Combining Statistical Clustering with Hydraulic Modeling for Resilient Reduction of Water Losses in Water Distribution Networks: Large Scale Application Study in the City of Patras in Western Greece

Abstract

Partitioning of water distribution networks (WDNs) into pressure management areas (PMAs) or district metered areas (DMAs) is the most widely applied method for the efficient management and reduction of real losses (leakages). Although PMA partitioning is a crucial task, most clustering methods are strongly affected by user-defined weighting factors that heavily affect the final outcome while being associated with heavy computational loads, leading to time-consuming applications. In this work, we use hierarchical clustering enriched with topological proximity constraints to develop an approach for the optimal sizing and allocation of PMAs (or DMAs) in water distribution networks that seeks to minimize water leakages while maintaining a sufficient level of hydraulic resilience. To quantify the latter, we introduce a resilience index that accounts for water leakages and nodal heads in pressure-driven and mixed pressure-demand ways, respectively. The strong points of the introduced approach are that (1) it uses the original pipeline grid as a connectivity matrix in order to avoid unrealistic clustering outcomes; (2) it is statistically rigorous and user unbiased as it is based solely on statistical metrics, thus not relying on and/or being affected by user-defined weighting factors; and (3) it is easy and fast to implement, requiring minimal processing power. The effectiveness of the developed methodology is tested in a large-scale application study in four PMAs (namely Boud, Kentro, Panahaiki, and Prosfygika) of the city of Patras in western Greece, which cover the entire city center and the most important part of the urban fabric of Patras, consisting of approximately 202 km of pipeline and serving approximately 58,000 consumers. Due to its simplicity, minimal computational requirements, and objective selection criteria, the suggested clustering approach for WDN partitioning can serve as an important step toward developing useful decision-making frameworks for water experts and officials, allowing for improved management and reduction of real water losses.