Fusing Data Analytics with Hydraulics in a Hydroinformatics Approach for Water Distribution System Monitoring

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This project will develop a novel scheme that seeks to provide full-scale monitoring from individual households to the entire water distribution system (WDS) by inexpensively combining various kinds of measurements from real-time metering of individual premise use to system flow and pressure conditions over time. The monitoring system will provide predictions on hydraulic conditions across the WDS over time. Comparing these predictions with field measurements capabilities in smart ways will increase burst detection accuracy, reduce detection time and improve accuracy of locating bursts resulting in shorter repair times, and lower costs and damages. Field demonstration and validation of the approaches within this project will demonstrate the active approach to burst detection/location. The project will promote inter-disciplinary graduate and undergraduate education and training, enhance research opportunities that promote female and underrepresented minority groups, and attract K-12 students to engineering programs.The objective of this project is to develop a new generation of WDS monitoring systems within a new interdisciplinary hydroinformatics paradigm by fusing hydraulic knowledge with data-driven spatio-temporal analytics. The real-time burst detection algorithm will employ likelihood ratio test statistics to compare predicted and measured pressures and flows in conjunction with multivariate control charts to maximize event detection rates and avoid false alarms. After a burst is determined to be occurring, the approach returns to the WDS hydraulics to estimate responses to bursts at various locations and correlate measurement deviations to predicted conditions. Given the relatively low implementation costs, the concepts and technologies developed in this research will have significant commercial potential in a sizable international market. The project will demonstrate a platform for water utilities to rapidly assimilate new sensing technology and reap broader benefits as opportunities to incorporate this expanded data resources in WDS control systems are clear. The spatio-temporal sensor fusion mechanism will enhance data analytics for solving problems in other complex non-stationary systems where real-time modeling, monitoring and decision-making are of interest. The integrated systems and civil engineering research collaboration and the link to practice through field studies offer unique opportunities for establishing an inter-disciplinary education program, for multidisciplinary training of graduate and undergraduate students, and for student research opportunities. Broad dissemination will be ensured by maintaining data and case libraries, publishing papers in conferences and refereed journals, and collaborating with industry partners.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.