1st Edition

Rip Current Prediction System for Swimmer Safety Towards operational forecasting using a process based model and nearshore bathymetry from video

By Leo Sembiring Copyright 2016
    152 Pages
    by CRC Press

    152 Pages
    by CRC Press

    Rip currents are among the most dangerous coastal hazards for the bathing public, and contribute to the highest portion of beach rescues all over the world. In order to help life guards in planning and preparing rescue resources so that casualties can be minimized, information about where and when rip currents may occur is needed. This can be provided by a predictive tool which combines meteorological forecasts, hydrodynamic models and remote-sensed observations.

    In this thesis, a methodology which can provide rip current forecasts for swimmer safety is developed and tested for Egmond aan Zee beach in the Netherlands. The approach uses the numerical model system CoSMoS, combined with daily estimates of nearshore-scale bathymetry obtained from a system called cBathy, which infers depths by estimating wave celerities from video imaging. Furthermore, in order to gain more knowledge on occurrences of rips at Egmond beach, a numerical study on the kinematics of rip currents and the safety implications for swimmers is presented as well. Coupling the video bathymetry estimates with CoSMoS in forecast mode shows that dangerous rips were correctly predicted. This thesis demonstrates the potential application of the proposed system for providing rip current forecasts at Egmond aan Zee.

    1 Introduction
    1.1 Problem statement
    1.2 Objectives and research approach
    1.2.1 Objectives
    1.2.2 Research questions
    1.3 Approach
    1.3.1 Coastal operational model
    1.3.2 Rip currents numerical modelling
    1.3.3 Nearshore bathymetry from ARGUS video
    1.3.4 Prediction system
    1.3.5 Case study site
    1.4 Outline

    2 Literature review on rip currents and rip current prediction systems
    2.1 Introduction
    2.2 Rip current review
    2.2.1 Generation and forcing of rip currents
    2.2.2 Bathymetrically controlled rip currents
    2.2.3 Numerical modelling of rip currents
    2.3 Rip current prediction systems
    2.3.1 Data driven approach
    2.3.2 Process based model approach
    2.4 Conclusion

    3 Coastal operational model – CoSMoS – system set up and validation
    3.1 Introduction
    3.2 The CoSMoS model system
    3.3 Model system validation
    3.3.1 Data and method
    3.3.2 Results and discussion
    3.4 Conclusions

    4 Dynamic modelling of rip currents for swimmer safety on a wind-sea meso-tidal beach
    4.1 Introduction
    4.2 Methods
    4.2.1 Model
    4.2.2 Data
    4.3 Results
    4.3.1 Tidal currents
    4.3.2 Drifter flow path comparison with data
    4.3.3 Drifter velocity comparison with data
    4.3.4 Rip current initiation and duration
    4.3.5 Rip current circulation and beach safety
    4.4 Discussion
    4.4.1 Importance of the wave group forcing
    4.4.2 Importance of the wind stress forcing
    4.5 Conclusions

    5 Beach bathymetry from video imagery
    5.1 Introduction
    5.2 A review on bathymetry estimation through remote sensing technique
    5.2.1 Depth inversion via wave dispersion relationship
    5.2.2 Depth inversion using other methods
    5.2.3 Shore line detection from video images
    5.3 Beach Wizard: Nearshore bathymetry estimation using wave roller dissipation from video
    5.3.1 Theory
    5.3.2 Wave dissipation maps from video
    5.3.3 Application (August 2011 field data)
    5.3.4 Discussion
    5.4 cBathy: Nearshore bathymetry estimation using pixel intensity time stacks
    5.4.1 Theory
    5.4.2 cBathy set up and pixel time stack collection for Egmond
    5.4.3 Application (June 2013 field data
    5.4.4 Discussion
    5.5 Integration of sub tidal bathymetry from cBathy with intertidal bathymetry from shoreline detection method
    5.5.1 Approach
    5.5.2 Results and discussions
    5.6 Conclusions

    6 Predicting rip currents: Combination of CoSMoS and bathymetry from video
    6.1 Introduction
    6.2 Applicability of cBathy bathymetry on the prediction of nearshore currents
    6.2.1 Comparison with field data
    6.2.2 Nearshore currents, model-model comparison
    6.3 A test case: summer 2013
    6.4 Conclusions

    7 Summary and outlook
    7.1 Summary
    7.1.1 Can we predict the occurrence, duration, and the magnitude of the rip currents at Egmond using process-based model? What is the added-value for swimmer safety warning systems?
    7.1.2 Can we obtain nearshore bathymetries through video technique for Egmond aan Zee in an operational mode?
    7.1.3 Can we apply nearshore bathymetry from video to predict nearshore currents and to forecast rip currents?
    7.2 Outlook
    7.2.1 Application of the system and how the information can be useful
    7.2.2 Future research topics

    Biography

    Leo Sembiring (1980, Kabanjahe, Indonesia) studied Civil Engineering at the Department of Bandung, Institute of Technology (ITB), West Java. He obtained his B.Sc in 2004 after writing a thesis on developing peak ground acceleration map due to tectonic earthquake for Sulawesi Island. In 2008, he started his graduate program in Coastal Engineering and Port Development program in UNESCO-IHE, Delft. He obtained his M.Sc degree in 2010 (with distinction). He carried out his master research at Deltares, working on the validation of wave and hydrodynamic model for The Dutch Coast (SWAN and DELFT3D) and application of data assimilation model Beach Wizard-dissipation maps in updating nearshore bathymetry. In June 2011, he started his PhD work on developing an operational forecasting system of rip currents for Egmond aan Zee beach. During this period, he spent most of his time at Deltares and occasionally at UNESCO-IHE. During his research, he was involved in SEAREX field campaign at Egmond aan Zee (August 2011), and responsible to organize and conduct his own field campaign on June 2013, during which he was assisted by MSc students from UNESCO-IHE.