CyperSEES: Type 2: Integrative Sensing and Prediction of Urban Water for Sustainable Cities

University Of Texas At Arlington, Arlington TX

Investigators

Abstract

Many cities face tremendous water-related challenges due to urban population growth and climate fluctuations. Even moderate rainfall can quickly fill and overflow urban water reserves. Urban areas are particularly susceptible not only to excesses and shortages of water but also to variations in water quality. This project protects urban areas from the shocks of extreme precipitation cycles and urbanization by advancing our understanding of the urban water cycle through the integration of advanced computing and cyber-infrastructure, environmental modeling, geoscience, and information science. This project utilizes high-resolution precipitation information from the network of Collaborative Adaptive Sensing of the Atmosphere (CASA) radars available in the Dallas-Fort Worth area, crowdsourced water observations for ubiquitous sensing of surface water over a large urban area, and new innovative wireless sensors for water quantity, water quality and soil moisture to close the observation gaps. Cloud computing is then used for advanced high-resolution modeling, data optimization, and predictive analytics to assess water quantity and quality in both the short and long term. This project advances our understanding of urban sustainability and the associated challenges through environmental, social and economic responses of a large city as an uncertain dynamic system.