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Congratulations to the 2019 Conference Poster Winners, Nick Diaz & Hesam Talebiyan!

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Evaluation of Flood Mitigation Strategies for Greens Bayou Watershed using HEC-RAS 2D

Meera Gaddit, Rice University

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Greens Bayou Watershed Analysis and Resiliency Planning: East Aldine

Jose Mario Lopez & Angelica Lastra, University of Houston

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Assessing the Effectiveness of Pump Storage Detention on the Greens Bayou

Tobi Li, Rice University

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Modeling Flooding in a Texas river system using a combination of spatially-distributed hydrologic and one and two dimensional hydraulic models 

Tom Blaney, Rice University

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The influence of native prairie vegetation on overland flow dynamics and riverine response in the Katy Prairie region (Houston, TX)

Morgan Garner, Rice University

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Texas Coastal Resiliency Master Plan 

Chris Levitz, AECOM

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Urban Design & Policy for Flood Protection" or "Flood Warning Systems

Gary Woods, Rice University

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Coupled Flood Alert System and Infrastructure Risk Modeling for Improved Situation Awareness During Severe Storm Events”

Pranavesh Panakkal, Rice University

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Challenges for the Application for Machine Learning in Real-Time Flood Alert Systems

Matthew Garcia, Rice University

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Machine Learning Algorithms for Flooding Prediction Applications in Flood Alert System (FAS)

William Sanders, University of Texas Arlington

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Flood-Radar: A user-informed local flood forecasting tool

Hesam Talebiyan, Rice University

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Evaluation of Multi-Radar Multi-Sensor (MRMS) and Stage IV Quantitative Precipitation Estimates (QPE) during Hurricane Harvey

Jiaqi Zhang, University of Texas - Arlington

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Flood Control Strategies to Mitigate Climate Change Induced Super Storms on Transportation Infrastructure

Cesar DoLago, University of Texas - San Antonio

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Geospatial Data Analytics for Studying Flood Exposure in Houston, TX

Behrang Bidadian, West Virginia 

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A Data Driven Approach to Hurricane Debris Modeling

Catalina Gonzalez, Rice University

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Deriving first floor elevations within residential communities located in Galveston using UAS-based data

Nick Diaz, Texas A&M - Galveston

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