2023 Volume 79 Issue 18 Article ID: 23-18175
In the Kyushu region, drifted debris released into the sea by heavy rains adversely affects the environment, fisheries, and coastal conservation facilities of the sea. The deposited driftwoods destroy the rich ecosystem, and fishing boats may not be able to go fishing due to concerns about collisions with driftwoods. The driftwoods drifting on the coast hinder the function of wave-dissipating blocks and may cause flowing into the land due to high waves. The Kyushu Regional Development Bureau recovers driftwoods using vessels relying on sightings. However, the collection is taking an enormous amount of time.
Therefore, in this study, we developed a driftwood drift prediction model to improve the efficiency of collecting driftwood. The driftwood drift prediction model is based on a particle tracking model that tracks the movement of water particles in Finite-Volume Community Ocean Model version 3.2, which is the unstructured-grid model. The unstructured mesh allows the model to reproduce the topography in detail. Additionally, the model is improved by adding buoyancy, wind drag, landfall, and surfacing to the water particle motion to predict driftwood drift in the study. Moreover, the model has been made more sophisticated with the addition of inverse analysis and external data loading functions for improvement of computational speed.
The simulation for the period of heavy rains in July 2020 and Typhoon Nanmadol in 2022 was conducted. As a result, we were able to explain the collection records in general, and estimated the origin rivers and drift paths of driftwood that drifted to each recovery site in both the heavy rain events. The results of the inverse analysis revealed that the driftwood washed ashore in Isahaya Bay after the July 2020 torrential rainfall was most likely discharged from the second-class rivers located in the bay and in the southern part of the bay.
