Search Results (5)

All urban and agricultural water distribution networks (WDNs), irrespective of their physical and operational characteristics, encounter substantial leakages which result in significant water losses, environmental degradation through increased carbon emissions, and noteworthy economic burdens. The current work aims to quantify both the environmental impact, estimated in terms of CO₂ emissions, and the economic implications associated with leakages and evaluate the effect of the most widely used leakage reduction strategies. The current approach is applied to the water distribution network of the city of Patras in Western Greece. Full article

While only a minimal fraction of global water resources is accessible for drinking water production, their uneven distribution combined with the climate crisis impacts leads to challenges in water availability. Leakage in water distribution networks compounds these issues, resulting in significant economic losses and environmental risks. A coherent review of (a) the most widely applied water loss estimation techniques, (b) factors influencing them, and (c) strategies for their resilient reduction provides a comprehensive understanding of the current state of knowledge and practices in leakage management. This work aims towards covering the most important leakage estimation methodologies, while also unveiling the factors that critically affect them, both internally and externally. Finally, a thorough discussion is provided regarding the current state-of-the-art technics for leakage reduction at the municipal-wide level. Full article

Hydraulic modeling of water distribution networks (WDNs) is a vital step for all water-related professionals towards the development of management practices and strategies that aim for the reduction of water losses and the associated financial cost and environmental footprint. In the current work, we develop an easy-to-implement methodology for the effective modeling of WDNs, which seeks to minimize the computational load without undermining the analysis’s accuracy, using the open access EPANET (Environmental Protection Agency Network Evaluation Tool) software package. The effectiveness of the proposed methodology is tested via a large-scale, real-world application for the city of Patras. Full article

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. Full article

Quantification of water losses (WL) in water distribution networks (WDNs) is a crucial task towards the development of proper strategies to reduce them. Currently, WL estimation methods rely on semi-empirical assumptions and different implementation strategies that increase the uncertainty of the obtained estimates. In this work, we compare the effectiveness and robustness of two widely applied WL estimation approaches found in the international literature: (a) the water balance, or top-down, approach introduced by the International Water Association (IWA), and (b) the bottom-up or minimum night flow (MNF) approach, based on a recently proposed probabilistic MNF estimation method. In doing so, we use users’ consumption and flow-pressure data from the 4 largest pressure management areas (PMAs) of the WDN of the city of Patras (the third largest city in Greece), which consist of more than 200 km of pipeline, cover the entire city center of Patras, and serve approximately 58,000 consumers. The obtained results show that: (a) when MNF estimation is done in a rigorous statistical setting from high resolution flow-pressure timeseries, and (b) there is sufficient understanding of the consumption types and patterns during day and night hours, the two approaches effectively converge, allowing for more reliable estimation of the individual WL components. In addition, when high resolution flow-pressure timeseries are available at the inlets of PMAs, the suggested version of the bottom-up approach with probabilistic estimation of MNF should be preferred as less sensitive, while allowing for confidence interval estimation of the individual components of water losses and development of proper strategies to reduce them. Full article