Education

Research Description

Dr. Dietrich develops computational models for wind waves and coastal circulation, and then applies these models to high-resolution simulations of ocean behavior. His goals are to understand how coastlines are threatened during storms, how materials are transported in the coastal environment, and how to convey these hazard risks for use in decision support. His research spans the disciplines of coastal engineering, numerical methods, computational mathematics, and high-performance computing.

Honors and Awards

• Outstanding Teacher Award, NC State University, 2018

Publications

Influence of storm timing and forward speed on tides and storm surge during Hurricane Matthew

Dietrich, J. (2019), Ocean Modelling. https://doi.org/10.1016/j.ocemod.2019.03.004

Predictive multi-hazard hurricane data-based fragility model for residential homes

Dietrich, J. (2019), Coastal Engineering. https://doi.org/10.1016/j.coastaleng.2019.04.008

Sensitivity of Storm Surge Predictions to Atmospheric Forcing during Hurricane Isaac

Dietrich, J. C., Muhammad, A., Curcic, M., Fathi, A., Dawson, C. N., Chen, S. S., & Luettich, R. A. (2018), Journal of Waterway Port Coastal and Ocean Engineering, 144(1). https://doi.org/10.1061/(asce)ww.1943-5460.0000419

Variability in Coastal Flooding predictions due to forecast errors during Hurricane Arthur

Cyriac, R., Dietrich, J. C., Fleming, J. G., Blanton, B. O., Kaiser, C., Dawson, C. N., & Luettich, R. A. (2018), Coastal Engineering, 137, 59–78. https://doi.org/10.1016/j.coastaleng.2018.02.008

An Earth's Future Special Collection: Impacts of the coastal dynamics of sea level rise on low-gradient coastal landscapes

Kidwell, D. M., Dietrich, J. C., Hagen, S. C., & Medeiros, S. C. (2017), Earths Future, 5(1), 2–9. https://doi.org/10.1002/2016ef000493

A Discontinuous Galerkin Coupled Wave Propagation/Circulation Model

Meixner, J., Dietrich, J. C., Dawson, C., Zijlema, M., & Holthuijsen, L. H. (2014), Journal of Scientific Computing, 59(2), 334–370. https://doi.org/10.1007/s10915-013-9761-5

Characterizing hurricane storm surge behavior in Galveston Bay using the SWAN plus ADCIRC model

Sebastian, A., Proft, J., Dietrich, J. C., Du, W., Bedient, P. B., & Dawson, C. N. (2014), Coastal Engineering, 88, 171–181. https://doi.org/10.1016/j.coastaleng.2014.03.002

Hindcast and validation of Hurricane Ike (2008) waves, forerunner, and storm surge

Hope, M. E., Westerink, J. J., Kennedy, A. B., Kerr, P. C., Dietrich, J. C., Dawson, C., … Westerink, L. G. (2013), Journal of Geophysical Research-Oceans, 118(9), 4424–4460. https://doi.org/10.1002/jgrc.20314

Limiters for spectral propagation velocities in SWAN

Dietrich, J. C., Zijlema, M., Allier, P.-E., Holthuijsen, L. H., Booij, N., Meixner, J. D., … Westerink, J. J. (2013), Ocean Modelling, 70, 85–102. https://doi.org/10.1016/j.ocemod.2012.11.005

Real-Time Forecasting and Visualization of Hurricane Waves and Storm Surge Using SWAN plus ADCIRC and FigureGen

Dietrich, J. C., Dawson, C. N., Proft, J. M., Howard, M. T., Wells, G., Fleming, J. G., … Gerritsen, M. (2013), Computational Challenges in the Geosciences, 156, 49–70. https://doi.org/10.1007/978-1-4614-7434-0_3

View all publications via NC State Libraries

Grants

Coupling of Inlet-Scale Erosion and Region-Scale Flooding Predictions

US Army - Corps of Engineers(9/24/18 - 12/31/19)

×

Coupling of Inlet-Scale Erosion and Region-Scale Flooding Predictions

Sponsor: US Army - Corps of Engineers

Start Date: 9/24/18

End Date: 12/31/19

Abstract

The goals of this project are to better understand the storm-induced erosion of barrier islands, and to develop ways to represent that erosion in predictive models on large domains. The critical objectives will be: (1) Develop a high-resolution hindcast of inlet creation in a barrier island system, (2) Explore the sensitivity of erosion predictions to the quality of input data, and (3) Implement a two-way coupling of small-scale erosion to larger-scale flooding. As a study area, we will consider the erosion of Hatteras Island during Hurricane Isabel (2003) and the creation of the so-called Isabel Inlet. The model will be validated with aerial surveys of island topography, collected immediately before and after the storm. We will quantify the model's ability to predict the inlet creation given coarse inputs, and identify the necessary resolution to include this process in larger-domain models. The evolving ground surface will be used to update topography in a region-scale flooding model, to examine how flow through the Isabel Inlet affected the back side of the island.

Close

PREEVENTS Track 2: Collaborative Research: Subgrid-Scale Corrections to Increase the Accuracy and Efficiency of Storm Surge Models

National Science Foundation (NSF)(9/01/17 - 8/31/21)

×

PREEVENTS Track 2: Collaborative Research: Subgrid-Scale Corrections to Increase the Accuracy and Efficiency of Storm Surge Models

Sponsor: National Science Foundation (NSF)

Start Date: 9/01/17

End Date: 8/31/21

Abstract

The goals of this project are to understand the correlations in storm surge properties within coastal regions like a bay or marsh, and then to convert those correlations into subgrid-scale corrections for forecast models. Storm surge models are the primary method for predicting inundation during strong storms. There is presently a divide between the high-resolution surge models used for hindcasts and climate studies, and coarse-resolution models used for real-time forecasts. High-resolution models are known to be more accurate, partly because they can represent the small-scale hydraulic features of the coastal environment, including the inlets and channels that convey surge into coastal areas. But while these high levels of resolution can increase accuracy, they cause the models to be too slow to use operationally for ensemble forecasts. However, nearby locations in surge models are known to have strong correlations in surface elevations and velocities which will be exploited here to increase accuracy and efficiency. The research objectives of this project are to: (1) understand and quantify the correlations between nearby locations, and between different spatial scales in storm surge models; (2) develop techniques for subgrid-scale corrections to increase accuracy in surge models; (3) implement corrections and test against high resolution solutions and existing storm data; and (4) transfer codes and techniques to academic and industry partners. This work will enhance fundamental understanding of surge, in particular how processes in nearby locations are linked, and how the essential degrees of freedom in the system may be extracted. It will improve our capability to model and forecast surge not only for the low-resolution models, where the technique will first be implemented, but also for higher-resolution models which will now be able to make use of the very high resolution lidar data that is now available in many regions. With these corrections, lower-resolution models will approach the accuracy of higher-resolution models with a much lower cost, which will increase accuracy of practical real-time ensemble simulations. This project will be a first step towards more accurate and efficient surge models and is seen as a necessary step towards more complete coastal modeling systems including wave propagation and pollutant transport, both of which may be adapted under this type of framework.

Close

Mapping and Visualization of Coastal Flood Forecasts for Decision Support

UNC - UNC Chapel Hill(7/01/16 - 12/30/17)

×

Mapping and Visualization of Coastal Flood Forecasts for Decision Support

Sponsor: UNC - UNC Chapel Hill

Start Date: 7/01/16

End Date: 12/30/17

Abstract

The focus of this proposed research is to connect forecast data for coastal flooding to the needs of emergency managers in NC, by working closely with the NC Department of Public Safety (NCDPS). Efficient visualizations of coastal flooding will allow emergency managers to promptly identify, analyze and disseminate information about high-risk areas. The incorporation of model results with other data sources will allow them to make better-informed decisions for evacuation measures and disaster management efforts. This research builds on previous and existing work to improve the utility of the forecast guidance.

Close

Establishment of Remote-Sensing Based Monitoring Program for Performance Limit State Assessment of the Sacramento Delta Levees

US Dept. of Homeland Security (DHS)(1/01/16 - 6/30/20)

×

Establishment of Remote-Sensing Based Monitoring Program for Performance Limit State Assessment of the Sacramento Delta Levees

Sponsor: US Dept. of Homeland Security (DHS)

Start Date: 1/01/16

End Date: 6/30/20

Abstract

The integrity and reliability of flood-control earthen dams and levees are essential components to homeland safety. The failure of such systems due to natural or man-made hazards may have monumental repercussions, sometimes with dramatic and unanticipated consequences on human life and the country’s economy. The levees network in the Sacramento-San Joaquin Delta support exceptionally rich agricultural area (over a $500 million annual crop value). Currently, the risk of levee failure in this area from potential flooding or draught threatens the lives of individuals living behind the levees, but also, the water quality in this water-transfer system. Preliminary risk assessment demonstrated a 40% chance that at least 30 islands within the Delta area would be flooded by simultaneous levee failures in a major earthquake in the next 25 years. The teamwork proposed herein will extend the remote sensing monitoring by InSAR and Joint Scatterer interferometry (JSInSAR) to monitor levees deformation with a resolution on the order of a few millimeters. The research team ay NCSU will participate by integrating the use of measurement data and modeling techniques, using the concept of performance limit states, to effectively achieve a performance based health assessment of the delta levees network.

Close

Interactions between Waves, Storm Surge and Beach Morphology during Storm Events

NCSU Sea Grant Program(2/01/16 - 6/30/18)

×

Interactions between Waves, Storm Surge and Beach Morphology during Storm Events

Sponsor: NCSU Sea Grant Program

Start Date: 2/01/16

End Date: 6/30/18

Abstract

Our goal is to improve simulations of coastal flooding in regions where the beach morphology is highly dynamic during a storm event. The feedback between waves, surge and morphology must be better linked, specifically through the extension and coupling of state-of-the-art numerical models. Although most morphology models are limited in their geographic extents, we will extend and apply a process-driven model to represent erosion and breaching at larger scales. And, although most wave, surge and morphology models are coupled with one-way communication, we will develop an automated system to map information in both ways. This research will produce modeling technologies that will benefit coastal communities within North Carolina, and we will share these technologies and findings with stakeholders. Simulations of wave propagation and flooding (and specifically the simulations from our models) are used in North Carolina and elsewhere for building design, the establishment of flood insurance rates, and real-time decision support during storm events. These predictions will be strengthened via the proposed tight coupling with a beach morphology model. The resulting modeling system will better represent the nearshore response to storm impacts.

Close

RADE: A Risk Analytics Discovery Environment for the North Carolina Data Sciences Analytics Initiative

North Carolina Data Science and Analytics Initiative (NCDSA)(8/15/16 - 8/15/17)

×

RADE: A Risk Analytics Discovery Environment for the North Carolina Data Sciences Analytics Initiative

Sponsor: North Carolina Data Science and Analytics Initiative (NCDSA)

Start Date: 8/15/16

End Date: 8/15/17

Abstract

This use case will develop a predictor of coastal property values in RADE, and then use that predictor to examine changes under future scenarios of climate and sea level changes. Given other geospatial data to describe a coastal property, the predictor will estimate the assessed price per square foot. Once a reliable predictor model is established, we will perturb it with scenarios of storm winds and flooding from detailed storm surge and wave simulations from the ADCIRC model (Westerink et al, 2008). RENCI has a very large database of ADCIRC simulations from recent FEMA-funded coastal risk assessments, including the Coastal Flood Insurance Study (Blanton and Luettich, 2010) and a comprehensive Sea Level Rise Impacts Assessment (NCDEM, 2009). We will insert the relevant outputs of these NC coastal model results into the data grid for use by this use case and any other interested researchers. The output includes inundation extents from a sequence of sea level rise increments up to 1 meter, various derived quantities for wind wave impacts, and coastal flooding.

Close

The Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE)

Consortium for Ocean Leadership, Inc.(1/01/15 - 3/31/18)

×

The Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE)

Sponsor: Consortium for Ocean Leadership, Inc.

Start Date: 1/01/15

End Date: 3/31/18

Abstract

The Consortium for Advanced Research on Transport of Hydrocarbon in the Environment (CARTHE) fuses into one group investigators with unique scientific and technical knowledge and extensive publications related to oceanic and atmospheric transport, air-sea interactions, tropical cyclones, laboratory experiments, computational modeling and observations. Our primary emphasis will remain on predictive oil transport modeling from a deep water well-head to the beach. Two new, ambitious experiments are proposed because of the potential for large coordinated field studies to discover new phenomena, focus our modeling activities, and provide data sets for their assessment: LASER will be targeted at understanding seasonal and sub-mesoscale variability in the DeSoto Canyon, and SOPYS will focus on transport processes across the continental shelf. These experiments are designed to complete transport pathways and address questions arising from GLAD and SCOPE. Lagrangian experiments are the most accurate way to quantify the net effect of all flow scales on ocean transport. We propose an approach that combines satellite, shipboard, and airborne observations of the upper ocean. A plane will be used for aerial observations with real-time communication of surface maps (high-resolution temperature, convergence zones) to the ocean vessels for detailed measurements. Virtual experiments before the field experiments will identify the phenomena, and a suite of operational models will be run during the experiments; model gaps will be identified after the field data is digested; improvements and parameterizations will follow. Laboratory experiments in the unique SUSTAIN laboratory (University of Miami) and uncertainty quantification will complement field and numerical work. Laboratory experiments at the University of Cambridge will serve to assess plume model developments. The scientific progress made during this project through a better understanding of the air-sea interaction will not only allow us to better respond to deep-ocean oil blowouts, but will also have far-reaching implications for navigation using local currents, potential off-shore green energy production, and the influence of upper-ocean flows on the ocean’s carbon intake in climate.

Close

Strengthening the Hurricane Wave and Surge Forecast Guidance Provided to Coastal Communities in North Carolina

NCSU Sea Grant Program(2/01/14 - 6/30/16)

×

Strengthening the Hurricane Wave and Surge Forecast Guidance Provided to Coastal Communities in North Carolina

Sponsor: NCSU Sea Grant Program

Start Date: 2/01/14

End Date: 6/30/16

Abstract

This proposal seeks funds to expand the utility and accuracy of wave, storm surge and flooding forecast guidance that is available to emergency managers in North Carolina using a high-resolution modeling system. Through discussions with them, the guidance from the forecast system will be targeted to their needs, so they can better utilize it while also understanding its strengths and limitations. In addition, the modeled representation of the North Carolina coastal waters will be enhanced to increase accuracy in specific regions of interest. North Carolina is particularly sensitive to waves, storm surge and flooding, given its geographic location and the protrusion of its coastline into the Atlantic. Severe storms such as hurricanes and nor-easters can devastate the natural and built environment along the complex system of barrier islands, bays and estuaries, and communities that comprise our coast. Several powerful storms have caused extensive flooding in recent years, including but not limited to Bertha and Fran (1996), Floyd (1999), Isabel (2003), Irene (2011) and Sandy (2012). Other, smaller storms have caused localized flooding in specific regions. The accurate prediction of waves, storm surge and flooding is essential for evacuation and protection of life and property. A computational modeling system for North Carolina has been established for forecasting of waves, surge and flooding at high resolution using high-performance computing resources. The models have been validated extensively and applied recently for the analysis of the levee protection system near New Orleans, the transport of oil following the destruction of the Deepwater Horizon drilling platform, and the development of new flood risk maps for the Gulf and Atlantic coasts. Within North Carolina, these models are utilized operationally to provide forecast guidance every day for coastal waves and inundation (http://nc-cera.renci.org/ ). In this proposed research, the forecast guidance from this modeling system will be expanded beyond Web-based delivery to include additional formats that are targeted to the needs of users within the state. These new formats will represent the guidance at high levels of geographic resolution and will be portable to the systems of these users, so they can combine and compare the forecast guidance with information from other sources. The resulting guidance will be more powerful because it will be placed directly into the hands of stakeholders who will have participated in its development, and who will be trained how to use it. In addition, by identifying regions of interest to them, the models will evolve to improve accuracy in their description of the coastal environment.

Close