The Rappahannock River Basin Commission is undergoing a collaborative water supply planning process for Virginia's Rappahannock River Basin. Participants in the planning process have indicated an interest in technical information about the possible impact conservation programs may have on reducing residential water demand. The potential influence of conservation programs is identified through a literature synthesis and a statistical analysis of residential water demand for a locality within the basin (Stafford County). In the literature synthesis, conservation programs are classified as voluntary or mandatory. Voluntary programs utilize financial incentives (such as water pricing and rebates) or educational incentives (such as radio ads and bill inserts) to encourage conservation, and mandatory programs utilize regulatory incentives (such as plumbing standards and bans on outdoor water use). The water demand statistical model was estimated to more specifically identify how Stafford residential water customers respond to water pricing/rate structure changes (financial incentives), imposition of federal regulations on plumbing standards (regulatory incentives), and a voluntary conservation program utilizing educational incentives. The results indicate that while many studies have found residential customers are responsive to price changes, Stafford residential water users have not significantly changed their water demand in response to price/rate structure changes. Previous literature also suggests federal plumbing standards potentially have a significant impact on water demand. The influence of new plumbing standards in the Stafford demand model was inconclusive and warrants further analysis. Consistent with the literature, voluntary conservation programs utilizing educational incentives alone did not substantially alter residential water demand in Stafford County. / Master of Science

The present work deals with the development of a computational geometric framework for vision modeling for performing visibility and legibility analyses in Digital Human Modeling (DHM) using the field-of-view (FoV), estimated geometrically from 3D tessellated head scans. DHM is an inter-disciplinary area of research with the prime objective of evaluating a product, job or environment for intended users through computer-based simulations. Vision modeling in the existing DHM’s has been primarily addressed through FoV modeling using right circular cones (RCC). Perimetry literature establishes that the human FoV is asymmetric due to unrestricted zygomatic vision and restrictions on the nasal side of the face. This observation is neither captured by the simplistic RCC models in DHM, nor rigorously studied in vision literature. Thus, the RCC models for FoV are inadequate for rigorous simulations and the accurate modeling of FoV is required in DHM. The computational framework developed in this work considers three broad components namely, the geometric estimation and representation of FoV, visibility and statistical visibility, and legibility of objects in a given environment. A computational geometric method for estimating FoV from 3D laser-scanned models of the human head is presented in this work. The strong one-to-one similarity between computed and clinically perimetry maps establishes that the FoV can be geometrically computed using tessellated head models, without necessarily going through the conventional interaction based clinical procedures. The algorithm for FoV computation is extended to model the effect of gaze-direction on the FoV resulting in binocular FoV. A novel unit-cube scheme is presented for robust, efficient and accurate modeling of FoV. This scheme is subsequently used to determine the visibility of 3D tessellated objects for a given FoV. In order to carry out population based visibility studies, the statistical modeling FoV and generation of percentile-based FoV curves are introduced for a given population of FoV curves. The percentile data thus generated was not available in the current ergonomics or perimetry literature. Advanced vision analysis involving character-legibility is demonstrated using the unit-cube with an improved measure to incorporate the effect of character-thickness on its legibility.