Research

Evolutionary History of Return-flow Channels Caused by Hurricane Harvey at San Jose Island, Texas, USA (2018-2019)

Supervisors: Dr. David Mohrig, Kathleen Wilson, Dr. Wonsuck Kim, Dr. Joel Johnson

 

Severe storms can have a significant impact on coastline morphology. Therefore, understanding coastline responses to storms is critical for promoting coastline resilience.

 

Return-flow channels are a morphodynamic consequence of storm-generated seaward flow. In the case of the ones on San Jose Island, these channels cut across two dune ridges, displaying scalloped heads at the landward margin and single downstream necks oriented perpendicular to the shoreline.

 

For my undergraduate honors research project at the University of Texas at Austin, I utilized lidar data, satellite imagery, fieldwork data, and numerical hydrodynamic modeling with ANUGA to investigate the evolution mechanism of return-flow channels on San Jose Island, Texas, resulting from Hurricane Harvey in 2017. 

 

Our findings contribute to the understanding of how pre-existing topography and connected low-topography affect the development and locations of return-flow channels. The numerical modeling component of this project allowed me to further develop my Python programming skills to tackle a geoscience challenge.

 

 This work was presented at AGU 2018 and EGU 2019 and is currently in the process of being prepared for publication. 

Modeling Coastal Inundation Driven by Hurricanes Frances and Jeanne in the Indian River Lagoon, Florida, USA (2017)

Supervisor: Dr. Mingshun Jiang


Hurricane-induced inundation can cause significant damage to lives and properties.


During my summer internship at the Harbor Branch Oceanographic Institute, Florida Atlantic University, I employed numerical simulation to simulate the coastal inundation in the Indian River Lagoon (IRL) driven by Hurricane Frances and Hurricane Jeanne in September, 2004. The model is based on an existing hydrodynamic model developed using Delft3D, with updated bathymetry.


I conducted four simulation runs and compared the results of each run with the high-water marks (HWMs) in the IRL and water level time-series data. The most accurate run was used to generate sea level maps to monitor the changes in water level within the IRL during the period of the storms.


Overall, the model predicted significant inundation in the lagoon. The sea level maps showed similar spatial changes in water level within the IRL for both Hurricane Frances and Hurricane Jeanne. The model can be applied for hazard prediction in future sea-level rise scenarios.

Class Projects

Recovery after Hurricane Harvey in Lydia Ann Channel and Mud blankets offshore
Corpus Christi Bay, Texas (2019)

Gan, Y.; Janecka, M.; Ruangsirikulchai A.; Xie, W.

 

Coursework: The Marine Geology and Geophysics Field Course 

 

The summer field course provided students with a unique hands-on experience in Marine Geology and Geophysics. We had opportunities to collect and analyze multibeam bathymetry, CHIRP, side-scan sonar, coring, and seismic data around Port Aransas in the Gulf of Mexico.

 

For the 2019 cohort, aboard a small research vessel, we investigated the recovery of Lydia Ann Channel following Hurricane Harvey in 2017. Over this two-year period, we observed the recovery of bedforms and lithology, and we discovered new subaqueous channels that hadn’t been there before. On a larger research vessel, we also studied the Texas Mud Blanket offshore Corpus Christi Bay, which was found to be actively aggrading.

 

I found this field experience to be incredibly rewarding!

Development of an Expert Analysis Tool based on an Interactive Subsidence Hazard Map for Urban Land Use in the City of Celaya, Mexico (2016)

Alloy, A. ; Gonzalez Dominguez, F. ; Nila Fonseca, A. L. ; Ruangsirikulchai, A. ; Gentle, J. N., Jr. ; Cabral, E. ; Pierce, S. A.

 

Coursework:  Intelligent Systems in Geosciences Program (2016)

This is project was a part of a six-week computational geosciences summer exchange program between the University of Texas at Austin and the Universidad Nacional Autónoma de México.

 

The city of Celaya in central Mexico has been experiencing land subsidence due to groundwater extraction. This extraction has led to the development of an active normal fault system that affects the city’s infrastructure.

 

Our group developed an online interactive map that enables users to access information related to land subsidence. We conducted fieldwork in Celaya, measuring fault directions and collecting data on fault locations, socioeconomic factors, and infrastructure.

 

We created a subsidence and associated faulting hazard map using an InSAR-derived subsidence velocity map and population data to identify hazard zones. This map improves communication between scientific and socio-economic disciplines by providing insights into various vulnerable urban elements.

 

The work was accepted to the American Geophysical Union Fall Meeting 2016.

 

Full Abstract: https://ui.adsabs.harvard.edu/abs/2016AGUFMIN13C1678A/abstract