Precision irrigation with artificial intelligence–integrated ground-penetrating radar reduces water stress in corn

Abstract

Water management is becoming increasingly vital in the Southern Great Plains due to declining levels of the Ogallala Aquifer and the increasing drought conditions. As water scarcity intensifies, precision irrigation technologies, such as artificial intelligence (AI) with integrated ground-penetrating radar (AI-Radar), can be a promising solution for optimizing water use at the field scale in crop production systems. This on-farm trial evaluates the AI-Radar irrigation system compared to a conventional irrigation system (subsurface drip, SSDI) in central Kansas. Spatial analysis of the water deficit index (WDI) determined using high-resolution satellite imagery showed significantly reduced values of this index under AI-Radar–based irrigation (0.15–0.16) compared to SSDI (0.20–0.24; p < 0.07) during critical tasseling to dough (VT–R4) growth stages. Lower WDI indicates more efficient spatial water distribution with minimal crop water stress. Addtionally, the AI-Radar system applied 23.5%–25.1% less irrigation water than the SSDI system while maintaining lower crop water stress. Therefore, this case study demonstrates that adopting AI-Radar–based irrigation could support groundwater conservation and regulatory compliance in the Southern Great Plains region.