Quantifying N2O emission hotspots and mitigation potential for individual fields in the US Corn Belt with a metamodeling approach

Abstract:

The US Corn Belt produces about 35% of the global corn and consumes the largest amount of nitrogen (N) fertilizer as a region worldwide. The excess application of N-fertilizer has been pervasive in this region, and the unrecovered N eventually enters the environment as pollutant or greenhouse gases (GHGs), among which Nitrous oxide (N₂O) is a major concern. Optimizing N management practices can increase farmers’ profit and also help reduce N₂O emissions in corn production. However, the practical information where and how much the mitigation is possible remains unclear. Process-based crop models are the primary tools for predicting crop yields, soil dynamics, and GHG emissions resulting from changes in agricultural management practices. However, its application to the millions of individual farms is prohibited by the expensive computing and storage cost. Alternatively, a reduced form of these models has been proposed to mimic the original model while reducing the computational burden significantly. In this study, we used a metamodeling approach to learn the key mechanisms regarding the N cycle from a process-based biogeochemical model, ecosys. Ecosys has been well-calibrated and validated for CO₂, energy, and water fluxes measured at multiple AmeriFlux sites as well as observed N₂O fluxes. Our results show that by feeding inputs of soil properties, monthly averaged weather data, and agricultural management practice, the metamodel we constructed can reproduce approximately 99% variability of the ecosys simulated N₂O at randomly selected 99 counties in Illinois, Indiana and Iowa. We further applied the metamodel to every cornfield in 9 states in the US Corn Belt with varying management scenarios. These scenario simulations allow us to quantify the differences between N₂O emissions under current practices and optimal practices, thereby identifying hotspots of N₂O emissions as well as places where mitigation efforts should be prioritized.