• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1143-1154
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• 2021

The selection of activation function has a great influence on the groundwater level prediction performance of artificial neural network (ANN) model. In this study, five activation functions were applied to ANN model for two groundwater level observation wells in the middle mountainous area of the Pyoseon watershed in Jeju Island. The results of the prediction of the groundwater level were compared and analyzed, and the optimal activation function was derived. In addition, the results of LSTM model, which is a widely used recurrent neural network model, were compared and analyzed with the results of the ANN models with each activation function. As a result, ELU and Leaky ReLU functions were derived as the optimal activation functions for the prediction of the groundwater level for observation well with relatively large fluctuations in groundwater level and for observation well with relatively small fluctuations, respectively. On the other hand, sigmoid function had the lowest predictive performance among the five activation functions for training period, and produced inappropriate results in peak and lowest groundwater level prediction. The ANN-ELU and ANN-Leaky ReLU models showed groundwater level prediction performance comparable to that of the LSTM model, and thus had sufficient potential for application. The methods and results of this study can be usefully used in other studies.

• Korean Journal of Remote Sensing
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• v.37 no.6_2
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• pp.1819-1827
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• 2021

Land-use/cover change caused by rapid urbanization in South Korea is one of the concerns in flood risk management because groundwater recharge by precipitation hardly occurs due to an increase in impermeable surfaces in urban areas. This study investigated the hydrologic effects of land-use/cover on groundwater recharge in the Yeonje-gu district of Busan, South Korea. A statistical time series analysis was conducted with temporal variations of precipitation and groundwater level to estimate lag-time based on correlation coefficients calculated from auto-correlation function (ACF), cross-correlation function (CCF), and moving average (MA) at five sites. Landform and land-use/cover within 250 m radius of the monitoring wells(GW01, GW02, GW03, GW04, and GW05) at five sites were identified by land cover and digital map using Arc-GIS software. Long lag-times (CCF: 42-71 days and MA: 148-161 days) were calculated at the sites covered by mainly impermeable surfaces(GW01, GW03, and GW05) while short lag-times(CCF: 4 days and MA: 67 days) were calculated at GW04 consisting of mainly permeable surfaces. The results suggest that lag-time would be one of the good indicators to evaluate the effects of land-use/cover on estimating groundwater recharge. The results of this study also provide guidance on the application of statistical time series analysis to environmentally important issues on creating an urban green space for natural groundwater recharge from precipitation in the city and developing a management plan for hydrological disaster prevention.

• Journal of Life Science
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• v.29 no.4
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• pp.410-420
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• 2019

Citrus unshiu peel extracts possess a variety of beneficial effects, and studies on their anticancer activity have been reported. However, the exact mechanisms underlying this activity remain unclear. In the current study, the apoptotic effect of ethanol extract of C. unshiu peel (EECU) on human breast adenocarcinoma MDA-MB-231 cells and related mechanisms were investigated. The results showed that the survival rate of MDA-MB-231 cells treated with EECU was significantly inhibited in a concentration-dependent manner, which was associated with the induction of apoptosis. EECU-induced apoptosis was associated with the activation of caspase-8 and caspase-9, which initiate extrinsic and intrinsic apoptosis pathways, respectively, and caspase-3, a representative effect caspase. EECU suppressed the expression of the inhibitor of apoptosis family of proteins, leading to an increased Bax/Bcl-2 ratio and proteolytic degradation of poly (ADP-ribose) polymerase. EECU also enhanced the loss of the mitochondrial membrane potential and cytochrome c release from the mitochondria to the cytosol, along with truncation of Bid. In addition, EECU activated AMP-activated protein kinase (AMPK), and compound C, an AMPK inhibitor, significantly weakened EECU-induced apoptosis and cell viability reduction. Furthermore, EECU promoted the generation of reactive oxygen species (ROS), which acted as upstream signals for AMPK activation as pretreatment of cells, with the antioxidant N-acetyl cysteine reversing both EECU-induced AMPK activation and apoptosis. Collectively, these findings suggest that EECU inhibits MDA-MB-231 adenocarcinoma cell proliferation by activating intrinsic and extrinsic apoptotic pathways, which was mediated through ROS/AMPK-dependent pathways.

• Journal of Life Science
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• v.29 no.1
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• pp.112-117
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• 2019

Herbal medicines are widely used as therapeutic products in many countries. Corni fructus (CF), the dried ripe sarcocarp of Cornus officinalis Sieb. et Zucc (Cornaceae), has been used for thousands of years in traditional medicine and has been reported to be effective for the prevention and treatment of various diseases, such as kidney diseases and diabetes. Recent research on CF has documented a wide spectrum of therapeutic properties, which include anti-inflammatory, ant-oxidative, immunomodulatory, and anti-cancer effects. However, there is no information on its safety. Therefore, in this study, the toxicity of water extract of CF to ICR mice was investigated. The mice received a single dose of water extract of CF (1,000, 2,000, and 5,000 mg/kg of body weight) via the oral route. Mortality, clinical signs, body weight changes, gross findings, and weights of the principal organs after 14 d were then assessed. The results revealed no adverse effects of CF as determined by clinical signs, body weights, or organ weights and no gross pathological findings in any of the treatment groups. These results suggest that the 50% lethal dose and approximated lethal dose of CF extract is over 5,000 mg/kg. The findings provide scientific evidence for the safety of CFs.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1071-1079
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• 2020

For integrated water management, it is essential to secure basic data such as the amount of agricultural water intake. The river water intake through the intake weir is carried out through the agricultural irrigation canal, and a method for measuring the quantity of water intake is required to suit the characteristics of the measuring points. In this study, the accuracy of the calculated flow data was determined by applying a microwave water surface current meter. The microwave water surface current meter is a method of calculating surface velocity using doppler effect, which is mainly used in high-velocities situations such as flood. Surface velocity is difficult to represent the average velocity of the entire section at low dicharges or high wind speeds, it is considered to be low in continuous utilization throughout the year, and it is necessary to verify whether the measurement using an microwave water surface curren meter is appropriate in agricultural irrigation canal. The data measured with an microwave water surface curren meter were compared with the actual flow data to calculate the intake data in agricultural irrigation canal. In agricultural irrigation canal, the low-level discharge calculated using an microwave water surface current meter at a minimum velocity of about 0.3 m/s and a minimum discharge of about 1.0 m3/s or higher was found to have a high tendency and accuracy compared to the standard discharge, especially when the high discharge was high. Although effective results can be obtained in terms of quantity at low discharge, it is deemed that subsequent studies are needed to calculate the average discharge of the cross section at low discharge, given that the trend of data is unstable. Through this study, it is suggested that it is appropriate to calculate the amount of water intake through the microwave water surface current meter in artificial waterways with a certain discharge or higher, so it is expected to be widely distributed as a method for measuring river water intake.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.

• 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.

• Journal of Environmental Impact Assessment
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• v.32 no.2
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• pp.134-145
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• 2023

Currently, the floodplains of major rivers are transforming into various types of waterfront spaces according to the increase in leisure activities and improved accessibility. In general, waterfront activities in river channels tend to be concentrated in summer, and the waterfront activities during this period directly affect water quality. Accordingly, it is necessary to accurately compare and evaluate the characteristics and water quality of waterfront activities during the period when waterfront activities are concentrated. In this study, the following research was conducted to compare and analyze the current status of waterfront activities of users of waterfront areas and the water quality of waterfront areas. First, three waterfront areas were selected for investigation using the information from the Ministry of Environment's water quality measurement network. Second, a survey was conducted on the satisfaction and types of waterfront activities targeting users of waterfront areas. Third, water quality grades were calculated based on monthly water quality measurement factors and compared. Fourth, statistical analysis (one-way analysis of variance) was conducted to see if there was a significant difference in water quality characteristics between periods of high waterfront activity and periods of low waterfront activity using water quality measurement data for the last 5 years. As a result of this analysis, the following conclusions were drawn in this study. First, the use of waterfront activities was investigated in the order of camping, water skiing, fishing, swimming, and rafting. Second, satisfaction factors for waterfront activities were investigated in the order of activity convenience, water quality, waterlandscape, transportation access convenience, and temperature. Third, it was found that satisfaction with water quality in waterfront areas was generally unsatisfactory regardless of the water quality grade presented by the competent authority. Fourth, as a result of comparing the water quality measurement network data of the Ministry of Environment by water quality grade, generally good grades were found, and in particular, there was a difference in grade frequency by season in the BOD category. Fifth, as a result of statistical analysis (one-way ANOVA) of water quality monitoring network data by season, there were statistically significant differences in COD, BOD, TP, and TOC except for DO. Considering the results of these studies, it is judged that it is necessary to prepare a comprehensive management system for water quality improvement in the waterfront zone and to improve water quality during periods of high waterfront activity, and to prepare a water quality forecasting system for waterfront areas in the future.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.233-246
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• 2023

In terms of understanding the water cycle and efficient water resource management, the importance of soil moisture has been highlighted. However, in Korea, the lack of qualified in-situ soil moisture data results in very limited utility. Even if satellite-based data are applied, the absence of ground reference data makes objective evaluation and correction difficult. The cosmic-ray neutron probe (CRNP) can play a key role in producing data for satellite data calibration. The installation of CRNP is non-invasive, minimizing damage to the soil and vegetation environment, and has the advantage of having a spatial representative for the intermediate scale. These characteristics are advantageous to establish an observation network in Korea which has lots of mountainous areas with dense vegetation. Therefore, this study was conducted to evaluate the applicability of the CRNP soil moisture observatory in Korea as part of the establishment of a Korean cOsmic-ray Soil Moisture Observing System (KOSMOS). The CRNP observation station was installed with the Gunup-ri observation station, considering the ease of securing power and installation sites and the efficient use of other hydro-meteorological factors. In order to evaluate the CRNP soil moisture data, 12 additional in-situ soil moisture sensors were installed, and spatial representativeness was evaluated through a temporal stability analysis. The neutrons generated by CRNP were found to be about 1,087 counts per hour on average, which was lower than that of the Solmacheon observation station, indicating that the Hongcheon observation station has a more humid environment. Soil moisture was estimated through neutron correction and early-stage calibration of the observed neutron data. The CRNP soil moisture data showed a high correlation with r=0.82 and high accuracy with root mean square error=0.02 m³/m³ in validation with in-situ data, even in a short calibration period. It is expected that higher quality soil moisture data production with greater accuracy will be possible after recalibration with the accumulation of annual data reflecting seasonal patterns. These results, together with previous studies that verified the excellence of CRNP soil moisture data, suggest that high-quality soil moisture data can be produced when constructing KOSMOS.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.43-54
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• 2023

Due to climate change, drought and flood occurrences have been increasing. Accurate projections of watershed discharges are imperative to effectively manage natural disasters caused by climate change. However, climate change and hydrological model uncertainty can lead to imprecise analysis. To address this issues, we used two lumped models, IHACRES and GR4J, to compare and analyze the changes in discharges under climate stress scenarios. The Hapcheon and Seomjingang dam basins were the study site, and the Nash-Sutcliffe efficiency (NSE) and the Kling-Gupta efficiency (KGE) were used for parameter optimizations. Twenty years of discharge, precipitation, and temperature (1995-2014) data were used and divided into training and testing data sets with a 70/30 split. The accuracies of the modeled results were relatively high during the training and testing periods (NSE>0.74, KGE>0.75), indicating that both models could reproduce the previously observed discharges. To explore the impacts of climate change on modeled discharges, we developed climate stress scenarios by changing precipitation from -50 % to +50 % by 1 % and temperature from 0 ℃ to 8 ℃ by 0.1 ℃ based on two decades of weather data, which resulted in 8,181 climate stress scenarios. We analyzed the yearly maximum, abundant, and ordinary discharges projected by the two lumped models. We found that the trends of the maximum and abundant discharges modeled by IHACRES and GR4J became pronounced as changes in precipitation and temperature increased. The opposite was true for the case of ordinary water levels. Our study demonstrated that the quantitative evaluations of the model uncertainty were important to reduce the impacts of climate change on water resources.