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Spatial prediction of soil properties in a watershed scale through maximum likelihood approach

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Title Spatial prediction of soil properties in a watershed scale through maximum likelihood approach
Not Available
 
Creator Santra, P.
Das, B.S.
Chakravarty, D.
 
Subject Residual maximum likelihood
Best linear unbiased prediction
Kriging
Semivariogram
Soil hydraulic properties
Elevation
 
Description Not Available
Surface map of soil properties plays an
important role in various applications in a watershed.
Ordinary kriging (OK) and regression kriging (RK) are
conventionally used to prepare these surface maps but
generally need large number of regularly girded soil samples.
In this context, REML-EBLUP (REsidual Maximum
Likelihood estimation of semivariogram parameters followed
by Empirical Best Linear Unbiased Prediction)
shown capable but not fully tested in a watershed scale. In
this study, REML-EBLUP approach was applied to prepare
surface maps of several soil properties in a hilly watershed
of Eastern India and the performance was compared with
conventionally used spatial interpolation methods: OK and
RK. Evaluation of these three spatial interpolation methods
through root-mean-squared residuals (RMSR) and mean
squared deviation ratio (MSDR) showed better performance
of REML-EBLUP over the other methods. Reduction
in sample size through random selection of sampling
points from full dataset also resulted in better performance
of REML-EBLUP over OK and RK approach. The detailed
investigation on effect of sample number on performance
of spatial interpolation methods concluded that a minimum sampling density of 4/km2 may successfully be adopted for
spatial prediction of soil properties in a watershed scale
using the REML-EBLUP approach
Not Available
 
Date 2019-05-06T11:15:10Z
2019-05-06T11:15:10Z
2011-07-26
 
Type Research Paper
 
Identifier Not Available
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/19259
 
Language English
 
Relation Not Available;
 
Publisher Elsevier