Detecting urban water consumption patterns: a time-series clustering approach

Abstract

Abstract The need for efficient management of water distribution systems is a growing concern for economic, environmental and social reasons. Water supply systems are commonly designed to ensure adequate behaviour under the worst conditions, such as maximum consumption, which leads to overestimation in supply tanks and energy waste. While overestimation should be considered, to account for unpredictable demands and emergency scenarios, we advocate that a detailed understanding of consumption patterns enables an improvement in water management and is additionally beneficial to correlated resources such as electricity. A novel framework to detect water consumption patterns is developed and applied to an urban scenario. Observed discrepancies among computed patterns enable readjustments of supplied water flowrate, thus promoting effective water allocation and pumping costs, while mitigating water contamination risks.