Neural Computing and Applications

, Volume 24, Issue 2, pp 383–389

Prediction of soil erodibility factor for Peninsular Malaysia soil series using ANN

  • Mohd Fazly Yusof
  • H. Md. Azamathulla
  • Rozi Abdullah
Original Article

DOI: 10.1007/s00521-012-1236-3

Cite this article as:
Yusof, M.F., Azamathulla, H.M. & Abdullah, R. Neural Comput & Applic (2014) 24: 383. doi:10.1007/s00521-012-1236-3

Abstract

Soil erodibility factor (susceptibility of soil to be lost to erosion) is one of the components of the universal soil loss equation. This study presents an artificial neural network (ANN) model using 74 soil series provided by the Department of Agriculture, Malaysia. The ANN model produces acceptable results: the K values for 74 soil series of Peninsular Malaysia give much better information to engineers in determining the soil loss and sediment yield for a given development area.

Keywords

Soil erodibility ANN Wischmeier erodibility equation Tew erodibility equation Peninsular Malaysia soil series 

Copyright information

© Springer-Verlag London 2012

Authors and Affiliations

  • Mohd Fazly Yusof
    • 1
  • H. Md. Azamathulla
    • 1
  • Rozi Abdullah
    • 2
  1. 1.River Engineering and Urban Drainage Research Centre (REDAC)Universiti Sains MalaysiaNibong TebalMalaysia
  2. 2.School of Civil EngineeringUniversiti Sains MalaysiaNibong TebalMalaysia

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