Social-network-based water supply network sectorization methodology using monte carlo simulation to predict economical and operational benefits

Abstract

Water Supply Network (WSN) sectorization is a broadly known technique aimed at enhancing water supply management. In general, existing methodologies for sectorization of WSNs are limited to assessment of the impact of its implementation over reduction of background leakage, underestimating increased capacity to detect new leakage events and undermining appropriate investment substantiation. In this work, we raise this issue and put in place a methodology to optimize sectors' design. To this end, we carry out a novel combination of the Short Run Economic Leakage Level concept (SRELL- corresponding to leakage level that can occur in a WSN in a certain period of time and whose reparation would be more costly than the benefits that can be obtained). With a non-deterministic optimization method based on Genetic Algorithms (GAs) in combination with Monte Carlo simulation. As an example of application, methodology is implemented over a 246 km pipe-long WSN, reporting 72 397 $/year as net profit.