Spatial Variability Analysis of Reclaimed Wetland Soil Nutrients in Sanjiang Plain, China

Author(s):  
Zilong Wang ◽  
Qiang Fu ◽  
Qiuxiang Jiang
2014 ◽  
Vol 5 (4) ◽  
pp. 348-355 ◽  
Author(s):  
Li Jing ◽  
Min Qingwen ◽  
Li Wenhua ◽  
Bai Yanying ◽  
Dhruba Bijaya G. C ◽  
...  

2015 ◽  
Vol 73 ◽  
pp. 59-63 ◽  
Author(s):  
Yonghui Wang ◽  
Li Zhang ◽  
Yimiti Haimiti

Author(s):  
G. S. Tagore ◽  
G. D. Bairagi ◽  
R. Sharma ◽  
P. K. Verma

A study was conducted to explore the spatial variability of major soil nutrients in a soybean grown region of Malwa plateau. From the study area, one hundred sixty two surface soil samples were collected by a random sampling strategy using GPS. Then soil physico-chemical properties i.e., pH, EC, organic carbon, soil available nutrients (N, P, K, S and Zn) were measured in laboratory. After data normalization, classical and geo-statistical analyses were used to describe soil properties and spatial correlation of soil characteristics. Spatial variability of soil physico-chemical properties was quantified through semi-variogram analysis and the respective surface maps were prepared through ordinary Kriging. Exponential model fits well with experimental semi-variogram of pH, EC, OC, available N, P, K, S and Zn. pH, EC, OC, N, P, and K has displayed moderate spatial dependence whereas S and Zn showed weak spatial dependence. Cross validation of kriged map shows that spatial prediction of soil nutrients using semi-variogram parameters is better than assuming mean of observed value for any un-sampled location. Therefore it is a suitable alternative method for accurate estimation of chemical properties of soil in un-sampled positions as compared to direct measurement which has time and costs concerned.


2019 ◽  
Vol 12 (3) ◽  
Author(s):  
Masoomeh Delbari ◽  
Peyman Afrasiab ◽  
Bahram Gharabaghi ◽  
Meysam Amiri ◽  
Armand Salehian

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