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Assessment of saturated hydraulic conductivity of red and lateritic soils under diverse land topography and vegetation using classical statistical analysis.

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Title Assessment of saturated hydraulic conductivity of red and lateritic soils under diverse land topography and vegetation using classical statistical analysis.
Not Available
 
Creator Momin, B.G., Ray, R., Patra, S.K.
 
Subject Saturated hydraulic conductivity, Red and lateritic soil, Multiple regression equation, Principal component analysis, Minimum data set
 
Description Not Available
Saturated hydraulic conductivity of the red and lateritic soils was assessed from the basic
properties using multivariate analysis techniques. The descriptive statistics showed that all
the soil variables were normally distributed and mostly displayed moderate to strong
correlation with each other. The stepwise multiple regression equation demonstrated that
clay fraction was the key indicator in explaining most variability of the saturated hydraulic
conductivity. The principal component analysis (PCA) was applied to reduce the number
of original variables. It indicated that sand, particle density and porosity were the highest
loaded variables in the first PCs; while silt, water holding capacity, porosity, electrical
conductivity and organic carbon in the second PCs and clay, bulk density and water
holding capacity in the third PCs, which altogether predicted 93.4% of the total variance.
The regressive model for saturated hydraulic conductivity using minimum data set (MDS)
from PCA such as sand, silt and WHC accounted for 94.3% of the variance was highly
predictive than the other models studied. The MDS model may thus provide a potential
tool for assessing the saturated hydraulic conductivity of the soils.
Not Available
 
Date 2019-11-26T04:52:47Z
2019-11-26T04:52:47Z
2018-09-10
 
Type Article
 
Identifier Momin, B.G., Ray, R., Patra, S.K., 2018. Assessment of saturated hydraulic conductivity of red and lateritic soils under diverse land topography and vegetation using classical statistical analysis. International Journal of Current Microbiology and Applied Sciences 7, 963-972.
ISSN: 2319-7706
http://krishi.icar.gov.in/jspui/handle/123456789/25402
 
Language English
 
Relation Not Available;
 
Publisher Excellent Publishers