Common thinking is that a cotton plant needs 10 gallons of water to produce a profitable boll load. Simple enough. The question then is when does the plant need water — and how much. The answer to this farming question is the same as so many others: It depends on your situation.
That’s a lot of help.
And that’s about as far as we came with this question for many years. Farmers and consultants either toiled with irrigation pans or a sharp pencil and the checkbook method. Answers today, however, are found in digital programs that raise cotton production opportunities as quickly as a soaking rain lifts leaves on a droughty field.
University of Georgia Precision Ag and Irrigation Extension Specialist Wesley Porter pours out information on a half-dozen irrigation scheduling apps, soil moisture sensors, and other tools that help minimize water use and maximize production.
“They take a lot of that time and responsibility off of the user, making it a lot easier for our farmers to make irrigation decisions,” Porter says. “It’s not about the total amount of water. It’s about correct timing to deliver water when the crop needs it. You have to find that system that integrates with your management.”
Georgia is among the land-grant universities working to make the front-end decision — which app or tool to use — easier for crop consultants and farmers.
“Our role is to make sure these tools are working in our environment so our farmers and consultants can move forward with confidence to use these tools to maximize their time and efficiency,” Porter adds. “We have to be confident that the tools we’re using are adapted to our environment and our crops.”
A few of the tools Porter has tested with positive results are seeing quick adoption in cotton. These include (in no particular order):
- FieldNET, Lindsey Corporation. This system uses local information about your field and site-specific information, such as soil type, planting date, and crop type. It can calculate growing degree days and use local rain data
or predictive data to create two variable rate prescription maps for the field. It doesn’t use soil moisture sensors.
- Valley Smart Farm Solutions, Valley Irrigation. The Valley system uses a soil moisture sensor and user-provided parameters such as crop and soil type to make recommendations based on the current rooting depth and the moisture requirements for the given crop stage.
- ReinCloud and CropX Agronomic Farm Management System. A partnership between Reinke Irrigation and CropX Inc., this system uses a soil moisture sensor calibrated for soil type to make daily irrigation recommendations that can be accessed and initiated either online or through a mobile device.
Porter has seen consistently positive trial results with the hybrid systems that focus on local data and are integrated with moisture sensors. Consultants and farmers who have questions about precision irrigation options can contact Porter or their local Extension agent.
Supercharging Your Water
Technology now topping the horizon includes TerraScribe imprinting technology from UpTerra. This California-based company is focused on decreasing input costs and increasing production by energizing irrigation water.
CEO Roland Van der Meer uses this analogy to simply explain the complex process of delivering highly charged water: “Water is water. H2O doesn’t change. But stagnant water has no charge; there’s no vitality to it. When you spin water, when you oscillate it, when it comes out of a rain cloud, spinning down, it’s fully charged. Rainwater has a very high charge, which is what makes it so good.”
With the UpTerra program, UpTerra Lead Agronomist Parker Christian says the water charge is customized to the field, so the plants maximize water efficiency and nutrient uptake. In Christian’s trials, he sees increased soil health year-on-year, better root development, and shorter internode length — all of which work together to consistently increase yield.
“This is a working solution to help farmers create the environment they need,” Christian says. He plans to work with Oklahoma State University to plant replicated trip trials this season.
Putting Technology to Use
Severe drought over the past two years has left Arizona struggling with water issues. Lake Mead reached a critical level last year, setting in motion contingency plans to help conserve and deal with shortages on the Colorado River.
“This is the first season in many decades that growers will have zero Colorado River water delivered to them,” states Kelly Thorp, a USDA ARS researcher based in Maricopa, AZ. “It’s a dire situation, and growers are reacting in several ways including reducing acres and fallowing land. They’re again facing a total reliance on groundwater, and there’s a need for improved irrigation management.”
Presenting at the 2023 Beltwide Cotton Conferences, Thorp outlined a two-year study using several different crop models along with data from a water content measurement system to schedule irrigation in Arizona.
“The Maricopa-Stanfield Irrigation District in central Arizona is primarily surface irrigated because it’s set up to receive Colorado River water through the irrigation system,” Thorp says. “But use of sprinkler irrigation is becoming more popular as is drip irrigation, especially on tribal lands with water rights and more access to water. They want to use the most modern irrigation systems to conserve as much water as they can.”
The research focused on developing irrigation scheduling tools using rate studies that look at various aspects of timing and rate of irrigation on cotton, quality, and yield. Drone applications were used for mapping and irrigation management, using a variable rate irrigation system based on various aspects that were sensed in the field.
Conducted in 2021 and 2022, the study consisted of 48 plots and six irrigation management systems. Three systems used stand-alone crop models, while the other three used the same crop models plus soil water content data provided by neutron-based probes throughout the season.
Weather data was compiled using an Arizona Meteorological Network station in the field site, a seven-day forecast from the National Digital Forecast Database, and the average of long-term weather from their weather station. Models were used to predict water needs for the week, and irrigation was scheduled for two days each week. Simulated root depth from each model was used to define the control volume, and the root zone water depletion from the probe data and from the model simulation was analyzed to determine the difference in depletion between the measured and simulated data.
“There’s a large variability in the rate recommendations due to the real field variability that exists,” points out Thorp. “One of our issues is that we have some limitations of the irrigation system. Things must be bounded, and the pressures maintained at a certain level to have the irrigation system work correctly. We’re also managing flowing canals, so we don’t want to overtop the canals or run them dry. So, we do need to put limits on the rates recommended by these models.”
The results to date show:
- The three stand-alone models overestimated water requirements, possibly due to the aridity at the Maricopa station. Marginal to no yield improvement was seen with the extra water.
- Neutron probe-assisted models reduced irrigation amounts by 8% to 19%. Yield was not significantly impacted in most cases.
- Combining soil water content data with irrigation scheduling models appears practical and promising to help improve irrigation recommendations.