Abstract
A major portion of the coastline of Kerala is under erosion, primarily due to the action of wind-generated waves. Accurate assessment of the nearshore wave climate is essential for detailed apprehension of the sediment processes that lead to coastal erosion. Numerical wave transformation models set up incorporating high-resolution nearshore bathymetry and nearshore wind data, prove to be sufficient for the purpose. But, running these models for decadal time scales incur huge computational cost. Thus, a Feed Forward Back Propagation ANN is developed to estimate the wave parameters nearshore with training datasets obtained from minimal set of numerical simulations of wave transformation using DELFT3D-WAVE. The numerical model results are validated using Wave Rider Buoy data available for the location. This hybrid methodology is utilized to hindcast nearshore wave climate of a location in north Kerala for a period of 40 years with the ANN model trained with 1-yr data. The model shows good generalization ability when compared to the results of numerical simulation for a period of 10 years. This paper illustrates the data and methodology adopted for the development of the numerical model and the proposed ANN model along with the statistical comparisons of the results obtained.
Research highlights
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A hybrid methodology, combining numerical modelling and soft computation using ANNs, is developed to obtain long-term nearshore wave hindcast. One years’ numerical model simulation is utilised to train the ANN models.
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The optimised ANNH, ANNT, ANNθmx and ANNθmy models, with 15, 25, 25 and 30 neurons respectively in their single hidden layer, show good generalization ability when compared to the results of numerical simulation for a period of 10 years. The coefficient of correlation between the numerical model results and the ANNH model is 0.99. Results of ANNT model and the combined result of ANNθmx, ANNθmy models show a coefficient of correlation of 0.97 with the corresponding numerical model results. The new methodology allows for faster reconstruction of long-term time series of nearshore wave parameters.
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The trained models are used for simulating nearshore wave parameters at a location in North Kerala coast for 40 years. The maximum Hs at the nearshore location from 40 years’ ANN simulation is 3.39 m. Hs exceeds 3 m only for 0.04% of the time. During monsoon, waves feature a narrow range of Tp as well as mean wave direction as opposed to the non-monsoon period.
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source: ECMWF ERA-Interim).
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Acknowledgements
The authors are thankful to the Indian National Centre for Ocean Information Services (INCOIS), Hyderabad, India for providing wave data. We thank the editor and the anonymous reviewers for their valuable comments which helped us to improve the manuscript.
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Rajindas K P and Shashikala A P together conceived this work, arrived at the research design and collected the data required. Rajindas analysed and interpreted the data, conducted numerical experiments and performed analysis of the results under the supervision of Shashikala. Rajindas drafted the original manuscript and Shashikala reviewed the draft, edited with her contributions to it and finalised the manuscript.
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Communicated by C Gnanaseelan
This article is part of the topical collection: Advances in Coastal Research.
Appendix
Appendix
The flow chart of the algorithm for MATLAB program used for developing the ANN models.
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Rajindas, K.P., Shashikala, A.P. Development of hybrid wave transformation methodology and its application on Kerala Coast, India. J Earth Syst Sci 130, 103 (2021). https://doi.org/10.1007/s12040-021-01612-3
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DOI: https://doi.org/10.1007/s12040-021-01612-3