
Johanna Rosman
· Associate Professor, Department of Earth Marine and Environmental SciencesVerifiedUniversity of North Carolina at Chapel Hill · Ecology and Evolutionary Biology
Active 1999–2026
About
Johanna Rosman is an Associate Professor and the Director of Graduate Admissions in the Department of Earth, Marine and Environmental Sciences at the University of North Carolina at Chapel Hill. She holds a Ph.D. in Civil and Environmental Engineering from Stanford University, obtained in 2006, a Master's degree in Environmental Fluid Mechanics and Hydrology from Stanford University in 2000, and a Bachelor's degree in Physics and Environmental Engineering from the University of Western Australia in 1998. Her research focuses on water motion at scales ranging from centimeters to kilometers in estuaries and the coastal ocean. She investigates how water moves in response to drivers such as wind, tides, waves, and density gradients, with implications for the transport of materials including nutrients, dissolved gases, sediment, and larvae. Her work employs a combination of field measurements, computer models, and theoretical approaches to understand and predict these processes. Current research interests include flow over complex multi-scale topography such as coral reefs and rocky coasts, the interplay between density stratification and turbulent mixing affecting dissolved oxygen levels in estuaries, and wave dynamics across marshes and living shorelines.
Research topics
- Physics
- Geography
- Oceanography
- Classical mechanics
- Remote sensing
- Materials science
- Geometry
- Ecology
- Environmental resource management
- Mathematics
- Biology
- Thermodynamics
- Mechanics
- Geology
- Environmental science
Selected publications
Zenodo (CERN European Organization for Nuclear Research) · 2026-04-08
datasetOpen accessThis repository contains .zip file of all of the ROMS simulations used to produce the results in a submitted manuscript. Each folder in the .zip file is named as the simulation conducted in the manuscript . The file within each folder is -ocean.estuary_test2.in #ROMS input file -ana_initial.h #analytic initial condition -ana_m2obc.h #analytic depth-averaged open boundary condition -ana_smflux.h #analytic surface boundary condition -ana_tobc.h #analytic tracer open boundary condition -estuary_test2.h #cpp file -Idealized_grid.nc #model grid data COAWST is an open source code and can be download at https://coawstmodel-trac.sourcerepo.com/coawstmodel_COAWST/. Descriptions of the input and output files can be found in the manual distributed with the model code and in the glossary at the end of the ocean.in file.
Wave Attenuation Across Living Shoreline Sills
Estuaries and Coasts · 2026-05-04
articleSenior authorUNC Libraries · 2026-03-07
articleOpen accessMost work on how estuarine dynamics impact dissolved oxygen (DO) distributions has focused on tides, but in shallow estuaries with large fetch or small tides, wind can be the primary mixing agent and also drives advection. To investigate how these processes affect DO distributions, an observational study was conducted in the shallow, microtidal Neuse Estuary. Salinity, DO, and velocity profiles were measured at multiple positions along and across the estuary over a 6‐month period. A one‐dimensional model (General Ocean Turbulence Model) provided additional insight into the response of salinity and DO to wind. Salinity and oxygen conservation equation terms were calculated from observations and simulations. Cross‐estuary wind drove lateral circulation and tilted the isohalines, reducing stratification; lateral advection and enhanced mixing reduced vertical gradients and increased the bottom DO. Down‐estuary wind tended to increase the exchange flow and stratification, but concurrently the surface wind‐mixed layer deepened over time. The balance of these processes determined if the water column became fully mixed or remained stratified, and the depth of the pycnocline and oxycline. An expression for steady state surface layer thickness was derived by considering the competition between the horizontal and vertical buoyancy flux, and the predictions agreed well with observations and simulations. Up‐estuary wind inhibited the exchange flow and the combination of advection and mixing homogenized the water column. While these patterns generally held for purely across‐ or along‐channel wind, the response was often more complex as the wind vector varied in orientation and with time.
Observations of Combined Wave and Current Interactions With a High Relief Coral Reef Bottom
Journal of Geophysical Research Oceans · 2026-03-01
articleOpen accessAbstract On reefs, interaction between the flow and complex bottom topography results in drag forces on currents, dissipation of wave energy, and generation of turbulence. Here, field observations on a shallow backreef were used to investigate wave and current interactions with the bottom at scales of individual colonies across a coral reef patch. Wave direction was aligned with current direction, and the ratio of wave orbital velocities to current () was less than 0.5. The time‐averaged flow was a network of wakes behind colonies. Wake signatures were also observed for wave orbital velocities associated with longer period (13–32 s) waves but were absent for shorter period (3–5 s) waves. This pattern was explained by a modified Keulegan‐Carpenter number representing the ratio of wave period ( T ) to time scale for advection of water past an obstacle with length scale L by the current ( L /). Turbulent dissipation rates were elevated in obstacle wakes. For examples where KC c > 1, time‐averaged dissipation varied in proportion to the mean of the cubed total (wave plus current) velocity, consistent with parameterization as work done by a quadratic drag force that varied with incident velocity during the wave cycle. Bulk friction coefficients estimated from volume‐integrated dissipation in colony wakes together with topography measurements were similar to previous estimates from the reef‐scale momentum budget. These results illustrate that, although uncertainties are large, a quadratic drag law in conjunction with spatial averaging is a reasonable approach for scaling up colony to reef‐scale drag and dissipation.
Zenodo (CERN European Organization for Nuclear Research) · 2026-04-08
datasetOpen accessThis repository contains .zip file of all of the ROMS simulations used to produce the results in a submitted manuscript. Each folder in the .zip file is named as the simulation conducted in the manuscript . The file within each folder is -ocean.estuary_test2.in #ROMS input file -ana_initial.h #analytic initial condition -ana_m2obc.h #analytic depth-averaged open boundary condition -ana_smflux.h #analytic surface boundary condition -ana_tobc.h #analytic tracer open boundary condition -estuary_test2.h #cpp file -Idealized_grid.nc #model grid data COAWST is an open source code and can be download at https://coawstmodel-trac.sourcerepo.com/coawstmodel_COAWST/. Descriptions of the input and output files can be found in the manual distributed with the model code and in the glossary at the end of the ocean.in file.
Journal of Geophysical Research Oceans · 2025-06-01
articleAbstract Most work on how estuarine dynamics impact dissolved oxygen (DO) distributions has focused on tides, but in shallow estuaries with large fetch or small tides, wind can be the primary mixing agent and also drives advection. To investigate how these processes affect DO distributions, an observational study was conducted in the shallow, microtidal Neuse Estuary. Salinity, DO, and velocity profiles were measured at multiple positions along and across the estuary over a 6‐month period. A one‐dimensional model (General Ocean Turbulence Model) provided additional insight into the response of salinity and DO to wind. Salinity and oxygen conservation equation terms were calculated from observations and simulations. Cross‐estuary wind drove lateral circulation and tilted the isohalines, reducing stratification; lateral advection and enhanced mixing reduced vertical gradients and increased the bottom DO. Down‐estuary wind tended to increase the exchange flow and stratification, but concurrently the surface wind‐mixed layer deepened over time. The balance of these processes determined if the water column became fully mixed or remained stratified, and the depth of the pycnocline and oxycline. An expression for steady state surface layer thickness was derived by considering the competition between the horizontal and vertical buoyancy flux, and the predictions agreed well with observations and simulations. Up‐estuary wind inhibited the exchange flow and the combination of advection and mixing homogenized the water column. While these patterns generally held for purely across‐ or along‐channel wind, the response was often more complex as the wind vector varied in orientation and with time.
UNC Libraries · 2025-03-19
articleOpen accessThe loss of functional and accreting coral reefs reduces coastal protection and resilience for tropical coastlines. Coral restoration has potential for recovering healthy reefs that can mitigate risks from coastal hazards and increase sustainability. However, scaling up restoration to the large extent needed for coastal protection requires integrated application of principles from coastal engineering, hydrodynamics, and ecology across multiple spatial scales, as well as filling missing knowledge gaps across disciplines. This synthesis aims to identify how scientific understanding of multidisciplinary processes at interconnected scales can advance coral reef restoration. The work is placed within the context of a decision support framework to evaluate the design and effectiveness of coral restoration for coastal resilience. Successfully linking multidisciplinary science with restoration practice will ensure that future large‐scale coral reef restorations maximize protection for at‐risk coastal communities.
Interplay Between Wind‐Driven Advection and Mixing of Salt and Dissolved Oxygen in a Microtidal Estuary
Open MIND · 2025-01-01
articleMost work on how estuarine dynamics impact dissolved oxygen (DO) distributions has focused on tides, but in shallow estuaries with large fetch or small tides, wind can be the primary mixing agent and also drives advection. To investigate how these processes affect DO distributions, an observational study was conducted in the shallow, microtidal Neuse Estuary. Salinity, DO, and velocity profiles were measured at multiple positions along and across the estuary over a 6‐month period. A one‐dimensional model (General Ocean Turbulence Model) provided additional insight into the response of salinity and DO to wind. Salinity and oxygen conservation equation terms were calculated from observations and simulations. Cross‐estuary wind drove lateral circulation and tilted the isohalines, reducing stratification; lateral advection and enhanced mixing reduced vertical gradients and increased the bottom DO. Down‐estuary wind tended to increase the exchange flow and stratification, but concurrently the surface wind‐mixed layer deepened over time. The balance of these processes determined if the water column became fully mixed or remained stratified, and the depth of the pycnocline and oxycline. An expression for steady state surface layer thickness was derived by considering the competition between the horizontal and vertical buoyancy flux, and the predictions agreed well with observations and simulations. Up‐estuary wind inhibited the exchange flow and the combination of advection and mixing homogenized the water column. While these patterns generally held for purely across‐ or along‐channel wind, the response was often more complex as the wind vector varied in orientation and with time.
Consistent spatial patterns in multiple trophic levels occur around artificial habitats
UNC Libraries · 2024-02-15
articleOpen accessWith increasing global rates of urbanization, it is important to understand the ecological functions of artificial structures. One way to assess the ecological functions of such structures is to test whether they function similarly to natural habitats. In marine systems, naturally occurring structured habitats, such as coral reefs and rocky reefs, support aggregations of planktivorous fish, often inducing spatial patterns in prey and predators. Whether similar spatial patterns occur around submerged artificial structures, which often have more abrupt topographies than natural habitats, remains less well understood. We tested whether consistent spatial patterns in planktivorous fish, their prey (zooplankton), and their predators (piscivorous fish) were present around artificial structures. We first documented spatial distributions of these 3 trophic groups around 15 marine artificial structures (shipwrecks) using acoustic surveys and then asked how spatial distributions of each trophic group relate to the others. We found that the center of planktivorous fish aggregations occurred an average of 39 m from habitat edges. Zooplankton prey were detected throughout nearly 25% of surveyed areas around habitats. Piscivorous fish predators concentrated closest to habitats. Further analyses revealed that these patterns sometimes related to environmental factors, such as water current magnitude and direction. Because spatial distributions of planktivorous fish, their prey, and their predators were consistent across sampled artificial structures, our findings suggest that artificial structures influence spatial patterns across adjacent trophic levels. This finding adds to a growing body of evidence that artificial habitats provide important ecological functions.
Coastal Engineering · 2023-10-17 · 3 citations
article
Recent grants
NSF · $292k · 2014–2019
NSF · $185k · 2011–2016
NSF · $314k · 2021–2026
Frequent coauthors
- 22 shared
James L. Hench
Duke University
- 16 shared
Stephen G. Monismith
Stanford University
- 15 shared
Jeffrey R. Koseff
Mechanics' Institute
- 5 shared
Melissa S. Duvall
Environmental Protection Agency
- 4 shared
Melissa W. Southwell
- 4 shared
Kristen A. Davis
Stanford University
- 4 shared
Nicholas J. Nidzieko
University of California, Santa Barbara
- 4 shared
Matthew A. Reidenbach
University of Virginia
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