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

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

Meera Gaddit, Rice University

Greens Bayou Watershed Analysis and Resiliency Planning: East Aldine

Jose Mario Lopez & Angelica Lastra, University of Houston

Assessing the Effectiveness of Pump Storage Detention on the Greens Bayou

Tobi Li, Rice University

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

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

Morgan Garner, Rice University

Texas Coastal Resiliency Master Plan 

Chris Levitz, AECOM

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

Gary Woods, Rice University

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

Pranavesh Panakkal, Rice University

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

Matthew Garcia, Rice University

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

William Sanders, University of Texas Arlington

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

Hesam Talebiyan, Rice University

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

Jiaqi Zhang, University of Texas - Arlington

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

Cesar DoLago, University of Texas - San Antonio

Geospatial Data Analytics for Studying Flood Exposure in Houston, TX

Behrang Bidadian, West Virginia 

A Data Driven Approach to Hurricane Debris Modeling

Catalina Gonzalez, Rice University

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

Nick Diaz, Texas A&M - Galveston

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