• Korean Journal of Ecology and Environment
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• v.48 no.2
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• pp.95-107
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• 2015

In order to identify long-term trends of water quality parameters in Lake Kyeongpo, Mann-Kendall test, Sen's slope estimator and linear regression were applied on data, with 15 parameters from three different sites and rainfall, monitored once in every two months from March to November during 1998~2013. Seasonal variation analysis only used Mann-Kendall test and Sen's slope estimator. Analysis result showed that salinity, transparency and nutrient variables (total phosphorus, dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen, ammonia nitrogen) were only parameters having statistically significant trend. In linear regression analysis, salinity (surface and bottom layer of all sites) and transparency (only at site 1), were figured out with statistically significant increasing trend, while in non-parametric statistical method, salinity and transparency in all sites (surface, middle, deep) were figured out with statistically significant increasing trend. Water quality parameters showing statistically significant decreasing trends were dissolved oxygen (surface layer of site 1 and bottom layer of sites 2 and 3), total phosphorus (sites 1 and 2), dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen and ammonia nitrogen in the linear regression analysis and, dissolved oxygen (bottom layer of all sites), total phosphorus, dissolved inorganic phosphorus, total nitrogen, nitrate nitrogen and ammonia nitrogen in the non-parametric method. Seasonal trend analysis result showed that salinity, turbidity, transparency and suspended solids in spring, salinity, transparency, nitrate nitrogen and suspended solids in summer and temperature, salinity, transparency and suspended solids in fall were the variables depending on the season with increasing trends. In general, rainfall during the research period showed decreasing trend. The significant reduction trends of nutrients in Lake Kyeongpo were believed to be related to lagoon restoration and water management project run by Gangneung city and under-water wear removal, but further detailed studies are needed to know the exact causes.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.28-38
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• 2019

Climate change on the Korean peninsula is progressing faster than the global average. For example, typhoons, extreme rainfall, heavy snow, cold, and heatwave that are occurring frequently. North Korea is particularly vulnerable to climate change-related natural disasters such as flooding and flooding due to long-term food shortages, energy shortages, and reckless deforestation and development. In addition, North Korea is classified as an unmeasured area due to political and social influences, making it difficult to obtain sufficient hydrologic data for hydrological analysis. Also, as interest in climate change has increased, studies on climate change have been actively conducted on the Korean Peninsula in various repair facilities and disaster countermeasures, but there are no cases of research on North Korea. Therefore, this study selects watershed characteristic variables that are easy to acquire in order to apply localization model to North Korea where it is difficult to obtain observed hydrologic data and estimates parameters based on meteorological and topographical characteristics of 16 dam basins in South Korea. Was calculated. In addition, as a result of reviewing the applicability of the parameter estimation equations calculated for the fifty thousand, Gangneungnamdaecheon, Namgang dam, and Yeonggang basins, the applicability of the parameter estimation equations to North Korea was very high.

• Journal of Korea Water Resources Association
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• v.53 no.2
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• pp.97-105
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• 2020

Recently, Artificial Neural Network receives attention as a data prediction method. Among these, a Long Shot-term Memory (LSTM) model specialized for time-series data prediction was utilized as a prediction method of hydrological time series data. In this study, the LSTM model was constructed utilizing deep running open source library TensorFlow which provided by Google, to predict inflows of multipurpose dams. We predicted the inflow of the Yongdam Multipurpose Dam which is located in the upper stream of the Geumgang. The hourly flow data of Yongdam Dam from 2006 to 2018 provided by WAMIS was used as the analysis data. Predictive analysis was performed under various of variable condition in order to compare and analyze the prediction accuracy according to four learning parameters of the LSTM model. Root mean square error (RMSE), Mean absolute error (MAE) and Volume error (VE) were calculated and evaluated its accuracy through comparing the predicted and observed inflows. We found that all the models had lower accuracy at high inflow rate and hourly precipitation data (2006~2018) of Yongdam Dam utilized as additional input variables to solve this problem. When the data of rainfall and inflow were utilized together, it was found that the accuracy of the prediction for the high flow rate is improved.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.1
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• pp.107-118
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• 2003

The purpose of this study is to assess the hydrological impact on a watershed from long-term land cover changes. Gyeongan-cheon watershed($558.2km^2$) was selected and WMS(watershed modeling system) HEC-1 model was adopted as an evaluation tool. To identify land cover changes, five Landsat images(1980/2/15, 1986/4/15, 1990/4/26, 1996/4/26, 2000/5/17) were selected and analyzed using maximum likelihood method. As a result, urban areas have increased by 5.6% and forest areas have decreased by 6.1% between 1980 and 2000. SCS curve number increased by 9.8. To determine model parameters and evaluate HEC-1 model, five storm events(1998/5/2, 1998/8/23, 1998/9/30, 1999/5/3, 2000/7/29) were used. The simulated stream flow agreed well with the observed one with relative errors ranging from 9% to 36%. For 254 mm daily rainfall of 30 years frequency, due to the increase of urban areas peak flow increased by $455m^3/sec$ and the time of peak flow reduced about four hours for 20 years land cover changes.

• Journal of Korean Society for Atmospheric Environment
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• v.33 no.2
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• pp.124-138
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• 2017

Physico-chemical measurement of non-refractory submicron particles($NR-PM_1$) was conducted in Baengnyeong Island, Korea using Aerodyne High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS) from 2012 to 2014. Organics and ammoniated sulfate were dominant species in $NR-PM_1$. The organics was found to have similar fractions(approximate 40%) of $NR-PM_1$ during the summer and winter, while the sulfate fractions of $NR-PM_1$ were calculated to be approximately 47% and 31% for the summer and winter, respectively, suggesting the possibility that particles provide non-acidic surfaces for condensation of nitric acid in the winter. The nitrate fractions of approximate 4% and 20% of $NR-PM_1$ were observed in August (summer) and November (winter), respectively, resulting that the relatively low concentration of sulfate in $NR-PM_1$ provided a non-acidic surface for nitric acid condensation and formation of particulate ammoniated nitrate is favored thermodynamically in winter. The new particle formation (NPF) event and particle growth rate were analyzed for each month in 2014 using Scanning Mobility Particle Sizer(SMPS). The Percent of NPF events was the highest in winter, but NPF event was not observed during summer due to relatively high temperature and frequent rainfall. The average particle growth rate was 3.5 nm/h and the highest particle growth rate was 5.5 nm/h in May. We observed the long-range transport of the anthropogenic sulfate from the East Asia during the intensive monitoring period of November between Qingdao and Baengnyeong Island in 2013. The relatively high concentrations of m/z 60 measured in HR-ToF-AMS was observed in May and June at Baengnyeong Island, suggesting the possibility of the influence of biomass burning from the East Asia to the Korean Peninsula.

• Korean Journal of Ecology and Environment
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• v.43 no.4
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• pp.492-502
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• 2010

The study objects were to analyze long-term and seasonal variations of nutrients (N, P), suspended solids, N:P ratios, algal chlorophyll, and trophic state along with general water quality parameters in four sampling sites including two intake tower sites supplying drinking water in Daechung Reservoir. For the analysis, we used water quality long-term data sampled during 1998~2007 by the Ministry of Environment, Korea. Interannual and seasonal trends in inflow and discharge near the intake tower facilities over the ten years were directly influenced by rainfall pattern. The distinct difference between wet year (2003) and dry year (2001) produced marked differences in water temperature, pH, dissolved oxygen, organic matter contents, nutrients, and these variables influenced algal biomass and trophic state. Values of TP varied depending on the year and locations sampled, but monthly mean TP always peaked during July~August when river inflow and precipitation were maxima. In contrast, TN varied little compared to TP, indicating lower influence by seasonal flow compared to phosphorus. The number of E. coli were highest in Site 2 (Chudong intake tower) and varied largely, whereas at other sites, the numbers were low and low variations. Contents of chlorophyll-${\alpha}$ (CHL), as an estimation of primary productivity, varied largely depending on the year and season. The maximum of CHL occurred at Muneu intake tower (S4) during 2006 when the precipitation and inflow were lowest. In contrast, another CHL peak was observed in Site 2 (Chudong intake tower) in 2006 when one of the largest typoons (Ewinia) occurred and river runoff were maximum. So the CHL maxima were associated with both wet year (high flow, high nutrient supply) and dry year (low flow, nutrient supply by littoral zone). Such conditions influenced trophic states, based on Trophic State Index of nutrients and CHL. Based on all analyses, we can provide some clues for management and protection strategies of two intake tower sites.

• Journal of Environmental Impact Assessment
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• v.13 no.4
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• pp.197-211
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• 2004

Visibility impairment was known as an indicator of the increased air pollution. In many previous studies, it is known that both directly emitted fine particles mainly from vehicles and secondary aerosols from photochemical reactions could contribute to this visibility impairment in addition to the meteorological condition. Furthermore, the visibility showed different change patterns according to the geographical condition. In order to research into the influence of these factors on visibility, this study analyzed the visibility at 15:00, observed from 1990 to 2001 in Seoul, Ganghwa, Susan, Gwangju, Jeju. As a result, the visibility was increased in Seoul except the rainfall period, but in Susan, Gwangju, Jeju, it decreased with the relative humidity (RH). Especially, in Seoul, the number of low visibility days was larger than other sites and variations of the visibility were sensitive to the concentration of air pollutants, such as TSP, $NO_2$, $O_3$. The visibility impairment was mainly observed in meteorological condition of RH<50% and relatively stationary front. Therefore it is inferred that photochemical smog could lead to the low visibility in Seoul. On the other hands, in Ganghwa and Susan, when RH was 60~70%, the low visibility observed under the influence of the transports of air pollutants from nearby cities as well as humid air mass from coastal region. And in Jeju, sea fog and humid air mass caused the visibility impairment when the RH was larger than 80%. Finally, during the observational period, some cases of low visibility phenomena were simultaneously observed in the vast region including Seoul, Susan, Ganghwa. It not only includes the visibility aggravation by Asian Dust, but also could be caused by the movement and diffusion of flying dust or secondary aerosols. Moreover, the result shows that these phenomena could be mainly influenced by meteorological factors covering the wide regions.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.277-286
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• 2021

This study compares the long-term hydrological cycles of the Seolmacheon and Cheongmicheon basin by applying the structural equation model (SEM). These two basins are found different especially in their land-use pattern. Both basins have the actual evapotranspiration data measured by the eddy-covariance method as well as the rainfall and runoff data. The length of the data considered in this study is nine years from 2010 to 2018. The structure of the SEM is determined by considering the correlations among the data as well as the general knowledge on the hydrological cycle. As a result, a total of three SEMs are applied sequentially to analyze their fittings. As irony would have it, two basins are found to be similar in the application of one SEM, but different in the application of another. Especially, when considering the feedback process between precipitation and evapotranspiration, two basins are found to be very different. That is, the feedback process between precipitation and evapotranspiration is found to be significant in the Cheongmicheon basin where the portion of agricultural area (i.e., paddy) is more than 40%.

• Ecology and Resilient Infrastructure
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• v.6 no.1
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• pp.23-33
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• 2019

Naeseong Stream is a sand-bed river that flows through the northern area of Gyeongbuk province. It is characterized by dynamic sandy bedforms developed in response to the seasonal hydrological fluctuation and by its unique riverine landscape called "white river." However, changes including construction of Yeongju Dam from 2010 and the extensive vegetation establishment around 2015 occurred along the Naeseong Stream. This paper aims to analyze climate, hydrology, and water quality as factors and to examine the possibility of channel changes accordingly. The second least precipitation during the last 60 years happened in 2015, which led to the lowest peak discharge in 50 years. The sediment characteristics of Naeseong Stream were not significantly different along the upstream and downstream reaches, but it was confirmed that annual minimum water level of the stream decreased continuously regardless of the dam construction. This suggests that intermittent drought and change in water quality are likely to provide favorable conditions for riparian vegetation establishment and the resulting physical changes have affected riverbed degradation. Therefore, it is necessary to conduct diversified monitoring in connection with river vegetation change in order to analyze the causes of river changes.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.30-30
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• 2023

This study aims to establish the multi-reservoir operation system model in the Upper Mun River Basin which includes 5 main dams namely, Mun Bon (MB), Lamchae (LC), Lam Takhong (LTK), Lam Phraphoeng (LPP), and Lower Lam Chiengkrai (LLCK) Dams. The knowledge and AI technology were applied aiming to develop innovative prototype for SMART dam-reservoir operation in future. Two different sorts of reservoir operation system model namely, Fuzzy Logic (FL) and Constraint Programming (CP) as well as the development of rainfall and reservoir inflow prediction models using Machine Learning (ML) technique were made to help specify the right amount of daily reservoir releases for the Royal Irrigation Department (RID). The model could also provide the essential information particularly for the Office of National Water Resource of Thailand (ONWR) to determine the short-term and long-term water resource management plan and strengthen water security against flood and drought in this region. The simulated results of base case scenario for reservoir operation in the Upper Mun from 2008 to 2021 indicated that in the same circumstances, FL and CP models could specify the new release schemes to increase the reservoir water storages at the beginning of dry season of approximately 125.25 and 142.20 MCM per year. This means that supplying the agricultural water to farmers in dry season could be well managed. In other words, water scarcity problem could substantially be moderated at some extent in case of incapability to control the expansion of cultivated area size properly. Moreover, using AI technology to determine the new reservoir release schemes plays important role in reducing the actual volume of water shortfall in the basin although the drought situation at LTK and LLCK Dams were still existed in some periods of time. Meanwhile, considering the predicted inflow and hydrologic factors downstream of 5 main dams by FL model and minimizing the flood volume by CP model could ensure that flood risk was considerably minimized as a result of new release schemes.