Integrative sensing and prediction of urban water for sustainable cities (iSPUW)

Friday, 19 December 2014: 10:50 AM
Dong-Jun Seo1, Nick Z. Fang1, Xinbao Yu1, Michael Zink2, Jean Gao3 and Branko Kerkez4, (1)Univ of TX-Arlington-Civil Eng, Arlington, TX, United States, (2)University of Massachusetts Amherst, Electrical and Computer Engineering, Amherst, MA, United States, (3)University of Texas at Arlington, Computer Science and Engineering, Arlington, TX, United States, (4)University of Michigan Ann Arbor, Ann Arbor, MI, United States
We describe a newly launched project in the Dallas-Fort Worth Metroplex (DFW) area to develop a cyber-physical prototype system that integrates advanced sensing, modeling and prediction of urban water, to support its early adoption by a spectrum of users and stakeholders, and to educate a new generation of future sustainability scientists and engineers. The project utilizes the very high-resolution precipitation and other sensing capabilities uniquely available in DFW as well as crowdsourcing and cloud computing to advance understanding of the urban water cycle and to improve urban sustainability from transient shocks of heavy-to-extreme precipitation under climate change and urbanization. All available water information from observations and models will be fused objectively via advanced data assimilation to produce the best estimate of the state of the uncertain system. Modeling, prediction and decision support tools will be developed in the ensemble framework to increase the information content of the analysis and prediction and to support risk-based decision making.