News: Summer Research Experience

2017/09/28 – DHS CRCoE
Students participate in second annual summer exchange program


Summer activities also included a one-day exchange where students from Johnson C. Smith University (JCSU) in Charlotte, N.C., visited North Carolina State University (NCSU). Nine students enrolled in a summer research program led by Dr. Hang Chen visited the NCSU Department of Civil, Construction, and Environmental Engineering (CCEE), where CRC PI Dr. Casey Dietrich exposed the students to the concepts of computing-intensive and coastal resilience research.

The visiting students learned about the CCCE department, along with summer and graduate program opportunities. Dr. Dietrich arranged presentations and discussions with faculty members in their computing and system group. Ten faculty members presented their interdisciplinary research projects addressing problems throughout civil and environmental engineering using computational tools. The JCSU students also interacted with Dr. Dietrich’s graduate students and learned more about their individual research projects.

News: Storm Surge Impacts during Hurricane Irma

2017/09/14 – The Daily Tar Heel
Hurricane Irma lets North Carolina off easy

Casey Dietrich, an assistant professor at N.C. State University, said Hurricane Irma’s effects were relatively minor in coastal North Carolina because its track was so far away.

“Along the southeast coast between Wilmington and Myrtle Beach, the wind speeds barely reached the cutoff for tropical-storm strength, 39 miles per hour, and only for a few hours,” he said.

Dietrich also works as a part of the Coastal Resilience Center, a group of universities, private companies and government agencies that are led by UNC. The CRC conducts research on the threats to coastal communities due to natural hazards and climate change.

News: Prediction of and Resilience Against Extreme Events

2017/09/12 – National Science Foundation
In wake of hurricanes … NSF awards $18.7 million in natural hazards research grants

In the decade from 2003 to 2013, natural disasters around the globe caused $1.5 trillion in economic damages and took the lives of almost 1.2 million people. Over that same 10-year period, the U.S. lost nearly $650 billion due to such disasters.

How can scientists better predict or prevent such catastrophes? How can they help people recover more quickly?

To find answers to these questions, the National Science Foundation (NSF) has awarded 15 new grants totaling $18.7 million through its PREEVENTS (Prediction of and Resilience Against Extreme Events) program. PREEVENTS is part of NSF’s Risk and Resilience portfolio.

PREEVENTS’ goals are to improve predictability and risk assessments of natural hazards, increase resilience to these events, and reduce their effects on human lives, societies and economies. PREEVENTS also supports research that will improve the understanding of the processes underlying natural hazards and extreme events.

News: Enhancing Storm Surge Visualization

2017/10/04 – Science Node
The aim of storm surge models: When a storm approaches, emergency managers want fast and accurate forecasts

Although our model provides water level predictions from the deep ocean all the way to the coastal floodplains, the system is limited by the model’s resolution. Topographic features at scales smaller than 500 feet, such as roadways or narrow stream channels, are often not included in the models because of the computer time needed to produce such high-resolution outputs. Because of this limitation, the extent of flooding can be underpredicted by the model.

2017/08/31 – National Consortium for Data Science
Data Fellows project aims to make storm surge predictions faster and more accurate

Continuing our North Carolina Sea Grant project and with new support from the National Consortium of Data Science, we are developing a method to improve prediction of the true flooding extent by combining the results of our model with more accurate elevation datasets.

To perform this prediction of the flooding extent, we use a Geographic Information System (GIS) called GRASS GIS that specializes in processing very large amounts of data. The project has two major objectives. The first is to process the modeled water levels and the elevation data set together, producing a map showing the extent of predicted flooding. When the modeled water levels are greater than the land elevation, flooding extends outward into neighboring, unflooded areas in the data set. By mapping the model results to the higher resolution data sets on elevation, we can create more accurate surge forecasts of overland flooding.

2017/08/08 – NC Sea Grant Coastwatch Currents
Fast, Accurate Forecasts of Coastal Flooding: Enhancing Visualization of Storm Surge Guidance to Support Emergency Managers

ncsgStorm surge models must be both fast and accurate to give coastal communities the guidance they need to prepare for and respond to a storm. Perhaps just as important is the need for these forecasts to be visualized in a way that is meaningful and useable by emergency managers.

ADCIRC forecasts are currently visualized using Kalpana, a Python script that converts the model output into formats compatible with commonly-used visualization applications such as ArcGIS and Google Earth. With support from the National Consortium of Data Science (NCDS) and in partnership with North Carolina Emergency Management (NCEM), our team has developed a new visualization method that makes use of enhanced topographic resolution along the flooding boundary. This results in modeled storm surge extending farther into estuaries and floodplains, increasing the accuracy of the forecast.