Asset Management Decision Support Model for Water Distribution Systems: Impact of Water Pipe Failure on Road and Water Networks

Abstract

Failure of a buried water pipeline can have an adverse effect on neighboring infrastructure, especially road networks. The impact of the failure of water pipelines on road networks and water distribution systems (WDSs) significantly increases the economic and social consequences of such failure. This paper presents a risk-informed decision support framework for WDSs considering the risk and the criticality of components to aid maintenance prioritization. The probability of water pipe failure is estimated using a physical probabilistic approach. The economic, operational, environmental, and social consequences of the failure of the integrated water and road segments are evaluated using 14 factors. The economic, operational, environmental, and social consequences are combined using fuzzy hierarchical inference to determine the overall consequence of the failure of each integrated segment (road and water network sharing the same geographical space). The risk of assets is determined by utilizing two approaches: risk equation and risk matrix. A shortest path–based network efficiency metric is then used to identify the impact of the failure of water pipelines on both infrastructure systems. The final decision alternatives are prepared by combining the outputs from the risk analysis and the network efficiency metric to prioritize maintenance tasks. A geospatial model is used to identify dependent road and collocated water segments sharing the same geographical space. The water and road networks of the Rancho Solano Zone III area of the city of Fairfield, California, are used to illustrate the proposed framework. The results show that the failure of a critical segment can have a significant impact on the efficiency of both networks. In the considered case study, the failure of a critical segment can result in about 7.5% and 9.6% system efficiency loss in the water and road networks, respectively. The proposed model is expected to assist in integrated municipal asset management decision-making.