Bulk Decay Coefficient Assessment for Different Water Temperatures: Ensemble Temperature State Estimation Approach

Most water supply systems rely on free chlorine residual to ensure disinfection through the network and at the user’s tap. Temperature increase is known to accelerate the chlorine decay process and is typically associated with water quality deterioration. This is a challenging situation under the current climate change scenario, which is bound to increase average temperatures and the intensity and frequency of extreme-temperature events. Moreover, water temperature varies through the supply network due to seasonal changes and thermal interaction, so it is not straightforward to model chlorine evolution through the network considering temperature effects. Previous works have highlighted the importance of considering the Arrhenius formula when accounting for temperature changes in the bulk chlorine decay coefficient (typically characterized through bottle tests), but these studies have never explicitly considered the uncertainty of the bulk decay coefficient itself. Recent studies have identified that the uncertainty of the bulk decay coefficient may be relevant (>15%) and should be considered when cross-comparing bottle test results (e.g., at different temperatures). The aim of this work is to propose a new method that statistically computes the mean and standard deviation of the key parameters in the Arrhenius formula (the reference bulk decay coefficient kb0 and activation coefficient E/R) from free chlorine residual bottle test results (with replicated measurements over samples from the entrance to the network) at different temperatures. This approach (here called the ensemble temperature state estimation approach) ensures that bottle test measurements at different temperatures are jointly assessed to derive an equation that provides the bulk decay coefficient at any water temperature. Therefore, the new method improves the characterization of the bulk decay component (and its associated uncertainty) and could be crucial for improving the understanding and modeling capabilities of complex chlorine dynamics within supply infrastructure.