Dynamic approaches to precision irrigation of cotton

Purpose: Zones for spatial irrigation management are often assumed to be static, dictated by non- or slowly-changing parameters, including elevation and slope, soil depth, texture and hydraulic properties, and other landscape properties. Sensing allows for the integration of static management zones (MZ) with a dynamic characterization of water status. Temporal remote sensing data, indicating crop status and, particularly, thermal imaging, indicating water status, suggests that, rather than static, dynamic re-zoning within crop seasons could be beneficial to precision water management. Methods: MZ delineation and precision irrigation for cotton were evaluated using a variable rate center pivot sprinkler system. The objectives were to evaluate precision management over time with both static and intra-seasonal dynamic zoning. Spatial distribution and irrigation decision-making were re-evaluated on a weekly basis. Irrigation followed commercial best management, based on target values of plant size (growth rate) in the early vegetative growth period and of plant water status (leaf water potential, LWP) in the reproductive and cotton boll production periods. Site-specific decision-making used drone-acquired normalized difference vegetation index as a proxy for crop height and growth rate and a thermal image-based crop water stress index as a proxy for LWP. Results and conclusion: Dynamic precision irrigation of cotton based on weekly decisions using the remote sensing products slightly decreased spatial variability while improving water productivity by 12% using static MZs and by 19% using dynamic MZs, compared to commercial uniform irrigation. The costs and benefits of implementing intra-seasonal dynamic zoning are discussed.