Submitted to: Irrigation Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/4/2019
Publication Date: 9/24/2019
Citation: Thorp, K.R. 2019. Long-term simulations of site-specific irrigation management for Arizona cotton production. Irrigation Science. 38(1):49-64. https://doi.org/10.1007/s00271-019-00650-6.
Interpretive Summary: Technologies are currently available for applying different irrigation rates at different locations in the field. However, further studies must identify cases where these technologies improve crop yield or save water. In this study, a comprehensive analysis of temporal weather patterns and spatial soil patterns was conducted at the Maricopa Agricultural Center in Arizona. Assessments of irrigation requirements for cotton production among the different weather and soil patterns were performed. The results demonstrated little benefit for technologies that apply different rates of water at different spatial locations, because no improvements in crop yield or savings of water were shown as compared to spatially uniform irrigation management. The research is particularly useful for growers who are considering options for technologies to improve water management on their farms and for researchers in the area of irrigation science.
Technical Abstract: Engineering technologies for site-specific irrigation management (SSIM) have already been developed for applications in precision irrigation. However, further studies are needed to identify scenarios where SSIM leads to better agronomic outcomes than conventional uniform irrigation management (CUIM). The objective was to conduct a long-term simulation study to compare SSIM and CUIM given spatial soil variability at the Maricopa Agricultural Center (MAC) in Arizona. More than 500 surface soil samples were collected across a 730-ha area of the MAC from 1984 to 1987. A more detailed soil data set was more recently obtained across a 5.9-ha area at a MAC location designated for SSIM studies. Ordinary kriging was used for spatial interpolation of soil hydraulic properties on a 10-m2 grid across MAC, and 11 parcels were delineate on quarter-sectional areas. Simulations of cotton production at the zone-level with a 30-year weather record were conducted using a field-tested algorithm to optimize irrigation management decisions for SSIM and CUIM. Long-term seed cotton yield, irrigation requirements, water use efficiency, and marginal net return for SSIM and CUIM strategies were often not different ($p=0.05$). Differences in seed cotton yield and irrigation requirements among the tested irrigation strategies were less than 10% and 5%, respectively, and within the typical range of model error. Most soils on the MAC have enough available water holding capacity to sustain cotton production at full potential with weekly CUIM, and advantages of SSIM were not consistently demonstrated by the simulations.