RUSLE and SEDD model integrated with GIS provides relatively easy, cost-effective and fast approach in the estimation of spatially distributed soil erosion and sediment yield of river basins. The results will help in the planning and management of natural resources to ensure sustainable development of the Pra River Basin.
Determination of Soil Erosion Vulnerability in the Lafa Basin of Ghana using RUSLE and GIS
International Journal of Engineering Research and, 2020
Soil erosion is the wearing away of the land surface by physical forces such as rainfall, flowing water, wind, temperature change, gravity, or other natural or anthropogenic agents. Soil erosion is one of the key variables used to assess and appreciate land degradation. The increased soil erosion in some portions of Lafa basin of Ghana has led to siltation of the river channel that is causing flooding in some parts of Accra, Ghana. Lafa basin is the most urbanised basin in Ghana. The objective of this study is to use Revised Universal Soil Loss Equation (RULSE) model and Geographical Information System (GIS) tool to determine the potential and actual soil erosion in the Lafa basin. Rainfall erosivity (R), slope length-steepness (LS), soil erodibility (K), cover management (C) and conversation practice (P) were used to generate soil erosion map and also Normalised Difference Vegetation Difference (NDVI) map from Landsat 7 image was generated to help produce cover management factor map. The model predicted 130 t/ha/yr and 51 t/ha/yr for potential and actual soil erosion of the study area, respectively. According to the model, most parts of the study area was not at risk to soil erosion although a few portions show very severe to highly severe soil erosion risks. The method developed can utilise existing data and provide results that are useful to managers when taking decisions about the management of land resources in the basin.
Soil erosion is a growing problem in Nigeria, particularly in South-Eastern Nigeria. This study focused on the estimation of the rate of soil erosion and soil loss potential using Re-vised Universal Soil Loss Equation (RUSLE2) and ArcGIS in the Upper Ebonyi River watershed. Soil data, land use inventory, digital elevation model, and climatic data were used as resource data sets to generate RUSLE2 factor values in ArcGIS environment. All factors used in RUSLE2 were calculated for the catchment area using local data. The rain-fall erosivity R-factor was calculated from the annual and monthly rainfall data and the soil erodibility K-factor calcu-lated from the soil map. Slopes and overall LS-values in the catchment were obtained from the DEM. The C-factor val-ues were computed using remote sensing (with NDVI). Sup-port practice P-factors were from terraces that exist on slopes. The results of the preliminary soil erosion assessment indicate that the average annual soil loss within the ...
Ghana Mining Journal, 2021
The Bonsa river is an important tributary of the Ankobra river in the Western Region of Ghana. The catchment of the Bonsa river has been undergoing rapid land cover changes due to human activities such as farming, illegal mining, population growth, among others which are likely to promote soil erosion and sediment yield in the river basin. To estimate the amount of soil eroded over a period and subsequent sediment yielded along the Bonsa river basin, the Revised Universal Soil Loss Equation (RUSLE) was integrated with Geographic Information System (GIS) to model the spatial distribution patterns in soil erosion and sediment yield within the catchment. Data used included annual rainfall records, soil map, Digital Elevation Model (DEM) and land-use map of the study area. Parameters of the model were determined and converted into raster layers using the raster calculator tool in ArcMap to produce a soil erosion map. The concept of Sediment Delivery Ratio (SDR) was applied to determine the annual sediment yield by combining a raster SDR layer with soil erosion map. The predicted soil loss and sediment yield values were found to be low. This may be due to high soil protective cover provided by vegetation as well as low topographic relief in the river basin. Though, the elements and processes responsible for soil erosion and sediment yield prevailing in the basin was found to be low, adverse situations could be developed with time if the prevailing conditions are not checked, as soil erosion is a natural gradual slow process. The gains made could be sustained by putting measures in place to control human activities, particularly, illegal mining (galamsey) in the basin, indiscriminate cutting down of trees and farmining activities along the Bansa river basin. This study will support monitoring, planning of water resources and help to improve sustainable water quality.
Modeling Earth Systems and Environment
Soil erosion is the main drivers in the world and Ethiopia in particular. This study has been conducted at Dijo watersheds in the Rift valley Basins of Ethiopia to estimate soil erosion rate and identify erosion hotspot areas for proper planning using Geographic Information System and Universal Soil Loss Equation adapted to Ethiopian condition. 64 years mean annual rainfall data for estimating erosivity factor, digital soil map for estimating soil erodibility factor, Digital Elevation Model for estimating topographic (LS) factor, Land use land cover for cover factor detection from Ethiopian ministry of water resources. The result reveals that the soil loss ranges from 0 ton/ha/year in flat slope to 38.09 ton/ha/year from steep slopes. The average soil loss rate is 2.2 tons per hectare per year and has been classified into three erosion severity classes as very low, low and moderate. The result also reveals that most of the watershed erosion severity evaluated under very low and low ...
MODELING SOIL EROSION USING RUSLE AND GIS TOOLS
George Ashiagbor, Eric K Forkuo, Prosper Laari, Raymond Aabeyir, 2013
Soil erosion involves detachment and transport of soil particles from top soil layers, degrading soil quality and reducing the productivity of affected lands. Soil eroded from the upland catchment causes depletion of fertile agricultural land and the resulting sediment deposited at the river networks creates river morphological change and reservoir sedimentation problems. However, land managers and policy makers are more interested in the spatial distribution of soil erosion risk than in absolute values of soil erosion loss. The aims of this paper is to model the spatial distribution of soil erosion in Densu River Basin of Ghana using RUSLE and GIS tools and to use the model to explore the relationship between erosion susceptibility, slope and Land use and Land Cover (LULC) in the Basin. The rainfall map, digital elevation model, soil type map, and land cover map, were input data in the soil erosion model developed. This model was then categorized into four different erosion risk classes. The developed soil erosion map was then overlaid with the slope and LULC maps of the of the study area to explore their effects on erosion susceptibility of the soil in the Densu River Basin.The Model, predicted 88% of the basin as low erosion risk and 6% as moderate erosion risk3% as high erosion risk and 3% as severe risk. The high and severe erosion areas were distributed mainly within the areas of high slope gradient and also sections of the moderate forest LULC class. Also, the areas within the moderate forest LULC class found to have high erosion risk had an intersecting high erodibility soil group.
Geomatics, 2022
Soil loss caused by erosion has destroyed landscapes, as well as depositing sterile material on fertile lands and rivers, clogged waterways and accelerated flash floods, declined the populations of fish and other species, and diminish soil fertility. In some places, erosion has also destroyed buildings, caused mudflow, create new landforms, displaced people, and slowed down the economy of the affected community by destroying roads and homes. Erosion is aggravated by climate change and anthropogenic factors such as deforestation, overgrazing, inappropriate methods of tillage, and unsustainable agricultural practices. In this study, remote sensing (RS) and geographic information (GIS) data and tools were used to model erosion and estimate soil loss in the catchment area of Koromi-Federe in Jos East, Plateau State Nigeria which is our study area. Soil loss estimation was performed using the revised universal soil loss equation (RUSLE) model and was computed by substituting the corresponding values of each factor inherent in the equation (rainfall erosivity, soil erodibility, slope steepness and slope length, cover management, and conservation practices) using RS and GIS tools. Soil data was obtained from the study area and analyzed in the laboratory, rainfall data, land cover, digital elevation model (DEM), as well as the management practice of the study area were the parameters computed in spatial analyst tool using map algebra based on RUSLE. The soil loss generated was classified into four classes and the results revealed 95.27% of the catchment with a tolerable loss of less than 10 t/h −1 /y −1. At 3.6%, a low or minimal loss of 10-20 t/h −1 /y −1 , at 1.03% there exists a moderate loss of 20-50 t/h −1 /y −1 , while there was and critical or high loss of >50 t/h −1 /y −1 at 0.12% of the catchment. The result showed that critical soil loss in the catchment area is exacerbated by the influence of the slope length and steepness, and the amount of rainfall received. This poses great concern with annual rainfall projected to increase up to 12% in West Africa. However, our sensitivity analysis revealed that it can be reduced with the effect of vegetated cover and management practices. This is an important finding as it can guide sustainability practices to control erosion and the loss of valuable lands in the region, especially now under climate change.
Results in geophysical sciences, 2022
Soil erosion is the main drivers in the world and Ethiopia in particular. This study has been conducted at Dijo watersheds in the Rift valley Basins of Ethiopia to estimate soil erosion rate and identify erosion hotspot areas for proper planning using Geographic Information System and Universal Soil Loss Equation adapted to Ethiopian condition. 64 years mean annual rainfall data for estimating erosivity factor, digital soil map for estimating soil erodibility factor, Digital Elevation Model for estimating topographic (LS) factor, Land use land cover for cover factor detection from Ethiopian ministry of water resources. The result reveals that the soil loss ranges from 0 ton/ha/year in flat slope to 38.09 ton/ha/year from steep slopes. The average soil loss rate is 2.2 tons per hectare per year and has been classified into three erosion severity classes as very low, low and moderate. The result also reveals that most of the watershed erosion severity evaluated under very low and low soil erosion severity classes covering 97.3% of the watershed areas which is due to the effect of mixed plantation of various tree and terraces. However, moderate soil erosion in the upper parts of the watershed could be due to the inherent characteristics of vertisols, lack of vegetation cover and terraces which should be given first priority for conservation interventions. From the gross soil erosion, 43,762 ton/year sediment yields have been estimated at watershed outlet. Policy aim at keeping land productivity will need to focus to reduce low and moderate soil erosion through terracing, inter-cropping, contour farming, strip cropping, conservation tillage, mulching and biological stabilizers based on their slope range, soil type and land use type. The current finding on erosion was evaluated based on the past 10 years land use land cover scenario; therefore, soil erosion might be reduced if the current land use land cover scenario considered. Finally, the integration of USLE and GIS is an effective tool in mapping the spatial distribution of soil erosion from the entire watershed. The moderate and low soil erosion severity areas should be managed through terracing, inter-cropping, contour farming, strip cropping, conservation tillage, mulching and biological stabilizers based on their slope range, soil type and land use type. Free grazing and cultivation of steep slope(Northern parts) contributed for moderate soil erosion in the watershed should be managed by cut-carry system, limiting the number of cattle units to be grazed in the specific plot of land and leaving the marginal steep slope areas with no ground covers for natural regeneration. Finally, the current finding on erosion was evaluated based on the past 10-year land use land cover scenario. Therefore, the soil erosion could be reduced if the current land use land cover scenario is considered. Keywords Conservation priority • Dijo watershed • Sediment yield • Soil erosion • Sub-watersheds • GIS • USLE • SLMP Abbreviations DEM Digital elevation model FAO Food and agricultural organization USLE Universal soil loss equation SCRP Soil conservation research program yr Year LULC Land use land cover ha Hectare WBISPP Woody biomass inventory and strategic planning project Electronic supplementary material The online version of this article (
GEOSPATIAL MODELLING OF SOIL EROSION IN ZARIA LOCAL GOVERNMENT AREA, KADUNA STATE -NIGERIA
The devastating effects of soil erosion on man, food and the environment in different parts of the world cannot be quantified. This study thus, modelled soil erosion using Revised Universal Soil Loss Equation (RUSLE) and Geospatial Information System (GIS) in Zaria Local Government Area (LGA). Rainfall data, soil, digital elevation model (DEM) and Land Use Land Cover (LULC) map of the area were used to determine rainfall erosivity (R-factor), soil erodibility (K-factor), slope factor (LS-factor) and cover management (C-factor), respectively in a GIS environment. The result was integrated based on the RUSLE to estimate the rate of soil erosion. The sediment yield of the study was estimated to be between 0 and 1445.22 t ha-1 year-1. The study indicated that about 78.259 km 2 (19.88%) of the study area have erosion rate of 0-606.42 t ha-1 year-1 while the rates
The Revised Universal Soil Loss Equation (RUSLE) parameters were assessed using Satellite Remote Sensing (RS) and GIS with a view to model soil erosion in Katsina area of Katsina State of Nigeria. Data on parameters such as slope factors, crop cover and management practice support (P) were obtained from obtained for Katsina area for Digital Elevation Model (DEM) and Landsat ETM +, 2002 of the area. The estimated potential mean annual soil loss of 17.35 ton/ac/yr based on the refined RUSLE was obtained for the study area. Also, the potential erosion rates from the erosion classes identified ranged from 0.0 to 4185.12 ton/ac/yr. About 65.47% of the study area was classified under the first class with erosion rate between 0.0 and 10 ton/ac/yr. The most severely eroded area with rates of erosion between 104.80 and 4,185.12 ton/ac/yr accounted for about 1.86% of the study area. On the whole, this study has demonstrated the significance of Satellite (RS) and GIS technologies in modeling erosion.