Advancements in Shoreline Variation Prediction Considering Mixed Grain Sizes

Abstract

Shoreline variations occurring in sea areas are caused by the combined effect of sediment transport due to the inflow and outflow of sediment caused by waves at the left and right boundaries of the sea area and the depth of movement limit. Although many studies have been conducted to understand the characteristics of sediment transport, assessment on valid sediment run-off supplied to the sea area from mountains and rivers in sea areas with river inflow and research on the sediment budget analysis considering the topographical characteristics of South Korean sea areas are insufficient. Therefore, the establishing mitigation measures considering comprehensive viewpoints is necessary to systematically respond to various natural and anthropogenic causes. Moreover, further research related to the setting and analysis of major parameters must be conducted for improving the prediction performance as well as the evaluation system for analyzing the sediment budget, which is a quantitative evaluation index for coastline management optimized for domestic waters. This study aimed to establish a comprehensive analysis system for analyzing the sediment run-off generated in domestic sea areas and develop a shoreline model (In-MPaS model) considering mixed grain sizes for advancing sediment run-off analysis. With the observation data, the parameters necessary for the numerical analysis were set, the sensitivity of the In-MPaS model according to the particle size distribution of the sediment constituting the sea area was evaluated, and the major parameters for improving the prediction performance were analyzed. Consequently, it was found that the prediction performance of the In-MPaS model improved in terms of valid sediment run-off as well as the sediments constituting the sea area (which was assumed to have mixed grain sizes rather than a single grain size(<i>D</i>₅₀). In particular, considering the topographical properties that regulate sediment transport due to the island (Deokbong Mountain) at the foreside of the river mouth bar, the shoreline prediction performance was significantly improved with the application of groins, which exhibit structurally similar performance.