Evaluation of failure risk in the sewerage system using Bayesian network and spatial multi-criteria decision making

Subject Areas :

Seyed Morteza  Ghoreishi ¹ (MSc student of Remote Sensing and GIS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran)
Mohammad Hassan  Vahidnia ² (Department of Remote Sensing and GIS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University)
Aminreza  Neshat ³ (Assistant Professor, Department of Remote Sensing and GIS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran)

Received: 2023-04-17 Accepted : 2023-06-21 Published : 2023-06-21

Keywords: Data envelopment analysis, Spatial analysis, multi-criteria decision analysis (MCDA), Sewerage System,

Abstract :

A failure in the sewage network as one of the important urban infrastructures can have adverse consequences, which sometimes even leads to the disruption of a part of a city's performance. In this article, the risk of failure in sewerage networks was conducted based on the combination of the probability of failure and the consequences of failure in the 4th water and sewerage area of Tehran. For this purpose, Bayesian networks were first used to obtain the probability of failure. The network was formed based on features such as deposits, pipe leakage, corrosion, pipe wear, and pipe deformation. For 1610 pipes, 70% of which were used for training and 30% for testing, the probability of pipe blockage was 6.7%, the probability of hydraulic failure was 2.2%, the probability of structural failure was 0.3%, and the total probability of failure for pipes was 8.7%. The overall average accuracy of this step was estimated at 76%. In estimating the consequences of failure, spatial analysis in GIS and the DEA multi-criteria decision-making method were used. Spatial analysis such as buffer for 9 spatial criteria made it possible to score pipes with high speed and efficiency in case of failure and its impact on the surroundings. The DEA method has the advantages of using objective and subjective data as well as reducing the number of pairwise comparisons. Finally, with the effect of PoF and CoF values on each other, the risk of pipe failure was obtained and by ranking them, 9 items in the network were identified as critical pipes. The results showed that such an approach has high reliability and the risk of failure can be estimated with proper accuracy.