Economic Analysis of Modern Irrigation Scheduling Strategies on Cotton Production Under Different Tillage Systems in South Georgia

Irrigation is a vital risk managing tool for row crop producers, which enables them to achieve higher and more consistent yield. Even though cotton is a drought-tolerant crop, producers still use irrigation to increase yield and manage production risks. The heavy usage of irrigation to meet the present demand in crop production in South Georgia is consequently depleting the ground water at an alarming rate. To ensure water quality and avoiding water scarcity in the near future, several modern irrigation scheduling methods are being developed and practiced. The goal of this research is to compare economic efficiency of five different irrigation scheduling methods under conservation and conventional tillage systems to identify the most profitable method.

A cotton field experiment was conducted in Camilla, Georgia, from 2013 to 2017 to compare five modern irrigation scheduling methods with dryland production (control). University of Georgia (UGA) Checkbook Method, the Smart Irrigation Cotton App, the University of Georgia Smart Sensor Array (UGA SSA), the Irrigator Pro for cotton, and the Cotton Water Stress Index (CWSI) are investigated under conservation and conventional tillage practices. As for the dryland control, they were only used in the conservation tillage. The market price and loan price for cotton was calculated based on fiber quality for each year. Irrigation cost will be calculated using the irrigation budgets developed by UGA Extension. Net return will be calculated by subtracting irrigation cost, harvesting, and ginning costs from the gross revenue of cotton production.

Preliminary results show that water use efficiencies were negative during wet years in 2013, and 2015 - 2017. The lint yields, seed yields and gross revenue were higher for dryland production in those wet years. Cotton App had the highest average value for gross revenue among all the irrigation scheduling methods, especially in dry years like 2014.