Should Crop Price Matter When Determining Irrigation Acreage?

According to recent estimates, an average of 128,000 million gallons of water is used for irrigation in the United States each day. Along with this staggeringly high usage, agriculture throughout the United States has been challenged by a reduced water supply, especially in the Southeast region where droughts have exasperated the already declining water stock. Major legislation, such as the Flint River Drought Protection Act (FRDPA) in Georgia, has limited water use for irrigation since 2001, and many other states have followed the trend. Current water irrigation techniques use an engineering or physical model to reduce irrigation proportionally, using the initial or current crop distribution to predict water need. This method does not take into account the economic or institutional conditions when determining the crop mix and irrigation levels, potentially wasting up to 27 percent of the water used for irrigation. These water savings are what many researchers, policymakers, and farmers are working to find, and a new model could be the solution.

In “Econometric Forecasting of Irrigation Water Demand Conserves a Valuable Natural Resource,” Swagata Banerjee and Babatunde Obembe create a model to show that by using price forecasting and risk evaluation, crop mix and irrigation techniques can be improved. Their main objective is to capture demand for water, which they do using estimated prices, and therefore expected profits, to determine the potential irrigated acreage for each crop, and therefore water usage. They then compare the product of this model to what actually happened over a time period or what would happen based on the physical models currently in place. The authors argue that this method is superior, since it can estimate acreage a year in advance, allowing either simultaneous or sequential changes in crop mix. This is opposed to the physical model, which only allows demand to be calculated based on the current crop.

Banerjee and Obembe compiled information on irrigation acreage, water use, and prices for Georgia, Alabama, and Mississippi from numerous sources within the US Department of Agriculture and Cooperative Extension Services. They then created time series data of irrigated acreage by crop for varying time periods in each state ranging from 1979 through 2008. The authors ran simulations of irrigated acreage reduction and used the model to predict water usage and crop mix determined by pricing and risk factors, comparing those results to actual usage within the time period analyzed.

By looking at an example using the physical model in Mississippi, it is clear the econometric model provides major benefits. Banerjee and Obembe found several instances where cotton farmers moved cotton out of irrigation and onto dry land due to acreage restrictions when the expected profit from cotton actually went up and vice versa. The model works to alleviate such counterintuitive behavior and, as a result, save water. The authors ran a simulation in Alabama mimicking a 50,000 acre reduction in irrigation for 2005 and 2006. Changing the crop mix and irrigation acreage in accordance with projected prices yields a water savings of 25 percent. A similar simulation for Georgia in 2001 based on the reduction from the FRDPA yields a water savings between 19 and 24 percent. Finally, in Mississippi, the authors find a water savings of 25 percent, although with higher prices for corn in 2007 and 2008, the authors speculate the water savings could actually be higher. Performing these simulations shows the value of this model in determining the crop mix and irrigation acreage needed to forecast water use.

While this technique allows farmers to better appropriate their water use, it also allows agricultural communities to save an important natural resource. This data can aid policy specialists in environmental, land allocation, and natural resource offices across the country, making this a progressive step forward for agricultural research. It also allows policymakers and implementers to better predict the impact of irrigation policy on total irrigated acreage and water demand, making their policy implementation during periods of drought potentially less devastating for farmers and their crop production. Farmers, by using this model, can allow their crop mix to better reflect the demand of the consumer based on the pricing of their product and not use as much water as they would otherwise. Fusing economics and agriculture to determine crop mixture and irrigation acreage is a benefit to all interests in the environmental spectrum.

Feature Photo: cc/(David Hinck)