This thesis puts forth a process for ontology driven distributed simulation through a case study. Ontology is regarded as a domain model, including objects, attributes, methods and object relations. The case study involves trajectory simulation. A trajectory simulation is a piece of software that calculates the flight path and other parameters of a munition, such as its orientation and angular rates, from launch to impact. Formal specification of trajectory simulation domain is available as a domain model in the form of an ontology, called Trajectory Simulation ONTology (TSONT). Ontology driven federation development process proposed in this thesis is executed in three steps. The first step is to analyze the TSONT and to create instances of individuals guided by the requirements of the targeted simulation application, called Puma Trajectory Simulation. Puma is the simulation of a ficticious air-to-ground guided bomb. The second step is to create the High Level Architecture(HLA) Federation Object Model (FOM) using Puma Simulation individuals. FOM will include the required object and interaction definitions to enable information exchange among federation members, including the Puma federate and the Exercise Manager federate. Transformation from the ontology to FOM is realized in two ways: manually, and by using a tool called OWL2OMT. The third step is to implement the Trajectory Simulation federation based on the constructed FOM. Thus, the applicability of developing HLA federates and the federation under the guidance of ontology is demonstrated.

Global flood forecasting can benefit developing countries and ungauged regions that lack observational data, computational infrastructure, and human capacity for streamflow modeling. Many technical challenges exist to provide flood predictions on a global scale. First, existing land surface forecasts use coarse resolution grid cells, which provide limited information when used for flood forecasting at local scales. There is, so far, no modeling system that can provide rapid and accurate global flood predictions with low cost. Second, accurate flood predictions often require integrating interdisciplinary models, data sources, and analysis routines into a workflow. Limited accessibility, reusability, and interoperability of models restrict integrated modeling from producing more reliable results. Web services have been demonstrated as an effective way for data and model sharing because of the capability of enabling communication among heterogeneous applications over the internet. However, publishing models or analysis routines as web services is still challenging and, hence, is not commonly done. To address the above challenges, I present a computational system for global streamflow prediction, using existing, well-established open source software tools, that quickly downscales the runoff generated from such coarse grid-based land surface models (LSMs) onto high-resolution vector-based stream networks then routes the results using a vector-based river routing model. A set of experiments are conducted to demonstrate the feasibility and credibility of this approach. I also present a tool to publish complex environmental models as web services by adopting the OpenGMS Wrapper System (OGMS-WS) and Docker. The streamflow prediction system is deployed as a web service using this tool, and the service is used to analyze the historical streamflow tendency in Bangladesh. Next, I present a ready-to-use tool called Tethys WPS Server, which provides a simplified and formalized way to expose web app functionality as standardized Open Geospatial Consortium (OGC) Web Processing Services (WPS) alongside a web app's graphical user interface. Three Tethys web apps are developed to demonstrate how web app functionality(s) can be exposed as WPS using Tethys WPS Server, and to show how these WPS can be coupled to build a complex modeling web app. In sum, this dissertation explores new computational approaches and software tools to advance global streamflow prediction and integrated environmental modeling.