Estimation of soil erosion in a semi-arid watershed of Tamil Nadu (India) using revised universal soil loss equation (rusle) model through GIS

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.

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Identification of Soil Erosion Prone Areas of Madhya Pradesh using USLE/ RUSLE

Journal of Agricultural Engineering ◽

10.52151/jae2021581.1744 ◽

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

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Geospatial Assessment of Soil Erosion Intensity and Sediment Yield Using the Revised Universal Soil Loss Equation (RUSLE) Model

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9060356 ◽

2020 ◽

Vol 9 (6) ◽

pp. 356 ◽

Cited By ~ 3

Author(s):

Ahsen Maqsoom ◽

Bilal Aslam ◽

Usman Hassan ◽

Zaheer Abbas Kazmi ◽

Mahmoud Sodangi ◽

...

Keyword(s):

Soil Erosion ◽

Sediment Yield ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Rusle Model ◽

High Severity ◽

Quantitative Mapping ◽

Severity Class ◽

Very High ◽

Soil Loss Equation

Land degradation caused by soil erosion is considered among the most severe problems of the 21stcentury. It poses serious threats to soil fertility, food availability, human health, and the world ecosystem. The purpose of the study is to make a quantitative mapping of soil loss in the Chitral district, Pakistan. For the estimation of soil loss in the study area, the Revised Universal Soil Loss Equation (RUSLE) model was used in combination with Remote Sensing (RS) and Geographic Information System (GIS). Topographical features of the study area show that the area is more vulnerable to soil loss, having the highest average annual soil loss of 78 ton/ha/year. Maps generated in the study show that the area has the highest sediment yield of 258 tons/ha/year and higher average annual soil loss of 450 tons/ha/year. The very high severity class represents 8%, 16% under high, 21% under moderate, 12% under low, and 13% under very low soil loss in the Chitral district. The above study is helpful to researchers and planners for better planning to control the loss of soil in the high severity zones. Plantation of trees and structures should be built like check dams, which effectively control the soil erosion process.

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Estimativa da erosividade da chuva por diferentes métodos e seu impacto na equação universal de perdas de solo, no semiárido pernambucano (Estimation of erosivity by different methods and their impact on the universal soil loss equation in Pernambuco semi-arid)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v12.3.p859-875 ◽

2019 ◽

Vol 12 (3) ◽

pp. 859

Author(s):

Joaquim Pedro de Santana Xavier ◽

Alexandre Hugo Cezar Barros ◽

Daniel Chaves Webber ◽

Luciano José de Oliveira Accioly ◽

Flávio Adriano Marques ◽

...

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Erosivity ◽

R Factor ◽

Semi Arid Region ◽

Erosion Loss ◽

R Factors ◽

Semi Arid ◽

Soil Loss Equation

Dentre os diversos métodos indiretos para estimar as perdas de solo por erosão, a Equação Universal de Perdas de Solo (EUPS) é a mais utilizada devido a sua robustez e por ser constituída de uma simples estrutura fatorial, que integra fatores naturais e antrópicos atuantes na perda de solos. A erosão é um dos fenômenos mais danosos ao solo e às atividades humanas e por isso seu estudo é importante. Para o cálculo das perdas de solo por meio da EUPS, a avaliação da erosividade das chuvas (fator R) é essencial, pois estima o fenômeno produzido pelas chuvas. O objetivo deste trabalho foi avaliar três metodologias disponíveis de obtenção da erosividade das chuvas para a região do semiárido pernambucano, avaliando sua influência nos resultados da EUPS. Os três modelos selecionados para estimar o Fator R foram desenvolvidos por Wischmeier e Smith (mais conhecido e utilizado), por Silva que estimou valores para diversas regiões do País e por Cantalice e outros que trabalharam especificamente para cada região climática do estado de Pernambuco. Os resultados indicam que as metodologias de Wischmeier e Smith e Silva obtiveram resultados de erosividade da chuva semelhantes, tendo Silva alcançado valores maiores. Cantalice e outros obtiveram os resultados mais baixos. Os resultados da EUPS indicam que, quantitativamente, os diferentes fatores R geram grande diferença nas perdas de solo, porém, qualitativamente chegam a resultados semelhantes na classificação de áreas de maior erosão, de acordo com a FAO. Logo, as três metodologias são viáveis na identificação de áreas prioritárias para a mitigação da erosão. A B S T R A C TAmong several indirect methods to estimate soil erosion loss, the Universal Soil Loss Equation (EUPS) is the most used due to its robustness and because it is constituted of a simple factorial structure that integrates natural and anthropic factors which act in the loss of soils. Erosion is one of the most damaging phenomena to the soil and the human activities, evidencing the importance of studying it. The evaluation of rainfall erosivity (R factor) is essential for the calculation of soil loss through the EUPS, since it is possible to estimate how significant rainfall is to the occurrence of this phenomenon. The objective of this work was to evaluate three methodologies to obtain the rainfall erosivity available for the semi - arid region of Pernambuco, evaluating its influence on the results of the EUPS. The three models used to estimate the R-factor were developed by Wischmeier and Smith, the best known and used model, Silva who estimated values for several regions of the country and Cantalice and others who worked specifically for each climatic region of the state of Pernambuco. As a result, very similar results of rainfall erosivity were obtained between Wischmeier and Smith´s and Silva´s methodology, with Silva reaching higher values of energy amplitude, while Cantalice and others obtained the lowest results. The results of EUPS indicate that, quantitatively, the different R factors generate a large difference in soil loss, but qualitatively they reach similar results in the classification of areas where erosion are greater, according to the FAO. Therefore, the three methodologies are feasible in the identification of priority areas for erosion mitigation.Keywords: soil, rainfall erosivity, USLE, GIS

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

10.22541/au.160946369.92099648/v1 ◽

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.

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Modeling Soil Erosion and Landscape Metric Analysis of River Catchments in Pulau Pinang, Malaysia

Journal of Southwest Jiaotong University ◽

10.35741/issn.0258-2724.55.3.19 ◽

2020 ◽

Vol 55 (3) ◽

Author(s):

Sumayyah Aimi Mohd Najib

Keyword(s):

Land Use ◽

Soil Erosion ◽

Soil Loss ◽

Diversity Index ◽

Land Use Changes ◽

Shannon Diversity Index ◽

Universal Soil Loss Equation ◽

Data Sampling ◽

Shannon Diversity ◽

Soil Loss Equation

To determine the soil erosion in ungauged catchments, the author used 2 methods: Universal Soil Loss Equation model and sampling data. Sampling data were used to verify and validate data from model. Changing land use due to human activities will affect soil erosion. Land use has changed significantly during the last century in Pulau Pinang. The main rapid changes are related to agriculture, settlement, and urbanization. Because soil erosion depends on surface runoff, which is regulated by the structure of land use and brought about through changes in slope length, land-use changes are one of many factors influencing land degradation caused by erosion. The Universal Soil Loss Equation was used to estimate past soil erosion based on land uses from 1974 to 2012. Results indicated a significant increase in three land-use categories: forestry, built-up areas, and agriculture. Another method to evaluate land use changes in this study was by using landscape metrics analysis. The mean patch size of built-up area and forest increased, while agriculture land use decreased from 48.82 patches in 1974 to 22.46 patches in 2012. Soil erosion increased from an estimated 110.18 ton/km2/year in 1974 to an estimated 122.44 ton/km2/year in 2012. Soil erosion is highly related (R2 = 0.97) to the Shannon Diversity Index, which describes the diversity in land-use composition in river basins. The Shannon Diversity Index also increased between 1974 and 2012. The findings from this study can be used for future reference and for ungauged catchment research studies.

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Estimating soil loss from a watershed in Western Deccan, India, using Revised Universal Soil Loss Equation

Landscape & Environment ◽

10.21120/le/10/1/2 ◽

2016 ◽

Vol 10 (1) ◽

pp. 13-25 ◽

Cited By ~ 5

Author(s):

Veena Joshi ◽

Nilesh Susware ◽

Debasree Sinha

Keyword(s):

Conservation Planning ◽

Soil Loss ◽

Tolerance Limit ◽

Design Tool ◽

Universal Soil Loss Equation ◽

The World ◽

Loss Models ◽

Gis Environment ◽

Semi Arid ◽

Soil Loss Equation

USLE (Universal Soil Loss Equation) is the original and the most widely accepted soil loss estimation technique till date which has evolved from a design tool for conservation planning to a research methodology all across the globe. The equation has been revised and modified over the years and became a foundation for several new soil loss models developed all around the world. The equation has been revised as RUSLE by Renard et al. (1991) and is computed in GIS environment. The Revised equation is landuse independent which makes it a useful technique to apply in a variety of environment. The present paper is an attempt to estimate soil loss from a semi-arid watershed in Western Deccan, India by employing RUSLE. The region is a rocky terrain and sediments are restricted to only a few localities. The result indicates that the region is at the threshold of soil tolerance limit.

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