Submitted to: Agricultural Water Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/7/2015
Publication Date: 6/23/2015
Citation: Oshaughnessy, S.A., Evett, S.R., Colaizzi, P.D. 2015. Dynamic prescription maps for site-specific variable rate irrigation of cotton. Agricultural Water Management. 159:123-138.
Interpretive Summary: Diminishing water available for agriculture due to competing uses coupled with the need for agriculture to be water smart is spurring a renewed interest in using variable rate irrigation (VRI) systems to improve crop water use efficiency.These systems are used with center pivot and linear move sprinklers to provide flexibility in delivering different watering rates along the sprinkler pipeline as it moves across a field. The set of instructions to control sprinkler movement, and location and amount of water applied is called a prescription map. Prescription maps are usually based on static information and entered into the sprinkler’s control panel at the beginning of the growing season. Dynamic maps can better meet changing crop water needs. ARS scientists (Bushland, Texas) developed software code to automate prescription maps based on a tested plant feedback system that uses crop canopy temperature and microclimatological measurements. Maps were generated every two days and used to irrigate a cotton crop alongside plots of manually scheduled irrigations using direct soil water measurements. The results from a two year study indicate that dynamic prescription maps can optimally manage irrigation scheduling of cotton producing water use efficiencies as high as the manual plots for levels equivalent to 75 percent and 50 percent replenishment of soil water depletion to field capacity in a semi-arid region.
Technical Abstract: A prescription map is a set of instructions that controls a variable rate irrigation (VRI) system. These maps, which may be based on prior yield, soil texture, topography, or soil electrical conductivity data, are often manually applied at the beginning of an irrigation season and remain static. The problem with static prescription maps is that they ignore spatiotemporal changes in crop water status. In a two-year study (2012 and 2013), a plant feedback system, including a wireless sensor network of infrared thermometers (IRTs), was used to develop dynamic prescription maps to accomplish adaptive irrigation scheduling for cotton (Gossypium hirsutum L.). One-half of a center pivot field was divided into manually and plant feedback-controlled irrigation treatment plots. Irrigation amount treatments were at three levels, 75, 50, and 25 percent of full as defined by either replenishment of crop water use to field capacity or by the equivalent threshold of the IRT sensed crop water stress. The system accepted user input to control irrigation for the manual treatment plots (I75M, I50M, and I25M), and calculated and compared a thermal stress index for each plant feedback-controlled treatment plot (I75C, I50C, and I25C) with a pre-determined threshold for automated irrigation scheduling. The effectiveness of the plant feedback irrigation scheduling system was evaluated by comparing measured lint yield, crop water use (ETc), and water use efficiency (WUE) with the manually scheduled treatment plots. Results for both years indicated that average lint yields were not significantly different between the manual and plant feedback-control plots at the I75 percent (181 and 182 g/ square meter, respectively in 2012; 115 and 103 g/square meter, respectively in 2013) and I50 percent (146 and 164 g/square meter, respectively in 2012; 95 and 117 g /square meter, respectively in 2013) irrigation treatment levels. Mean water use efficiencies (WUE) among treatment levels were greater for the plant feedback-control plots as compared with the manual-control treatment plots for both years, but not significantly different. Importantly, the automatic plant feedback system did not require the time consuming and expensive manual reading of neutron probe access tubes that was required to schedule the manual treatments. These results demonstrate that the integration of a plant feedback system with a commercial VRI system could be used to control site-specific irrigation management for cotton at higher irrigation treatment levels, i.e. I75 percent and I50 percent. Such a system can facilitate the use of a VRI system by automating prescription map coding and providing dynamic irrigation control instructions to meet variable crop water needs throughout the irrigation season. As of yet, further research is required to maintain automatic deficit irrigation at a level equivalent to 25 percent replenishment of crop water use relative to field capacity.