Identifying Coastal Waste Sources Using Drifter Buoy-Based Floating Debris Pathway Analysis at River Outlets on Jeju Island, South Korea

Abstract

This study applied a low-cost and low-power internet of things (IoT)-based drifting buoy to identify the origin characteristics and transport mechanisms of marine litter derived from riverine sources along the coast of Jeju Island, South Korea. The buoys, equipped with a Global Navigation Satellite System positioning module and a cellular modem, were deployed at the estuaries of four rivers on Jeju Island-Cheonmicheon, Geumseongcheon, Hyodoncheon, and Hwabukcheon-during rainfall periods that induce outflows, and their trajectories were analyzed with wind and ocean current data. The experiments demonstrated that buoy trajectories varied according to the discharge direction of each outlet. At Cheonmicheon, buoys drifted offshore toward the east; at Geumseongcheon, they moved southwestward and remained near the harbor; at Hyodoncheon, they stagnated near the outlet, indicating potential local accumulation; and at Hwabukcheon, they were transported eastward and accumulated along the northern shore.The buoy trajectory data from the Cheonmicheon outlet were selected for the trajectory-environment interaction analysis because these data provided the longest records for examining correlations between buoy movement and environmental factors such as wind and currents. Accordingly, the trajectories of buoys that traveled farther offshore at Cheonmicheon were analyzed, and the vector similarity coefficient (VSC) results showed that the buoy movement was more closely aligned with ocean currents (0.501 ± 0.209 and 0.273 ± 0.264) than with wind (-0.487 ± 0.147 and -0.289 ± 0.253), indicating a current-dominant drift tendency. The windage coefficients (0.013 ± 0.002 and 0.014 ± 0.003) further indicated that the influence of wind speed on buoy motion was limited compared to that of ocean currents. These results suggest that marine litter from Jeju Island's rivers exhibits variable transport patterns depending on the influence of ocean currents and wind and that IoT-based drifter buoys provide a practical means of monitoring and understanding coastal marine litter dynamics.

1. Introduction

Marine litter directly affects the survival of marine biota and destroys their habitats, and coastal waste that drifts ashore and accumulates along the coastline degrades the landscape of marine tourist destinations, thereby exerting negative impacts on local communities and economies. The safety of maritime navigation is also threatened by marine litter, increasing the likelihood of vessel accidents, and the collection and disposal of such waste requires substantial financial resources (Ministry of Oceans and Fisheries, 2021). Moreover, marine litter can be transported to neighboring countries, occasionally causing international conflicts (Jwa, 2023). Among various types of marine litter, plastics constitute the largest proportion and persist for long periods once they enter the marine environment. In particular, styrofoam buoys, plastic bottles, vinyl packaging materials, and household products—which account for most plastic debris—are fragmented into microplastics through external factors such as ultraviolet radiation and friction, leading to long-term damage to marine ecosystems (Kershaw, 2016; Seo and Kim, 2019).

Along the coast of Jeju Island, the amount of marine litter collected exceeded 10,000 tons for the first time in 2015, increasing to 18,357 tons in 2020 and 22,082 tons in 2021, showing a steady annual increase. More than half of this litter is reported to originate from land-based sources within Jeju Island, entering the ocean through rivers and drainage channels, while the remainder is presumed to derive from fishing activities or inflows from other regions (Jwa, 2023). Currently, the coastal waste monitoring program in Jeju Island conducts regular surveys at three sites, Sagye-ri, Gimnyeong-ri, and Wimi-ri. As of 2021, a total of 833 items (146.0 kg) were collected at Gimnyeong-ri, 441 items (61.9 kg) at Sagye-ri, and 1,986 items (42.8 kg) at Wimi-ri. Specifically, plastics accounted for the largest proportion of litter at Gimnyeong-ri during the monitoring period, while the number of foreign-origin items at Sagye-ri increased sharply from one in 2019 to 107 in 2021. At Wimi-ri, other materials (1,144 items, 21.9 kg) and glass (427 items, 4.2 kg) were the most frequently collected. These continuous monitoring results indicate that marine litter entering Jeju Island’s coastal waters does not simply drift offshore but tends to accumulate as coastal waste around specific coastal zones and river estuaries (Jwa, 2023).

In South Korea, a comprehensive policy for reducing marine plastics has been established to address marine litter; however, the current measures remain focused on collection and cleanup activities, with limited scientific approaches such as identifying sources or tracking transport pathways (Ministry of Oceans and Fisheries, 2021). Marine litter is globally transported by winds and ocean currents, and previous studies have reported that its deposition patterns in marine and coastal environments vary depending on current directions and seasonal changes (Critchell et al., 2019). Jeju Island, due to its unique geographical and climatic conditions, is one of the regions frequently affected by the inflow and accumulation of marine litter along its coastlines (Gil, 2022). The spatial distribution of litter in Jeju Island is strongly influenced by environmental factors such as ocean current and monsoon directions, as well as local rainfall intensity (Kim et al., 2019; 2022). Furthermore, the flow of ocean currents and precipitation patterns has been altered by climate change, complicating the transport routes of marine litter (Lincoln et al., 2022). Therefore, to accurately identify the sources of coastal waste in Jeju Island and establish effective management strategies, a systematic analysis of litter origins that incorporates climatic and oceanic factors is required.

Numerous studies have been conducted to collect and analyze information on the transport pathways of marine litter through experimental observations. In South Korea, research at the Nakdong River estuary tracked the movement of floating debris during the rainy and typhoon seasons using buoys equipped with Global Navigation Satellite System (GNSS) receivers and satellite communication modules, and analyzed correlations between litter movement, wind direction and speed, and surface currents (Jang et al., 2014). Another study examined the wintertime movement characteristics of foreign-origin marine litter entering the Yellow Sea using satellite-based tracking buoys, comparing their trajectories with tidal and wind data (Kim et al., 2019). Likewise, several studies have explored the transport mechanisms of marine litter using satellite-communication-based drifters, despite their high equipment and operational costs (Ruiz et al., 2022).

Recently, new approaches have been reported that utilize more economical cellular communication networks to observe the movement of marine litter in coastal environments. Merlino et al. (2023) developed open-source microcontroller-based drifter buoys equipped with a GNSS receiver and a low-power cellular communication modem in the Arno River basin, Italy, to record in real time the transport pathways of plastic debris entering the ocean through rivers. This study demonstrated the potential policy applications of such systems, including source identification of floating debris, selection of collection areas, and efficient allocation of resources for monitoring. Similarly, internet of things (IOT) technologies that employ low-cost, low-power, and widely available communication infrastructures have been applied in South Korea to develop maritime IoT platforms for enhancing the efficiency of marine environment monitoring (Song et al., 2021), while another study has utilized Narrowband-IoT (NB-IoT) communication technologies to track shipping containers on vessels navigating coastal waters (Kavuri et al., 2020). These technologies highlight the potential to effectively replace expensive satellite-based communication systems, such as Iridium, for drifter buoys designed to simulate marine litter. In regions such as Jeju Island, where ocean currents, monsoonal winds, and heavy rainfall interact in complex ways, traditional static coastal monitoring limited to predetermined shoreline sites is insufficient to trace debris transport pathways; therefore, low-cost IoT-based drifter buoys provide a promising and effective alternative for such tracking studies.

This study focuses on land-based marine litter transported through rivers, which constitutes a major source of debris entering the coastal waters of Jeju Island (Jwa, 2023). It aims to develop and apply an IoT-based drifter buoy system in Jeju Island, South Korea to identify the sources of riverine (land-based) marine litter and analyze its transport mechanisms in relation to environmental factors such as wind and ocean currents across four rivers selected according to their discharge directions. The development process involved designing the buoy casing and assembling modular components, including an open-source microcontroller, a GNSS receiver for real-time positioning, a multi-network cellular communication module, and a low-power control algorithm enabling periodic data transmission and sleep mode operation. In this process, the study sought to enhance experimental efficiency by adopting a low-cost IoT communication technology utilizing cellular communication networks, thereby complementing the limitations of conventional marine litter monitoring systems that rely on costly satellite-based equipment and services.

2. Materials and Methods

2.1. Study Area

This study was conducted on Jeju Island, located to the south of the Korean Peninsula (Fig. 1). Jeju is an island surrounded by the sea, and its surrounding waters are open to all directions, thereby allowing active water exchange with adjacent seas. Consequently, this region exhibits significant spatiotemporal variations in ocean circulation due to the combined effects of meteorological factors such as wind, as well as tidal and current dynamics (Cha and Moon, 2020). Owing to these climatic and geographical conditions, the inflow and accumulation of marine litter occur frequently around Jeju, and their spatial and temporal distribution patterns tend to be complex (Kim et al., 2019). Most rivers on Jeju Island are short and intermittent, remaining dry under normal weather conditions but producing large amounts of surface runoff during typhoons or monsoon events, which directly transport land-based waste into the ocean (Jwa, 2023). Differences in hydrodynamic conditions around the coastal regions of Jeju Island, including coastal current energy and dominant particle transport directions, have been identified in previous studies using numerical ocean models (Cha and Moon, 2020). Based on these results, it is expected that the transport characteristics of floating debris would also vary among river outlets with different discharge orientations. By selecting outlets that discharge toward the east, west, south, and north, this study aims to analyze how regional variations influence the movement and accumulation of marine litter along different sectors of the island’s coast. Therefore, this study selected four river estuaries representing different discharge directions—Cheonmicheon (eastward discharge), Geumseongcheon (westward discharge), Hyodoncheon (southward discharge), and Hwabukcheon (northward discharge)—as observation sites to investigate the correlation between wind and ocean current factors and the transport pathways of marine litter discharged through river systems.

Fig. 1. The study area is Jeju Island, located to the south of the Korean Peninsula. The outlets of the rivers where the buoys were deployed—Cheonmicheon, Geumseongcheon, Hyodoncheon, and Hwabukcheon—are marked with red dots; rainfall observation sites near the river outlets—Seongsan, Gosan, Seogwipo, and Jeju—are indicated by yellow dots; and coastal marine litter monitoring sites within Jeju Island—Gimnyeong-ri, Sagye-ri, and Wimi-ri—are shown as green dots (background image from Earthstar Geographics).

2.2. Drifter Buoy System for Tracking Marine Litter

A low-cost and low-power IoT-based drifter buoy was developed in this study to track the transport pathways of floating debris (Fig. 2), as the research objective to establish a practical system for monitoring riverine marine litter. The control unit consists of an open-source microcontroller equipped with a GNSS receiver to acquire real-time position data, and the communication module supports multiple mobile network standards, including NB-IoT, LTE-M (Cat-M1), and GPRS (2G). This multi-network compatibility ensures stable data transmission and reception even in offshore environments where communication infrastructure is limited and allows connectivity to various national networks while drifting. The positioning accuracy of the GNSS receiver module is less than 2.5 m (circular error probable, 50%) under open-sky conditions (SIMCom Wireless Solutions Limited, 2021).

Fig. 2. Operating logic of the internet of things (IoT)–based drifter buoy for tracking marine litter.

Power is supplied by a rechargeable lithium-ion battery, and to enhance energy efficiency, the system measures GNSS-based positions at one-hour intervals, which are sufficient to capture the movement of marine litter during long-term monitoring and provide a temporal resolution comparable to that of wind and ocean current observations. The collected data are then transmitted a cloud server, after which the system switches to sleep mode. This low-power operation minimizes energy consumption and enables long-term data collection. When network connectivity becomes unstable at sea, collected data are temporarily stored in internal memory and automatically uploaded to the cloud server once the connection is restored near coastal areas, thereby preventing data loss. This integrated system design effectively addresses communication instability issues in marine environments while ensuring efficient and continuous data acquisition.

2.3. Data Collection of Buoy Trajectories at River Outlets on Jeju Island

To analyze the movement patterns of marine litter discharged from rivers on Jeju Island, four river outlets representing the east, west, south, and north regions—Cheonmicheon, Geumseongcheon, Hyodoncheon, and Hwabukcheon—were selected as buoy deployment sites (Table 1). Most rivers on Considering these characteristics, this study conducted drifting buoy experiments during rainfall periods to observe debris transport under realistic outflow conditions. Two experiments were carried out during the summer rainy season, in July and August, to obtain sufficient trajectory data for each river. The timing of buoy deployment was carefully determined based on the official tidal prediction tables provided by the Korea Hydrographic and Oceanographic Agency (https://www.khoa.go.kr/swtc).

Table 1. Deployment locations, timings, and quantities of buoys released at the river outlets in the eastern, western, southern, and northern regions of Jeju Island

Because the tide gauge stations are not located exactly at the river mouths, representative nearby stations were selected: Seongsanpo for the Cheonmicheon outlet, Moseulpo for the Geumseongcheon outlet, Seogwipo for the Hyodoncheon outlet, and Jeju for the Hwabukcheon outlet. The deployments were conducted during the spring tide period, which coincided with rainfall events, to capture realistic riverine discharge and nearshore mixing conditions. The deployment times were synchronized with the predicted high-water stages at each station: Seongsanpo (July 14, 11:36, 207 cm; August 11, 10:42, 228 cm), Moseulpo (July 13, 11:33, 217 cm; August 10, 10:41, 239 cm), Seogwipo (July 14, 11:39, 251 cm; August 11, 10:46, 275 cm), and Jeju (July 13, 11:51, 231 cm; August 10, 10:59, 246 cm). These conditions represent strong spring-tide phases, ensuring that the buoy trajectories reflected realistic flow conditions influenced by both tidal and rainfall-driven processes. The water depths at each deployment site, obtained from the Ocean Data in Grid Framework of the Korea Hydrographic and Oceanographic Agency (www.khoa.go.kr/oceangrid), were as follows: Cheonmicheon – 0.6 m, Geumseongcheon – 1.4 m, Hyodoncheon – 4.1 m, and Hwabukcheon – 25.7 m, showing a gradual deepening trend toward the offshore direction. After the experiments, daily rainfall data measured at weather observation stations near each river outlet were obtained from the Korea Meteorological Administration (https://www.weather.go.kr/) to verify rainfall intensity (Figs. 3, 4).

Fig. 3. Buoy deployment experiments(red circles). (a) Cheonmicheon (eastern outlet, deployed on August 11, 2025). (b) Geumseongcheon (western outlet, deployed on July 13, 2025). (c) Hyodoncheon (southern outlet, deployed on August 12, 2025). (d) Hwabukcheon (northern outlet, deployed on July 13, 2025), showing examples of buoy release.

Fig. 4. Daily rainfall records observed at weather stations located near the buoy deployment sites from July 1 to August 31, 2025. (a) Seongsan (near the Cheonmicheon outlet). (b) Gosan (near the Geumseongcheon outlet). (c) Seogwipo (near the Hyodoncheon outlet). (d) Jeju (near the Hwabukcheon outlet). The first and second buoy deployment dates are marked by blue dashed lines.

The deployed buoys acquired geographical coordinates and time information from the GNSS receiver and transmitted these data to a cloud server via a cellular communication network. The cloud server was configured to simultaneously store and manage data from multiple buoys, enabling the long-term collection of large datasets without loss. The buoy trajectory data were organized in chronological order and linearized between consecutive points to reconstruct continuous movement paths, from which parameters such as movement direction, distance, and accumulation locations were derived. This process not only enables intuitive interpretation of short-term movement patterns but also helps identify phenomena such as stagnation, recirculation, and offshore dispersion occurring in specific regions.

2.4. Correlation Analysis Between Wind, Ocean Currents, and Buoy Movement

To identify the correlation between buoy trajectories and actual climatic and oceanographic conditions, wind and ocean current data were collected and analyzed (Table 2). For the climatic factors, 6-hourly wind data with a spatial resolution of 0.25° × 0.25°, provided by the NOAA Operational Model Archive and Distribution System (NOMADS) under the National Oceanic and Atmospheric Administration (NOAA) were used to examine the temporal variations of atmospheric fields during the study period. For the oceanographic factors, surface current data with a spatial resolution of 0.083° × 0.083° and a 6-hour temporal interval from the Copernicus Marine Environment Monitoring Service (CMEMS) were obtained to derive current velocity and directional vectors directly comparable to the buoy’s movement direction and speed (Fig. 5). As visualized in Fig. 5, the wind and current grid points are distributed at regular intervals around the coastline, ensuring adequate coastal coverage.

Table 2. Spatial and temporal resolution of wind and ocean current data for comparative analysis with buoy trajectories

Fig. 5. Example visualization of environmental data: (a) wind vectors and (b) ocean current (background images from OpenStreetMap contributors, TomTom, Garmin, FAO, METI/NASA, USGS, and Earthstar Geographics).

Although the temporal resolution of these datasets (6-hour interval) is coarser than the buoy’s 1-hour sampling interval, the analysis utilized the wind and current vectors from the grid points closest to each buoy position at the corresponding timestamps, ensuring spatial correspondence between the environmental factors and the drifter buoy measurements. Since the CMEMS ocean current dataset provides reference information on the physical state, variability, and dynamics of the global ocean and the European regional seas (von Schuckmann et al., 2016), its current data were utilized in this study. These environmental datasets were analyzed together with the buoy trajectories, enabling interpretation of the dispersion and retention mechanisms of riverine-origin debris in relation to the prevailing wind and ocean current conditions.

The analysis quantitatively evaluated the similarity between the movement vectors of wind and ocean currents and those derived from buoy trajectories by calculating the vector similarity coefficient (VSC) using Eq. (1) (Xu et al., 2016).

\(\begin{align}R_{v} \approx \frac{\sum_{i=1}^{N} A_{i} \cdot B_{i}}{\sqrt{\sum_{i=1}^{N}\left|A_{i}\right|^{2}} \sqrt{\sum_{i=1}^{N}\left|B_{i}\right|^{2}}}\end{align}\)       (1)

Here, A_i represents vector of the buoy trajectory at time step i, and B_i denotes vector of the environmental field (wind or ocean current) at the same time step, while N is the total number of time steps or vector pairs used for comparison. The VSC, denoted as R_v, quantifies the directional similarity between two vectors over the entire time series, where values closer to 1 indicate a higher degree of directional agreement.

Since buoy position data were collected at 1-hour intervals, whereas wind and ocean current data were provided at instantaneous values at 6-hour intervals, temporal synchronization of the time series was necessary for the vector similarity analysis. To achieve this, buoy displacement vectors were calculated from positional differences between the 3-hour averaged positions before and after the reference times centered at 03:00, 09:00, 15:00, and 21:00 (UTC+9), and these were considered as the buoy movement vectors corresponding to those reference times. This averaging approach allowed the buoy vectors to represent the displacement trend within each 6-hour time window, while mitigating geolocation errors from GNSS positioning. The buoy vectors at each reference time were then paired with the nearest wind and current vectors for subsequent analysis. The wind and current vectors were extracted from the closest oceanic grid cells corresponding to each buoy position. Although this approach cannot fully capture small-scale coastal processes, it provided the most reliable spatial matching possible between the buoy trajectories and environmental datasets.

In addition, to quantitatively evaluate the relative influence of wind and ocean currents on buoy movement, a windage coefficient (α) analysis was conducted. The windage coefficient is defined as an index that normalizes the difference between the actual drifting velocity of the buoy (\(\begin{align}\overrightarrow{v_{a}}\end{align}\)) and the surrounding current velocity (\(\begin{align}\overrightarrow{v_{s}}\end{align}\)) by the wind velocity (\(\begin{align}\overrightarrow{v_{w}}\end{align}\)), as expressed in Eq. (2). This coefficient represents the relative contribution of wind to the buoy’s movement, where a smaller value indicates a greater dominance of ocean currents, while a larger value implies a stronger influence of wind (Zheng et al., 2025).

\(\begin{align}\alpha=\frac{\left|\overrightarrow{v_{a}}-\overrightarrow{v_{s}}\right|}{\left|\overrightarrow{v_{w}}\right|}\end{align}\)       (2)

The VSC was used to evaluate the directional similarity between the buoy trajectories and the vectors of wind and ocean currents, while the windage coefficient served as a complementary indicator to quantify the relative contribution of wind to the magnitude of the buoy’s drift velocity. Through these procedures, the influence of meteorological and oceanographic conditions on buoy movement characteristics was quantitatively compared across different periods and regions.

3. Results

3.1. Characteristics of Buoy Trajectories at River Outlets on Jeju Island

Drifter buoys were deployed at the discharges of four rivers on Jeju Island—Cheonmicheon, Geumseongcheon, Hyodoncheon, and Hwabukcheon—during the first period (July 13–14, 2025) and the second period (August 10–11, 2025) (Table 1). The resulting buoy trajectories revealed distinct spatial movement patterns among the four river outlets (Fig. 6).

Fig. 6. Buoy trajectories at river outlets on Jeju Island: (a) Cheonmicheon (eastern outlet), (b) Geumseongcheon (western outlet), (c) Hyodoncheon (southern outlet), and (d) Hwabukcheon (northern outlet).The buoy deployment sites are indicated by blue dots(background images from Esri, Maxar, Earthstar Geographics, Vantor, and the GIS User Community).

At the Cheonmicheon (eastern outlet), two buoys were deployed during the first observation period, recording movement distances of 18.34 km over approximately 19 hours (965 m/h) and 73.99 23.3 km over 53 hours (1,396 m/h), respectively (Fig. 6a). Although both buoys were released at the same time, their early trajectories exhibited different movement patterns: buoy 1-1 drifted offshore for about nine hours before data transmission stopped, whereas buoy 1-2 initially moved northward and then extended eastward after approximately 12 hours. During the second period, one buoy was deployed and drifted 137.78 km over approximately 140 hours (984 m/h). In all cases, the buoys exhibited an offshore-drifting tendency, forming long eastward trajectories, suggesting that Cheonmicheon is a location with a high potential for offshore transport of riverine debris.

At the Geumseongcheon (western outlet), two buoys were deployed during the first observation period, recording movement distances of 0.38 km (39.53 m/h) and 5.46 km (58.5 m/h), respectively (Fig. 6b), trajectories 1-1 and 1-2). The two buoys exhibited distinct movement patterns: buoy 1-1 drifted inland along the river channel, whereas buoy 1-2 moved westward along the coastline. During the second period, the buoy deployed at Geumseongcheon traveled a total distance of 0.80 km over approximately 1 hour, with an average velocity of 800 m/h (Fig. 6b, trajectory 2-1). Although relatively rapid short-term movement was observed, the buoy ultimately tended to remain near the western coastal area.

At the Hyodoncheon (southern outlet), the buoys consistently exhibited stagnation near the outlet throughout both observation periods, showing no significant offshore movement (Fig. 6c). During the first period, two buoys were deployed, drifting only 62.8 m and 61.3 m, respectively. Similarly, in the second period, two buoys were deployed, and their movement distances were also very short—34.9 m and 8.4 m. Overall, the buoys repeatedly remained within a confined area near the outlet without any apparent offshore drift. These results suggest that debris discharged from the Hyodoncheon outlet during the summer rainfall season is likely to remain within the nearshore zone for extended periods, contributing to the accumulation of coastal debris.

At the Hwabukcheon (northern outlet), buoy movement was largely confined to the coastal area near the outlet during both observation periods, with no distinct tendency for offshore dispersion (Fig. 6d). During the first period, one buoy drifted eastward for approximately 0.87 km over 12 hours (72.5 m/h) before remaining within the estuary area (Fig. 6d, trajectory 1-1). In the second period, two buoys were deployed, recording eastward movements of 6.29 km (1,048.33 m/h) and 5.28 km (660.20 m/h), respectively; however, both trajectories followed a refracted path along the coastline (Fig. 6d), trajectories 2-1 and 2-2. Therefore, the Hwabukcheon outlet can be characterized as a region where debris tends to drift eastward along the nearshore zone and accumulate along the northern coastline of Jeju Island, rather than being transported offshore.

As a result, among the river outlets along the coast of Jeju Island, floating debris discharged from the Cheonmicheon outlet on the eastern side was classified as exhibiting an offshore-dispersing pattern, whereas debris released from the Geumseongcheon, Hyodoncheon, and Hwabukcheon outlets tended to remain near the outlet or along the coastal zone. These results demonstrate distinct spatial variations in debris transport and accumulation among the river outlets around Jeju Island. Although bathymetric data for each river outlet were not available, the drifter buoys floated at the sea surface, and thus subsurface depth variations were assumed to have minimal influence on their trajectories.

3.2. Results of the Correlation Analysis Between Wind, Ocean Currents, and Buoy Trajectories

The buoy trajectory data from the Cheonmicheon outlet were selected for the trajectory–environment interaction analysis, as they provided the longest continuous records for examining correlations between buoy movement and environmental factors such as wind and currents. Among these, buoys 1-2 and 2-1 exhibited the most extended continuous trajectories (Fig. 6a), which were used for the correlation analysis. The buoys released at the Cheonmicheon outlet during the first deployment period tended to move offshore, exhibiting a VSC pattern that was strongly aligned with the current direction. The average VSC value between the current and buoy vectors was calculated as 0.501 ± 0.209 (Fig. 7a), whereas the average VSC between current and wind vectors was –0.487±0.147. These results quantitatively confirm that ocean currents acted as the dominant external force influencing buoy movement during the first period.

Fig. 7. Time-series analysis of the vector similarity coefficient (VSC) between the buoys deployed at the Cheonmicheon outlet and the wind and current vectors: (a) first deployment period (July 2025) and (b) second deployment period (August 2025). Blue points indicate the VSC between the buoys and the wind, while red points represent the VSC between the buoys and the currents.

In the second buoy deployment at the Cheonmicheon outlet in August 2025, partial movement of the buoys was observed along the northeastern coast of Jeju Island (Fig. 6a). The VSC between the buoy trajectories and the ocean currents was 0.273 ± 0.264 (Fig. 7b), while the average VSC between the current and wind vectors was –0.289 ± 0.253. These VSC values indicate that although currents generally remained the dominant factor influencing buoy movement, this pattern was not consistent throughout the entire observation period.

Specifically, at 21:00 on August 13 and 09:00 on August 14, the VSC between the buoy and wind vectors exceeded that between the buoy and current vectors. To determine whether this was due to unusually strong winds or weak currents, the corresponding environmental data were examined. At 21:00 on August 13, the wind speed was approximately 20.00 m/s and the current speed was 0.25 m/s, with correlation coefficients of –0.970 for the current and 0.978 for the wind. At 09:00 on August 14, the wind speed was 23.69 m/s, and the current speed was 0.34 m/s; their respective correlation coefficients were –0.695 and 0.912. These values were not significantly different from those at other times (wind speed 23.45 ± 0.79 m/s, current speed 0.18 ± 0.02 m/s) during the observation period. Thus, the temporary dominance of wind influence appears to be due to directional alignment rather than exceptional magnitude.

To intuitively compare the relative magnitudes and directional alignments of the buoy, current, and wind vectors at each time step, a visualization was performed to reveal how closely the buoy trajectories corresponded to either currents or wind (Fig. 8). In the case of July 15 at 15:00, when the VSC between the buoy and the current was negative, the buoy vector was more closely aligned with the wind vector than with the current vector (Fig. 8a). Similarly, at 21:00 on August 13 and 09:00 on August 14, the buoy trajectories also showed greater directional similarity with the wind.

Fig. 8. Comparison of the directions and velocities of the buoy, ocean current, and wind vectors at the Cheonmicheon outlet: red vectors indicate the buoy, blue vectors indicate the ocean current, and black vectors indicate the wind. (a) shows the observations from the first deployment period in July 2025, and (b) shows those from the second deployment period in August 2025.

In addition, an integrated analysis of the data obtained from the first (July) and second (August) buoy deployment experiments at the Cheonmicheon outlet revealed that the calculated maximum windage coefficient was 0.027, indicating that the contribution of wind to the buoy’s movement speed was very limited (Table 3). This suggests that even when the absolute wind velocity exceeded the current velocity, the wind’s relative influence on the actual buoy movement remained minimal. During July, the VSC between the buoy and ocean current was 0.501 ± 0.209, and the α value was 0.012 ± 0.002, supporting the conclusion that ocean currents served as the primary driving force behind the buoy trajectories, while wind acted only as a secondary factor. Similarly, during August, the α value remained small at 0.014 ± 0.003. Even during specific time periods such as 21:00 on August 13 and 09:00 on August 14—when the VSC between the buoy and wind exceeded that between the buoy and current—the consistently low α values demonstrate that although the buoy directionally aligned with the wind, the actual velocity contribution from the wind was limited.

Table 3. Calculated windage coefficient values for each observation time during the buoy tracking experiments at the Cheonmicheon outlet in July and August 2025

4. Discussion

Based on the buoy tracking experiments conducted at the four river outlets on Jeju Island—Cheonmicheon, Geumseongcheon, Hyodoncheon, and Hwabukcheon—the movement characteristics of buoys simulating floating debris were identified. At the Cheonmicheon (eastern outlet), the buoys traveled long distances offshore immediately after leaving the outlet, indicating that land-based floating debris discharged from the eastern rivers of Jeju Island can rapidly move beyond the coastal zone into the open sea (Fig. 6a). In contrast, at the Geumseongcheon (western outlet), the floating debris dispersed along the coastline and ultimately remained near the western shore (Fig. 6b). At the Hyodoncheon (southern outlet), the buoys stagnated near the outlet, showing a clear tendency for local accumulation of floating debris (Fig. 6c), while at the Hwabukcheon (northern outlet), the movement was limited by harbor structures and complex coastal topography, resulting in debris accumulation along the northern coast (Fig. 6d). Overall, offshore dispersion of floating debris in the coastal waters of Jeju Island was observed mainly in the eastern region, whereas most debris tended to remain and accumulate along the island’s coastal zones.

Although the experimental sites in this study differ spatially from the regular coastal debris monitoring sites in Jeju (Gimnyeong-ri, Sagye-ri, and Wimi-ri), the two datasets can be interpreted in a complementary manner. The buoys deployed at the Geumseongcheon outlet tended to move southwestward along the western coast toward Sagye-ri, which corresponds to the long-term accumulation pattern of plastic debris observed at the Sagye-ri shoreline. Meanwhile, the Hyodoncheon outlet is geographically close to the Wimi-ri coast, one of the plastic debris monitoring sites, suggesting that this area is also likely to be influenced by similar nearshore environmental conditions.

This implies that the observed stagnation of buoys near the coast may directly contribute to coastal debris accumulation. In addition, the buoys released from the Hwabukcheon outlet tended to move eastward along the coast toward Gimnyeong-ri, consistent with the long-term accumulation patterns of plastic debris recorded there. These results indicate that land-based floating debris discharged into Jeju’s coastal waters tends to accumulate along the shoreline rather than disperse offshore. In contrast, the offshore-dispersing tendency observed at the Cheonmicheon outlet suggests the potential for floating debris from Jeju’s eastern rivers to be transported beyond the island’s coastal zone into the open sea.

The correlation between buoy trajectories and environmental factors showed varying patterns depending on observation time and site-specific meteorological and oceanic conditions. While a strong similarity with ocean currents was observed during most periods, buoy trajectories were occasionally more closely aligned with the wind direction (Figs. 7, 8). This trend indicates that the behavior of surface-floating objects is not governed by a single factor but rather responds to multiple external forces that vary across time and space. The results that ocean currents act as the primary factor determining buoy movement are consistent with previous studies. Rohrs et al. (2012) reported that ocean currents have a major influence on drifter trajectories, and similarly, in this study, the buoy trajectories exhibited high VSC values with currents, although certain time points showed higher wind VSC values. Delpeche-Ellmann et al. (2021) also identified numerous cases in the Gulf of Finland where drifter trajectories were almost identical to wind directions, suggesting that situations exist in which wind can dominate the motion of surface drifters. Indeed, Krauss et al. (1989) demonstrated that undrogued buoys can respond sensitively to wind effects and that applying such data to current analysis without accounting for wind influence may be inappropriate, even under weak wind conditions.

The windage coefficient analysis further supports this interpretation. The calculated windage coefficient values were generally 0.012 ± 0.002 during the first buoy deployment at the Cheonmicheon outlet and 0.014 ± 0.003 during the second deployment, with the maximum value reaching only about 0.027 (Table 3). This indicates that although the absolute wind velocity was higher than that of the current, its actual contribution to buoy movement was relatively limited. For instance, at 21:00 on August 13 and 09:00 on August 14, the wind direction was aligned with the buoy movement direction; however, the corresponding windage coefficients were only 0.027 and 0.022, respectively, quantitatively confirming that the wind’s contribution to the buoy velocity vector was minor. Therefore, these results suggest that while ocean currents generally act as the dominant driving force governing the movement of marine litter along Jeju Island’s coast, there are periods when a temporary increase in the windage coefficient can lead to a relatively greater contribution from wind.

In line with the stated objective of developing and applying the system, this study demonstrated the potential of the IoT-based drifter buoy system, which offers advantages such as low cost, low power consumption, and modular design. However, its use is limited to tracking the movement of floating debris, meaning the results may not reflect the transport patterns of submerged or beached debris. In addition, differences in spatial and temporal resolution and the complexity of coastal environments may have caused discrepancies between environmental datasets and actual buoy observations. Despite these limitations, the system’s real-time data transmission capability and flexible design make it suitable for broader applications, including marine litter monitoring, coastal management, and other environmental observation tasks.

This study primarily investigated the influence of wind and ocean surface currents on the movement of surface-floating debris; however, additional environmental factors such as tidal currents, tidal height, and wave action may also play significant roles in shaping debris trajectories, particularly in nearshore regions. The potential effects of tides and wave dynamics are recognized as critical components to be incorporated in future research to achieve a more comprehensive understanding of how wind, currents, tides, and waves collectively govern debris transport processes. Future research should incorporate additional environmental parameters such as wave conditions, tides, and bathymetry to provide a more comprehensive understanding of marine litter movement and accumulation patterns.

5. Conclusions

This study conducted IoT-based drifter buoy experiments at four river outlets on Jeju Island to analyze the transport characteristics of marine litter. The results showed spatial contrasts: buoys at Cheonmicheon (eastern outlet) dispersed offshore, while those at Geumseongcheon, Hyodoncheon, and Hwabukcheon generally remained near the coast, indicating that a large proportion of land-based debris from Jeju Island’s rivers tends to accumulate along coastal areas rather than disperse into the open sea.

The correlation analysis between buoy trajectories from Cheonmicheon and environmental factors demonstrated that ocean currents were the primary driving force of buoy movement. High VSC values between the current and buoy vectors confirmed a strong directional correlation, while temporary increases in wind–buoy VSC values indicated short intervals during which wind direction influenced buoy motion. Quantitative evaluation using the windage coefficient showed values of 0.012 ± 0.002 and 0.014 ± 0.003 during the first and second deployments, respectively, with a maximum of 0.027—verifying that the wind’s contribution to buoy velocity was limited even when wind speed exceeded that of the current. These results emphasize that while currents primarily determine the magnitude of motion, wind can momentarily affect the direction of floating debris. Consequently, the combined use of VSC and windage coefficients provides a complementary framework for distinguishing the relative roles of wind and ocean currents in marine litter transport around Jeju Island.

Author Contributions

Conceptualization: Hyun CU; Data curation, Formal analysis: All authors; Funding acquisition: Kang M; Investigation, Methodology: All authors; Project administration: Kang M, Hyun CU; Resources: All authors; Software: Kang M, Park J, Hyun CU; Supervision: Hyun CU; Validation: Kang M, Hyun CU; Visualization: Kang M, Park J, Hyun CU; Writing–original draft: Kang M, Park J, Hyun CU; Writing–review & editing: Kang M, Park J, Hyun CU.

Conflicts of Interest

No potential conflict of interest relevant to this article was reported.

Funding

This work was supported by the Korea Foundation for Women in Science, Engineering, and Technology (WISET) grant, funded by the Ministry of Science and ICT (MSIT) under the Team Research Program for Female Engineering Students (WISET-2025-145).

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.