Large scale groundwater flow and contaminant transport modeling

This work introduces a combination of the vertically integrated Analytic Element and deterministic Streamline methods for watershed-scale groundwater flow and contaminant transport modeling. This new method combines the Analytic Element Method's ability of modeling large spatial domains while preserving stream-scale details, with the conceptional elegance of the Streamline method. Both methods allow for parallel processing in order to reduce model run-times. The intended use of this new method is the study of non-point source contaminant transport on the watershed scale (e.g., nutrient loading to surface water from agricultural fields). A new iterative Analytic Element Method algorithm is devised for solving 2D steady-state groundwater flow models containing large numbers of head-specified elements (e.g. rivers and lakes). The new algorithm improves convergence of models containing head-specified elements by explicitly computing fluxes of all such features at the start of each iteration. The new algorithm also enables the use of efficient parallel processing on distributed-memory super-computers. The combination of parallel processing and reduced number of iterations significantly extends the size and complexity of problems that can be modeled using the Analytic Element Method. The vertically integrated Analytic Element Method flow solution is used to construct three-dimensional particle tracks that define the geometry of the Streamline Method by approximating vertical flow. The inherently parallel nature of the algorithm supports the development of reactive transport models for spatial domains much larger than current grid-based methods. The applicability of the new approach is verified for cases with negligible transverse dispersion through comparisons to analytic solutions and existing numerical solutions, and parallel performance is demonstrated through a realistic test problem based on the regional-scale transport of agricultural contaminants from spatially distributed sources.