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Estuaries and Coasts

, Volume 42, Issue 2, pp 348–364 | Cite as

Two Models Solutions for the Douro Estuary: Flood Risk Assessment and Breakwater Effects

  • I. IglesiasEmail author
  • S. Venâncio
  • J. L. Pinho
  • P. Avilez-Valente
  • J. M. P. Vieira
Article

Abstract

Estuarine floods are one of the most harmful and complex extreme events occurring in coastal environments. To predict the associated effects, characterize areas of risk, and promote population safety, numerical modeling is essential. This work performs a comparison and a combination of two 2-dimensional depth-averaged estuarine models (based on openTELEMAC-MASCARET and Delft3D hydrodynamic software packages), to develop a two-model ensemble approach that will improve forecast robustness when compared to a one-model approach. The ensemble was applied to one of the main Portuguese estuaries, the Douro river estuary, to predict the expected water levels associated with extreme river discharges in the present-day configuration with the new breakwaters. This is a region that is periodically under heavy flooding, which entails economic losses and damage to protected landscape areas and hydraulic structures. Both models accurately simulated water levels and currents for tidal- and flood-dominated validation simulations, with correlation values close to 1, RMSE below 15%, and small Bias and Skill coefficient close to 1. The two-model ensemble results revealed that the present-day estuarine mouth configuration will produce harsher effects for the riverine populations in case identical historical river floods take place. This is mainly due to the increase in the area and volume of the estuary’s sand spit related to the construction of the new breakwaters.

Keywords

Estuarine modeling Models ensemble Hydrodynamics Floods Douro estuary 

Notes

Funding Information

This research was supported by the Research Line ECOSERVICES, integrated in the Structured Program of R&D&I INNOVMAR: Innovation and Sustainability in the Management and Exploitation of Marine Resources (NORTE-01-0145-FEDER-000035), funded by the Northern Regional Operational Programme (NORTE2020) through the European Regional Development Fund (ERDF), and by the Brazilian National Council for Scientific and Technological Development (CNPq) through a scholarship granted to the 2nd author (Process 200016 / 2014-8).

References

  1. Araújo, M.F., J.-M. Jouanneau, P. Valério, T. Barbosa, A. Gouveia, O. Weber, A. Oliveira, A. Rodrigues, and J.M.A. Dias. 2002. Geochemical tracers of northern Portuguese estuarine sediments on the shelf. Progress in Oceanography 52 (2–4): 277–297.CrossRefGoogle Scholar
  2. Araújo, M.A.V.C., A. Mazzolari, and A. Trigo-Teixeira. 2013. An object oriented mesh generator: Application to flooding in the Douro estuary. Journal of Coastal Research Special Issue 65: 642–647.CrossRefGoogle Scholar
  3. Azevedo, I.C., P.M. Duarte, and A.A. Bordalo. 2006. Pelagic metabolism of the Douro estuary (Portugal) — Factors controlling primary production. Estuarine, Coastal and Shelf Science 69 (1–2): 133–146.CrossRefGoogle Scholar
  4. Azevedo, I.C., P.M. Duarte, and A.A. Bordalo. 2008. Understanding spatial and temporal dynamics of key environmental characteristics in a mesotidal Atlantic estuary (Douro, NW Portugal). Estuarine, Coastal and Shelf Science 76 (3): 620–633.CrossRefGoogle Scholar
  5. Azevedo, I.C., A.A. Bordalo, and P.M. Duarte. 2010. Influence of river discharge patterns on the hydrodynamics and potential contaminant dispersion in the Douro estuary (Portugal). Water Research 44 (10): 3133–3146.CrossRefGoogle Scholar
  6. Azevedo, I.C., A.A. Bordalo, and P.M. Duarte. 2014. Influence of freshwater inflow variability on the Douro estuaryprimary productivity: A modelling study. Ecological Modelling 272: 1–15.CrossRefGoogle Scholar
  7. Baker, L., and D. Ellison. 2008. Optimization of pedo-transfer functions using an artificial neural network ensemble method. Geoderma 144 (1–2): 212–224.CrossRefGoogle Scholar
  8. Bastos, L., A. Bio, J.L.S. Pinho, H. Granja, and A. Jorge da Silva. 2012. Dynamics of the Douro estuary sand spit before and after breakwater construction. Estuarine, Coastal and Shelf Science 109: 53–69.CrossRefGoogle Scholar
  9. Bastos, L., A. Bio and I. Iglesias. 2016. The importance of marine observatories and of RAIA in particular. Frontiers in Marine Science 3.  https://doi.org/10.3389/fmars.2016.00140.
  10. Becker, J.J., D.T. Sandwell, W.H.F. Smith, J. Braud, B. Binder, J. Depner, D. Fabre, J. Factor, S. Ingalls, S.-H. Kim, R. Ladner, K. Marks, S. Nelson, A. Pharaoh, R. Trimmer, J. Von Rosenberg, G. Wallace, and P. Weatherall. 2009. Global bathymetry and elevation data at 30 arc seconds resolution: SRTM30_PLUS. Marine Geodesy 32: 355–371.CrossRefGoogle Scholar
  11. Bordalo, A.A., and M.E.C. Vieira. 2005. Spatial variability of phytoplankton, bacteria and viruses in the mesotidal salt wedge Douro Estuary (Portugal). Estuarine, Coastal and Shelf Science 63: 143–154.CrossRefGoogle Scholar
  12. Cantelaube, P., and J.-M. Terres. 2005. Seasonal weather forecasts for crop yield modelling in Europe. Tellus A 57: 476–487.CrossRefGoogle Scholar
  13. Carvalho, GS. 1999. A responsabilidade das estruturas portuárias na migração das praias para o interior. In Comunicações das Primeiras Jornadas de Engenharia Costeira e Portuária, 209–226. Delegação Portuguesa, Porto: Associação Internacional de Navegação.Google Scholar
  14. Corti, S., and V. Pennati. 2000. A 3-D hydrodynamic model of river flow in a delta region. Hydrological Processes 14: 2301–2309.CrossRefGoogle Scholar
  15. deCastro, M., M. Gómez-Gesteira, M.N. Lorenzo, I. Álvarez, and A.J.C. Crespo. 2008. Influence of atmospheric modes on coastal upwelling along the western coast of the Iberian Peninsula, 1985 to 2005. Climate Research 36: 169–179.CrossRefGoogle Scholar
  16. Delft3D-FLOW. 2011. User Manual—Simulation of multi-dimensional hydrodynamic flows and transport phenomena, including sediments. Netherlands: Deltares 674p.Google Scholar
  17. Dias, AAP. 2010. O Estuário do Rio Douro — O Risco de Cheias. Graduation thesis. Faculdade de Letras, Universidade do Porto, Portugal.Google Scholar
  18. Dias, J.M., and J.F. Lopes. 2006. Implementation and assessment of hydrodynamic, salt and heat transport models: The case of Ria de Aveiro lagoon, Portugal. Environmental Modelling and Software 21: 1–15.CrossRefGoogle Scholar
  19. Dias, J.M.A., R. Gonzalez JM Jouanneau, M.F. Araújo, T. Drago, C. Garcia, A. Oliveira, A. Rodrigues, J. Vitorino, and O. Weber. 2002. Present day sedimentary processes on the northern Iberian shelf. Progress in Oceanography 52: 249–259.CrossRefGoogle Scholar
  20. Dias, J.M., M.C. Sousa, X. Bertin, A.B. Fortunato, and A. Oliveira. 2009. Numerical modeling of the impact of the Ancão Inlet relocation (Ria Formosa, Portugal). Environmental Modelling and Software 24: 711–725.CrossRefGoogle Scholar
  21. Dodet, G., X. Bertin, and R. Taborda. 2010. Wave climate variability in the North-East Atlantic Ocean over the last six decades. Ocean Modelling 31: 120–131.CrossRefGoogle Scholar
  22. Egbert, G.D., A.F. Bennett, and M.G.G. Foreman. 1994. TOPEX/POSEIDON tides estimated using a global inverse model. Journal Geophysical Research 99: 24821–24852.CrossRefGoogle Scholar
  23. Gomes, M.P., J.L. Pinho, J.S. Antunes do Carmo, and L. Santos. 2015. Hazard assessment of storm events for The Battery, New York. Ocean & Coastal Management 118: 22–31.CrossRefGoogle Scholar
  24. Gómez-Gesteira, M., L. Gimeno, M. deCastro, M.N. Lorenzo, I. Alvarez, R. Nieto, J.J. Taboada, A.J.C. Crespo, A.M. Ramos, I. Iglesias, J.L. Gomez-Gesteira, F.E. Santo, D. Barriopedro, and I.F. Trigo. 2011. The state of climate in NW Iberia. Climate Research 48: 109–144.CrossRefGoogle Scholar
  25. Granja, HM, L Bastos, JLS Pinho, J Gonçalves, RF Henriques, A Bio, J Mendes and A Magalhães. 2011. Integração de metodologias no estabelecimento de um programa de monitorização costeira para avaliação de risco. Abstract retrieved from: VII Conferência Nacional de Cartografia e Geodesia, Porto, pp. 11.Google Scholar
  26. Horritt, M.S., and P.D. Bates. 2002. Evaluation of 1D and 2D numerical models for predicting river flood inundation. Journal of Hydrology 268: 87–99.CrossRefGoogle Scholar
  27. Hu, K., P. Ding, Z. Wang, and S. Yang. 2008. A 2D/3D hydrodynamic and sediment transport model for the Yangtze Estuary, China. Journal of Marine Systems 77: 114–136.CrossRefGoogle Scholar
  28. Iglesias, I., S. Venâncio, R. Peixoto, J.L. Pinho, P. Avilez-Valente, J. Vieira. 2016. The Douro Estuary: Modelling comparison for floods prevention. Actas das 4.as Jornadas de Engenharia Hidrográfica. Instituto Hidrográfico. ISBN 978-989-705-097-8.Google Scholar
  29. IH. 1994. Campanha Hidromorfológica para o Estudo da Barra do Douro. Relatório Técnico. Lisboa: Divisão de Oceanografia Física, Instituto Hidrográfico.Google Scholar
  30. IH. 2012. Bathymetric model of Douro. Lisboa: Divisão de Hidrografia, Instituto Hidrográfico http://www.hidrografico.pt/cartografia-nautica-digital.php. Accessed April 2016.Google Scholar
  31. IPCC—Intergovernmental Panel on Climate Change. 2016. https://www.ipcc.ch/. Accessed July 2016.
  32. Jones, J.E., and A.M. Davies. 2010. Application of a finite element model to the computation of tides in the Mersey Estuary and Eastern Irish Sea. Continental Shelf Research 30: 491–514.CrossRefGoogle Scholar
  33. Krige, D.G.. 1951. A statistical approach to some mine valuations and allied problems at the Witwatersrand. Master’s thesis, University of Witwatersrand.Google Scholar
  34. Krogh, A., and J. Vedelsby. 1995. Neural network ensembles cross validation and active learning. Advances in Neural Information Processing Systems 7: 231–238.Google Scholar
  35. Li, M., L. Zhong, and W.C. Boicourt. 2005. Simulations of Chesapeake Bay estuary: Sensitivity to turbulence mixing parameterizations and comparison with observations. Journal of Geophysical Research 110: 2159–2202.CrossRefGoogle Scholar
  36. Lynch, D.R., and W.R. Gray. 1979. A wave equation model for finite element tidal computation. Computers and Fluids 7: 207–228.CrossRefGoogle Scholar
  37. Magalhães, C.M., A.A. Bordalo, and W.J. Wiebe. 2002. Temporal and spatial patterns of intertidal sediment-water nutrient and oxygen fluxes in the Douro River estuary, Portugal. Marine Ecology Progress Series 233: 55–71.CrossRefGoogle Scholar
  38. Matheron, G. 1963. Principles of geostatistics. Economic Geology 58: 1246–1266.CrossRefGoogle Scholar
  39. Mendes, R., N. Vaz, and J.M. Dias. 2013. Potential impacts of the mean sea level rise on the hydrodynamics of the Douro river estuary. Journal of Coastal Research Special Issue 65: 1951–1956.CrossRefGoogle Scholar
  40. Mohan Das, D., R. Singh, A. Kumar, D.R. Mailapalli, A. Mishra and C. Chatterjee. 2016. A multi-model ensemble approach for stream flow simulation. In Innovations in Agricultural and Biological Engineering, Modeling Methods and Practices in Soil and Water Engineering, ed. B. Panigrahi, M.R. Goyal, 71–102. Apple Academic Press. Chapter 4.Google Scholar
  41. Monteiro, I.O., W.C. Marques, E.H. Fernandes, R.C. Gonçalves, and O.O. Möller. 2011. On the effect of earth rotation, river discharge, tidal oscillations, and wind in the dynamics of the Patos Lagoon coastal plume. Journal of Coastal Research 27: 120–130.CrossRefGoogle Scholar
  42. Néelz, S., and G. Pender. 2010. Benchmarking of 2D Dyfraulic modelling packages. UK: DEFRA/Environment Agency Retrieved from: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/290884/scho0510bsno-e-e.pdf.Google Scholar
  43. Néelz, S., and G. Pender. 2013. Benchmarking the latest generation of 2D hydraulic modelling packages. UK: DEFRA/Environment Agency Retrieved from: http://evidence.environment-agency.gov.uk/FCERM/Libraries/FCERM_Project_Documents/SC120002_Benchmarking_2D_hydraulic_models_Report.sflb.ashx.Google Scholar
  44. Oliveira, J.M.P. 1973. O Espaço Urbano do Porto — Condições Naturais e Desenvolvimento. Coimbra: Instituto de Alta Cultura, Centro de Estudos Geográficos, Edições Afrontamento 496p.Google Scholar
  45. Pardé, M. 1966. Les crues du Douro d’aprés une étude portugaise remarquable. Vol. 23, 93–169. Lisboa: Boletim Trimestral de Informação, Direcção Geral dos Serviços Hidráulicos.Google Scholar
  46. Pinho, J.L.S., J.M.P. Vieira and D.R.C.B. Neves. 2010. Efeito das obras da embocadura na hidrodinâmica, intrusão salina e dinâmica sedimentar do estuário do Rio Douro. 10° Congresso da Água. Alvor, Portugal.Google Scholar
  47. Pinto, J. 2007. Influência do regime de escoamento fluvial na hidrologia e dinâmica do estuário do Douro. Relatório final de estágio, Universidade de Évora.Google Scholar
  48. Portela, L.I. 2008. Sediment transport and morphodynamics of the Douro River estuary. Geo-Marine Letters 28: 77–86.CrossRefGoogle Scholar
  49. Putra, S.S., M. van der Wegen, J. Reyns, A. van Dam, D.P. Solomatine, and J.A. Roelvink. 2015. Multi station calibration of 3D flexible mesh model: a case study of the Columbia Estuary. Procedia Environmental Sciences 28: 297–306.CrossRefGoogle Scholar
  50. Rahman, A and V Venugopal. 2015. Inter-comparison of 3D tidal flow models applied to Orkney Islands and Pentland Firth. Proceedings of the 11th European Wave and Tidal Energy Conference, pp: 10.Google Scholar
  51. Robins, P.E., and A.G. Davies. 2010. Morphological controls in sandy estuaries: The influence of tidal flats and bathymetry on sediment transport. Ocean Dynamics 60: 503–517.CrossRefGoogle Scholar
  52. Rodrigues, R., C. Brandão and J.P. da Costa. 2003. As Cheias no Douro Ontem, Hoje e Amanhã. Ministério das Cidades, Ordenamento do Território e Ambiente, Instituto da Água. Report. http://snirh.pt/snirh/download/Douro_hoje.pdf. Accessed 16 Nov 2016.
  53. Roy Bhowmik, S.K., and V.R. Durai. 2010. Application of multi-model ensemble techniques for real time district level rainfall forecasts in short range time scale over Indian region. Meteorology and Atmospheric Physics 106 (1–2): 19–35.CrossRefGoogle Scholar
  54. Rozante, J.R., D.S. Moreira, R.C.M. Godoy, and A.A. Fernandes. 2014. Multi-model ensemble: Technique and validation. Geoscientific Model Development Discussions 7: 2333–2343.CrossRefGoogle Scholar
  55. Santos, I., A.C. Teodoro, and F. Taveira-Pinto. 2010. Análise da evolução morfológica da restinga do rio Douro. Abstract retrieved from: 5as Jornadas de Hidráulica, 14. Porto: Recursos Hídricos e Ambiente.Google Scholar
  56. Silva, A. 1996. Implementação de um modelo hidromorfológico para a Barra do Douro: contribuição para a compreensão do sistema. Abstract retrieved from: 3° Congresso da Água, Lisboa. Available at http://maretec.mohid.com/MaretecManagement/ConferencePapers.asp.
  57. SNIRH—Sistema Nacional de Informação de Recursos Hídricos. 2016. http://snirh.apambiente.pt/. Accessed June 2016.
  58. Symonds, A.M., T. Vijverberg, S. Post, B. van der Spek, J. Henrotte and M. Sokolewicz. 2016. Comparison between Mike 21 FM, Delft3D and Delft3D FM flow models of Western Port Bay, Australia. Proceedings of 35th Conference on Coastal Engineering, Antalya, Turkey.Google Scholar
  59. Tebaldi, C., and R. Knutti. 2007. The use of the multi-model ensemble in probabilistic climate projections. Philosophical Transactions of the Royal Society – A 365: 2053–2075.CrossRefGoogle Scholar
  60. Teng, J., A. Jakeman, J. Vaze, B. Croke, D. Dutta, and S. Kim. 2017. Flood inundation modelling: A review of methods, recent advances and uncertainty analysis. Environmental Modelling and Software 90: 201–216.CrossRefGoogle Scholar
  61. Thomson, M.C., F.J. Doblas-Reyes, S.J. Mason, R. Hagedorn, S.J. Connor, T. Phindela, A.P. Morse, and T.N. Palmer. 2006. Malaria early warnings based on seasonal climate forecasts from multi-model ensembles. Nature 439: 576–579.CrossRefGoogle Scholar
  62. Trauth, M. 2006. MATLAB® recipes for earth sciences. Springer.Google Scholar
  63. Van Maren, D.S., T. Van Kessel, K. Cronin, and L. Sittoni. 2015. The impact of channel deepening and dredging on estuarine sediment concentration. Continental Shelf Research 95: 1–14.CrossRefGoogle Scholar
  64. Vieira, M.E.C., and A.A. Bordalo. 2000. The Douro estuary (Portugal): A mesotidal salt wedge. Oceanologica Acta 23: 585–594.CrossRefGoogle Scholar
  65. Viitak, M., M. Maljutenko, V. Alari, Ü. Suursaar, S. Rikka, and P. Lagemaa. 2016. The impact of surface currents and sea level on the wave field evolution during St. Jude storm in the eastern Baltic Sea. Oceanologia 58: 176–186.CrossRefGoogle Scholar
  66. Wan, Y., H. Wu F Gu, and D. Roelvink. 2014. Hydrodynamic evolutions at the Yangtze estuary from 1998 to 2009. Applied Ocean research 47: 291–302.CrossRefGoogle Scholar
  67. Weigel, A.P., M.A. Liniger, and C. Appenzeller. 2008. Can multi-model combination really enhance the prediction skill of probabilistic ensemble forecasts? Quarterly Journal of the Royal Meteorological Society 134: 241–260.CrossRefGoogle Scholar
  68. WMO. 2012. Guidelines on ensemble prediction systems and forecasting. WMO-No. 1091. Geneva: World Meteorological Organization http://www.wmo.int/pages/prog/www/Documents/1091_en.pdf. Accessed 16 Nov 2016.Google Scholar

Copyright information

© Coastal and Estuarine Research Federation 2018

Authors and Affiliations

  1. 1.Centro Interdisciplinar de Investigação Marinha e Ambiental (CIIMAR)Universidade do PortoMatosinhosPortugal
  2. 2.Centro do Território, Ambiente e Construção (CTAC), Departamento de Engenharia CivilUniversidade do MinhoBragaPortugal
  3. 3.Departamento de Engenharia CivilUniversidade Federal do Triângulo MineiroUberabaBrazil
  4. 4.Faculdade de EngenhariaUniversidade do PortoPortoPortugal

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