Journal
PRECISION AGRICULTURE
Volume 16, Issue 4, Pages 441-454Publisher
SPRINGER
DOI: 10.1007/s11119-015-9388-7
Keywords
Predictive map; Ordinary kriging; Regression kriging; Available water capacity; Precision irrigation
Categories
Funding
- Regional Government of Extremadura [GRU 10130, A-E-11-0255-4]
- ROMA S.L. [A-E-11-0255-4]
- FEDER
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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.
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