Baltimore Ecosystem Study Institute of Ecosystem Studies

2010 BES Annual Meeting Presentation and Poster Abstracts



 
Modeling Nitrogen Transport and Transformation in Aquifers using a Particle Tracking Approach
 
Cui, Zhengtao
Co-Authors: Zhengtao Cui, Claire Welty, Reed Maxwell

 
Abstract: Nitrogen is one of the most common groundwater contaminants in the Chesapeake Bay area. Regulatory efforts are being implemented to reduce nitrogen loads to the bay. Mathematical modeling can be used as a management tool to help assess nitrogen reduction efforts. However, current groundwater contaminant models are inefficient, lack a heterogeneity feature, or are not physically based. To meet these needs, we developed a particle tracking-based numerical model to simulate nitrogen transport and transformation in aquifers. The particle-tracking method has several advantages over finite-difference or finite-element approaches in terms of performance and accuracy, particularly for heterogeneous, advectively-dominated systems. This model is based on an existing Lagrangian, particle tracking model, SLIM-FAST. Geochemical reactions and biodegradation processes have been added to the SLIM-FAST code. The operator splitting technique is used to performance transport and chemical reactions in two steps. This is a hybrid approach because the reactions are modeled by solving the reaction system of equations using the species concentrations instead of particle collisions. The kinetics of the reactions are modeled by the multiple-Monod equations. The VODE algorithm has been chosen as the solver for the non-linear system of ODEs. Ongoing work includes verification of the new code against other numerical and analytical models. When combined with a stochastic groundwater flow model, the model can be used to study nitrogen transport and transformation in fractured rock aquifers that underlie the Chesapeake Bay watershed. For example, subsurface nitrogen loads and the effects of extreme precipitation events on nitrogen loading can be estimated.