Submitted to: International Conference on Precision Agriculture Abstracts & Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 5/29/2018
Publication Date: 6/24/2018
Citation: Sudduth, K.A., Kitchen, N.R., Vories, E.D., Drummond, S.T. 2018. Compensating for soil moisture effects in estimation of soil properties by electrical conductivity sensing. International Conference on Precision Agriculture, June 24-27, 2018, Montreal, Canada. Paper No. 5099. Available: https://www.ispag.org/proceedings/?action=abstract&id=5099.
Interpretive Summary: Variable rate irrigation (VRI) allows changing the amount of water delivered from place to place within a field based on differences in modeled or measured crop water need. One approach to VRI uses soil water sensors buried at a number of places within the field; however, it is difficult with this approach to accurately represent the spatial variability in soil water content. Therefore, the goal of this research was to develop whole-field maps of profile soil water content that could be used as a more accurate input for planning VRI applications. We collected spatially dense data at multiple dates using a soil apparent electrical conductivity (ECa) instrument. ECa responds to multiple soil properties, including texture, and importantly in this case, soil water content. By combining the ECa data with soil water content data from a few probes buried in the field, we were able to create maps of profile water content variations within the field. These high-resolution maps have the potential to benefit producers interested in controlling VRI based on soil measurements, as well as researchers who may want to develop VRI methodologies based on this new data source.
Technical Abstract: Bulk apparent soil electrical conductivity (ECa) is the most widely used soil sensing modality in precision agriculture. Soil ECa relates to multiple soil properties, including clay content (i.e., texture) and salt content (i.e., salinity). However, calibrations of ECa to soil properties are not temporally stable, due in large part to soil moisture differences between measurement dates. Therefore, the objective of this research was to investigate the effects of temporal soil moisture variations on ECa data collected within a field with highly varying soil texture and a growing cotton crop. A variable-rate irrigation experiment imposed additional soil water content (WC) variability. Data were collected with an electromagnetic induction ECa sensor four times within the 2017 growing season, and a fifth time pre-planting. Profile WC to approximately 68 cm depth was measured using time-domain reflectometry (TDR) sensors within season and gravimetrically pre-planting. Regressions estimating WC from ECa data were developed and used to map spatially variable WC. Changes in ECa-estimated WC between measurement dates corresponded reasonably well with a mapped water balance. These results are a step toward the overall goals of this research, which are to estimate WC from ECa and also to standardize ECa-based estimates of other soil properties for WC variation. Such standardized estimates would be beneficial, for example, to more effectively translate ECa data into texture information that could be used for establishing variable-rate irrigation strategies.