Robust decision support tools that aid water utilities to make informed, swift and precise decisions are becoming the need of the hour. Application of sophisticated models to aid the process of condition assessment and risk analysis on water pipelines have been limited owing to the lack of scalability, inability to incorporate external open source datasets and mathematically complicated output results. Interactive visualization of resultant model output is the key element in extracting valuable information to support decision making. This thesis presents a framework for visualization of data related to drinking water pipelines. Critical components of strategic, tactical and operational level decision making are explored in context with data presentation and information depiction. This thesis depicts various aspects of developing GIS web applications and their important functionalities for query and visualization of data. Multiple facets of data storage, standardization and application development are highlighted in this document. Publishing of application geo processing services in web environment is done through Virginia Tech enterprise geodatabase. Risk assessment and Performance models developed by a utility are projected in the application environment through help of widgets. Applications are coded into links on a Drupal website (www.pipeid.org) for model dissemination and utility engagement purposes. / Master of Science / Drinking water supply network primarily consists of pipelines, pumping stations, reservoir basins and treatment plants. Water pipelines are routinely inspected to check their condition and maintain appropriate water quality. Management of these subsurface assets should be given prime importance for maintaining high standards of services at acceptable cost to customers. An integral step in accomplishing this task is to view pipeline network in a geographic map. Different factors affecting pipeline condition are displayed on the map in the form of individual layers. Such real-world problems are analyzed with the help of Geographical Information System (GIS) tools that incorporate spatial features with tabular information. Moreover, interpretation of raw data into meaningful insights and distribution of allocated knowledge to all the concerned parties can be efficiently accomplished using rich internet applications. This thesis presents a framework to use GIS tools for developing web applications using raw data samples from contacted water utilities. Sample web applications are created and discussed in the form of case studies. Also, the challenges in water utility sector with respect to utilizing GIS tools for supporting daily decision-making processes is highlighted in this document. The recommendation to improve the suggested framework and adding more functionalities to developed applications are presented at the end with references.

Previous authors have developed many different types of water pipe condition and failure models using the various methodologies available.  Contrary, current utilities are struggling to maintain their current water infrastructure system, due to the lack of effective prediction tools at hand.  The gap between the methodologies available in academic research and the tools available to current water utilities needs to be addressed.  This paper presents a fuzzy inference prediction model used to forecast the performance rating of individual drinking water pipeline sections (node to node) in which utilities can easily apply to their drinking water infrastructure system. Prior to the development of a prediction model, a through literature and current practice review is completed detailing and summarizing all the available mathematical models.  Following, an infrastructure overview is presented detailing the various pipe materials, lifecycle and failure modes and mechanisms.  A data structure is also detailed which lists all parameters that affect the condition and/or performance of a pipeline.  All of these tools are successfully used to develop a fuzzy inference performance model. The fuzzy inference performance model is considered novel in that it considers close to 30 pipe parameters.  Moreover, the performance model is applied using the Western Virginia Water Authority (WVWA) and the Washington Suburban Sanitary Commission (WSSC) databases to evaluate and verify the predicting results.  Lab testing of several pipe samples is also used to evaluate the model.  The testing consists of a ring bearing test which is used to calculate the rupture modulus of the pipe.  Comparing the original vs. the current rupture modulus can determine the remaining strength of the pipe.  The remaining strength can then be used to assess the performance results predicted by the fuzzy inference model. Further a framework is set forth which utilizes the model's predicted performance ratings to develop deterioration curves which can be used as a tool to forecast and plan future inspection, repair, rehabilitation and replacement of water pipelines.  The deterioration model is made up of a Markov chain approach coupled with a non-optimization technique. / Ph. D.