• 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 Intelligence and Information Systems
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• v.29 no.3
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• pp.1-17
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• 2023

With the recent rapid development of ICT(Information and Communication Technology) and the popularization of digital devices, the size of the online market continues to grow. As a result, we live in a flood of information. Thus, customers are facing information overload problems that require a lot of time and money to select products. Therefore, a personalized recommender system has become an essential methodology to address such issues. Collaborative Filtering(CF) is the most widely used recommender system. Traditional recommender systems mainly utilize quantitative data such as rating values, resulting in poor recommendation accuracy. Quantitative data cannot fully reflect the user's preference. To solve such a problem, studies that reflect qualitative data, such as review contents, are being actively conducted these days. To quantify user review contents, text mining was used in this study. The general CF consists of the following three steps: user-item matrix generation, Top-N neighborhood group search, and Top-K recommendation list generation. In this study, we propose a recommendation algorithm that applies an extended similarity measure, which utilize quantified review contents in addition to user rating values. After calculating review similarity by applying TF-IDF, Word2Vec, and Doc2Vec techniques to review content, extended similarity is created by combining user rating similarity and quantified review contents. To verify this, we used user ratings and review data from the e-commerce site Amazon's "Health and Personal Care". The proposed recommendation model using extended similarity measure showed superior performance to the traditional recommendation model using only user rating value-based similarity measure. In addition, among the various text mining techniques, the similarity obtained using the TF-IDF technique showed the best performance when used in the neighbor group search and recommendation list generation step.

• Korean Journal of Ecology and Environment
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• v.37 no.4 s.109
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• pp.411-422
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• 2004

A limnological survey was conducted in a reservoir, Lake Hoengsung located in Kangwondo, Korea, from July 2000 to September 2001 on the monthly basis. Phosphorus loading from the watershed was estimated by measuring total phosphorus concentration in the main tributary. Secchi disc transparency, epilimnetic (0-5 m) turbidity, chlorophyll a (Chl-a), total phosphorus (TP), total nitrogen(TN) and silica concentration were in the range of 0.9-3.5 m, 0.1-8.5 NTU, 0.3-32.4 mgChl $m^{-3}$, 5-46 mgP $m^{-3}$, 0.83-3.55 mgN $L^{-1}$ and 0.5-9.6 mgSi $L^{-1}$, respectively. Green algae and cyanobacteria dominated phytoplankton community in warm seasons, from July through October, 2000. In July a green alga (Scenedesmus sp.) was dominant with a maximum cell density of 10,480 cells mL. Cyanobacteria (Microcystics sp.) dominated in August and September with cell density of 3,492 and 295 cells mL ,respectively. Species diversity of phytoplankton was highest (2.22) in July. The trophic state of the reservoir can be classified as eutrophic on the basis of TP, Chl-a, and Secchi disc transparency. Because TP concentration was high in flood period, most of phosphorus loading was concentrated in rainy season. TP loading was calculated by multiplying TP and flow rate. The dam managing company measured inflow rate of the reservoir daily, while TP was measured by weekly surveys. TP of unmeasured days was estimated from the empirical relationship of TP and the flow rate of the main tributary; $TP=5.59Q^{0.45}\;(R^2=0.47)$. Annual TP loading was calculated to be 4.45 tP $yr^{-1}$, and the areal P loading was 0.77 gP $m^{-2}\;yr^{-1}$ which is similar to the critical P loading for eutrophication by Vollenweider's phosphorus model, 0.72 gP $m^{-2}\;yr^{-1}$.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.905-916
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• 2018

The purpose of this study is to evaluate the climate change impact on watershed hydrology and flow duration in Geum River basin ($9,645.5km^2$) especially by extreme scenarios. The rainfall related extreme index, STARDEX (STAtistical and Regional dynamical Downscaling of EXtremes) was adopted to select the future extreme scenario from the 10 GCMs with RCP 8.5 scenarios by four projection periods (Historical: 1975~2005, 2020s: 2011~2040, 2050s: 2041~2070, 2080s: 2071~2100). As a result, the 5 scenarios of wet (CESM1-BGC and HadGEM2-ES), normal (MPI-ESM-MR), and dry (INM-CM4 and FGOALS-s2) were selected and applied to SWAT (Soil and Water Assessment Tool) hydrological model. The wet scenarios showed big differences comparing with the normal scenario in 2080s period. The 2080s evapotranspiration (ET) of wet scenarios varied from -3.2 to +3.1 mm, the 2080s total runoff (TR) varied from +5.5 to +128.4 mm. The dry scenarios showed big differences comparing with the normal scenario in 2020s period. The 2020s ET for dry scenarios varied from -16.8 to -13.3 mm and the TR varied from -264.0 to -132.3 mm respectively. For the flow duration change, the CFR (coefficient of flow regime, Q10/Q355) was altered from +4.2 to +10.5 for 2080s wet scenarios and from +1.7 to +2.6 for 2020s dry scenarios. As a result of the flow duration analysis according to the change of the hydrological factors of the Geum River basin applying the extreme climate change scenario, INM-CM4 showed suitable scenario to show extreme dry condition and FGOALS-s2 showed suitable scenario for the analysis of the drought condition with large flow duration variability. HadGEM2-ES was evaluated as a scenario that can be used for maximum flow analysis because the flow duration variability was small and CESM1-BGC was evaluated as a scenario that can be applied to the case of extreme flood analysis with large flow duration variability.

• Korean Journal of Ecology and Environment
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• v.42 no.2
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• pp.260-269
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• 2009

Hwabuk Dam has been under construction to reduce flood damage in Nakdong River watershed and to supply stable water for middle area of Gyeongbuk Province. Therefore, fish investigation in up and downstream of the dam was conducted from 2004 to 2008 in order to determine any negative effect on fish community due to dam construction and to use as fundamental data for conserving species diversity and maintaining stream health. According to data analysis on water quality, temperature, dissolved oxygen, pH, suspended solids, and total E-coli had seasonal variation, but they did not significantly differ in sites. However, biological and chemical oxygen demand, chlorophyll-a, nitrogen, and phosphorus representing organic matter and nutrient concentration were higher in upper site and decreased to lower site so that they differed by site. Concentration of arsenic among the heavy metals was less than 0.05 mg $L^{-1}$, which is regulated for protection of human health in water quality standard, except for 0.092 mg $L^{-1}$ in June 2005. During the study period, the total number of fish caught from the 6 sites was 10,263 representing 7 families 19 species. Among them, dominant and subdominant species were Korean chub (Zacco koreanus, 62.5%) and Chinese minnow (Rhynchocypris oxycephalus, 10.6%) which inhabit mostly in mid and upper streams, Korea. Among the 19 species, Korean endemic species were 9 species (47.4%) including Korean slender gudgeon (Squalidus gracilis majimae), Korean dark sleeper (Odontobutis platycephala), and Korean shiner (Coreoleuciscus splendidus). There was several individuals of the $1^{st}$-class endangered species, Naktong nose loach (Koreocobitis nahtongensis), caught in 2005${\sim}$2007, and no introduced species of fish was found in entire sampling period. According to result of community analysis, dominance index decreased toward lower site, but diversity and richness indices increased toward lower site. The equation of length-weight relationship on the dominant species was TW=0.000003$(TL)^{3.2603}$. The parameter b in the equation was greater than 3.0 indicating good nutritional condition in the populations. Compared to populations of Korean chub in other streams, the population in Hwabuk Dam watershed had higher mean of condition factor by size indicating better growth rate. With fish fauna and multi-metric health assessment model in each sampling attempt, index of biotic integrity (IBI) was evaluated and it resulted mostly in good (26${\sim}$35) and excellent (36${\sim}$40) condition in all sites, and the mean of IBI was the highest in site 5. The results indicate that it is very important to study not only environmental impact assessment with fish composition but also stream health assessment in order to conserve healthy aquatic ecosystem.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.