Application of artificial neural networks to forecasting water quality in a chloraminated water distribution system

Abstract

Accurate forecasting of disinfection residuals in a water distribution system (WDS) is essential for optimal control of disinfectant dosing in order to maintain good water quality within the system. The most commonly used disinfectant in the drinking water treatment process throughout the world is chlorine. Previously, artificial neural networks (ANNs) have been used successfully to predict chlorine residuals in chlorinated WDSs. Recently, an increasing number of water utilities are using chloramine as a secondary disinfectant in WDSs. Chloramine has several advantages compared with chlorine including fewer issues with disinfection by-products (DBP) and longer persistence. However, limited r..