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How Much Water Weight Have You Lost? Quantifying Rehabilitation Effectiveness in the Collection System

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Knoxville Utilities Board (KUB), Knoxville, TN, has performed and continues to perform largescale sewer rehabilitation projects within their collection system. These projects are mainly in response to a Consent Decree (CD) with the United States Environmental Protection Agency (EPA) and the Tennessee Department of Environment (TDEC) which became effective February 2005. Sewer rehabilitation activities have included cured-in-place pipe (CIPP) lining of gravity sewer mains up to and including laterals to private property lines, pipe replacement, and manhole rehabilitation. To measure the effectiveness of such projects, KUB set out to assess the qualitative and quantitative reductions made in rainfall dependent inflow and infiltration (RDI/I) in several study areas by performing pre- and post-rehabilitation flow monitoring from 2003 through 2008. The goal of this assessment being to estimate future RDI/I reductions due to similar rehabilitation and to update credits taken within a Capacity Assurance Program (CAP) required under the CD.

This paper presents and compares the results from two tools used to assess the reductions KUB gained from their rehabilitation activities. The first tool is a common practice which evaluates reductions based on control areas in conjunction with rehabilitation study areas under a traditional linear fit statistical model. The second tool evaluates the reductions gained based on a non-linear extrapolation model developed by Dr. Zhi Zhang at the University of North Carolina, Charlotte.

The results of 16 minibasin study areas were compiled and the overall RDI/I reduction in the non-linear extrapolation model results were 8% higher than that of the traditional linear regression analysis. The larger benefit though was the lack of dependence on multiple control minibasins under the non-linear method. Data under the traditional linear fit approach was limited due to finding precipitation events common to both the control and study areas. Trending showed a higher degree of data correlation for the non-linear model approach and a greater potential for reducing control data in the future.

Keywords: Linear Regression; Non-Linear Extrapolation Model; Post-Rehabilitation; RDI/I Reduction

Document Type: Research Article


Publication date: 2011-01-01

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