Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.

Digital soil mapping has been widely used to develop statistical models of the relationships between environmental variables and soil attributes. This study aimed at determining and mapping the spatial distribution of the variability in soil chemical properties of the agricultural floodplain lands o...

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Main Authors: Dinesh Panday, Bijesh Maharjan, Devraj Chalise, Ram Kumar Shrestha, Bikesh Twanabasu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC6203375?pdf=render
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author Dinesh Panday
Bijesh Maharjan
Devraj Chalise
Ram Kumar Shrestha
Bikesh Twanabasu
author_facet Dinesh Panday
Bijesh Maharjan
Devraj Chalise
Ram Kumar Shrestha
Bikesh Twanabasu
author_sort Dinesh Panday
collection DOAJ
description Digital soil mapping has been widely used to develop statistical models of the relationships between environmental variables and soil attributes. This study aimed at determining and mapping the spatial distribution of the variability in soil chemical properties of the agricultural floodplain lands of the Bara district in Nepal. The study was carried out in 23 Village Development Committees with 12,516 ha total area, in the southern part of the Bara district. A total of 109 surface soil samples (0 to 15 cm depth) were collected and analyzed for pH, organic matter (OM), nitrogen (N), phosphorus (P, expressed as P2O5), potassium (K, expressed as K2O), zinc (Zn), and boron (B) status. Descriptive statistics showed that most of the measured soil chemical variables (other than pH and P2O5) were skewed and non-normally distributed and logarithmic transformation was then applied. A geostatistical tool, kriging, was used in ArcGIS to interpolate measured values for those variables and several digital map layers were developed based on each soil chemical property. Geostatistical interpolation identified a moderate spatial variability for pH, OM, N, P2O5, and a weak spatial variability for K2O, Zn, and B, depending upon the use of amendments, fertilizing methods, and tillage, along with the inherent characteristics of each variable. Exponential (pH, OM, N, and Zn), Spherical (K2O and B), and Gaussian (P2O5) models were fitted to the semivariograms of the soil variables. These maps allow farmers to assess existing farm soils, thus allowing them to make easier and more efficient management decisions and maintain the sustainability of productivity.
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spelling doaj.art-38dafe24f9a64c63990e5fb41b617c412022-12-22T01:14:09ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-011310e020635010.1371/journal.pone.0206350Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.Dinesh PandayBijesh MaharjanDevraj ChaliseRam Kumar ShresthaBikesh TwanabasuDigital soil mapping has been widely used to develop statistical models of the relationships between environmental variables and soil attributes. This study aimed at determining and mapping the spatial distribution of the variability in soil chemical properties of the agricultural floodplain lands of the Bara district in Nepal. The study was carried out in 23 Village Development Committees with 12,516 ha total area, in the southern part of the Bara district. A total of 109 surface soil samples (0 to 15 cm depth) were collected and analyzed for pH, organic matter (OM), nitrogen (N), phosphorus (P, expressed as P2O5), potassium (K, expressed as K2O), zinc (Zn), and boron (B) status. Descriptive statistics showed that most of the measured soil chemical variables (other than pH and P2O5) were skewed and non-normally distributed and logarithmic transformation was then applied. A geostatistical tool, kriging, was used in ArcGIS to interpolate measured values for those variables and several digital map layers were developed based on each soil chemical property. Geostatistical interpolation identified a moderate spatial variability for pH, OM, N, P2O5, and a weak spatial variability for K2O, Zn, and B, depending upon the use of amendments, fertilizing methods, and tillage, along with the inherent characteristics of each variable. Exponential (pH, OM, N, and Zn), Spherical (K2O and B), and Gaussian (P2O5) models were fitted to the semivariograms of the soil variables. These maps allow farmers to assess existing farm soils, thus allowing them to make easier and more efficient management decisions and maintain the sustainability of productivity.http://europepmc.org/articles/PMC6203375?pdf=render
spellingShingle Dinesh Panday
Bijesh Maharjan
Devraj Chalise
Ram Kumar Shrestha
Bikesh Twanabasu
Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.
PLoS ONE
title Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.
title_full Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.
title_fullStr Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.
title_full_unstemmed Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.
title_short Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS.
title_sort digital soil mapping in the bara district of nepal using kriging tool in arcgis
url http://europepmc.org/articles/PMC6203375?pdf=render
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