Development of a point-source model to improve simulations of manure lagoon interactions with the environment.

In recent decades animal agriculture in the U.S. has moved from small, distributed operations to larger, concentrated animal feeding operations (CAFOs). CAFOs are defined by federal regulations based on animal numbers and confinement criteria. Because of the size of these operations, the excessive amount of manure generated is typically stored in lagoons, pits, or barns prior to field application or transport to other farms. Water and air quality near CAFOs can be impaired through the overflow of lagoons, stormwater runoff, lagoon seepage or emissions, motivating the following research question: what manure lagoon parameters impact pollutant fate and transport across multiple mechanisms? To address this question, a CAFO lagoon module was developed to assess lagoon overflow risk, groundwater quality, and ammonia emissions of a dairy lagoon. The results from 10,000 Monte Carlo simulations indicated that lagoon overflow is a rare occurrence for simulated environmental conditions in Washington (3.17%). Second, we developed a groundwater module to complete a groundwater quality assessment of a Dairy Lagoon in Washington using analytical and semi-analytical solutions for groundwater solute transport. The long-term effects of this lagoon on water quality were explored as well as the effectiveness of improving the lagoon lining to reduce seepage. Doubling the lagoon liner thickness attenuated peak groundwater ammonia-N concentrations by 2.8. Lastly, we constructed an air quality module and found that ammonia emissions were not sensitive to changes in lagoon liner construction, but small reductions in lagoon pH significantly reduced yearly average ammonia emissions. The combined model can be used to improve understanding of the impacts of CAFO lagoon overflow and seepage and develop sustainable management practices at the field scale for these key components of the agricultural landscape.