scholarly journals Quantification of Soil Losses along the Coastal Protected Areas in Kenya

Land ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 137 ◽  
Author(s):  
Yves Hategekimana ◽  
Mona Allam ◽  
Qingyan Meng ◽  
Yueping Nie ◽  
Elhag Mohamed
Keyword(s):  
Soil Erosion ◽  
Protected Areas ◽  
Coastal Area ◽  
Soil Loss ◽  
Meteorological Data ◽  
Coastal Areas ◽  
Slope Length ◽  
Input Parameters ◽  
Slope Factor ◽  
Factor C

Monitoring of improper soil erosion empowered by water is constantly adding more risk to the natural resource mitigation scenarios, especially in developing countries. The demographical pattern and the rate of growth, in addition to the impairments of the rainfall pattern, are consequently disposed to adverse environmental disturbances. The current research goal is to evaluate soil erosion triggered by water in the coastal area of Kenya on the district level, and also in protected areas. The Revised Universal Soil Loss Equation (RUSLE) model was exercised to estimate the soil loss in the designated study area. RUSLE input parameters were functionally realized in terms of rainfall and runoff erosivity factor (R), soil erodibility factor (K), slope length and gradient factor (LS), land cover management factor (C) and slope factor (P). The realization of RUSLE input parameters was carried out using different dataset sources, including meteorological data, soil/geology maps, the Digital Elevation Model (DEM) and processing of satellite imagery. Out of 26 districts in coastal area, eight districts were projected to have mean annual soil loss rates of >10 t·ha−1·y−1: Kololenli (19.709 t·ha−1·y−1), Kubo (14.36 t·ha−1·y−1), Matuga (19.32 t·ha−1·y−1), Changamwe (26.7 t·ha−1·y−1), Kisauni (16.23 t·ha−1·y−1), Likoni (27.9 t·ha−1·y−1), Mwatate (15.9 t·ha−1·y−1) and Wundanyi (26.51 t·ha−1·y−1). Out of 34 protected areas at the coastal areas, only four were projected to have high soil loss estimation rates >10 t·ha−1·y−1: Taita Hills (11.12 t·ha−1·y−1), Gonja (18.52 t·ha−1·y−1), Mailuganji (13.75.74 t·ha−1·y−1), and Shimba Hills (15.06 t·ha−1·y−1). In order to mitigate soil erosion in Kenya’s coastal areas, it is crucial to regulate the anthropogenic disturbances embedded mainly in deforestation of the timberlands, in addition to the natural deforestation process caused by the wildfires.

scholarly journals The Impact of Farming and Land Ownership on Soil Erosion

2014 ◽  
Vol 62 (5) ◽  
pp. 883-890
Author(s):  
Olga Čermáková ◽  
Miloslav Janeček ◽  
Andrea Jindrová ◽  
Jan Kořínek
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Large Scale ◽  
Research Area ◽  
Water Erosion ◽  
Small Scale ◽  
Slope Length ◽  
The Difference ◽  
Factor C ◽  
The Impact

The aim of this paper was to compare two methods of farming, especially their effect on water soil erosion. The examined methods were (1) large-scale farming, where more than 50% of the land was leased, and (2) small-scale farming, where the land was almost exclusively privately owned. The research area was 8 cadastres in the district of Hodonín, South Moravia, Czech Republic. In these cadastres 48 land blocks representing both large-scale and small-scale farming (i.e. owners and tenants) were chosen. The long-term average annual soil loss caused by water erosion (G) was calculated using the erosion model USLE 2D and ArcGIS 10.1. The nonparametric Mann-Whitney test was used for the statistical evaluation of the data. The difference between the soil loss (G) on land blocks farmed by small producers (owners) and large producers (tenants) was significant (p < 0.05). Differences between the values of the cropping-management factor (C) were not statistically significant (p = 0.054). Based on the analysis of other variables in the USLE equation it can be stated that a continuous slope length, conditioned by the size of land blocks, played an important role in the amount of soil loss caused by water erosion. Above all, to protect the soil from erosion and maintain soil quality it is necessary to reduce the size of land blocks farmed by tenants and improve the crop rotation systems.

scholarly journals Assessment of Soil Erosion by RUSLE Model using Remote Sensing and GIS of Indla-Ghatkhed, District-Amravati, Maharashtra

2021 ◽  
pp. 247-253
Author(s):  
N. W. Ingole ◽  
S. S. Vinchurkar
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Crop Cover ◽  
Conservation Practice ◽  
Slope Length Factor ◽  
Pixel Value ◽  
Factor C ◽  
Soil Erosion Assessment

The catchment boundary of Indla Ghatkhed watershed covers an area about 14..62 sq km. The erosion is a natural geomorphic process occurring continually over the earth’s surface and it largely depends on topography, vegetation, soil and climatic variables and, therefore, exhibits pronounced spatial variability due to catchments heterogeneity and climatic variation. This problem can be circumvented by discrediting the catchments into approximately homogeneous sub-areas using Geographic Information System (GIS). Soil erosion assessment modeling was carried out based on the Revised Universal Soil Loss Equation (RUSLE). A set of factors are involved in RUSLE equation are A = Average annual soil loss (mt/ha/year), R = Rainfall erosivity factor (mt/ha/year), k = Soil erodibility factor, LS = Slope length factor, C = Crop cover management factor, P = Supporting conservation practice factor. These factors extracted from different surface features by analysis and brought in to raster format. The output depicts the amount of sediment rate from a particular grid in spatial domain and the pixel value of the outlet grid indicates the sediment yield at the outlet of the watershed.

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.

scholarly journals Estimation of Soil Erosion using USLE and GIS

2019 ◽  
Vol 8 (2) ◽  
pp. 3936-3939
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Environmental Problem ◽  
Gis Technique ◽  
Economic Imbalances ◽  
Factor C ◽  
Soil Loss Equation

Soil erosion is one of the most serious environmental problem which must be taken in to consideration to prevent economic imbalances in nature. Soil erosion not only affect the agricultural productivity but also increases level of sedimentation. The study was carried out to determine the soil erosion for the watershed which is located in Godavari middle sub basin, Nanded district, Maharashtra state (India). The universal soil loss equation (USLE) and Geographic information system (GIS) technique was used to determine soil erosion. Present study revealed that, the study area is under moderate erosion with an average soil loss 7.233 tones/ha/yr. Where as minimum and maximum erosion rate observed as 5.39 tones/ha/yr to 10.27 tones/ha/yr respectively. The various maps of USLE factors prepared in QGIS environment. Statistically significant relationship obtained between soil loss and cover management factor (C). It was observed that C factor more influences in soil loss than any other factor.

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 Sediment Yield and Soil Loss Estimation Using GIS Based Soil Erosion Model: A Case Study in the MAN Catchment, Madhya Pradesh, India

2021 ◽  
Vol 8 (1) ◽  
pp. 26
Author(s):  
Manti Patil ◽  
Radheshyam Patel ◽  
Arnab Saha
Keyword(s):  
Spatial Distribution ◽  
Soil Erosion ◽  
Soil Loss ◽  
Crop Production ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Reservoir Sedimentation ◽  
Reservoir Water ◽  
Slope Length ◽  
Soil Erosion Rate

Soil erosion is one of the most critical environmental hazards of recent times. It broadly affects to agricultural land and reservoir sedimentation and its consequences are very harmful. In agricultural land, soil erosion affects the fertility of soil and its composition, crop production, soil quality and land quality, yield and crop quality, infiltration rate and water holding capacity, organic matter and plant nutrient and groundwater regimes. In reservoir sedimentation process the consequences of soil erosion process are reduction of the reservoir capacity, life of reservoir, water supply, power generation etc. Based on these two aspects, an attempt has been made to the present study utilizing Revised Universal Soil Loss Equation (RUSLE) has been used in integration with remote sensing and GIS techniques to assess the spatial pattern of annual rate of soil erosion, average annual soil erosion rate and erosion prone areas in the MAN catchment. The RUSLE considers several factors such as rainfall, soil erodibility, slope length and steepness, land use and land cover and erosion control practice for soil erosion prediction. In the present study, it is found that average annual soil erosion rate for the MAN catchment is 13.01-tons/ha/year, which is higher than that of adopted and recommended values for the project. It has been found that 53% area of the MAN catchment has negligible soil erosion rate (less than 2-tons/ha/year). Its spatial distribution found on flat land of upper MAN catchment. It has been detected that 26% area of MAN catchment has moderate to extremely severe soil erosion rate (greater than 10-tons/ha/year). Its spatial distribution has been found on undulated topography of the middle MAN catchment. It is proposed to treat this area by catchment area treatment activity.

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 Modelisation Du Risque D’érosion Hydrique Par L’équation Universelle Des Pertes En Terre Dans Le Rif Occidental: Cas Du Bassin Versant De Moulay Bouchta (Maroc)

2018 ◽  
Vol 14 (3) ◽  
pp. 524 ◽  
Author(s):  
Anis Zouagui ◽  
Mohamed Sabir ◽  
Mustapha Naimi ◽  
Mohamed Chikhaoui ◽  
Moncef Benmansour
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Agricultural Land ◽  
Land Development ◽  
Principal Component ◽  
Slope Length ◽  
Increased Risk ◽  
Effect Of Support ◽  
Soil Losses

Soil erosion causes many environmental and socio-economic problems: loss of biodiversity, decrease in the productivity of agricultural land, siltation of dams and increased risk of flooding. It is therefore essential to establish a detailed evaluation of this process before any spatial planning. To evaluate the effects of soil erosion spatially and quantitatively in order to face this phenomenon, and propose the best conservation and land development strategies, the Universal Soil Loss Equation (USLE) coupled with a geographic information system (GIS) is applied. This model is a multiplication of the five erosion factors: the erosivity of the rain, the erodibility of the soil, the inclination and the slope length, the vegetation cover and the anti-erosion practices. The study area is the Moulay Bouchta watershed (7 889 ha), which is located in the western part of the Rif Mountains, is characterized by a complex and contrasting landscape. The resulting soil loss map shows an average erosion rate of 39.5 (t/ha/yr), 87% of the basin has an erosion rate above the tolerance threshold for soil loss (7 (t/ha/yr)). Soil losses per subbasin range from 16.2 to 81.4 (t/ha/yr). The amount of eroded soil is estimated at 311,591 (t/yr), corresponding to a specific degradation of 12.1 (t/ha/yr). In the absence of any erosion control, 25% of the soil losses would reach the new dam located a little upstream of the basin outlet, reducing its water mobilization capacity to 59,625 (m3/yr). The application of Principal Component Analysis (PCA) to soil erosion factors shows a significant influence of topographic factor (LS) on soil erosion process, followed by the effect of support practices (P), then by soil erodibility (K).

scholarly journals GIS Based Universal Soil Erosion Estimation in District Chakwal Punjab, Pakistan

2020 ◽  
Vol 11 (2) ◽  
pp. 30-36
Author(s):  
Saima Siddiqui ◽  
Mirza Wajid Ali Safi ◽  
Aqil Tariq ◽  
Naveed Ur Rehman ◽  
Syed Waseem Haider
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Management Practices ◽  
Rainwater Harvesting ◽  
Landsat 8 ◽  
River Channels ◽  
Slope Length ◽  
Raster Calculator ◽  
Aster Gdem ◽  
Steep Slopes

Soil erosion is a serious environmental problem faced by district Chakwal. Unpredictable short term and high intensity rainfall, improper cultivation and deforestation have accelerated the soil erosion in the district. The agricultural productivity of the study area can be enhanced by understanding, estimating and controlling the root causes of soil erosion. This study was undertaken to estimate and spatially represent the rate of average annual soil erosion in Chakwal using GIS/RS techniques. The soil erosion was estimated using Universal Soil Loss Equation (USLE) model. To find out parameters of USLE, ASTER GDEM of 30 m resolution was used to estimate slope length and elevation of the study area. Landsat 8 satellite imagery of year 2019, was used to prepare land use map using supervised classification. Soil map with texture and geomorphology was used to identify soils of study area and rainfall data of last 7 years was also studied. Finally, the soil loss has been computed using raster calculator of ArcGIS 10.2 software. The average annual soil loss was predicted up to 268,619 tons/acre/year, of which maximum soil erosion was occurring near the steep slopes and river channels. It is necessary to adapt sustainable land management practices to reduce the risk of further soil erosion, by adopting rainwater harvesting and choosing right crops for suitable soil types.

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.

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