Profiling urban water consumption patterns in Ho Chi Minh City using time series clustering method

The rapid urbanization and population growth in Ho Chi Minh City, Vietnam, have posed significant challenges for the management of water resources. This study aims to analyze the water consumption patterns of different user groups in the Ben Thanh Water Supply Area of the city using a time series clustering approach. By applying feature extraction and K-Means clustering, an unsupervised learning technique, this research identifies distinct water consumption patterns among 36 district metering areas in the study region. The findings provide valuable insights into the heterogeneous usage behaviors of various consumer segments, ranging from low-volume, consistent users to high-volume, irregular consumers. These insights can guide the development of targeted and effective water management strategies, enabling utility providers and policymakers to implement efficient and sustainable practices that cater to the specific needs and requirements of the diverse consumer base within Ho Chi Minh City’s urban landscape. The study contributes to the existing literature by being the first to profile water consumption patterns in the Ben Thanh Water Supply Area using advanced time series clustering techniques, paving the way for more data-driven water management solutions in this rapidly growing metropolitan area.