scholarly journals Quantifying the water soil erosion hazard using RUSLE, GIS, and RS approach: A case study of Al-Qshish River Basin, Lattakia, Syria.

2021 ◽  
Author(s):  
Hazem Ghassan Abdo
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Environmental Sustainability ◽  
Soil Loss ◽  
Coastal Region ◽  
Spatial Average ◽  
Basic Step ◽  
Erosion Hazard ◽  
Gis Environment ◽  
Very High

Abstract Soil erosion is one of the most prominent geomorphological hazards threatening environmental sustainability in the coastal region of western Syria. The current war conditions in Syria has led to a lack of field data and measurements related to assessing soil erosion. Mapping the spatial distribution of potential soil erosion is a basic step in implementing soil preservation procedures mainly in the river catchments. The present paper aims to conduct a comprehensive assessment of soil erosion severity using revised universal soil loss equation (RUSLE) and remote sensing (RS) data in geographic information system (GIS) environment across the whole Al-Qshish river basin. Quantitatively, the annual rate of soil erosion in the study basin was 81.13 t ha− 1 year − 1 with a spatial average reaching 55.18 t ha− 1 year − 1. Spatially, the soil erosion hazard map was produced with classification into five susceptible-zones: very low (40.99%), low (40.49%), moderate (8.90%), high (5.41%) and very high (4.21%). The current study presented a reliable assessment of soil loss rates and classification of erosion-susceptible areas within the study basin. These outputs can be relied upon to create measures for maintaining areas with high and very high soil erosion susceptibility under the current war conditions.

scholarly journals Soil erosion vulnerability in the verde river basin, southern minas gerais

2014 ◽  
Vol 38 (3) ◽  
pp. 262-269 ◽  
Author(s):  
Vinícius Augusto de Oliveira ◽  
Carlos Rogério de Mello ◽  
Matheus Fonseca Durães ◽  
Antônio Marciano da Silva
Keyword(s):  
Soil Erosion ◽  
River Basin ◽  
Minas Gerais ◽  
Annual Rainfall ◽  
Southeastern Brazil ◽  
Rainfall Erosivity ◽  
Verde River ◽  
Gis Environment ◽  
Elevation Model ◽  
Very High

Soil erosion is one of the most significant environmental degradation processes. Mapping and assessment of soil erosion vulnerability is an important tool for planning and management of the natural resources. The objective of the present study was to apply the Revised Universal Soil Loss Equation (RUSLE) using GIS tools to the Verde River Basin (VRB), southern Minas Gerais, in order to assess soil erosion vulnerability. A annual rainfall erosivity map was derived from the geographical model adjusted for Southeastern Brazil, calculating an annual value for each pixel. The maps of soil erodibility (K), topographic factor (LS), and use and management of soils (C) were developed from soils and their uses map and the digital elevation model (DEM) developed for the basin. In a GIS environment, the layers of the factors were combined to create the soil erosion vulnerability map according to RUSLE. The results showed that, in general, the soils of the VRB present a very high vulnerability to water erosion, with 58.68% of soil losses classified as "High" and "Extremely High" classes. In the headwater region of VRB, the predominant classes were "Very High" and "Extremely High" where there is predominance of Cambisols associated with extensive pastures. Furthermore, the integration of RUSLE/GIS showed an efficient tool for spatial characterization of soil erosion vulnerability in this important basin of the Minas Gerais state.

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 A GIS-based estimation of soil erosion parameters for soil loss potential and erosion hazard in the city of Kinshasa, the Democratic Republic of Congo

2018 ◽  
Vol 378 ◽  
pp. 51-57 ◽  
Author(s):  
Martin Tshikeba Kabantu ◽  
Raphael Muamba Tshimanga ◽  
Jean Marie Onema Kileshye ◽  
Webster Gumindoga ◽  
Jules Tshimpampa Beya
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Soil Loss ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Geographical Information ◽  
Republic Of Congo ◽  
Erosion Hazard ◽  
The City ◽  
Very High

Abstract. Soil erosion has detrimental impacts on socio economic life, thus increasing poverty. This situation is aggravated by poor planning and lack of infrastructure especially in developing countries. In these countries, efforts to planning are challenged by lack of data. Alternative approaches that use remote sensing and geographical information systems are therefore needed to provide decision makers with the so much needed information for planning purposes. This helps to curb the detrimental impacts of soil erosion, mostly emanating from varied land use conditions. This study was carried out in the city of Kinshasa, the Democratic Republic of Congo with the aim of using alternative sources of data, based on earth observation resources, to determine the spatial distribution of soil loss and erosion hazard in the city of Kinshasa. A combined approach based on remote sensing skills and rational equation of soil erosion estimation was used. Soil erosion factors, including rainfall-runoff erosivity R), soil erodibility (K), slope steepness and length (SL), crop/vegetation and management (C) were calculated for the city of Kinshasa. Results show that soil loss in Kinshasa ranges from 0 to 20 t ha−1 yr−1. Most of the south part of the urban area were prone to erosion. From the total area of Kinshasa (996 500 ha), 25 013 ha (2.3 %) is of very high ( >  15 t ha−1 yr−1) risk of soil erosion. Urban areas consist of 4.3 % of the area with very high ( >  15 t ha−1 yr−1) risk of soil erosion compared to a very high risk of 2.3 % ( >  15 t ha−1 yr−1) in the rural area. The study shows that the soil loss in the study area is mostly driven by slope, elevation, and informal settlements.

scholarly journals Soil Erosion Susceptibility Prediction in Railway Corridors Using RUSLE, Soil Degradation Index and the New Normalized Difference Railway Erosivity Index (NDReLI)

2022 ◽  
Vol 14 (2) ◽  
pp. 348
Author(s):  
Yashon O. Ouma ◽  
Lone Lottering ◽  
Ryutaro Tateishi
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Soil Degradation ◽  
Bare Soil ◽  
Landsat 8 ◽  
Arid Environments ◽  
Degradation Index ◽  
Erosivity Index ◽  
Loss Index ◽  
Very High

This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better that the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.

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.

RUSLE Model based Assessment of Soil Erosion in Parbati River Basin, Central India using Google Earth Engine and GIS

2021 ◽  
Author(s):  
Rohit Kumar ◽  
Benidhar Deshmukh ◽  
Kiran Sathunuri
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Spatial Pattern ◽  
River Basin ◽  
Soil Loss ◽  
Google Earth ◽  
Rusle Model ◽  
High Soil ◽  
Basin Scale ◽  
Google Earth Engine

<p>Land degradation is a global concern posing significant threat to sustainable development. One of its major aspects is soil erosion, which is recognised as one of the critical geomorphic processes controlling sediment budget and landscape evolution. Natural rate of soil erosion is exacerbated due to anthropogenic activities that may lead to soil infertility. Therefore, assessment of soil erosion at basin scale is needed to understand its spatial pattern so as to effectively plan for soil conservation. This study focuses on Parbati river basin, a major north flowing cratonic river and a tributary of river Chambal to identify erosion prone areas using RUSLE model. Soil erodibility (K), Rainfall erosivity (R), and Topographic (LS) factors were derived from National Bureau of Soil Survey and Land Use Planning, Nagpur (NBSS-LUP) soil maps, India Meteorological Department (IMD) datasets, and SRTM30m DEM, respectively in GIS environment. The crop management (C) and support practice (P) factors were calculated by assigning appropriate values to Land use /land cover (LULC) classes derived by random forest based supervised classification of Sentinel-2 level-1C satellite remote sensing data in Google Earth Engine platform. High and very high soil erosion were observed in NE and NW parts of the basin, respectively, which may be attributed to the presence of barren land, fallow areas and rugged topography. The result reveals that annual rate of soil loss for the Parbati river basin is ~319 tons/ha/yr (with the mean of 1.2 tons/ha/yr). Lowest rate of soil loss (i.e. ~36 tons/ha/yr with mean of 0.22 tons/ha/yr) has been observed in the open forest class whereas highest rate of soil loss (i.e. ~316 tons/ha/yr with mean of 32.08 tons/ha/yr) have been observed in gullied area class. The study indicates that gullied areas are contributing most to the high soil erosion rate in the basin. Further, the rate of soil loss in the gullied areas is much higher than the permissible value of 4.5–11 tons/ha/yr recognized for India. The study helps in understanding spatial pattern of soil loss in the study area and is therefore useful in identifying and prioritising erosion prone areas so as to plan for their conservation.</p>

scholarly journals Estimating Human Impacts on Soil Erosion Considering Different Hillslope Inclinations and Land Uses in the Coastal Region of Syria

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2786 ◽  
Author(s):  
Safwan Mohammed ◽  
Hazem G. Abdo ◽  
Szilard Szabo ◽  
Quoc Bao Pham ◽  
Imre J. Holb ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Agricultural Land ◽  
Human Impacts ◽  
Coastal Region ◽  
Water Erosion ◽  
Land Uses ◽  
Erosion Processes

Soils in the coastal region of Syria (CRoS) are one of the most fragile components of natural ecosystems. However, they are adversely affected by water erosion processes after extreme land cover modifications such as wildfires or intensive agricultural activities. The main goal of this research was to clarify the dynamic interaction between erosion processes and different ecosystem components (inclination, land cover/land use, and rainy storms) along with the vulnerable territory of the CRoS. Experiments were carried out in five different locations using a total of 15 erosion plots. Soil loss and runoff were quantified in each experimental plot, considering different inclinations and land uses (agricultural land (AG), burnt forest (BF), forest/control plot (F)). Observed runoff and soil loss varied greatly according to both inclination and land cover after 750 mm of rainfall (26 events). In the cultivated areas, the average soil water erosion ranged between 0.14 ± 0.07 and 0.74 ± 0.33 kg/m2; in the BF plots, mean soil erosion ranged between 0.03 ± 0.01 and 0.24 ± 0.10 kg/m2. The lowest amount of erosion was recorded in the F plots where the erosion ranged between 0.1 ± 0.001 and 0.07 ± 0.03 kg/m2. Interestingly, the General Linear Model revealed that all factors (i.e., inclination, rainfall and land use) had a significant (p < 0.001) effect on the soil loss. We concluded that human activities greatly influenced soil erosion rates, being higher in the AG lands, followed by BF and F. Therefore, the current study could be very useful to policymakers and planners for proposing immediate conservation or restoration plans in a less studied area which has been shown to be vulnerable to soil erosion processes.

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 AVALIAÇÃO MULTITEMPORAL DAS PERDAS DE SOLOS NA BACIA DO RIO TAQUARIZINHO-MS

2003 ◽  
Vol 52 ◽  
Author(s):  
Antonio Conceição Paranhos Filho ◽  
Alberto Pio Fiori ◽  
Leonardo Disperati ◽  
Cristiane Lucchesi ◽  
Alessandro Ciali ◽  
...  
Keyword(s):  
River Basin ◽  
Soil Loss ◽  
Soil Cover ◽  
Conservation Practices ◽  
Climate Data ◽  
Mato Grosso ◽  
Multi Temporal ◽  
The Mean ◽  
Gis Environment ◽  
Mato Grosso Do Sul

O ambiente SIG (Sistema de Informações Geográficas) é o ideal para integrar dados, informações e cartas de naturezas diferentes. Por exemplo, dados climáticos e cartas topográficas ou de solos podem ser analisados em conjunto, levando toda a informação para uma base comum, o que permite a sua integração e uso. A Equação Universal de Perdas dos Solos (EUPS ou USLE) é atualmente utilizada, com sucesso, como uma forma para a avaliação da perda dos solos por erosão laminar e foi aplicada para a Bacia do Rio Taquarizinho (ao Sul de Coxim, Mato Grosso do Sul), região que apresentou grandes modificações no tipo de uso e ocupação do solo no período analisado. Neste trabalho são apresentados os parâmetros envolvidos com a USLE, alguns obtidos da digitalização de cartas temáticas e tabelas como de Erosividade das chuvas (R), Erodibilidade do solo (K) ou Uso e Manejo do Solo e Práticas Conservacionistas (CP) e outros, como Comprimento (L) e Declividade de vertentes (S,) obtidos em ambiente SIG, através de dados topográficos. O ambiente SIG permitiu a completa integração entre os dados para a obtenção dos parâmetros da USLE e os resultados. Para a Bacia do Rio Taquarizinho a USLE foi aplicada em três diferentes momentos: 1966, 1985 e 1996. Esta aplicação multitemporal mostrou a tendência evolutiva do processo erosivo na região. Para os valores absolutos da taxa de erosão laminar dos solos, de 1966 a 1996, em alguns locais, o desmatamento implicou num aumento da taxa de erosão laminar dos solos em mais de 50 vezes. As perdas médias anuais de solo por erosão laminar foram representadas por valores médios, para toda a Bacia do Taquarizinho, de 4,44 ton/ha. para 1966, de 5,53 ton/ha. para 1985 e de 8,65 ton/ha. para 1996. MULTITEMPORAL EVALUATION OF SOIL LOSS IN THE TAQUARIZINHO BASIN, MATO GROSSO DO SUL - BRAZIL Abstract The GIS - Geographic Information System environment is ideal for integrating data, information and different kinds of maps. For example, climate data and topographic or soil cover maps can be analyzed together, bringing all the information into a common base, thus permitting integration and use. The Universal Soil Loss Equation (USLE) is currently used successfully as a form of evaluating soil loss via laminar erosion, and it was applied to the Taquarizinho River Basin (to the south of Coxim, Mato Grosso do Sul State), a region which showed great changes in the type of use and occupation of the soil during the period analyzed. In the present work are presented the parameters involved in the USLE, some obtained from the digitalization of thematic maps and tables, such as the Rain Erosive Potential (R), Soil Erodability (K), and Cover and Management of the Soil and Conservation Practices (CP), and others, such as Length (L) and Slope Declivity (S), obtained from the GIS environment, from topographic data. The GIS environment permitted a complete integration between the data used to obtain the USLE parameters, and the results. For the Taquarizinho River Basin, the USLE was applied to three different periods: 1966, 1985 and 1996. This multi-temporal application showed a tendency of evolving erosion in the region. Calculations of the absolute values of rates of laminar erosion of the soils indicate that deforestation has lead to an increase of more than fifty times in such erosion, from 1966 to 1996. The mean annual losses of soil from laminar erosion for the entire Taquarizinho River Basin are calculated to have been 4.44 ton/ha in 1996, 5.53 ton/ha in 1985, and 8.65 ton/ha in 1996.

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