Skip to main content
SpringerLink
Log in

Calibration of shoreline change model using an optimization algorithm

  • Published:
Journal of Coastal Conservation Aims and scope Submit manuscript

Abstract

As the prediction and preparation for coastline change are regarded as an important social issue, improving the accuracy of the numerical shoreline change model to predict long-term shoreline changes is becoming increasingly important. Most shoreline change models contain several parameters to reflect the local characteristics of the study area, and their performance can be significantly enhanced by calibrating the parameters with the field data. However, as the number of the parameters increases, the model calibration becomes extremely difficult, especially in the model application for a long and complicated shoreline. In the present study, a method for calibrating the parameters of a shoreline change model that uses an optimization algorithm is proposed. Subsequently, its performance is demonstrated by applying the model to the Gangneung littoral cell set on the East Coast of Korea. First, the parameter calibration was performed using the records of 17 years (1980–1996) for all input data, including artificial coastal developments, conservation efforts, wave climate statistics, and the observed shoreline data. Subsequently, the calibrated model was verified using the data of the next 17 years (1997–2013). The results showed that the model calibration using the optimization technique significantly improved the accuracy of the shoreline change model.

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
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15

Similar content being viewed by others

References

  • Arora RJ (2015) Optimization: algorithms and applications. CRC Press

  • Beck TM (2019) Tracking sediment bypassing, geomorphological analysis, and regional sediment management at tidal inlets. School of Geosciences, University of South Florida, Doctoral dissertation

    Google Scholar 

  • Benson HP (1998) An outer approximation algorithm for generating all efficient extreme points in the outcome set of a multiple objective linear programming problem. J Glob Optim 13:1–24

    Article  Google Scholar 

  • Bruun P (1962) Sea-level rise as a cause of shore erosion. Journal of the waterways and harbors division. ASCE 88(1):117–132

    Google Scholar 

  • Burden RL, Faires JD (1985) Numerical analysis. Prindle, Weber & Schmidt

    Google Scholar 

  • Chun I, Kang H, Oh B (2017) Investigation on the characteristics and domestic applicability of regional sediment management. Journal of Coastal Disaster Prevention 4:273–283 (in Korean)

    Google Scholar 

  • Davees M, Kamphuis JW (1998) Oneline, a numerical model for shoreline change. 26th international conference on coastal engineering. ASCE. Pp. 2668-2681

  • Donghae Regional Office of Oceans and Fisheries (2010) Report on the design of Namhangjin-ri coastal maintenance project in Gangneung, Korea

  • Esteves LS, da Silva ARP, Arejano TB, Pivel MAG, Vranjac MP (2003) Coastal development and human impacts along the Rio Grande do Sul beaches, Brazil. Journal of Coastal Research. Special issue no. 35. Pp. 548-556

  • Frey AE (2015) Using GenCade to create a sediment budget in SBAS, ERDC/CHL CHETN-IV-105. US Army Engineer Research and Development Center, Vicksburg, MS

    Google Scholar 

  • Frey AE, Connell K, Hanson H, Larson M, Thomas R, Munger S, Zunde A (2012) GenCade version 1 model theory and user’s guide, ERDC/CHL TR-12-25. US Army Engineer Research and Development Center, Vicksburg, MS

    Google Scholar 

  • Frey AE, King DB, Munger S (2014) Recommendations and requirements for GenCade, ERDC/CHL TR-14-6. US Army Engineer Research and Development Center, Vicksburg, MS

    Book  Google Scholar 

  • Gangwondo (2014) Monitoring report of coastal erosion. The province of Gangwon, Korea

    Google Scholar 

  • Hallermeier RJ (1980) A profile zonation for seasonal sand beaches from wave climate. Coast Eng 4:253–277

    Article  Google Scholar 

  • Hanson H, Kraus, NC (1989) GENESIS: generalized model for simulating shoreline change, report 1: technical reference. Technical report CERC-89-19, U.S. Army engineer waterways experiment stations, coastal engineering research center, Vicksburg, MS

  • Jayappa KS, Deepika B (2018) Impacts of coastal erosion, anthropogenic activities and their management on tourism and coastal ecosystems: a study with reference to Karnataka coast, India. In: Botero C., Cervantes O., Finkl C. (eds) beach management tools - concepts, methodologies and case studies. Coastal research library, Vol 24. Springer, Cham

  • Jun K, Lee DY (2005) Estimation report of deep water design wave. BSPE95100-1767-2. Korea Institute of Science and Technology. (in Korean)

  • Kang H, Chun I, Oh B (2017) Establishment of a regional sediment management system for the littoral cell of Gangneung Port, In Korean Society of Coastal Disaster Prevention of the 5th Annual Conference 2017. Journal of Coastal Disaster Prevention, pp. 23–24. (in Korean)

  • Kang H, Chun I, Oh B (2018) Estimation of the depth of closure near Gangneung port in Korea. Proceedings from the international coastal symposium (ICS) 2018 (Busan, Republic of Korea). Journal of coastal research, special issue no. 85, pp. 1361-1365

  • KHOA (2013) National coastline survey data. Agency, Korea Hydrographic and Oceanographic

    Google Scholar 

  • KHOA (2016) Coastal material classification map. Agency, Korea Hydrographic and Oceanographic

    Google Scholar 

  • Kim I-H, Kim J-H, Choi J-K, Ryu H-Y, Hur D-S (2014) A study on a characteristics of sediment transport around Myeongseondo at Jinha Beach” Journal of Coastal Disaster Prevention, 1(3), pp. 113–117

  • Labuz TA (2015) Environmental impacts-coastal erosion and coastline changes. In: the BACC II author team (eds) second assessment of climate change for the Baltic Sea basin. Regional climate studies. Springer, Cham

  • Larson M, Kraus NC, Hanson H (2003) Modeling regional sediment transport and coastal evolution along the Delmarva Peninsula. In proceedings coastal sediments ‘03, ASCE

  • Leatherman SP, Zhang K, Douglas BC (2000) Sea level rise shown to drive coastal erosion. Eos. Vol. 81(6). Pp. 55-57

  • Morton RA, Miller TL, Moore LJ (2004) National assessment of shoreline change: Part 1: Historical shoreline changes and associated coastal land loss along the U.S. Gulf of Mexico: U.S. Geological Survey Open-file Report 2004–1043, 45p

  • Nelder JA, Mead R (1965) A simplex method for function minimization. Comput J 7:308–313

    Article  Google Scholar 

  • Powell MJD (2007) A view of algorithms for optimization without derivatives (Report). Cambridge University, Department of Applied Mathematics and Theoretical Physics

    Google Scholar 

  • Rao SS (2009) Engineering optimization: theory and practice, Wiley

  • Roelvink D, Reniers A (2011) A guide to modelling coastal morphology. World Scientific

  • Rosati JD (2005) Concepts in sediment budgets. J Coast Res 21(2):307–322

    Article  Google Scholar 

  • Sanjaume E, Pardo-Pascual JE (2005) Erosion by human impact on the Valencian coastline (E of Spain). Journal of coastal research. Special Issue 49:76–82

    Google Scholar 

  • Szmytkiewicz M, Biegowski J, Kaczmarek LM, Okroj T, Ostrowski R, Pruszak Z, Różyńsky G, Skaja M (2000) Coastline changes nearby harbour structures. Comparative analysis of one-line models versus field data 40(2):119–139

    Google Scholar 

  • Thomas RC, Frey AE (2013) Shoreline change modeling using one-line models: general model comparison and literature review. ERDC/CHL CHETN-II-55. US Army Corps of Engineers

  • Toimil A, Losada IJ, Camus P, Díaz-Simal P (2017) Managing coastal erosion under climate change at the regional scale. Coast Eng 128:106–122

    Article  Google Scholar 

  • Townsend KE, Thomas, RC, Frey AE (2014) Shoreline change modeling using one-line models: application and comparison of GenCade, Unibest, and Litpack. ERDC/CHL CHETN-IV-102, US Army Corps of Engineers

Download references

Acknowledgements

This work was supported by the Ministry of Oceans and Fisheries of the Republic of Korea for the governmental research projects “Development of Coastal Erosion Control Technology (2018)” and “Construction of Ocean Research Station and their Application Studies (2019)”.

Author information

Authors and Affiliations

  1. Structural & Seismic Technology Group, KEPCO Research Institute, Daejeon, Republic of Korea

    Haneul Kang

  2. Department of Civil Engineering, Konkuk University Seoul, 120 Neungdong-ro, Gwangjin-gu, Seoul, Republic of Korea

    Insik Chun

  3. Sea & River Technology Ltd., Uiwang, Republic of Korea

    Byungcheol Oh

Authors
  1. Haneul Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Insik Chun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Byungcheol Oh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Insik Chun.

Additional information

Publisher’s note

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

Artificial coastal developments and conservation efforts record of the study area

Artificial coastal developments and conservation efforts record of the study area

Table 8 Summary of the coastal structures record of the study area
Full size table
Table 9 Dredging and beach nourishment history of the study area
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kang, H., Chun, I. & Oh, B. Calibration of shoreline change model using an optimization algorithm. J Coast Conserv 24, 33 (2020). https://doi.org/10.1007/s11852-020-00750-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s11852-020-00750-y

Keywords

Search

Navigation