Spotting the Rise of Swine Lagoons

Spotting the Rise of Swine Lagoons

In North Carolina, there are almost as many swine as there are people. Those swine produce several million tons of manure every year, much of which gets stored and treated in outdoor “waste lagoons.”

The brown-pink waste lagoons have increasingly dotted eastern North Carolina’s landscape since the 1980s, as swine farms transitioned from raising animals on open land to raising them in concentrated animal feeding operations (CAFOs). The lagoons offer a place to store the waste while microbial communities break it down. The treated liquid slurry is sometimes disposed of by spraying it on nearby fields to be used as a fertilizer.

But over time, the excess nutrients from the waste—mostly nitrogen and phosphorus—can build up and disrupt the natural balance of soils, surface water, and groundwater. To better understand these potential “legacy effects” on the environment, scientists first need a more detailed picture of where the lagoons are located and how long they have been operating.

That’s where satellites can help. Lise Montefiore and colleagues at North Carolina State University used the decades-long record of Landsat 5 satellite images to get a detailed view of where the lagoons are clustered, and to chronicle the historical expansion of the state’s swine farming industry. In addition to pinpointing where the waste lagoons of CAFO’s are located, the researchers also determined when they were constructed.

“Such information is useful for understanding how animal agriculture may pressure natural systems and impact adjacent communities,” Montefiore said. Their results were published in Nature Scientific Reports.

A few lagoons in Brunswick County are visible in this image (above), acquired on October 1, 2020, with the Operational Land Imager (OLI) on Landsat 8. The inset image, from Maxar Technologies via Google, shows a detailed view of one of the lagoons.

The waste ponds are typically pink or brown, geometrically shaped, and located near barns. Montefiore and colleagues used these attributes to manually identify (in Google Earth Pro) the locations of 3,405 waste lagoons across the coastal plain of North Carolina.

Previous estimates calculated the numbers of swine lagoons at the scale of counties. Duplin and Sampson counties, for example, have hundreds of lagoons, while Brunswick County has only a handful (map above). But as the researchers acquired precise location information for each lagoon, it became apparent that they were clustered within smaller areas within each of these counties (maps below).

The maps are especially novel because they show trends in lagoon construction since the industrialization of swine farms in the 1980s, and through the moratorium on the construction and expansion of swine farms in 1997 and its aftermath.

To identify when each lagoon was constructed, the researchers analyzed images from the Landsat 5 satellite. They used a total of 959 images to ensure that at least one image captured each lagoon every year from 1984 to 2012. The year in which the satellite’s near infrared band observed the land surface transition from dry to wet indicated the year of lagoon construction.

The images revealed a rapid change in the density of lagoons at local, sub-watershed scales. Before 1986, swine waste lagoons were present in 197 sub-watersheds. By the start of the moratorium in 1997, they were spread across 436 sub-watersheds.

“The most interesting results speak to how dramatically the swine CAFO density and footprint increased in North Carolina over a relatively short time period,” Montefiore said.

Looking forward, the researchers think that the new data could inform water quality models that simulate the long-term effects of applying manure to non-food crops. It could also help scientists estimate the timeline of recovery from an overabundance of nutrients. “Such information,” Montefiore said, “is critical to understanding and assessing the long-term responses to management and water quality policies.”

NASA Earth Observatory images by Joshua Stevens, using Landsat data from the U.S. Geological Survey and data courtesy of Montefiore, L. R., et al. (2022). Story by Kathryn Hansen.

References & Resources