Estimating Transition Probabilities in Markov Chain-Based Deterioration Models for Management of Wastewater Systems
Publication: Journal of Water Resources Planning and Management
Volume 132, Issue 1
Abstract
Accurate prediction of the current and future conditions of wastewater systems using available assessment data is crucial for developing appropriate proactive maintenance and rehabilitation strategies for an aging wastewater collection and conveyance system. This paper proposes a method to estimate the transition probabilities of different condition states in Markov chain-based deterioration models for wastewater systems using an ordered probit model. The proposed model is applied and evaluated using the condition data of sewer pipes managed by the City of San Diego’s Metropolitan Wastewater Department. The developed model presents some advantages in estimating transition probabilities over the approaches developed in the past, including the nonlinear optimization-based approach, in terms of versatility in the implementation, precision of the estimated data, and appropriateness of the assumptions in the model. The paper concludes that the ordered probit model approach is a statistically sound and robust method; however, in order to gain greater accuracy in deterioration modeling, periodic assessment of the wastewater systems with more data types is desirable.
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Acknowledgments
This research was funded in part by a grant from the Purdue Research Foundation and in part by grant CMS-0201364 from the National Science Foundation. Their support is gratefully acknowledged. Any opinions, findings, conclusions, or recommendations expressed in this study are those of the writers and do not necessarily reflect the views of the National Science Foundation or the Purdue Research Foundation. The writers thank Mr. Dean Gipson of the Metropolitan Wastewater Department (MWWD), City of San Diego, for his assistance in providing data used in this study. The writers thank Professor Fred Mannering for his advice in developing and calibrating the ordered probit model.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 132 • Issue 1 • January 2006
Pages: 15 - 24
Copyright
© 2006 ASCE.
History
Received: Oct 28, 2004
Accepted: Feb 1, 2005
Published online: Jan 1, 2006
Published in print: Jan 2006
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