Age–based vs condition–state reliability modelling for wastewater lift stations

This paper presents a reliability-based case study for wastewater lift station asset management using two modelling approaches applied within a unified analytical framework: the Weibull-based Integrated Asset Management System and a discrete Markovian deterioration model. The analysis applies to 134 lift stations in the City of Sugar Land, Texas, covering pumps, controls, SCADA, and related components. The Weibull model estimates risk from age-based probabilities of failure, while the Markov model represents transitions among Good, Fair, Poor, and Failed condition states derived from age-to-state discretisation using expected useful life fractions. Both models were calibrated using the same dataset and evaluated over a ten-year period under three funding scenarios: do-nothing, US$2.5 million per year, and US$5 million per year. The Markov model produced smoother deterioration trends, lower long-term system risk, and higher efficiency stability than the Weibull process. Sensitivity testing confirmed model robustness across repair times and deterioration rates. The results show how comparing age-based and condition-state modelling approaches within a single framework can inform risk forecasting and investment planning decisions for municipal utilities with limited condition monitoring data.