ACOMPARISON OF THE R-FACTOR IN THE UNIVERSAL SOIL LOSS EQUATION AND REVISED UNIVERSAL 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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Spatial and temporal prediction and uncertainty of soil loss using the revised universal soil loss equation: a case study of the rainfall–runoff erosivity R factor

Ecological Modelling ◽

10.1016/s0304-3800(01)00507-5 ◽

2002 ◽

Vol 153 (1-2) ◽

pp. 143-155 ◽

Cited By ~ 60

Author(s):

Guangxing Wang ◽

George Gertner ◽

Vivek Singh ◽

Svetlana Shinkareva ◽

Pablo Parysow ◽

...

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Runoff ◽

Temporal Prediction ◽

R Factor ◽

Soil Loss Equation

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A Review on Rainfall Erosivity (R factor) in Universal Soil Loss Equation

International Journal of Academic Research in Business and Social Sciences ◽

10.6007/ijarbss/v8-i2/3988 ◽

2018 ◽

Vol 8 (2) ◽

Author(s):

Mohamad Nazuhan ◽

Zullyadini A. Rahaman ◽

Zainuddin Othman

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Erosivity ◽

R Factor ◽

Soil Loss Equation

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Rainfall Erosivity and Erodibility of Inceptisols in the Southwest Colombian Andes

Experimental Agriculture ◽

10.1017/s0014479700025904 ◽

1996 ◽

Vol 32 (1) ◽

pp. 91-101 ◽

Cited By ~ 12

Author(s):

M. Ruppenthal ◽

D. E. Leihner ◽

T. H. Hilger ◽

J. A. Castillo F.

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Clay Soils ◽

Rainfall Erosivity ◽

Soil Erodibility ◽

Study Region ◽

The Third ◽

R Factor ◽

Colombian Andes ◽

Soil Loss Equation

SUMMARYThe rainfall erosivity (R) and soil erodibility (K) factors of the Universal Soil Loss Equation (USLE) were determined on two sites in the Colombian Cauca Department over a five year period when rainfall was mostly lower than average. The results showed that the high erosion potential of the soils can be attributed more to high rain erosivity than soil erodibility. The R factor explained between 59 and 81% of the variation in soil loss recorded on continuously clean-tilled fallow plots. The erodibility of Inceptisols in the study region is classified as low. Values for soil erodibility (K) ranged from 0.012 to 0.015 (measured in SI units) in the fifth year of permanent bare fallowing. K factors were higher in the rainy than in the dry season. Soils, previously under grass vegetation, were very resistant to erosion in the first two years of bare fallowing. In the third year erodibility increased sharply and continued to increase steadily until the sixth year. K factors predicted by the USLE nomograph underestimated the empirically-determined erodibility of these highly aggregated clay soils.

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Rainfall erosivity estimation using gridded daily precipitation datasets

10.5194/hess-2020-633 ◽

2020 ◽

Author(s):

Maoqing Wang ◽

Shuiqing Yin ◽

Tianyu Yue ◽

Bofu Yu ◽

Wenting Wang

Keyword(s):

Soil Loss ◽

Daily Precipitation ◽

Universal Soil Loss Equation ◽

Lower Probability ◽

Rainfall Erosivity ◽

Correction Factors ◽

Random Errors ◽

Gridded Data ◽

R Factor ◽

Soil Loss Equation

Abstract. Rainfall erosivity is one of the most important factors incorporated into the empirical soil erosion models USLE (Universal Soil Loss Equation) and RUSLE (Revised Universal Soil Loss Equation). Gridded precipitation datasets have been widely used in the estimation of rainfall erosivity, whereas biases due to scale differences between gridded data and gauge data have been ignored. Based on daily precipitation observations from over 2000 stations in China, as well as four widely used gauge-based gridded daily precipitation datasets, CPC, GPCC, CN05.1 and NMIC, this study compared the probability density functions (PDFs) of the gridded and gauge datasets using the skill score method, quantified the bias of rainfall erosivity (including the R-factor and 1-in-10-year event rainfall erosivity) estimated using the gridded daily precipitation datasets from that estimated using the gauge daily precipitation dataset based on the area reduction factor (ARF) method, and established correction factors for rainfall erosivity maps generated from gridded datasets. The results showed that the gridded daily data reduced the frequency of no-rain days and the intensity of heavy precipitation. In the eastern part of China, the grid-estimated R-factor values were underestimated by 15–40 % compared with the gauge-estimated values, and the grid-estimated 1-in-10-year event rainfall erosivity values were underestimated by 25–50 %, whereas in the western part of China, noticeable random errors were introduced. The lower probability and intensity of the daily precipitation larger than the 90th percentile in the gridded datasets were mainly responsible for the underestimation. CN05.1 was the most-recommended among the four datasets, as it had the lowest mean relative error (MRE), and the accuracy was higher for the eastern part of China than for the western part of China. The MREs were 16.1 % and 25.1 % for the R-factor after applying correction factors of 1.708 and 1.010, respectively, for the eastern and western part of China. The 1-in-10-year event erosivity had larger correction factors and MREs than did the R-factor, with the MREs being 22.1 % and 27.2 % after applying correction factors of 1.959 and 1.880, respectively, for the eastern and western part of China. This study pointed out that in the applications of gridded precipitation datasets, the empirical models established based on gauge precipitation data should not be used directly for the gridded data, or a bias correction process needed to be considered for the model outputs.

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Differentiation and regionalization of rainfall erosivity factor values in the Czech Republic

Soil and Water Research ◽

10.17221/2/2011-swr ◽

2012 ◽

Vol 7 (No. 1) ◽

pp. 1-9 ◽

Cited By ~ 4

Author(s):

M. Janeček ◽

V. Květoň ◽

E. Kubátová ◽

D. Kobzová

Keyword(s):

Czech Republic ◽

Soil Loss ◽

Universal Soil Loss Equation ◽

Rainfall Erosivity ◽

The Czech Republic ◽

Average Value ◽

R Factor ◽

Soil Loss Equation

The rain erosivity R-factor is one of the main parameters in the Universal Soil Loss Equation (USLE). This paper describes the procedure used to update, differentiate and regionalize the rainfall erosivity R-factor. For the Czech Republic it is recommended to use the average value R = 40.

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Technical Notes: A Robust Estimator of the R-factor for the Universal Soil Loss Equation

Transactions of the ASAE ◽

10.13031/2013.27535 ◽

1996 ◽

Vol 39 (2) ◽

pp. 559-561 ◽

Cited By ~ 67

Author(s):

B. Yu ◽

C. J. Rosewell

Keyword(s):

Soil Loss ◽

Universal Soil Loss Equation ◽

Robust Estimator ◽

R Factor ◽

Soil Loss Equation

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

FROPIL (Forum Profesional Teknik Sipil) ◽

10.33019/fropil.v7i2.1627 ◽

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.

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