A data-driven approach is developed and proven for ranking the risk of low disinfection residual in water distribution storage tanks, 1 month ahead. The forecasting methodology uses water quality data collected from drinking water treatment plants, storage tank outlets, and rainfall data as inputs. This methodology was developed and tested with data from a water utility serving more than 5 million people. Results show high-risk category prediction accuracy of 75%–80%. Using a final year of unseen validation data, more than 90% of the storage tanks ranked in the top 20 by the forecasting methodology experienced low disinfectant residual in the following month. Storage tanks are critical water distribution system infrastructure that are currently managed reactively. The adoption of such readily transferable machine learning approaches enables direct proactive management strategies and efficient interventions that can help ensure drinking water quality.

Discoloured drinking water, caused by elevated concentrations of organic and inorganic particles, is unacceptable. It occurs due to accumulation and subsequent mobilisation of material from within drinking water distribution infrastructure. Discolouration is currently partially explained by either the theories of cohesive layers or gravitational sedimentation. It is proposed and shown here how the processes behind these two theories both occur and how to integrate them to better explain observed behaviour and inform operational interventions to reduce discolouration. Deficiencies in understanding regarding the process and factors that influence material accumulation are highlighted. Future research addressing these deficiencies will enable determination of long term sustainable management strategies balancing capital investment and operational maintenance to safeguard distribution of high quality drinking water.

Water temperature is often monitored at water sources and treatment works; however, there is limited monitoring of the water temperature in the drinking water distribution system (DWDS), despite a known impact on physical, chemical and microbial reactions which impact water quality. A key parameter influencing drinking water temperature is soil temperature, which is influenced by the urban heat island effects. This paper provides critique and comprehensive summary of the current knowledge, policies and challenges regarding drinking water temperature research and presents the findings from a survey of international stakeholders. Knowledge gaps as well as challenges and opportunities for monitoring and research are identified. The conclusion of the study is that temperature in the DWDS is an emerging concern in various countries regardless of the water source and treatment, climate conditions, or network characteristics such as topology, pipe material or diameter. More research is needed, especially to determine (i) the effect of higher temperatures, (ii) a legislative limit on temperature and (iii) measures to comply with this limit.