Characteristics of Wind Distribution in the Doyo-deung Barrier Islands off the Coast of the Nakdong River Estuary based on Marine Environmental Information System–Automatic Weather Station Data, Busan, South Korea

Abstract

In this study, we developed a Nakdong- marine environmental information system (N-MEIS) using automatic weather station (AWS) data to elucidate the characteristics of wind distribution and land/sea breezes in the Doyo-deung barrier islands located in the brackish water zone off the coast of the Nakdong River Estuary (NRE), Busan, South Korea. From May 2015 to the present day, the N-MEIS was run in real-time with sampling intervals of 10 second using long-term evolution communication, an operation rate of approximately 98% in AWS, and periodic marine observations recorded 1–4 times per year. From April 2016 to October 2019, the average annual wind speed in the Doyo-deung barrier islands was 3.8 m/s (range, 2.11–5.1 m/s) and the maximum wind speed, recorded in February 2019, was 46.8 m/s. These values are usually influenced by lowpressure blasts or instantaneous wind speed. However, the maximum monthly mean velocity is also influenced by typhoons occurring in early autumn from August to September. Based on the percentages of wind directions recorded, the prevailing winds blow in ESE’ly and SSW’ly directions. The distribution of wind directions in summer was similar to that in spring, and the distribution in autumn tended to be similar to that in winter. The mean wind velocities at Yeongdo and Gadeokdo islands approximately 9–12 km west, were two times higher than those at Haeundae beach approximately over 20 km east of the study area. Research on the dynamic wind distribution is necessary to manage erosion and sedimentation around the barrier islands, beach pollution from floating materials transported overland, coastal sand dune activity, changes in migratory bird habitats, and impacts on ecosystem health more effectively. The evolution and developments of the N-MEIS facilitates this process understand. Further studies should integrate real-time/periodic marine observations and predictions with environmental sensitivity index (ESI) maps.