Soil erodibility and its prediction in semi-arid regions

Title
Soil erodibility and its prediction in semi-arid regions
Publication Date
2019-02-15
Author(s)
Ostovari, Yaser
Ghorbani-Dashtaki, Shoja
Kumar, Lalit
( author )
OrcID: https://orcid.org/0000-0002-9205-756X
Email: lkumar@une.edu.au
UNE Id une-id:lkumar
Shabani, Farzin
Type of document
Journal Article
Language
en
Entity Type
Publication
Publisher
Taylor & Francis
Place of publication
United Kingdom
DOI
10.1080/03650340.2019.1575509
UNE publication id
une:1959.11/29987
Abstract
Pedotransfer functions (PTFs) have been used to save time and cost in predicting certain soil properties, such as soil erodibility (K-factor). The main objectives of this study were to develop appropriate PTFs to predict the K-factor, and then compare new PTFs with Universal Soil Loss Equation (USLE) and the Revised Universal Soil Loss Equation (RUSLE) K-factor models. The K-factor was measured using 40 erosion plots under natural rainfall in Simakan Watershed, an area of 350 km2 in central of Iran. The Regression Tree (RT) and Multiple Linear Regression (MLR) were used to develop PTFs for predicting the K-factor. The result showed that the mean of measured K was 0.01 t h MJ−1 mm−1. The mean K value predicted by USLE and RUSLE was 2.08 and 2.84 times more than the measured K, respectively. Although calcium carbonate was not considered in the original USLE and RUSLE K-factors, it appeared in the advanced PTFs due to its strong positive significant impact on aggregate stability and soil infiltration rate, resulting in decreased K-factor. The results also showed that the RT with R2 = 0.84 had higher performance than developed MLR, USLE and RUSLE for the K estimation.
Link
Citation
Archives of Agronomy and Soil Science, 65(12), p. 1688-1703
ISSN
1476-3567
0365-0340
Start page
1688
End page
1703

Files:

NameSizeformatDescriptionLink