101720 Apparent Electrical Conductivity to Characterize Soil Water Content.

Poster Number 319-712

See more from this Division: ASA Section: Agronomic Production Systems
See more from this Session: On-Farm Research: Advancing Precision Ag Tools, Data Analysis and Extension implications (includes student competition)

Tuesday, November 8, 2016
Phoenix Convention Center North, Exhibit Hall CDE

Alfonso de Lara1, Raj Khosla2 and Louis Longchamps1, (1)Colorado State University, Fort Collins, CO
(2)C013 Plant Sciences Bldg., 1170 Campus Delivery, Colorado State University, Fort Collins, CO
Poster Presentation
  • de Lara Alfonso_Poster.pdf (1.5 MB)
  • Abstract:
    Precision irrigation (PI) is a relatively new concept in agriculture, and it provides a vast potential for water saving. As part of site-specific farming, PI needs to be explored and is still very much a research issue. Among the challenges of PI is the reliable characterization of the soil water content (SWC) in management zones. For this purpose, commercial retailers are employing apparent soil electrical conductivity (ECa) to create irrigation prescription maps. The accuracy of this method has not been properly studied at the field scale. Hence, the objectives of this research were (i) to assess the potential of ECa measurement to characterize spatial distribution of SWC at the field scale, and (ii) to determine whether soil properties coupled with ECa could further improve the characterization of the SWC. This study was conducted on two fields at the Agricultural Research, Development and Education Center, at Colorado State University. In-field SWC was measured using neutron probes at 41 and 31 locations for site I and II, respectively. Soil ECa measurements were acquired using Geonics EM38-MK2 unit. In addition, cation exchange capacity, clay, organic matter and salt content were coupled with soil ECa to estimate SWC. Data analysis was performed using the statistical software R. Statistical correlations and multiple linear regressions were obtained from the properties that were statistically significant (p value < 0.05). Results of this study showed that SWC found to be statistically different across ECa derived zones, indicating that ECa accurately characterized the SWC. Organic matter and salt content significantly improved the SWC assessment when combined with the ECa. The development of prescription maps for variable rate irrigation should be tailor made depending on the specific field characteristics influencing soil water content.

    See more from this Division: ASA Section: Agronomic Production Systems
    See more from this Session: On-Farm Research: Advancing Precision Ag Tools, Data Analysis and Extension implications (includes student competition)

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