Full Description

As water distribution infrastructure ages, utility managersmust weigh the benefits and costs of pipe repairs againstthose of replacement. Although models have been proposedto help managers make these decisions, they have not been ableto incorporate the environmental and geographic factors thatinfluence infrastructure condition. This article introduces a diagnostictool that uses system data and pipe break records to helpmanagers identify regions across the network that contain aggressiveenvironments and that may be most prone to failure.The aggressivity index (AI) is an indicator based on historicalnetwork performance. Spatial disaggregation is used to assessvariability within the network; observed break data are used to infervariable aggressivity across the domain. The AI enables current andpotential influences of aggressive environments to be factored inwithout the need to explicitly identify and measure physical propertiesthat may influence degradation of cast-iron pipe networks.Development of an effective pipe replacement schedule isimpossible without insight into the current and future state ofdeterioration. For systems with a low rate of pipe failure, networkmonitoring or quantification of influential factors may be almostas expensive as pipe replacement. The AI provides an alternativeto costly monitoring-based approaches to main replacement andenables utility managers to compile an efficient replacementschedule that targets pipes in specific areas. Includes 26 references, table, figures.

Product Details

Edition: Vol. 95 - No. 5 Published: 05/01/2003 Number of Pages: 7 File Size: 1 file , 390 KB