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Erosivity Factor of the Revised Universal Soil Loss Equation (RUSLE) - A Systematized Review

Shaheemath Suhara K K1 , Anu Varughese2 * , Anjaly C Sunny2 and Anjitha Krishna P R3

1 Tamil Nadu Agricultural University, Tamil Nadu India

2 KCAET, Kerala Agricultural University, Kerala India

3 Dayalbagh Educational Institute, Agra, Uttar Pradesh India

Corresponding author Email: anu.varughese@kau.in

DOI: http://dx.doi.org/10.12944/CWE.18.2.02

The Revised Universal Soil Loss Equation (RUSLE) is a globally accepted erosion model which has gained good acceptability. Among the five influences of the RUSLE method of soil erosion estimation, the erosivity factor (R) represents rainfall event’s ability to produce erosion. It is mainly affected by rainfall intensity and kinetic energy of the rain. The erosion index represented by EI30 is the most common R-factor estimation method. Due to the non-availability of rainfall intensity data in many watersheds, researchers have developed methods for erosivity estimation using rainfall depth. The Modified Fournier Index method has gained popularity. Recently, different models using machine learning techniques and ANN are also being set up to establish the R-factor for soil loss estimation. These models can estimate the R-factor quickly and more accurately. They can even predict the R-factor for the future to predict soil loss and plan conservation measures accordingly. An attempt has been made here to review different methodologies proposed by scientists across the globe for arriving at the R-factor for soil loss estimation using RUSLE model.

EI30; Erosivity; Modified Fournier Index; R-factor; RUSLE

Copy the following to cite this article:

Suhara K. K. S, Varughese A, Sunny A. C, Krishna P. R. A. Erosivity Factor of the Revised Universal Soil Loss Equation (RUSLE) - A Systematized Review. Curr World Environ 2023;18(2). DOI:http://dx.doi.org/10.12944/CWE.18.2.02

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Suhara K. K. S, Varughese A, Sunny A. C, Krishna P. R. A. Erosivity Factor of the Revised Universal Soil Loss Equation (RUSLE) - A Systematized Review. Curr World Environ 2023;18(2).