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view all  View all projects RESEARCH PROJECT

Integrated Sensing and Prediction of Urban Water for Sustainable Cities

Principal Investigator

Postdoctoral Researcher

Graduate Students

Dong-Jun Seo
Dong-Jun Seo, PhD
Position:

Associate Professor, University of Texas at Arlington

Research interests:
  • Surface water hydrology
  • Radar hydrology
  • Remote sensing of precipitation and other hydrometeorological and hydrologic variables
  • Assimilation of hydrologic and hydrometeorological data, stochastic and probabilistic methods and techniques
  • Ensemble forecasting of hydrologic and hydrometeorological variables
  • Optimal estimation, stochastic control, statistical hydrology
  • Stochastic modeling of hydrologic processes in space and time
Contact:
djseofoo@uta.edu
817-272-5063
Seongjin Noh
Seongjin Noh
Position:

Research Associate, University of Texas at Arlington

Research interests:
  • Data assimilation
  • Particle filtering
  • Flood forecasting
  • Integrated hydrologic modeling
Contact:
Seongjin.nohfoo@uta.edu
682-330-2579
Behzad Nazari
Behzad Nazari, PhD
Position:

Graduate Research Assistant, University of Texas at Arlington

Research interests:
  • Hydraulic modelling
  • Urban flood modeling
  • Inundation mapping
  • River engineering
Contact:
Nazarifoo@uta.edu
817-272-9130
Hamideh Habibi
Hamideh Habibi
Position:

Graduate Research Assistant, University of Texas at Arlington

Research interests:
  • Flood forecasting
  • Distributed hydrologic modeling
  • Hydraulic modeling
  • Remote sensing of precipitation
Contact:
Hamideh.habibifoo@mavs.uta.edu
817-272-9130

Timeline

October 2014 - September 2018


ABSTRACT

Many cities face tremendous water-related challenges from urban population growth and climate change. Urban areas are particularly susceptible not only to excesses and shortages of water but also to water quality. Even moderate rainfall can quickly fill and overflow urban water courses. Flash wash off of large impervious areas can quickly contaminate stormwater. This project improves urban sustainability from transient shocks of heavy-to-extreme precipitation under climate change and urbanization, and advances understanding of the urban water cycle through synergistic integration of advances in computing and cyber-infrastructure, environmental modeling, geoscience, and information science. This project utilizes very high-resolution precipitation information from the network of Collaborative Adaptive Sensing of the Atmosphere (CASA) X-band radars uniquely available in the Dallas-Fort Worth Metroplex (DFW) area, crowdsources water observations for ubiquitous sensing of surface water over a large urban area, and deploys 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 assimilation, parameter optimization, ensemble prediction, and data-based discovery to maximize the information content of the analysis and prediction of water quantity and quality for short- to long-term scales. The outcome of this project will allow impact-specific multi-scale and multi-dimensional risk-based decision making related to threats and risks associated with urban water to a wide spectrum of users and stakeholders, and advance general understanding of urban sustainability and associated challenges through environmental, social and economic response of a large city as an uncertain dynamic system.


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PROJECT RESOURCES

University of Texas Arlington - iSPUW Website

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