Wave runup and overtopping on smooth-slope NEXC block

• Main Authors: Benson, Y. A., Abd. Wahab, Ahmad Khairi, Othman, Ilya Khairanis, Jamal, Mohamad Hidayat, Mat Desa, Safari, Lee, H. L., Md. Noh, Md. Nasir
• Format: Conference or Workshop Item
• Language: English
• Published: 2021
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://eprints.utm.my/id/eprint/96372/1/IlyaKhairanisOthman2021_WaveRunupandOvertoppingonSmooth.pdf; http://eprints.utm.my/id/eprint/96372/; http://dx.doi.org/10.1088/1755-1315/880/1/012013
• Institution: Universiti Teknologi Malaysia

Constant wave runup and overtopping during monsoon coupled with storm-surge events have poses threat to the coastal's community in flooding and land loss. The study was to further the research on the wave interaction issue using the modified NAHRIM Coastal Protection and Expansion (NEXC) block. The aim was to determine the significant relationship prediction model from the experiment variables due to water level changes. The study was conducted in 30 m long, 2 m height, and 1.5 m width of wave flume using gamma 3.30 of wave height JONSWAP spectrum under 1:15 and 1:8 mobile bed scenarios. Parameters were downscaled to 1:10 and based on Peninsular Malaysia's east coast hydrodynamics conditions. 36 different test scenarios were simulated every 20 minutes with three repetitions, enables 108 samples to be retrieved. Using statistical tools, correlation tests between the variables in the experiment results indicates wave runup, significant wave height and overtopping discharges are strongly correlated to the bed gradient and smooth-slope NEXC block. Changes in water level from shallow to deep, mild to steep mobile bed gradient with 30 to 60 block affect the relationship Hs-q decrease while Ru2%-q positively increase. Overtopping was not directly affected by water level but positively affected on wave runup and negatively to significant wave height. The fitted relationship design model using a General Full Factorial method was verified with 0.338069 of standard error and 98.12 % of R-square. Finally, the significant relationship predictive model was obtained to have 26 interaction terms in the model successful.