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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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Autores principales: Panday, Dinesh, Maharjan, Bijesh, Chalise, Devraj, Shrestha, Ram Kumar, Twanabasu, Bikesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203375/
https://www.ncbi.nlm.nih.gov/pubmed/30365521
http://dx.doi.org/10.1371/journal.pone.0206350
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author Panday, Dinesh
Maharjan, Bijesh
Chalise, Devraj
Shrestha, Ram Kumar
Twanabasu, Bikesh
author_facet Panday, Dinesh
Maharjan, Bijesh
Chalise, Devraj
Shrestha, Ram Kumar
Twanabasu, Bikesh
author_sort Panday, Dinesh
collection PubMed
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 P(2)O(5)), potassium (K, expressed as K(2)O), zinc (Zn), and boron (B) status. Descriptive statistics showed that most of the measured soil chemical variables (other than pH and P(2)O(5)) 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, P(2)O(5), and a weak spatial variability for K(2)O, 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 (K(2)O and B), and Gaussian (P(2)O(5)) 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 pubmed-62033752018-11-19 Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS Panday, Dinesh Maharjan, Bijesh Chalise, Devraj Shrestha, Ram Kumar Twanabasu, Bikesh PLoS One Research Article 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 P(2)O(5)), potassium (K, expressed as K(2)O), zinc (Zn), and boron (B) status. Descriptive statistics showed that most of the measured soil chemical variables (other than pH and P(2)O(5)) 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, P(2)O(5), and a weak spatial variability for K(2)O, 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 (K(2)O and B), and Gaussian (P(2)O(5)) 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. Public Library of Science 2018-10-26 /pmc/articles/PMC6203375/ /pubmed/30365521 http://dx.doi.org/10.1371/journal.pone.0206350 Text en © 2018 Panday et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Panday, Dinesh
Maharjan, Bijesh
Chalise, Devraj
Shrestha, Ram Kumar
Twanabasu, Bikesh
Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS
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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203375/
https://www.ncbi.nlm.nih.gov/pubmed/30365521
http://dx.doi.org/10.1371/journal.pone.0206350
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