Analysis of urban pipe deterioration using Copula method

Date
2016
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University of Delaware
Abstract
Aging water main systems are becoming a growing concern for maintenance. The structural deterioration of water mains is affected by different factors, such as pipe age, pipe material, soil conditions, pipe size, and climate conditions, among others. Since pipes are underground and obtaining data for pipes is difficult and expensive, various statistical modeling methods have been used to analyze the factors contributing to the pipe condition deterioration and to predict the failure of pipes. This research applies the copula method to urban pipe data analysis to generate data that can be used to determine remaining life. Copula modeling is an emerging method of modeling that has been widely used in financial sectors. It has recently been used in hydrology and pavement management sectors, but the method has not been applied to other civil engineering disciplines. This research uses copula modeling to determine dependency between several variables of pipe condition and to compare how it may be a better choice for determining correlation dependency for data that are non-normal and skewed. The copula method is very useful when marginal distributions of water pipe condition variables belong to different families of distributions. Copula modeling is used to generate large volumes of data. The large data sets generated can then be used for evaluating the current pipe condition models and the appropriateness of those models for determining the remaining life of a pipe or pipe condition. In this paper, multivariate vine copula modeling was applied to water pipe data. The Bayesian inference approach was applied for parameter estimation, and GIS was used for analyzing soil properties’ effects on pipe condition assessment.
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