Environmental Fluid Mechanics

, Volume 17, Issue 2, pp 323–353 | Cite as

Modeling and data assessment of longitudinal salinity in a low-gradient estuarine river

  • Peter BacopoulosEmail author
  • Ethan J. Kubatko
  • Scott C. Hagen
  • Andrew T. Cox
  • Teddy Mulamba
Original Article


Continuous data of vertical-profile salinity were analyzed for four stations located successively upriver in a macrotidal estuary, the lower St. Johns River (Northeast Florida, USA). The data analysis confirmed well-mixed salinity conditions in the river with at most 1.3 ppt of vertical variability at Dames Point (river km 20), where the main variations of salinity are along the longitudinal axis of the river. Given the well-mixed salinity conditions and dominant horizontal structure of salinity variations in the river, we present and apply a barotropic, two-dimensional modeling approach for hydrodynamic-salinity transport simulation in the lower St. Johns River. When properly forced by offshore surge, high-resolution wind fields and freshwater river inflows, the model replicated the salinity measurements remarkably well, including the separation into tidal and sub-tidal components. The data and model results show that, at times, offshore winds and surge can be more influential on longitudinal salinity variations than local winds over the river. We demonstrate the importance of using proper boundary conditions to force the model relative to the minimal sensitivity of the model to parameter adjustment of horizontal mixing and uncertainty-based perturbation of wind and inflow forcings.


Salinity Hydrodynamics Estuary Macrotidal Winds Freshwater river inflow 



This research was funded in part under Award No. 1045151 from the National Science Foundation (NSF), Award No. 0915118 from NSF-Division of Mathematical Sciences (DMS), Contract No. W912EP-06-D-0012 from Taylor Engineering, Inc. and the U.S. Army Corps of Engineers (USACE), and the Louisiana Sea Grant Laborde Chair endowment. Faculty support was provided in part by the St. Johns River Report Team (SJRRT). Student support was provided in part by the Taylor Engineering Research Institute (TERI). The Surface-water Modeling System by Aquaveo, Inc. was used to generate the mesh applied in the numerical simulations. FigureGEN by J. Casey Dietrich was used to generate the maps used in the figures of this paper. The authors thank Peter V. Sucsy and Tim Cera of the St. Johns River Water Management District (SJRWMD) for providing a wealth of information on the lower St. Johns River. The statements and conclusions are those of the authors and do not necessarily reflect the views of NSF, NSF-DMS, Taylor Engineering, Inc., USACE, Louisiana Sea Grant, SJRRT, TERI, Aquaveo, Inc., J. Casey Dietrich and SJRWMD, or their affiliates.


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.JacksonvilleUSA
  2. 2.Department of CivilEnvironmental and Geodetic EngineeringThe Ohio State UniversityColumbusUSA
  3. 3.Department of Civil and Environmental Engineering/Center for Computation & TechnologyLouisiana State UniversityBaton RougeUSA
  4. 4.Oceanweather Inc.Cos CobUSA
  5. 5.School of EngineeringUniversity of North FloridaJacksonvilleUSA

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