Novel Eulerian Approach with Cellular Automata Modelling to Estimate Water Quality in a Drinking Water Network

Abstract

The forecast analysis of the exposure to the contamination risk in a water distribution network requires increasing the quality of the applied input/outputs modeling. This need involves using non-traditional models responding to the increasingly high computation requirements. In this scenario, the Cellular Automata paradigm represents a new frontier with considerable potential. Specifically, this paper describes the Eulerian Water quAlity Modeling—Cellular Automata (EWAM-CA) model, aimed at simulating the sodium hypochlorite (chlorine) injection, transport, and reaction phase in a medium-sized drinking water network. The EWAM-CA accuracy was compared with the Epanet software on a Fossolo water network, in Bologna town (Italy), considering a constant and an impulsive input respectively. Due to CA's intrinsic aptitude for parallel computing, a parallel version of EWAM-CA was developed. Moreover, using the capability of the cellular automata to manage the modeling asynchronously, improving the computational efficiency, we propose a novel approach based on activation/deactivation asynchronous rules, avoiding unnecessary calculations in nodes or pipes where no pollution occurs. The different EWAM-CA versions were compared for the case study, and the parallel EWAM-CA approach coupled with asynchronous functionality significantly improved computational performance.