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Modeling Groundwater and Crop Production in the U.S. High Plains

Modeling Groundwater and Crop Production in the U.S. High Plains
By Jady Carmichael  
 
An international team of more than 2 dozen researchers has found a novel approach to modeling groundwater levels and crop production to forecast future resource availability and yields. The model the researchers developed was inspired by ecology’s Lotka-Volterra equations, a mathematical explanation for the cyclical population dynamics of predator and prey species.
 
Previous models for forecasting groundwater levels have relied on Hubbert’s curve, an equation with its basis in production rates and demand for a given resource. (The model is named after M. King Hubbert, the geologist who famously predicted in 1956 that crude oil production would reach a peak in the 1970s.) However, the research team behind the new model wanted to develop a method that would couple the dynamics of groundwater withdrawals and crop production. As Assaad Mrad, the lead author on the study and a Ph.D. candidate at Duke University, explained, “we looked at crop production as the predator and groundwater resources as the prey, and we found that [this model] describes the trends in groundwater extraction and crop production rates very accurately. These were the seeds of the project that stemmed from the goal of introducing more rigorous mathematical techniques to [the science of] sustainability.”
“That kind of modeling approach that is drawn from ecology had not really been applied to this kind of physical system before,” said Erin Haacker, an assistant professor of hydrogeology at the University of Nebraska–Lincoln who was not part of the new study. Haacker noted that compared with other hydrologic modeling, which tends to use “a much more physical-based approach” that sets expectations based on physics and checks to see whether they match the data, the model developed by Mrad and his colleagues “uses a really empirical statistical approach” that “fit the [model’s] parameters based on what the observation data told them.”
 
The paper detailing the innovative methodology was published in the Proceedings of the National Academy of Sciences of the United States of America in October.
 
Putting Their Ideas to the Test
 
To test their ideas, Mrad and the other researchers gathered irrigation and crop yield data for Nebraska, Kansas, and Texas. Portions of all three states depend on the Ogallala Aquifer, a vast underground reservoir whose declining stores have been causing concern for years. This massive aquifer underlies parts of eight states in the U.S. High Plains, a region often referred to as America’s breadbasket because of the enormous amounts of grain grown there.
 
Also called the High Plains Aquifer, the Ogallala supplies water for almost 30% of irrigated crops and livestock in the entire country. The aquifer’s north–south orientation extends through different climates, ranging from hot and dry in the Texas Panhandle to comparatively wet and cool in Nebraska. The crosscutting aquifer allowed researchers to “disentangle the effect of climate on groundwater recharge, crop production, and groundwater extraction,” Mrad said.

 

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