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

2016 ◽  
Vol 10 (1) ◽  
pp. 13-25 ◽  
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.

scholarly journals 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)

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

scholarly journals A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates

2018 ◽  
Vol 22 (11) ◽  
pp. 6059-6086 ◽  
Author(s):  
Rubianca Benavidez ◽  
Bethanna Jackson ◽  
Deborah Maxwell ◽  
Kevin Norton
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Gully Erosion ◽  
Data Availability ◽  
Universal Soil Loss Equation ◽  
Soil Productivity ◽  
Temporal Scales ◽  
Erosion Models ◽  
The World ◽  
Soil Loss Equation

Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape to address the problem strategically. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviews the different sub-factors of USLE and RUSLE, and analyses how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with (R)USLE and related approaches. Within each sub-factor section, the strengths and limitations of the different equations are discussed, and guidance is given as to which equations may be most appropriate for particular climate types, spatial resolution, and temporal scale. We investigate some of the limitations of existing (R)USLE formulations, such as uncertainty issues given the simple empirical nature of the model and many of its sub-components; uncertainty issues around data availability; and its inability to account for soil loss from gully erosion, mass wasting events, or predicting potential sediment yields to streams. Recommendations on how to overcome some of the uncertainties associated with the model are given. Several key future directions to refine it are outlined: e.g. incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and compiling consistent units for the future literature to reduce confusion and errors caused by mismatching units. The potential of combining (R)USLE with the Compound Topographic Index (CTI) and sediment delivery ratio (SDR) to account for gully erosion and sediment yield to streams respectively is discussed. Overall, the aim of this paper is to review the (R)USLE and its sub-factors, and to elucidate the caveats, limitations, and recommendations for future applications of these soil erosion models. We hope these recommendations will help researchers more robustly apply (R)USLE in a range of geoclimatic regions with varying data availability, and modelling different land cover scenarios at finer spatial and temporal scales (e.g. at the field scale with different cropping options).

Assessment of Soil Loss using Revised Universal Soil Loss Equation (RUSLE): A Remote Sensing and GIS Approach

2018 ◽  
Vol 2 (1) ◽  
pp. 65-75 ◽  
Author(s):  
Ajaykumar Kadam ◽  
B. N. Umrikar ◽  
R. N. Sankhua
Keyword(s):  
Remote Sensing ◽  
Soil Loss ◽  
Remote Sensing Data ◽  
Tropical Rainfall Measuring Mission ◽  
Remote Sensing And Gis ◽  
Universal Soil Loss Equation ◽  
Rainfall Erosivity ◽  
Slope Length ◽  
Gis Environment ◽  
Soil Loss Equation

A comprehensive methodology that combines Revised Universal Soil Loss Equation (RUSLE), Remote Sensing data and Geographic Information System (GIS) techniques was used to determine the soil loss vulnerability of an agriculture mountainous watershed in Maharashtra, India. The spatial variation in rate of annual soil loss was obtained by integrating raster derived parameter in GIS environment. The thematic layers such as TRMM [Tropical Rainfall Measuring Mission] derived rainfall erosivity (R), soil erodibility (K), GDEM based slope length and steepness (LS), land cover management (C) and factors of conservation practices (P) were calculated to identify their effects on average annual soil loss. The highest potential of estimated soil loss was 688.397 t/ha/yr. The mean annual soil loss is 1.26 t/ha/yr and highest soil loss occurs on the main watercourse, since high slope length and steepness. The spatial soil loss maps prepared with RUSLE method using remote sensing and GIS can be helpful as a lead idea in arising plans for land use development and administration in the ecologically sensitive hilly areas.

scholarly journals A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

2018 ◽  
Author(s):  
Rubianca Benavidez ◽  
Bethanna Jackson ◽  
Deborah Maxwell ◽  
Kevin Norton
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Data Availability ◽  
Water Bodies ◽  
Universal Soil Loss Equation ◽  
Soil Productivity ◽  
Temporal Scales ◽  
Erosion Models ◽  
The World ◽  
Soil Loss Equation

Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape and use land management and other strategies to effectively manage the problem. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviewed the different components of USLE and RUSLE etc., and analysed how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with R/USLE and related approaches. We investigate some of the limitations of R/USLE, such as issues in data-sparse regions, its inability to account for soil loss from gully erosion or mass wasting events, and that it does not predict sediment pathways from hillslopes to water bodies. These limitations point to several future directions for R/USLE studies: incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and using consistent units for future literature. These recommendations help to improve the applicability of the R/USLE in a range of geoclimatic regions with varying data availability, and at finer spatial and temporal scales for scenario analysis.

KAJIAN EROSI LAHAN DI KAWASAN AIR STRIP RUNWAY 2600 BANDARA DEPATI AMIR (PGK) BERDASARKAN TATA GUNA LAHAN MASTERPLAN ULTIMATE

2019 ◽  
Vol 7 (2) ◽  
pp. 100-111
Author(s):  
Miskar Maini ◽  
Junita Eka Susanti
Keyword(s):  
Sediment Yield ◽  
Soil Loss ◽  
Universal Soil Loss Equation ◽  
Delivery Ratio ◽  
Sediment Delivery Ratio ◽  
Sediment Delivery ◽  
Soil Loss Equation

Standar permintaan engineering pesawat agar desain bangunan infrastruktur di area Air Strip Runway 2600 yang ada dapat mempunyai fungsi lain. Sedangkan kondisi lain sangat menentukan keselamatan karena lahan di sekitar Air Strip Runway 2600 Bandara Depati Amir (PGK) jika tidak ditutupi vegetasi seperti rumput, kondisi lain lahan yang belum ditutupi vegetasi di sekitar Air Strip Runway 2600 berpotensi akan mengalami erosi lahan, kemudian hasil erosi lahan ini akan terbawa oleh aliran air sehingga akan masuk ke saluran drainase yang akan menyebabkan sedimentasi pada saluran drainase tersebut, akhirnya akan berkurang efektifitas kinerja saluran drainase tersebut. Metode yang digunakan untuk memprediksi laju rata-rata erosi di area Air Strip Runway 2600 dengan memperhitungkan faktor erosivitas hujan, erodibilitas tanah, kemiringan lereng atau panjang lereng, pengelolaan tanaman dan konservasi tanah, yang masing masing tata guna lahan tersebut mengacu pada Masterplan Ultimate Bandara Depati Amir (PGK). Perhitungan dilakukan menggunakan persamaan USLE (Universal Soil Loss Equation) yang dikembangkan oleh Wischmeier dan Smith (1965, 1978), kemudian Sediment Delivery Ratio (SDR) dan Sediment Yield.Hasil penelitian ini, prediksi laju erosi permukaan pada area Air Strip Runway 2600 Bandara Depati Amir (PGK) tahun pertama yang mencapai 5,60 mm/tahun atau 100,76 Ton/Ha/tahun, laju erosi tahun kedua mencapai 3,38 mm/tahun atau 60,84 Ton/Ha/tahun dapat diklasifikasikan ke dalam kelas bahaya erosi sedang (kelas III) dan nilai SDR adalah sebesar 56,3%, nilai sediment yield (SR) pada tahun pertama sebesar 5.887,59 Ton/Tahun, pada tahun kedua ketika rumput pada area Air Strip telah tumbuh dengan sempurna terjadi penurunan hasil sediment yield yaitu nilai SR sebesar 3.554,85 Ton/Tahun.

Cover and management factors for the Universal Soil-Loss Equation for forest ecosystems in the Marmara region, Turkey

2005 ◽  
Vol 214 (1-3) ◽  
pp. 118-123 ◽  
Author(s):  
Süleyman Özhan ◽  
A. Nihat Balcı ◽  
Necdet Özyuvaci ◽  
Ahmet Hızal ◽  
Ferhat Gökbulak ◽  
...  
Keyword(s):  
Soil Loss ◽  
Forest Ecosystems ◽  
Universal Soil Loss Equation ◽  
Marmara Region ◽  
Management Factors ◽  
Cover And Management Factors ◽  
Soil Loss Equation
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