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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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 |
work_keys_str_mv |
AT alfonsodelara characterizingspatialvariabilityinsoilwatercontentforprecisionirrigationmanagement AT rajkhosla characterizingspatialvariabilityinsoilwatercontentforprecisionirrigationmanagement AT louislongchamps characterizingspatialvariabilityinsoilwatercontentforprecisionirrigationmanagement |
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