This dissertation represents the research and development of new concepts and techniques for modeling the knowledge about the many concepts we as hydrologists must understand such that we can execute models that operate in terms of conceptual abstractions and have those abstractions translate to the data, tools, and models we use every day. This hydrologic knowledge includes conceptual (i.e. semantic) knowledge, such as the hydrologic cycle concepts and relationships, as well as functional (i.e. procedural) knowledge, such as how to compute the area of a watershed polygon, average basin slope or topographic wetness index. This dissertation is presented as three papers and a reference manual for the software created. Because hydrologic knowledge includes both semantic aspects as well as procedural aspects, we have developed, in the first paper, a new form of reasoning engine and knowledge base that extends the general-purpose analysis and problem-solving capability of reasoning engines by incorporating procedural knowledge, represented as computer source code, into the knowledge base. The reasoning engine is able to compile the code and then, if need be, execute the procedural code as part of a query. The potential advantage to this approach is that it simplifies the description of procedural knowledge in a form that can be readily utilized by the reasoning engine to answer a query. Further, since the form of representation of the procedural knowledge is source code, the procedural knowledge has the full capabilities of the underlying language. We use the term "functional ontology" to refer to the new semantic and procedural knowledge models. The first paper applies the new knowledge model to describing and analyzing polygons. The second and third papers address the application of the new functional ontology reasoning engine and knowledge model to hydrologic applications. The second paper models concepts and procedures, including running external software, related to watershed delineation. The third paper models a project scenario that includes integrating several models. A key advance demonstrated in this paper is the use of functional ontologies to apply metamodeling concepts in a manner that both abstracts and fully utilizes computational models and data sets as part of the project modeling process.

The Florida Keys National Marine Sanctuary (FKNMS) encompasses North America's only living coral barrier reef and the third longest barrier reef in the world, making it a unique national treasure of international notoriety (FKNMS, 2005). Recent evidence of environmental decline within the sanctuary has created a sense of urgency to understand and protect the valuable resources within. This thesis contributed to the understanding of habitat connectivity to aid managers and decision makers in the creation of additional Marine Protected Areas (MPAs) in the FKNMS to help prevent further environmental decline. This research specifically focused on modeling larval transport and larval connectivity among Acropora palmata (Lamarck, 1816) populations, coral habitats and MPAs in the upper and middle FKNMS. The transport of larvae in relation to ocean currents is a very limited area of research, and the analytic modeling results may serve as powerful guides to decisions about the relative importance of individual coral habitats and MPAs in the study area.Larval transport was modeled with ArcGIS and TauDEM using SoFLA-HYCOM simulated ocean currents during the A. palmata spawning season. This model allowed for the assessment of coral habitat and A. palmata population larval connectivity. The dependence of three distant A. palmata test populations on other upstream coral habitats and A. palmata populations significantly differed (Kruskal-Wallis test, P less than 0.0001). The clonally diverse Sand Island Reef A. palmata population's larval connectivity was significantly higher compared to other distant monoclonal populations (Mann-Whitney test, P less than 0.0001). Compared to the clonal structure of each test population determined by Baums, Miller, and Hellberg (2006), results indicated simulated larval connectivity may be a determinant of A. palmata population clonal diversity.By modeling MPA and coral habitat connectivity, this study also identified unprotected and distant coral habitat areas with the greatest downstream influence on MPAs; these may serve as potential coral larvae sources. It is recommended that establishing these areas as no-take MPAs would improve overall coral habitat and MPA network connectivity.