Regression Analysis And Forecasting For Urban Water Supply

1154 words - 5 pages

Tampa Bay Water Regression Analysis and Forecasting for Urban Water Supply Introduction Hydrology, or the "science of water", has evolved a great deal in the past 50 years. One of the most difficult challenges facing today's utility engineers and planners is an understanding the effects of urbanization on the hydrological behavior of their systems. These issues are critical to bring a balanced perspective to the allocation and management of water resources. Engineers have traditionally had a limited vision of the problem and its extent of impact on the water system. Today's technology allows urban water suppliers to optimize water production while still protecting the environment. Tampa Bay Water ( is an example of one such company.Tampa Bay Water is Florida's largest wholesale water supplier. Their 11 member counties serve more than 1.8 million residents in the Tampa Bay region. Tampa Bay Water's mission is to provide reliable supplies of high-quality water to meet future and present needs in an environmentally and economically efficient manner. The objective ensures water demanded for their region can be met with minimal adverse environmental impacts by using sophisticated computer models to analyze and forecast conditions at their water supply facilities.Tampa Bay Water currently operates 12 wells, 11 of which are operated under an integrated system. Tampa Bay Water uses forecasting and complex regression analysis to optimize production schedules from the wells in order to meet member county demands. They also want to maximize ground-water levels at a selected set of surface wells called control points. Operating policies and infrastructure physical limits are reflected in the optimization model as constraints.The Optimization Model for Tampa Bay Water Tampa Bay's optimization plan utilizes an integrated hydrologic simulation model and optimization model to manage their 11 wellfields as an integrated water supply system. The hydrologic model simulates changes in water levels due to changes in stress. The optimization model schedules production from the wellfields in order to meet demands from their member counties. The output of the simulation/optimization modeling is a bi-weekly schedule prioritizing the production wells and their respective levels. This modeling improves Tampa Bay Water's ability to understand the water-level effects of well operations that impact the environment.The optimization model also seeks to maximize ground-water levels at specific wells, while meeting projected demands for the 11 member counties. The decision variables are the pumping rates at each production well and the ground-water levels in monitoring wells. The problem is subject to two general constraint sets and three specific constraint sets. The general constraint set consists of a system of equations describing the surface and ground-water hydrology and the variable boundaries. The specific constraint sets consist of the demand...

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