Doctor of Philosophy (PhD)


Civil and Environmental Engineering

Document Type



Coastal and riverine flooding constitutes a major environmental hazard that affect millions of people residing along the world’s coastline. Improved understanding of the driving mechanisms that can cause flooding within coastal watersheds requires advanced hydrologic and coastal storm surge simulation. Such advanced simulation is dependent upon an accurate digital elevation model (DEM) for the optimal topographical representation of the true domain in the discretized model grid (mesh). However, it is not possible to afford mesh resolution as fine as contemporary DEMs, resolved at sub-10 meters, due to the impractical computational expense. Therefore, significant elevation barriers such as roadbeds, levees, railroads, and natural ridges that conduct, impede or otherwise influence surface-water flow propagation, referred to throughout this dissertation as ‘vertical features,’ must be identified and considered in the development of an unstructured mesh. An algorithm, named PyVF, is developed to automate the extraction of vertical features based on only two parameters, a differential elevation threshold and a local feature radius. The algorithm is applied to a state-of-the-art DEM at 1-m resolution to test the robustness of the algorithm for the automatic extraction of potential vertical features. Furthermore, the extracted potential vertical features are downscaled according to specified constant or variable sizing function, for use in unstructured mesh generation with fixation of vertical features, including direct assignment of DEM cell elevation, in the mesh. Finally, PyVF is also well-suited for overland flow/flood modeling, and demonstrated herein for the commonly used models SWAT and HEC-RAS, concerning the automatic extraction of ridge and valley features for model grid development or adjustment.



Committee Chair

Hagen, Scott C.