Ocean Dynamics

, Volume 69, Issue 11–12, pp 1311–1331 | Cite as

Realistic modelling of shelf-estuary regions

A multi-corner configuration for Baía de Todos os Santos
  • Martinho Marta-AlmeidaEmail author
  • Guilherme C. Lessa
  • Alessandro L. Aguiar
  • Fabiola N. Amorim
  • Mauro Cirano
Part of the following topical collections:
  1. Topical Collection on Coastal Ocean Forecasting Science supported by the GODAE OceanView Coastal Oceans and Shelf Seas Task Team (COSS-TT) - Part II


A very high-resolution modelling configuration was created for the estuary of Baía de Todos os Santos – BTS, Brazil (300 to 400 m), and adjacent coastal waters (600 to 1200 m). The adoption of a multi-corner domain approach allowed the variable spatial resolution required to resolve the shelf, the bay and their interactions. Seven years were simulated using realistic oceanic, atmospheric and riverine forcing. Model validation was done against observations showing the model skill to reproduce the thermohaline field, the tidal currents, as well as the variability of the free surface at tidal and sub-tidal time scales. The results provide the first representation of the tidal wave propagation along the bay, in terms of maps of amplitudes, phases and ellipses of the barotropic currents for the main tidal constituents. By analysing the residual currents at different depths, in terms of averages over the simulation period, several prominent structures were identified and named: (i) Salvador eddy (up to 0.2 m s−1); (ii) St Antonio current (up to 0.45 m s−1); (iii) Salvador current (up to 0.5 m s−1); (iv) Itaparica eddy (up to 0.2 m s−1); (v) Ilha dos Frades southern eddy (up to 0.1 m s−1); and (vi) Ilha dos Frades northern eddy (up to 0.2 m s−1). The model set-up proved to be highly efficient and robust simulating the BTS shelf-estuary region and such an approach may be suitable to other estuarine systems.


Baía de Todos os Santos ROMS Multi-corner domain Tidal propagation Residual circulation Shelf-estuary dynamics 


  1. Aguiar AL, Cirano M, Pereira J, Marta-Almeida M (2014) Upwelling processes along a western boundary current in the Abrolhos–Campos region of Brazil. ContShelf Res 85:42–59. CrossRefGoogle Scholar
  2. Aguiar AL, Cirano M, Marta-Almeida M, Lessa GC, Valle-Levinson A (2018) Upwelling processes along South Equatorial Current bifurcation region and Salvador Canyon (13S), Brazil. ContShelf Res 171:77–96. CrossRefGoogle Scholar
  3. Aguiar AL, Valle-Levinson A, Cirano M, Marta-Almeida M, Lessa GC, Paniagua-Arroyave JF (2019) Ocean-estuary exchange variability in a large tropical estuary. ContShelf Res 172:33–49. CrossRefGoogle Scholar
  4. Amante C, Eakins BW (2009) ETOPO1 1 Arc-Minute Global Relief Model: Procedures, Data Sources and Analysis. NOAA Technical Memorandum NESDIS NGDC-24, National Geophysical Data Center.
  5. Amorim FN, Cirano M, Marta-Almeida M, Middleton JF, Campos EJD (2013) The seasonal circulation of the Eastern Brazilian shelf between 10S and 16S: A modelling approach. ContShelf Res 65:121–140. CrossRefGoogle Scholar
  6. Aubrey D, Speer P (1985) A study of non-linear tidal propagation in shallow inlet/estuarine systems Part i: Observations. Estuar Coast Shelf S 21:185–205. CrossRefGoogle Scholar
  7. Cabanes C, Grouazel A, von Schuckmann K, et al. (2013) The CORA dataset: validation and diagnostics of in-situ ocean temperature and salinity measurements. Ocean Sci 9:1–18. CrossRefGoogle Scholar
  8. Chapman D (1985) Numerical treatments of cross-shelf open boundaries in a barotropic coastal ocean model. JPhysOceanogr 15:1060–1075.<1060:NTOCSO>2.0.CO;2 CrossRefGoogle Scholar
  9. Cirano M, Lessa GC (2007) Oceanographic characteristics of baiá de Todos os Santos, Brazil. Rev Bras Geofís 25:363–387. CrossRefGoogle Scholar
  10. da Silva A, Young AC, Levitus S (1994) Atlas of Surface Marine Data 1994, Volume 1: algorithms and procedures. NOAA atlas NESDIS 6, U.S department of commerce, Washington, D.C.Google Scholar
  11. Dai A, Qian T, Trenberth KE, Milliman JD (2009) Changes in continental freshwater discharge from 1948-2004. JClimate 22:2773–2791. CrossRefGoogle Scholar
  12. Dee DP, Uppala SM, Simmons AJ, et al. (2011) The ERA-interim reanalysis: configuration and performance of the data assimilation system. QuartJRoyMeteorSoc 137:553–597. CrossRefGoogle Scholar
  13. Driscoll TA, Vavasis SA (1998) Numerical conformal mapping using cross-ratios and Delaunay Triangulation. SIAM J Sci Comput 19:1783–1803. CrossRefGoogle Scholar
  14. Egbert GD, Erofeeva SY (2002) Efficient inverse modeling of barotropic ocean tides. JAtmosOceanic Technol 19:183–204.<0183:EIMOBO>2.0.CO;2 CrossRefGoogle Scholar
  15. Fall K, Harris C, Friedrichs C, Rinehimer J, Sherwood C (2014) Model behavior and sensitivity in an application of the cohesive bed component of the community sediment transport modeling system for the York River Estuary, VA, USA. J Mar Sci Eng 2:413–436. CrossRefGoogle Scholar
  16. Flather R (1976) A tidal model of the northwest European continental shelf. Mém Soc R Sci Liége 6:141–164Google Scholar
  17. Haidvogel DB, Beckmann A (1999) Numerical Ocean Circulation Modeling. World Scientific Publishing CompanyGoogle Scholar
  18. Haidvogel DB, Arango H, Budgell WP et al (2008) Ocean forecasting in terrain-following coordinates: Formulation and skill assessment of the Regional Ocean Modeling System. J Comput Phys 227:3595–3624. CrossRefGoogle Scholar
  19. Hetland RD (2010) A Python interface to Pavel Sakov’s C-based Gridgen Orthogonal Grid Generation Package., accessed: 2014 & 2015
  20. Hetland RD, MacDonald DG (2008) Spreading in the near-field Merrimack River plume. Ocean Model 21:12–21. CrossRefGoogle Scholar
  21. Kanamitsu M, Ebisuzaki W, Woollen J et al (2002) NCEP-DOE AMIP-II Reanalysis (R-2). BullAmerMeteorSoc 83:1631–1643. CrossRefGoogle Scholar
  22. Lessa GC, Bittencourt AC, Brichta A, Dominguez JML (2000) A reevaluation of the late quaternary sedimentation in Todos os Santos Bay (BA), Brazil. An Acad Bras Ciênc 72:573–590. CrossRefGoogle Scholar
  23. Lessa GC, Cirano M, Tanajura CAS, Silva RR (2009) Oceanografia física. In: Hatje V, de Andrade J B (eds) Baía de Todos os Santos: aspectos oceanográficos, EDUFBA, Salvador, pp 68–119Google Scholar
  24. Lessa GC, Souza MFL, Mafalda Junior PO, Gomes DF, Souza CS, Teixeira CEP, de Souza JRLB, Zucchi MR (2018) Variabilidade intra-anual da oceanografia da Baía de Todos os Santos: evidências de três anos de monitoramento. In: Hatje V, Dantas L M V, de Andrade J B (eds) Baía de Todos os Santos: avanços nos estudos de longo prazo, EDUFBA, Salvador, pp 157–192Google Scholar
  25. Lima JAM, Martins RP, Tanajura CAS et al (2013) Design and implementation of the Oceanographic Modeling and Observation Network (REMO) for operational oceanography and ocean forecasting. Rev Bras Geofís 31:209–228. Google Scholar
  26. Magris RA, Marta-Almeida M, Monteiro JA, Ban NC (2019) A modelling approach to assess the impact of land mining on marine biodiversity: Assessment in coastal catchments experiencing catastrophic events (SW Brazil). Sci Total Environ 659:828–840. CrossRefGoogle Scholar
  27. Marchesiello P, McWilliams JC, Shchepetkin A (2001) Open boundary conditions for long-term integration of regional oceanic models. Ocean Model 3:1–20. CrossRefGoogle Scholar
  28. Marques CAF, Ferreira JA, Rocha A, et al. (2006) Singular spectrum analysis and forecasting of hydrological time series. Phys Chem Earth ABC 31:1172–1179. CrossRefGoogle Scholar
  29. Marta-Almeida M, Pereira J, Cirano M (2011a) Development of a pilot Brazilian regional operational ocean forecast system, REMO-OOF. J Oper Oceanogr 4:3–15. CrossRefGoogle Scholar
  30. Marta-Almeida M, Ruiz-Villarreal M, Otero P, Cobas M, Peliz A, Nolasco R, Cirano M, Pereira J (2011b) OOFε: A python engine for automating regional and coastal ocean forecasts. Environ Model Softw 26:680–682. CrossRefGoogle Scholar
  31. Marta-Almeida M, Hetland RD, Zhang X (2013a) Evaluation of model nesting performance on the Texas-Louisiana continental shelf. JGeophysRes 118:2476–2491. CrossRefGoogle Scholar
  32. Marta-Almeida M, Ruiz-Villarreal M, Pereira J, Otero P, Cirano M, Zhang X, Hetland RD (2013b) . Efficient tools for marine operational forecast and oil spill tracking. Mar Pollut Bull 71:139–151. CrossRefGoogle Scholar
  33. Marta-Almeida M, Mendes R, Amorim FN, Cirano M, Dias JM (2016) . Fundão dam collapse: Oceanic dispersion of river doce after the greatest brazilian environmental. Mar Pollut Bull accident 112:359–364. CrossRefGoogle Scholar
  34. Marta-Almeida M, Cirano M, Soares CG, Lessa GC (2017) A numerical tidal stream energy assessment study for baiá de Todos os Santos, Brazil. Renew Energ 107:271–287. CrossRefGoogle Scholar
  35. Mellor GL, Yamada T (1974) A hierarchy of turbulent closure models for planetary boundary layers. JAtmosSci 31:1791–1806.<1791:AHOTCM>2.0.CO;2 CrossRefGoogle Scholar
  36. Moriarty J, Harris C, Hadfield M (2014) A hydrodynamic and sediment transport model for the Waipaoa shelf, New Zealand: Sensitivity of fluxes to spatially-varying erodibility and model nesting. J Mar Sci Eng 2:336–369. CrossRefGoogle Scholar
  37. Oke PR, Larnicol G, Fujii Y et al (2015a) Assessing the impact of observations on ocean forecasts and reanalyses: Part 1, Global studies. J Oper Oceanogr 8:s49–s62. CrossRefGoogle Scholar
  38. Oke PR, Larnicol G, Jones EM et al (2015b) Assessing the impact of observations on ocean forecasts and reanalyses: Part 2, Regional applications. J Oper Oceanogr 8:s63–s79. CrossRefGoogle Scholar
  39. Penven P, Debreu L, Marchesiello P, McWilliams JC (2006) Evaluation and application of the ROMS 1-way embedding procedure to the central california upwelling system. Ocean Model 12:157–187. CrossRefGoogle Scholar
  40. Penven P, Marchesiello P, Debreu L, Lefévre J (2008) Software tools for pre- and post-processing of oceanic regional simulations. Environ Model Softw 23:660–662. CrossRefGoogle Scholar
  41. Rienecker MM, Suarez MJ, Gelaro R, et al. (2011) MERRA: NASA’s modern-era retrospective analysis for research and applications. JClimate 24:3624–3648. CrossRefGoogle Scholar
  42. Rivas D, Samelson RM (2011) A numerical modeling study of the upwelling source waters along the Oregon coast during 2005. JPhysOceanogr 41:88–112. CrossRefGoogle Scholar
  43. Saha S, Moorth S, Pan HL, et al. (2010) The NCEP climate forecast system reanalysis. BullAmerMeteorSoc 91:1015–1057. CrossRefGoogle Scholar
  44. Sakov P (2009) An orthogonal grid generator based on the CRDT algorithm (by conformal mapping)., accessed: 2014 & 2015
  45. Santana R, Teixeira C, Lessa GC (2018) The impact of different forcing agents on the residual circulation in a tropical well mixed estuary (Baía de Todos os Santos, Brazil). JCoastal Res 34:544–558. CrossRefGoogle Scholar
  46. Shchepetkin AF, McWilliams JC (2005) The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Model 9:347–404. CrossRefGoogle Scholar
  47. Sikirić MD, Janeković I, Kuzmić M (2009) A new approach to bathymetry smoothing in sigma-coordinate ocean models. Ocean Model 29:128–136. CrossRefGoogle Scholar
  48. Wallcraft AJ, Metzger EJ, Carroll SN (2009) Design description for the HYbrid Coordinate Ocean Model (HYCOM) version 2.2. Tech. rep. Naval Research Laboratory, Stennins Space Center, MSGoogle Scholar
  49. Warner JC, Geyer WR, Arango HG (2010) Using a composite grid approach in a complex coastal domain to estimate estuarine residence time. Comput. Geosci. 36:921–935. CrossRefGoogle Scholar
  50. Zhang X, Hetland RD, Marta-Almeida M, DiMarco SF (2012) A numerical investigation of the Mississippi and Atchafalaya freshwater transport, filling and flushing times on the Texas-Louisiana Shelf. JGeophysRes 117:C11009. CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Universidade de VigoCampus Lagoas-MarcosendeVigoSpain
  2. 2.Centro Oceanográfico de A CoruñaInstituto Español de OceanografíaA CoruñaSpain
  3. 3.Instituto de GeociênciasUniversidade Federal do Rio de JaneiroRio de JaneiroBrazil
  4. 4.Instituto de GeociênciasUniversidade Federal da BahiaSalvadorBrazil
  5. 5.Departamento de Engenharia AmbientalUniversidade Federal do Espírito SantoVitóriaBrazil

Personalised recommendations