Spatial Variability of Physical Soil Quality Index of an Agricultural Field
A field investigation was carried out to evaluate the spatial variability of physical indicators of soil quality of an agricultural field and to construct a physical soil quality index (SQIP) map. Surface soil samples were collected using 10 m×10 m grid from an Inceptisol on Ganges Tidal Floodplain...
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2014-01-01
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Series: | Applied and Environmental Soil Science |
Online Access: | http://dx.doi.org/10.1155/2014/379012 |
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doaj-b129b83c15ec496496f0545eb1571ff92020-11-24T23:03:29ZengHindawi LimitedApplied and Environmental Soil Science1687-76671687-76752014-01-01201410.1155/2014/379012379012Spatial Variability of Physical Soil Quality Index of an Agricultural FieldSheikh M. Fazle Rabbi0Bina R. Roy1M. Masum Miah2M. Sadiqul Amin3Tania Khandakar4Soil Science Discipline, Khulna University, Khulna 9208, BangladeshSoil Science Discipline, Khulna University, Khulna 9208, BangladeshSoil Science Discipline, Khulna University, Khulna 9208, BangladeshSoil Science Discipline, Khulna University, Khulna 9208, BangladeshSoil Science Discipline, Khulna University, Khulna 9208, BangladeshA field investigation was carried out to evaluate the spatial variability of physical indicators of soil quality of an agricultural field and to construct a physical soil quality index (SQIP) map. Surface soil samples were collected using 10 m×10 m grid from an Inceptisol on Ganges Tidal Floodplain of Bangladesh. Five physical soil quality indicators, soil texture, bulk density, porosity, saturated hydraulic conductivity (KS), and aggregate stability (measured as mean weight diameter, MWD) were determined. The spatial structures of sand, clay, and KS were moderate but the structure was strong for silt, bulk density, porosity, and MWD. Each of the physical soil quality indicators was transformed into 0 and 1 using threshold criteria which are required for crop production. The transformed indicators were the combined into SQIP. The kriged SQIP map showed that the agricultural field studied could be divided into two parts having “good physical quality” and “poor physical soil quality.”http://dx.doi.org/10.1155/2014/379012 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sheikh M. Fazle Rabbi Bina R. Roy M. Masum Miah M. Sadiqul Amin Tania Khandakar |
spellingShingle |
Sheikh M. Fazle Rabbi Bina R. Roy M. Masum Miah M. Sadiqul Amin Tania Khandakar Spatial Variability of Physical Soil Quality Index of an Agricultural Field Applied and Environmental Soil Science |
author_facet |
Sheikh M. Fazle Rabbi Bina R. Roy M. Masum Miah M. Sadiqul Amin Tania Khandakar |
author_sort |
Sheikh M. Fazle Rabbi |
title |
Spatial Variability of Physical Soil Quality Index of an Agricultural Field |
title_short |
Spatial Variability of Physical Soil Quality Index of an Agricultural Field |
title_full |
Spatial Variability of Physical Soil Quality Index of an Agricultural Field |
title_fullStr |
Spatial Variability of Physical Soil Quality Index of an Agricultural Field |
title_full_unstemmed |
Spatial Variability of Physical Soil Quality Index of an Agricultural Field |
title_sort |
spatial variability of physical soil quality index of an agricultural field |
publisher |
Hindawi Limited |
series |
Applied and Environmental Soil Science |
issn |
1687-7667 1687-7675 |
publishDate |
2014-01-01 |
description |
A field investigation was carried out to evaluate the spatial variability of physical indicators of soil quality of an agricultural field and to construct a physical soil quality index (SQIP) map. Surface soil samples were collected using 10 m×10 m grid from an Inceptisol on Ganges Tidal Floodplain of Bangladesh. Five physical soil quality indicators, soil texture, bulk density, porosity, saturated hydraulic conductivity (KS), and aggregate stability (measured as mean weight diameter, MWD) were determined. The spatial structures of sand, clay, and KS were moderate but the structure was strong for silt, bulk density, porosity, and MWD. Each of the physical soil quality indicators was transformed into 0 and 1 using threshold criteria which are required for crop production. The transformed indicators were the combined into SQIP. The kriged SQIP map showed that the agricultural field studied could be divided into two parts having “good physical quality” and “poor physical soil quality.” |
url |
http://dx.doi.org/10.1155/2014/379012 |
work_keys_str_mv |
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