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

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Springer US
Copyright © 2015 by Springer Science+Business Media New York
Life Sciences; Agriculture; Soil Science & Conservation; Remote Sensing/Photogrammetry; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Atmospheric Sciences
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