Water distribution network expansion: an evaluation from the perspective of complex networks and hydraulic criteria

Abstract

The expansion of water distribution networks is nowadays essential to meet the pressing population growth in many cities worldwide. With the subsequent increase in water demand, the hydraulic behaviour of a water supply system can change dramatically due to the significant head losses in the pipes caused by the larger flows released by pumping systems and reservoirs to supply the higher water consumption of the network. Strategical studies are necessary to delimit risk regions where a demand increase may affect the system too negatively. To analyse expansion scenarios with the lowest risk of failure and damage for the supply network operations, this research studies hydraulic performance and connectivity under various demand increase scenarios using calculations of complex network metrics together with relevant hydraulic criteria. For these two types of calculations, this research, developed in a Python framework, uses, respectively, the NetworkX 2.5 and WNTR 0.3.0 packages. The C-Town network is employed as a case study, and demand increasing scenarios are implemented on 30 nodes along the peripheral regions of the network to simulate the growth of the cities. Then, these scenarios are evaluated using the TOPSIS methodology, thus determining the best and worst sectors to expand the capacity of the network.

The Impact of Large-Scale Water Diversion Projects on the Water Supply Network: A Case Study in Southwest China

“…Giudiciani [28] et al studied the influence of topology on undirected and unweighted graphs in indicators based on network attributes such as connectivity and robustness. Thomas Anchita [29] used calculations of complex network indicators and associated hydraulic criteria and studied hydraulic performance and connectivity under various demand increase scenarios. Meng [30] used stress-strain testing to propose a general mapping framework of network elasticity and topological properties to analyze the key influencing factors of water supply network elasticity.…”