【摘 要】
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Wave overtopping at a sea dike was observed using video images during a storm in July 2018 at Rizhao Coast,China.A shore-based video monitoring system was mounted to collect coastal images with a sample frequency of 1 Hz in the beginning 10 min of each ho
【机 构】
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State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering,Hohai University,Nanjing
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Wave overtopping at a sea dike was observed using video images during a storm in July 2018 at Rizhao Coast,China.A shore-based video monitoring system was mounted to collect coastal images with a sample frequency of 1 Hz in the beginning 10 min of each hour during daylight.A method to extract the frequency,location,width and duration of individual overtopping events based on the shore-based video monitoring system was developed.A total of 6252 individual overtopping events were detected over a 360m long sea dike during the storm of 10 h in a safe and labor-saving way,enabling a detailed analysis of the temporal and spatial variation of wave overtopping.The temporal variation of overtopping duration,frequency and volume is basically in sync with the change of tidal level (R =0.87,0.82 and 0.76,respectively).The increase of wave height increases the overtopping frequency significantly.We found a high correlation between the hourly observed data and the predicted results of two commonly used formulae.Unlike the previous field measurements of overtopping that were limited in a single location,significant spatial variation of overtopping in the alongshore direction is found.The overtopping volume varies with a factor of 6 within the range of several wave lengths.It is further revealed that the spatial variation of overtopping is highly correlated with the alongshore variation of surf zone width with a correlation coefficient of 0.895.The present study suggests the feasibility of shore-based video monitoring technique to capture the main features of wave overtopping at coastal dikes,providing new possibilities to monitor wave overtopping in the field and to improve prediction tools.
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