A methodology based on apparent electrical conductivity and guided soil samples to improve irrigation zoning

A methodology based on apparent electrical conductivity and guided soil samples to improve... The spatial variability of soils is one of the main problems faced when planning irrigation management, especially when large tracts of agricultural land are involved. Parameters such as soil texture or soil water content are fundamental for understanding the determining factors of a soil with respect to water. Available water capacity (AWC) is a vital indicator when considering soil properties from the point of view of irrigation management. An analysis was made in this study of the relationship between the apparent electrical conductivity (ECa), a parameter which can be determined through intensive data sampling, and AWC. After demonstrating the relationship, a geostatistical methodology was used to develop efficient predictive maps for soil characterisation from the point of view of irrigation with the help of guided soil sampling based on the ECa. Ordinary and regression kriging models were used to generate predictive maps of AWC. When the maps were statistically evaluated, those generated using a regression kriging approach were found to be more robust, though the resolution of the maps generated through ordinary kriging was acceptable. This information is of interest when considering the design of more efficient irrigation systems. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Precision Agriculture Springer Journals

A methodology based on apparent electrical conductivity and guided soil samples to improve irrigation zoning

Loading next page...
 
/lp/springer_journal/a-methodology-based-on-apparent-electrical-conductivity-and-guided-X5SQWau1Fv
Publisher
Springer Journals
Copyright
Copyright © 2015 by Springer Science+Business Media New York
Subject
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
ISSN
1385-2256
eISSN
1573-1618
D.O.I.
10.1007/s11119-015-9388-7
Publisher site
See Article on Publisher Site

Abstract

The spatial variability of soils is one of the main problems faced when planning irrigation management, especially when large tracts of agricultural land are involved. Parameters such as soil texture or soil water content are fundamental for understanding the determining factors of a soil with respect to water. Available water capacity (AWC) is a vital indicator when considering soil properties from the point of view of irrigation management. An analysis was made in this study of the relationship between the apparent electrical conductivity (ECa), a parameter which can be determined through intensive data sampling, and AWC. After demonstrating the relationship, a geostatistical methodology was used to develop efficient predictive maps for soil characterisation from the point of view of irrigation with the help of guided soil sampling based on the ECa. Ordinary and regression kriging models were used to generate predictive maps of AWC. When the maps were statistically evaluated, those generated using a regression kriging approach were found to be more robust, though the resolution of the maps generated through ordinary kriging was acceptable. This information is of interest when considering the design of more efficient irrigation systems.

Journal

Precision AgricultureSpringer Journals

Published: Jan 30, 2015

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off