|Abstract:||Our interests in reactive nitrogen and the nitrogen cycle have shifted from increasing the efficiency of nitrogen delivery to target crop species to decreasing environmental damage caused by intensive agricultural practices. Enhancing the reactive nitrogen use to increase food production to meet future demand inevitably contributes to an increase in the reactive nitrogen load in the environment, often adversely impacting downstream ecosystems. Many novel strategies have been developed over the years to provide better management practices and, yet, the problem remains unresolved due to the complexity and spatial heterogeneity of the nitrogen cycle. In agricultural fields, anthropogenic activities, such as fertilizer applications and installation of subsurface tile drainage network, further complicate our ability to characterize the dynamics of nitrogen in the soil. Specific interpretation methods are thus required to gain a better understanding of the transformation and transport properties of soil nitrogen. We posit that one of these properties is the estimation of age, which is an analysis of an elapsed time in a particular state within a control volume. While age provides a trace of previous interactions between nitrogen species, concentration provides a snapshot of concurrent interactions of nitrogen dynamics. The combined analysis of concentration and age of soil nitrogen thus has the potential to provide an improved understanding of nitrogen dynamics.
The objective of this research is to develop an analytical framework and a model to characterize the “age” of soil nitrogen in different states such as nitrate, immobile ammonium, mobile ammonia, and mobile ammonium, which can be used to provide an assessment of the time elapsed since inorganic nitrogen has been introduced into the soil system. The birth process for inorganic soil nitrogen corresponds to mineralization, atmospheric deposition, and fertilizer. By using the age model, we aim to understand how topographic depressions and tile drains drive the spatial heterogeneity of nutrient concentration and age distribution over agricultural fields. Towards this objective, we develop a model for nitrogen age by considering various transformations associated with organic and inorganic nitrogen, and their transport and transit-time distributions. Here, a coupled three-dimensional ecohydrological and biogeochemical model is developed to explore the spatial variability and heterogeneity of soil nitrogen concentration and age. The studies conducted in this dissertation correspond to agricultural farms cultivating corn-soybean rotation, a common agricultural practice in the Midwestern United States. Our results show that the age of nitrogen is lower under soybean cultivation compared to corn although no fertilizer is applied for soybean cultivation. This result arises because the soybean utilizes the nitrogen fertilizer left from the previous year, thereby removing the older nitrogen and reducing nitrogen age. By analyzing the impacts of topographic depressions on the concentration and age of soil nitrogen, we show that in areas that represent closed topographic depressions, relatively lower nitrate concentration and age are observed compared to areas that are not classified as topographic depressions. This result arises because higher surface water depths in the topographic depressions increase the downward transport of water that carries more dissolved nitrate to the deeper soil layer. Also, we find a gradual decrease in the age of nitrate on the rising limb of nitrate efflux at a depth of 1.6 m, the bottom boundary for our simulation, and the opposite is true for the falling limb, indicating that the rising limb of nitrate efflux is more relevant to younger nitrate constituents and vice versa. For the tile drain study, we find that the ages of the nitrate and mobile ammonia/um in tile drainage range from 1 to 3 years, and within a year, respectively. These findings indicate that practices and policies for reducing nitrogen loadings have time lags between the implementation of mitigation plans and their responses, thus requiring mid- and long-term strategic plans. The research conducted in this dissertation have broad applications. The models and methods used in this study can be applied to other research issues, such as how climate change impacts the predictive understanding of nutrient age and its distribution across the watershed, and how to achieve sustainable agricultural practices by using the model developed in this dissertation as a guide for iterative and interactive learning processes to refine recommendations for adaptive management.