Spatiotemporal quantification of inflow and infiltration through a multi-parametric analysis of wastewater...

The identification and quantification of extraneous water, i.e., infiltration and inflow, in sewage networks is imperative yet inherently complex, given its diverse origins and the intricate interplay between geological, land-use, and hydrological factors that govern its dynamics. By adopting a novel multi-parameter approach to address a recognized knowledge gap, this study introduced a regional-scale spatiotemporal analysis that provides the ability to distinguish infiltration from inflow contributions under varying hydrological conditions. It explored methods for identifying and quantifying I&I utilizing stable isotopes of oxygen (δ¹⁸O), electric conductivity (EC), chemical oxygen demand (COD) and turbidity as tracers in combination with flow and hydrological data. Localized I&I was estimated over a 24-hour period during both low and high groundwater levels and under dry and wet weather conditions. Spatiotemporal analysis was performed on a regional scale over the course of a year, encompassing 50 pump stations and the wastewater treatment plant. During dry weather periods, the contributions of groundwater to the total flow were analyzed using δ¹⁸O, EC, COD and turbidity. By combining δ¹⁸O's stability with the sensitivity of EC and COD to anthropogenic influences, the two components of I&I during wet weather periods were estimated by pairing the tracers. The conservative nature of δ¹⁸O made it an effective tracer for identifying different water sources and understanding the effect of hydrological conditions on sewage networks. EC and COD, highly influenced by the daily dynamics of human activities, provided valuable information on the dilution effect caused by extraneous water. Turbidity measurements conducted at pump stations were affected by pumping-induced fluctuations, rendering turbidity-based estimations unreliable. During the 24-hour sampling campaign, I&I contributed up to 51% in the snowmelt period in spring and as little as 5% in the snow accumulation period in winter. Spatial analysis indicated variations across both space and time, with extraneous water reaching up to 73.4%. The findings reveal that even within a single municipality, extraneous water contributions vary considerably, emphasizing the need for management strategies tailored to both site and source. By implementing this approach and using tracers appropriate for the network conditions, utilities can identify the dominant sources of extraneous water and critical hotspots within the network and prioritize targeted investigations and/or rehabilitation measures.