Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management

Among one of the many challenges in implementing precision irrigation is to obtain an accurate characterization of the soil water content (SWC) across spatially variable fields along the crop growing season. The accuracy of characterizing SWC has been tested primarily on a small-scale and has receiv...

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Main Authors: Alfonso de Lara, Raj Khosla, Louis Longchamps
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Agronomy
Subjects:
Online Access:http://www.mdpi.com/2073-4395/8/5/59
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spelling doaj-ccabbd3859c247f3853c10ea097357892021-04-02T03:15:19ZengMDPI AGAgronomy2073-43952018-04-01855910.3390/agronomy8050059agronomy8050059Characterizing Spatial Variability in Soil Water Content for Precision Irrigation ManagementAlfonso de Lara0Raj Khosla1Louis Longchamps2Department of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523-1170, USADepartment of Soil and Crop Sciences, Colorado State University, Fort Collins, CO 80523-1170, USAAgriculture and Agri-Food Canada, St-Jean-sur-Richelieu, QC, CanadaAmong one of the many challenges in implementing precision irrigation is to obtain an accurate characterization of the soil water content (SWC) across spatially variable fields along the crop growing season. The accuracy of characterizing SWC has been tested primarily on a small-scale and has received little attention from the scientific community at the field scale. Hence, the objective of this study was to assess the characterization of the spatial distribution of soil water content at the field scale by the apparent electrical conductivity (ECa). In evaluating the current aim, ECa survey was compared against repeated measurements of SWC at five depths using neutron probe. Results showed that mean SWC was different across ECa derived management zones, which indicates that on a macro-scale, soil ECa could effectively characterize the mean differences in SWC across management zones. Results also showed that deep ECa (0–150 cm) survey outperformed shallow survey (0–75 cm). Considering other soil properties, such as organic matter content and salt content, further improved the relationship between SWC and ECa.http://www.mdpi.com/2073-4395/8/5/59prescription mapsmall-scalefield scalespatial distributionmanagement zones
collection DOAJ
language English
format Article
sources DOAJ
author Alfonso de Lara
Raj Khosla
Louis Longchamps
spellingShingle Alfonso de Lara
Raj Khosla
Louis Longchamps
Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management
Agronomy
prescription map
small-scale
field scale
spatial distribution
management zones
author_facet Alfonso de Lara
Raj Khosla
Louis Longchamps
author_sort Alfonso de Lara
title Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management
title_short Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management
title_full Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management
title_fullStr Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management
title_full_unstemmed Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management
title_sort characterizing spatial variability in soil water content for precision irrigation management
publisher MDPI AG
series Agronomy
issn 2073-4395
publishDate 2018-04-01
description Among one of the many challenges in implementing precision irrigation is to obtain an accurate characterization of the soil water content (SWC) across spatially variable fields along the crop growing season. The accuracy of characterizing SWC has been tested primarily on a small-scale and has received little attention from the scientific community at the field scale. Hence, the objective of this study was to assess the characterization of the spatial distribution of soil water content at the field scale by the apparent electrical conductivity (ECa). In evaluating the current aim, ECa survey was compared against repeated measurements of SWC at five depths using neutron probe. Results showed that mean SWC was different across ECa derived management zones, which indicates that on a macro-scale, soil ECa could effectively characterize the mean differences in SWC across management zones. Results also showed that deep ECa (0–150 cm) survey outperformed shallow survey (0–75 cm). Considering other soil properties, such as organic matter content and salt content, further improved the relationship between SWC and ECa.
topic prescription map
small-scale
field scale
spatial distribution
management zones
url http://www.mdpi.com/2073-4395/8/5/59
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AT rajkhosla characterizingspatialvariabilityinsoilwatercontentforprecisionirrigationmanagement
AT louislongchamps characterizingspatialvariabilityinsoilwatercontentforprecisionirrigationmanagement
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