Skip to main content
SpringerLink
Log in

Optimization of Bottom Friction Coefficient Using Inverse Modeling in the Persian Gulf

  • Article
  • Published:
Ocean Science Journal Aims and scope Submit manuscript

Abstract

A practical method for the calibration of the ocean circulation model is introduced using measured water levels along the Persian Gulf coastlines. Dimensional analysis is employed to present a new Manning formulation as a function of water depth, mean velocity, vegetation, and bed sediment size. The ocean circulation model is configured by applying the pre-defined Manning formula, including empirical parameters. The direct minimization approach of data assimilation is then applied to find the optimum bottom friction distribution. MIKE21 and AUTOCAL modules of DHI are selected for simulation and optimization, respectively. The optimization method using spatially varying friction results in slight overall improvement of model outputs, compared to applying a constant friction. The bottom friction in shallow vegetated areas is significantly modified, which highlights the effect of the vegetation on bed resistance in shallow waters.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Alder J (2003) Putting the coast in the Sea Around Us project. Sea Around Us Newsl 15:1–2

    Google Scholar 

  • Aldridge JN, Davies AM (1993) A High-resolution three-dimensional hydrodynamic tidal model of the Eastern Irish sea. J Phys Oceanogr 23:207–224. https://doi.org/10.1175/1520-0485(1993)023%3c0207:AHRTDH%3e2.0.CO;2

    Article  Google Scholar 

  • Al-Ghadban AN, Al Dousary A, Jacob PG, Behbehani M, Cacers P (1998) Mineralogy, genesis and sources of surficial sediments in the ROPME Sea area. Terra Scientific Publishing Company, Tokyo, p 24

    Google Scholar 

  • Baptist MJ, Babovic V, Rodríguez Uthurburu J, Keijzer M, Uittenbogaard RE, Mynett A, Verwey A (2007) On inducing equations for vegetation resistance. J Hydraul Res 45:435–450. https://doi.org/10.1080/00221686.2009.9521996

    Article  Google Scholar 

  • Blott SJ, Pye K (2012) Particle size scales and classification of sediment types based on particle size distributions: review and recommended procedures. Sedimentology 59:2071–2096. https://doi.org/10.1111/j.1365-3091.2012.01335.x

    Article  Google Scholar 

  • Caldwell PC, Merrifield MA, Thompson PR (2015) Sea level measured by tide gauges from global oceans as part of the Joint Archive for Sea Level (JASL) since 1846. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.7289/v5v40s7w

    Article  Google Scholar 

  • Cavalcante GH, Kjerfve B, Feary DA (2012) Examination of residence time and its relevance to water quality within a coastal mega-structure: The Palm Jumeirah Lagoon. J Hydrol 468–469:111–119. https://doi.org/10.1016/j.jhydrol.2012.08.027

    Article  Google Scholar 

  • Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette JJ, Park BK, Peubey C, de Rosnay P, Tavolato C, Thépaut JN, Vitart F (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597. https://doi.org/10.1002/qj.828

    Article  Google Scholar 

  • DHI (2017a) MIKE 21 & MIKE 3 flow model FM—sand transport module. Hørsholm, DHI, p 83

    Google Scholar 

  • DHI (2017b) Auto calibration tool user guide. Hørsholm, DHI, p 64

    Google Scholar 

  • Egbert GD, Erofeeva SY (2002) Efficient inverse modeling of barotropic ocean tides. J Atmos Ocean Technol 19:183–204. https://doi.org/10.1175/1520-0426(2002)019%3c0183:EIMOBO%3e2.0.CO;2

    Article  Google Scholar 

  • Egbert GD, Ray RD, Bills BG (2004) Numerical modeling of the global semidiurnal tide in the present day and in the last glacial maximum. J Geophys Res Ocean 109:C03003. https://doi.org/10.1029/2003JC001973

    Article  Google Scholar 

  • El Kadi AK, Paquier A (2009) One-dimensional numerical modeling of sediment transport and bed deformation in open channels. Water Resour Res 45:1–20. https://doi.org/10.1029/2008WR007134

    Article  Google Scholar 

  • Franchini M, Galeati G, Berra S (1998) Global optimization techniques for the calibration of conceptual rainfall-runoff models. Hydrol Sci J 43:443–458. https://doi.org/10.1080/02626669809492137

    Article  Google Scholar 

  • Gad MA, Saad A, El-Fiky A, Khaled M (2013) Hydrodynamic Modeling of Sedimentation in the Navigation Channel of Damietta Harbor in Egypt. Coast Eng J 55:1350007–1–1350007–31. https://doi.org/10.1142/S0578563413500071

    Article  Google Scholar 

  • Hanken N-M, Bjørlykke K, Nielsen JK (2010) Carbonate sediments Nils-Martin. In: Bjørlykke K (ed) Petroleum geoscience: from sedimentary environments to rock physics. Springer, Berlin

    Google Scholar 

  • Hill MC (1998) Methods and guidelines for effective model calibration; with application to UCODE, a computer code for universal inverse modeling, and MODFLOWP, a computer code for inverse modeling with MODFLOW, US Geological Survey, Water Resources Investigations Report 98-4005, p 98

  • Kagan BA, Sofina EV, Rashidi E (2012) The impact of the spatial variability in bottom roughness on tidal dynamics and energetics, a case study: the M2 surface tide in the North European Basin. Ocean Dyn 62:1425–1442. https://doi.org/10.1007/s10236-012-0571-3

    Article  Google Scholar 

  • Khosravi M, Siadat Mousavi SM, Chegini V, Vennell R (2018) Across-channel distribution of the mean and tidal flows in the Khuran Channel, Persian Gulf, Iran. Int J Marit Technol 10:1–6. https://doi.org/10.29252/ijmt.10.1

    Article  Google Scholar 

  • Kobashi D, Mazda Y (2005) Tidal flow in riverine-type mangroves. Wetl Ecol Manag 13:615–619. https://doi.org/10.1007/s11273-004-3481-4

    Article  Google Scholar 

  • Lak R (2009) Marine Geology investigation of the Persian Gulf, Tehran. Iran, p 2

  • Lardner RW, Al-Rabeh AH, Gunay N (1993) Optimal estimation of parameters for a two-dimensional hydrodynamical model of the Arabian Gulf. J Geophys Res 98:18229. https://doi.org/10.1029/93JC01411

    Article  Google Scholar 

  • Lu X, Zhang J (2006) Numerical study on spatially varying bottom friction coefficient of a 2D tidal model with adjoint method. Cont Shelf Res 26:1905–1923. https://doi.org/10.1016/j.csr.2006.06.007

    Article  Google Scholar 

  • Madsen H (2003) Parameter estimation in distributed hydrological catchment modelling using automatic calibration with multiple objectives. Adv Water Resour 26:205–216. https://doi.org/10.1016/S0309-1708(02)00092-1

    Article  Google Scholar 

  • Madsen H (2007) Model calibration guideline. DHI Group, Hørsholm, p 90

    Google Scholar 

  • NCC (2017) Atlas map and geodetic information (in Persian). National Cartographic Center, Tehran

    Google Scholar 

  • Nicolle A, Karpytchev M (2007) Evidence for spatially variable friction from tidal amplification and asymmetry in the Pertuis Breton (France). Cont Shelf Res 27:2346–2356. https://doi.org/10.1016/j.csr.2007.06.005

    Article  Google Scholar 

  • Nunes V, Pawlak G (2008) Observations of bed roughness of a coral reef. J Coast Res 2:39–50. https://doi.org/10.2112/05-0616.1

    Article  Google Scholar 

  • PMO (2009) Monitoring and modeling study of Iranian coasts. Ports & Maritime Organization, Tehran

    Google Scholar 

  • Pokavanich T, Alosairi Y, Graaff RDE, Morelissen R, Verbruggen W, Al-Rifaie Kh, Altaf T, Al-Said T (2015) Three-dimensional Arabian gulf hydro-environmental modeling using Delft3D. In: Proceedings of the 36th IAHR World Congress, Hague, 28 Jun–3 Jul 2015

  • Rakha KA, Al-Banaa K, Al-Ragum A, Al-Hulail F (2008) Hydrodynamic study on the currents at an intake Basin in Kuwait. In: PIANC-COPEDEC VII: Seventh International Conference on Coastal and Port Engineering in Developing Countries, Dubai, 24–28 Feb 2008

  • Ranji Z, Hejazi K, Soltanpour M, Allahyar MR (2017) Inter-comparison of recent tide models for the Persian Gulf and Oman Sea. In: 35th International Conference on Coastal Engineering (ICCE 2016), Antalya, 17–20 Nov 2016. https://doi.org/10.9753/icce.v35

  • Rasmussen J, Madsen H, Jensen KH, Refsgaard JC (2016) Data assimilation in integrated hydrological modelling in the presence of observation bias. Hydrol Earth Syst Sci 20:2103–2118. https://doi.org/10.5194/hess-20-2103-2016

    Article  Google Scholar 

  • Robinson AR, Lermusiaux PFJ, Sloan NQ (1998) Data assimilation. In: Brink KH, Robinson AR (eds) The Sea, Volume 10: the global coastal ocean—processes and methods. Wiley, New York

    Google Scholar 

  • Sandwell DT, Gille ST, Smith WHF (eds) (2002) Bathymetry from space: oceanography, geophysics, and climate. Geoscience Professional Services, Bethesda, p 24

    Google Scholar 

  • Sohrabi Athar M, Ardalan AA, Karimi R (2019) Hydrodynamic tidal model of the persian gulf based on spatially variable bed friction coefficient. Mar Geod 42:25–45. https://doi.org/10.1080/01490419.2018.1527799

    Article  Google Scholar 

  • Spalding M, Kainuma M, Collins L (2010) World atlas of mangroves (version 3). Routledge, London, p 336

    Book  Google Scholar 

  • Struve J, Falconer RA, Wu Y (2003) Influence of model mangrove trees on the hydrodynamics in a flume. Estuar Coast Shelf Sci 58:163–171. https://doi.org/10.1016/S0272-7714(03)00072-6

    Article  Google Scholar 

  • UNEP-WCMC (2003) Global distribution of seagrasses (version 6.0). UN Environment World Conservation Monitoring Centre, Cambridge. https://doi.org/10.34892/x6r3-d211

    Book  Google Scholar 

  • UNEP-WCMC, WorldFishCenter, WRI, TNC (2018) Global distribution of warm-water coral reefs, compiled from multiple sources including the Millennium Coral Reef Mapping Project. Version 4.1. UN Environment World Conservation Monitoring Centre, Cambridge. https://doi.org/10.34892/t2wk-5t34

    Book  Google Scholar 

  • Van Rijn LC (1993) Principles of sediment transport in rivers, Estuaries and Coastal Seas. Aqua Publications, Amsterdam, p 1200

    Google Scholar 

  • Watson R, Alder J, Booth S, Christensen V, Kaschner K, Kitchingman A, Lai S, Palomares MLD, Valdez F, Pauly D (2004) Welcome to www.seaaroundus.org: launching our ‘product’ on the web. Sea Around Us Newsl 22:1–8

    Google Scholar 

  • Wentworth CK (1922) A scale of grade and class terms for clastic sediments. J Geol 30:377–392. https://doi.org/10.1086/622910

    Article  Google Scholar 

  • Wessel P, Smith WHF (1996) A global, self-consistent, hierarchical, high-resolution shoreline database. J Geophys Res Solid Earth 101:8741–8743. https://doi.org/10.1029/96JB00104

    Article  Google Scholar 

  • Zhang J, Lu X, Wang P, Wang YP (2011) Study on linear and nonlinear bottom friction parameterizations for regional tidal models using data assimilation. Cont Shelf Res 31:555–573. https://doi.org/10.1016/j.csr.2010.12.011

    Article  Google Scholar 

Download references

Acknowledgements

The authors gratefully acknowledge the support of DHI by providing the software license. We would also like to express our gratitude to PMO for providing the water level data and Dr. Razieh Lak from Geological Survey of Iran for supplying the bed sediment map of the Persian Gulf. Thanks are also extended to Dr. Reza Kamalian from University of Qom, Dr. Arash Bakhtiari from International Marine and Dredging Consultants and Dr. Hossein Ardalan from Water Research Institute of Iran for their kind assistance in this study.

Author information

Authors and Affiliations

  1. Civil Engineering Department, K. N. Toosi University of Technology, Tehran, 19967-15433, Iran

    Zahra Ranji & Mohsen Soltanpour

Authors
  1. Zahra Ranji
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mohsen Soltanpour
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zahra Ranji.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ranji, Z., Soltanpour, M. Optimization of Bottom Friction Coefficient Using Inverse Modeling in the Persian Gulf. Ocean Sci. J. 56, 331–343 (2021). https://doi.org/10.1007/s12601-021-00040-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12601-021-00040-0

Keywords

Search

Navigation