• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1043-1060
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• 2023

An acceleration of climate change in recent years has led to increased attention towards 'blue carbon' which refers to the carbon captured by the ocean. However, our comprehension of marine ecosystems is still incomplete. This study classified and analyzed global marine eco-provinces using k-means clustering considering carbon cycling. We utilized five input variables during the past 20 years (2001-2020): Carbon-based Productivity Model (CbPM) Net Primary Production (NPP), particulate inorganic and organic carbon (PIC and POC), sea surface salinity (SSS), and sea surface temperature (SST). A total of nine eco-provinces were classified through an optimization process, and the spatial distribution and environmental characteristics of each province were analyzed. Among them, five provinces showed characteristics of open oceans, while four provinces reflected characteristics of coastal and high-latitude regions. Furthermore, a qualitative comparison was conducted with previous studies regarding marine ecological zones to provide a detailed analysis of the features of nine eco-provinces considering carbon cycling. Finally, we examined the changes in nine eco-provinces for four periods in the past (2001-2005, 2006-2010, 2011-2015, and 2016-2020). Rapid changes in coastal ecosystems were observed, and especially, significant decreases in the eco-provinces having higher productivity by large freshwater inflow were identified. Our findings can serve as valuable reference material for marine ecosystem classification and coastal management, with consideration of carbon cycling and ongoing climate changes. The findings can also be employed in the development of guidelines for the systematic management of vulnerable coastal regions to climate change.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.2
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• pp.68-81
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• 2006

As one of the on-going projects to investigate the biogeochemical characteristics of tidal flat, we develop seasonal mass balance calculations (or DIP, DIN and DON in Gomso Bay. We have obtained 13-hours time-series data of salinity, tidal current, nutrients, and chlorophyll-a of seawater for spring, dry summer, rainy summer and winter during $1999{\sim}2000$. DIP of $-1.10{\times}10^6g\;P\;day^{-1},\;-4.50{\times}10^5g\;P\;day^{-1}$ was out-fluxed from the bay to the bay proper for spring and dry summer, respectively. Whereas $1.06{\times}10^4g\;P\;day^{-1}$ of net influx of DIP was found during winter and $2.72{\times}10^6g\;P\;day^{-1}$ of net influx was also found during the rainy summer. Therefore we suggest the role of Gomso tidal flat as a source of DIP fur the seasons of spring and summer, but as an opposite role during the rainy summer and winter but much smaller in magnitude. Except winter, the advection process by tidal current is found the most dominant flux among the diverse fluxes of DIP in the bay. Whereas ground water is estimated as the strongest flux of TDN except winter. TDN of $1.38{\times}10^7g\;N\;day^{-1},\;2.45{\times}10^6g\;N\;day^{-1},\;and\;4.65{\times}10^7g\;N\;day^{-1}$ was in-fluxed to the bay from the bay proper far spring, rainy summer and summer, respectively. Only $-1.70{\times}10^7g\;N\;day^{-1}$ of net out-flux was found during the winter. Therefore we suggest the role of Gomso tidal flat as a sink of TDN far the year round except winter.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.13 no.1
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• pp.1-14
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• 2008

Eight comprehensive oceanographic cruises on a squared $30{\times}30\;km$ area have been made to investigate the short and long-term impacts on the water qualities due to the sand mining operations at Exclusive Economic Zone (EEZ) in the central Yellow Sea from 2004 to 2007. The area was categorized to 'Sand Mining Zone', 'Potentially Affected Zone', and 'Reference Zone'. The investigation covered suspended solids, nutrients (nitrate, nitrite, ammonium, phosphate), and chlorophyll-a in seawater and several parameters such as water temperature, salinity, pH, and ORP. Additionally, several intensive water collections were made to trace the suspended solids and other parameters along the turbid water by sand mining activities. The comprehensive investigation showed that suspended solids, nitrate, chlorophyll-a and ORP be sensitively responding parameters of seawater by sand mining operations. The intensive collection of seawater near the sand mining operation revealed that each parameter show different distribution pattern: suspended solids showed an oval-shaped distribution of the north-south direction of 8 km wide and the east-west direction of 5 km wide at the surface and bottom layers. On the other hand, phosphate showed so narrow distribution not to traceable. Also ammonium showed a limited distribution, but its boundary was connected to the high nitrate and chlorophyll-a concentrations with high N/P ratios. From the last 4 years of the comprehensive and intensive investigations, we found that suspended solids, ammonium, nitrate, chlorophyll-a, and ORP revealed the sensitive parameters of water quality for tracing the sand mining operations in seawater. Especially suspended solids and ORP would be useful tracers for monitoring the water qualities of remote area like EEZ in Yellow Sea.

• Journal of Service Research and Studies
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• v.14 no.2
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• pp.1-17
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• 2024

One of the most important decisions for managers in the online banner advertising industry, is to choose the best banner alternative for exposure to customers. Since it is difficult to know the click probability of each banner alternative in advance, managers must experiment with multiple alternatives, estimate the click probability of each alternative based on customer clicks, and find the optimal alternative. In this reinforcement learning process, the main decision problem is to find the optimal balance between the level of exploitation strategy that utilizes the accumulated estimated click probability information and exploration strategy that tries new alternatives to find potentially better options. In this study we analyze the impact of word-of-mouth effects and the number of alternatives on the optimal exploration-exploitation strategies. More specifically, we focus on the word-of-mouth effect, where the click-through rate of the banner increases as customers promote the related product to those around them after clicking the exposed banner, and add it to the overall reinforcement learning process. We analyze our problem by employing the Multi-Armed Bandit model, and the analysis results show that the larger the word-of-mouth effect and the fewer the number of banner alternatives, the higher the optimal exploration level of advertising reinforcement learning. We find that as the probability of customers clicking on the banner increases due to the word-of-mouth effect, the value of the previously accumulated estimated click-through rate knowledge decreases, and therefore the value of exploring new alternatives increases. Additionally, when the number of advertising alternatives is small, a larger increase in the optimal exploration level was observed as the magnitude of the word-of-mouth effect increased. This study provides meaningful academic and managerial implications at a time when online word-of-mouth and its impact on society and business is becoming more important.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.13-19
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• 2024

An analysis of the coastal water temperature in the Tongyeong waters, the eastern sea of the South Sea of Korea, revealed that the water temperature rose sharply before the typhoon made landfall. The water temperature rise occurred throughout the entire water column. An analysis of the sea surface temperature data observed by NOAA(National Oceanic and Atmospheric Administration) satellites, indicated that sea water with a temperature of 30℃ existed in the eastern waters of the eastern South Sea of Korea before the typhoon landed. The southeastern sea of Korea is an area where ocean currents prevail from west to east owing to the Tsushima Warm Current. However, an analysis of the satellite data showed that seawater at 30℃ moved from east to west, indicating that it was affected by the Ekman transport caused by the typhoon before landing. In addition, because the eastern waters of the South Sea are not as deep as those of the East Sea, the water temperature of the entire water layer may remain constant owing to vertical mixing caused by the wind. Because the rise in water temperature in each water layer occurred on the same day, the rise in the bottom water temperature can be considered as owing to vertical mixing. Indeed, the southeastern sea of Korea is a sea area where the water temperature can rise rapidly depending on the direction of approach of the typhoon and the location of high temperature formation.

• Journal of the Korean earth science society
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• v.45 no.1
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• pp.1-18
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• 2024

This study analyzed the effect of warming on PM_2.5 aerosol production in mid-latitude East Asia during June 2020 using PM_2.5 aerosol anomalies, which were identified by incorporating meteorological and climate data into the Weather Research Forecasting model coupled with Chemistry (WRF-Chem) model. The decadal temperature change trend over a 30-year period (1991-2020) in East Asia showed that recent warming has been greater in summer than in winter. Summer warming in East Asia generated low and high pressure in the lower and upper troposphere, respectively, over China. The boundary between the lower tropospheric low and upper tropospheric high pressure sloped along the terrain from the Tibetan Plateau to Korea. The eastern China, Yellow Sea, and Korean regions experienced a convergence of warm and humid southwesterly airflows originating from the East China Sea with the development of a northwesterly Pacific high pressure. In June 2020, the highest temperatures were observed since 1973 in Korea. Meanwhile, enhanced warming in East Asia increased the production of PM_2.5 aerosols that travelled long distances from eastern China to Korea. PM_2.5 anomalies, which were derived solely by inputting meteorological and climatic data (1991-2020) into the WRF-Chem model and excluding emission variations, showed a positive distribution extending from eastern China to South Korea across the Yellow Sea as well as over the Pacific Northwest. Thus, the contribution of warming to PM_2.5 aerosols in East Asia during June 2020 was more than 50%. In particular, PM_2.5 aerosols were transported from eastern China to Korea through the Yellow Sea, where the warm and humid southwesterly airflows implied wet scavenging of sulfate but promoted nitrate production.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.

• Journal of the Korean earth science society
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• v.45 no.3
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• pp.203-213
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• 2024

This study aimed to investigate the seasonal patterns of multiple bar formation in summer and flattening in winter on the macrotidal Sinduri beach in Taean, and to understand the processes their formation and subsequent flattening. Beach profiling has been conducted regularly over the last four years using a VRS-GPS system. Surface sediment samples were collected seasonally along the transectline, and grain size analyses were performed. Tidal current data were acquired using a TIDOS current observation system during both winter and summer. The Sinduri macrotidal beach consists of two geomorphic units: an upper high-gradient beach face and a lower gentler sloped intertidal zone. High berms and beach cusps did not develop on this beach face. The approximately 400-m-wide intertidal zone comprises distinct 2-5 lines of multiple bars. Mean grain sizes of sand bars range from 2.0 to 2.75 phi, corresponding to fine sands. Mean sizes show shoreward coarsening trend. Regular beach-profiling survey revealed that the summer profile has a multi-barred morphology with a maximum of five bar lines, whereas, the winter profile has a non-barred, flat morphology. The non-barred winter profiles likely result from flattening by scour-and-fill processes during winter. The growth of multiple bars in summer is interpreted to be formed by a break-point mechanism associated with moderate waves and the translation of tide levels, rather than the standing wave hypothesis, which is stationary at high tide. The break-point hypothesis for multi-bars is supported by the presence of the largest bar at mean sea-level, shorter bar spacing toward the shore, irregular bar spacing, strong asymmetry of bars, and the 10-30 m shoreward migration of multi-bars.

• Journal of Korea Water Resources Association
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• v.57 no.8
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• pp.509-518
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• 2024

Flash drought is a rapid-onset drought that occurs rapidly over a short period due to abrupt changes in meteorological and environmental factors. In this study, we utilized satellite-based soil moisture product from the Advanced Microwave Scanning Radiometer-2(AMSR2) ascending X-band to calculate the weekly Flash Drought Intensity Index (FDII). We also analyzed the characteristics of flash droughts on the Korean Peninsula over a 10-year period from 2013 to 2022. The analysis of monthly spatial distribution patterns of the irrigation period across the Korean Peninsula revealed significant variations. In North Korea (NK), a substantial increase in the rate of intensification (FD_INT) was observed due to the rapid depletion of soil moisture, whereas South Korea (SK) experienced a significant increase in drought severity (DRO_SEV). Additionally, regional time series analysis revealed that both FD_INT and DRO_SEV were significantly high in the Gangwon province of both NK and SK. The estimation of probability density by region revealed a clear difference in FD_INT between NK and SK, with SK showing a higher probability of severe drought occurrence primarily due to the high values of DRO_SEV. As a result, it is inferred that the occurrence frequency and damage of flash droughts in NK are higher than those in SK, as indicated by the higher density of large FDII values in the NK region. We analyzed the correlation between DRO_SEV and the Evaporative Stress Index (ESI) across the Korean Peninsula and confirmed a positive correlation ranging from 0.4 to 0.6. It is concluded that analyzing overall drought conditions through the average drought severity holds high utility. These findings are expected to contribute to understanding the characteristics of flash droughts on the Korean Peninsula and formulating post-event response plans.