• Journal of Korea Water Resources Association
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• v.56 no.2
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• pp.75-89
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• 2023

As the Mekong River basin is a nationally shared river, it is difficult to collect precipitation data, and the quantitative and qualitative quality of the data sets differs from country to country, which may increase the uncertainty of hydrological analysis results. Recently, with the development of remote sensing technology, it has become easier to obtain grid-based precipitation products(GPPs), and various hydrological analysis studies have been conducted in unmeasured or large watersheds using GPPs. In this study, rainfall-runoff simulation in the Mekong River basin was conducted using the SWAT model, which is a quasi-distribution model with three satellite GPPs (TRMM, GSMaP, PERSIANN-CDR) and two GPPs (APHRODITE, GPCC). Four water level stations, Luang Prabang, Pakse, Stung Treng, and Kratie, which are major outlets of the main Mekong River, were selected, and the parameters of the SWAT model were calibrated using APHRODITE as an observation value for the period from 2001 to 2011 and runoff simulations were verified for the period form 2012 to 2013. In addition, using the ConvAE, a convolutional neural network model, spatio-temporal correction of original satellite precipitation products was performed, and rainfall-runoff performances were compared before and after correction of satellite precipitation products. The original satellite precipitation products and GPCC showed a quantitatively under- or over-estimated or spatially very different pattern compared to APHPRODITE, whereas, in the case of satellite precipitation prodcuts corrected using ConvAE, spatial correlation was dramatically improved. In the case of runoff simulation, the runoff simulation results using the satellite precipitation products corrected by ConvAE for all the outlets have significantly improved accuracy than the runoff results using original satellite precipitation products. Therefore, the bias correction technique using the ConvAE technique presented in this study can be applied in various hydrological analysis for large watersheds where rain guage network is not dense.

• Korean Journal of Environmental Biology
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• v.41 no.1
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• pp.18-30
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• 2023

Forest destruction is an inevitable result of the development processes. According to the environmental impact assessment, over 10% of the destroyed trees need to be recycled and transplanted to minimize the impact of forest destruction. However, the rate of successful transplantation is low, leading to a high rate of tree death. This is attributable to a lack of consideration for environmental factors when choosing a temporary site for transplantation and inadequate management. To monitor transplanted trees, a field survey is essential; however, the spatio-temporal aspect is limited. This study evaluated the applicability of remote sensing for the effective monitoring of transplanted trees. Vegetation indices based on satellite remote sensing were derived to detect time-series changes in the status of the transplanted trees at three temporary transplantation sites. The mortality rate and vitality of transplanted trees before and after the transplant have a similar tendency to the changes in the vegetation indicators. The findings of this study showed that vegetation indices increased after transplantation of trees and decreased as the death rate increased and vitality decreased over time. This study presents a method for assessing newly transplanted trees using satellite images. The approach of utilizing satellite photos and the vegetation index is expected to detect changes in trees that have been transplanted across the country and help to manage tree transplantation for the environmental impact assessment.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.14 no.2
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• pp.102-117
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• 2009

This study was carried out to investigate the extent to which benthic environment of Ulsan Bay was disturbed by organic materials and trace metals from the megacity and industrial complex. Field survey for benthic environment and macroinvertebrate community was seasonally conducted from February to November 2006 at nine stations covering the inside and outside of the bay. TOC was on average 1.7% while four (As, Cu, Pb, Zn) out of seven trace metals measured exceeded the Effects Range Low (ERL) in most of the stations. Total number of species sampled was 199 and mean density was 4,578 ind./$m^2$, both of which were greatly dominated by the polychaetes. Dominant species were Aphelochaeta monilaris (22.6%), Ruditapes philippinarum (17.1%), Magelona japonica (12.2%), Lumbrineris longifolia (9.9%) and their distribution was ruled by the difference in the benthic environmental condition of each station. From the multivariate analyses, four stational groups were identified: northern part of the bay, middle and lower part of the bay, the intersection of Taewha River and Gosa stream and outside of the bay. As a result, the community heterogeneity of inner bay was much more greater than that of outer bay. SIMPER analysis showed that four groups were represented by R. philippinarum-Capitella capitata, A. monilaris-Balanoglossus carnosus, Sinocorophium sinensis-Cyathura higoensis and M. japonica-Ampharete arctica, respectively. Spatio-temporal changes of macroinvertebrate communities in Ulsan Bay were closely related to those of depth, mean grain size and organic content, and Zn was also a meaningful factor in that context.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.4
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• pp.287-304
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• 2007

This study was carried out to investigate spatio-temporal variations of benthic environment and macrobenthic polychaete communities in Gamak Bay where excessive organic matters from untreated sewage effluents and fish and shellfish farming activities have been accumulated in certain regions. Such environmental variables as sediment composition, organic content, acid volatile sulfide and dissolved oxygen content etc. were measured and polychaete specimens were taken in September 1999 and February 2000. In September 1999, organic contents were up to three times higher in the northwestern part of the bay and the area closed to Gukdong harbor than in the rest of the bay. In particular, benthic environment of the northwestern part of the bay was extremely deteriorated by the occurrence of hypoxia and highly concentrated sulfide. Of 28 stations investigated in summer, 5 stations located in the northwestern part were azoic. In the rest of the stations, a total of 119 polychaete species were sampled with a mean density of 900 $ind./m^2$. While species richness was higher in the entrance and central part of the bay where water exchanges with open sea were relatively active, density was higher in the moderately enriched stations neighbouring Gukdong harbor and fish farms where such potential indicators of organic pollution as Aphelochaeta monilaris, Lumbrineris longifolia were largely dominant. In February 2000, a total of 81 polychaete species appeared with a mean density of 2,802 $ind./m^2$ from 12 stations sampled in winter. Azoic areas were recolonized by Capitella capitata, Pseudopolydora paucibranchiata and Dipolydora socialis which showed maximum density in the innermost station. On the other hand, the rest of the stations were dominated by Euchone alicaudata and Praxillella affinis. The configuration of the stations sampled in summer and winter on the multidimensional scaling plots reflected the position of each stations within the bay in which there were great differences in organic content, sulfide concentration and oxygen content rather than in sediment composition. Therefore, heterogeneities in polychaete community structure in Gamak Bay were primarily influenced by the degree of the disturbance depending on the position within the bay.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.26 no.2
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• pp.127-139
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• 2024

Climate change has increased extreme weather events likewise heatwaves, heavy rain, and drought. Unlike other natural disaster, drought is a slowly developing phenomenon and thus drought damage increases as the drought continues. Therefore, it is necessary to understand the characteristics and mechanism of drought occurrence. Agricultural drought occurs when the water supply needed by crops becomes insufficient due to lack of soil water. Therefore, soil water is used as a key variable affecting agricultural drought. In this study, we examined the spatio-temporal distribution and trends of drought across the Korean Peninsula by determining the soil available water content (SAWC) through a model that integrated soil, meteorological, and crop data. Moreover, an investigation into the correlation between meteorological variables and the SAWC was conducted to assess how meteorological characteristics influence the nature of drought occurrences. During the soybean cultivation period, the average SAWC was lowest in 2018 at 88.6% and highest in 2021 at 103.2%. Analysis of the spatial distribution of SAWC by growth stage revealed that the lowest SAWC occurred during the flowering stage (S3) in 2018, during the leaf extension stage (S2) in 2019, during the seedling stage (S1) in 2020, again during the flowering stage (S3) in 2021, and during the seedling stage (S1) in 2022. Based on the average SAWC across different growth stages, the frequency of upland drought was the highest at 22 times during the S3 in 2018. The lowest SAWC was primarily influenced by a significant negative correlation with rainfall and evapotranspiration, whereas the highest SAWC showed a significant positive correlation with rainfall and relative humidity, and a significant negative correlation with reference evapotranspiration.