University of Arizona - Civil and Architectual Engineering and Mechanics
Drinking water distribution systems (DWDS) are the last step in delivering potable water to end-users. In order to provide adequate potable water there are multiple hydraulic and water quality objectives that must be satisfied. Over the years, the research within our group has generally focused on DWDS water quality issues associated with disinfectant and by-product dynamics and contamination warning systems. Through both laboratory and field-scale studies, we have been successful in representing observed DWDS water quality dynamics through the use of complex water quality simulations. However, there have also been discrepancies that, in part, result from inaccurate representation of the underlying hydraulics that define transport characteristics, such as residence time and travel paths. These results, which have been supported by tracer studies, have moved our research into improving end-user demand estimates, which drive the underlying hydraulics, to improve our capabilities for water quality research.
Our move into demand estimation has been focused on the development of a real-time demand estimation and forecasting algorithm using the hydraulic information (i.e., flows, pressures) available from utilities. Using our framework, we have been able to estimate demands for both synthetic and real-world systems that adequately represent the observed hydraulic information, but have also uncovered additional challenges. The first of these is that the approach(es) used to aggregate demands - to ensure a feasible estimation problem - and the relative location of the existing measurements can have significant impacts on the demand estimation problem. The second challenge, as we circle back to our water quality interests, is that by simply matching the observable hydraulics, we are not guaranteed improvements in the system-wide transport characteristics. This presentation will summarize our past water quality successes and challenges, our current research in the real-time demand estimation area, and provide current thoughts on the future challenges associated with real-time and water quality modeling.