Assessing and transferring soil health information in a hilly terrain

Vaibhav Chhipa, A. Stein (Corresponding Author), Hari Shankar, Justin George K, F. Alidoost

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Abstract

Spatial variability of soil health related variables in a hilly terrain may be high, and its characterization may
require many samples. Our research compares deterministic and geostatistical interpolation methods in two hilly
areas in India. The soil in the study area was acidic, without salts and with sufficient organic carbon content.
Hence, three soil parameters – pH, Electrical Conductivity (EC) and Total Organic Carbon (TOC) were considered.
The optimal sampling scheme was designed using Spatial Simulated Annealing (SSA) with the minimized
kriging variance as a criterion. This resulted in 96 locations in the first area and 7 locations in the second
area. It was explored how spatial information from one area could be used in a second, topographically similar
area. The study focused on pH as the key variable for soil health. Regression kriging performed best for all the
soil variables at the surface and sub-surface levels. Bayesian kriging allows one to use prior information and
hence was used to transfer from the first to the second area. A mean error of 0.15, a root mean square error of
0.28 and a residual variance equal to 0.73 respectively were observed. We conclude that with modern interpolation
methods important information on soil health can be collected even with sparse amounts of data.
Original languageEnglish
Pages (from-to)130-138
Number of pages9
JournalGeoderma
Volume343
Early online date27 Feb 2019
DOIs
Publication statusPublished - 1 Jun 2019

Keywords

  • ITC-ISI-JOURNAL-ARTICLE

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