• Korean Journal of Microbiology
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• v.54 no.4
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• pp.428-435
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• 2018

In this study, we isolated and identified bacteria from freshwater and soil collected from Osang reservoir, to screen antimicrobial bacteria against various pathogenic bacteria. 38 strains were isolated and assigned to the class Proteobacteria (22 strains), Actinobacteria (7 strains), Bacteroidets (6 strains), and Firmicutes (3 strains) based on 16S rRNA gene sequence analysis. Among them, strain OS17 showed a good growth inhibition against 5 methicillin-resistant Staphylococcus aureus subsp. aureus strains and Bacillus cereus, Bacillus subtilis, Filobasidium neoformans. As a result of the 16S rRNA gene sequence analysis, strain OS17 show the high similarity with Burkholderia ambifaria $AMMD^T$, B. diffusa $AM747629^T$, B. tettitorii $LK023503^T$ 99.8%, 99.7%, 99.6%, respectively. We investigated cell growth and antimicrobial activity according to commercial culture medium, temperature, pH for culture optimization of strain OS17. Optimal conditions for growth and antimicrobial activity in strain OS17 were found to be: YPD medium, $35^{\circ}C$ and pH 6.5. When the strain was cultured in LB, NB, TSB, R2A media at $20^{\circ}C$ and $25^{\circ}C$, the antimicrobial activity did not show. Culture filtrate of strain OS17 showed antimicrobial activity against 5 MRSA strains, Bacillus cereus, Bacillus subtilis, and Filobasidium neoformans with inhibition zones from 2 to 8 mm. Optimal reaction time was 48 h in YPD medium, 100 rpm and 0.3 vvm in 2 L-scale fed-batch fermentation process for antimicrobial activity. Culture optimization of strain OS17 can be improved on antimicrobial activity. Therefore, the antimicrobial activity of Burkholderia sp. OS17 had potential as antibiotics for pathogens including MRSA.

• Applied Chemistry for Engineering
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• v.33 no.6
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• pp.563-573
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• 2022

This work aimed to develop a new equation for turbidity (Turb) simulation and prediction using statistical methods based on principal component analysis (PCA) and multiple linear regression (MLR). For this purpose, water samples were collected monthly over a five year period from Cheurfa dam, an important reservoir in Northwestern Algeria, and analyzed for 12 parameters, including temperature (T°), pH, electrical conductivity (EC), turbidity (Turb), dissolved oxygen (DO), ammonium (NH₄⁺), nitrate (NO₃^-), nitrite (NO₂^-), phosphate (PO₄^3-), total suspended solids (TSS), biochemical oxygen demand (BOD₅) and chemical oxygen demand (COD). The results revealed a strong mineralization of the water and low dissolved oxygen (DO) content during the summer period. High levels of TSS and Turb were recorded during rainy periods. In addition, water was charged with phosphate (PO₄^3-) in the whole period of study. The PCA results revealed ten factors, three of which were significant (eigenvalues >1) and explained 75.5% of the total variance. The F1 and F2 factors explained 36.5% and 26.7% of the total variance, respectively and indicated anthropogenic pollution of domestic agricultural and industrial origin. The MLR turbidity simulation model exhibited a high coefficient of determination (R² = 92.20%), indicating that 92.20% of the data variability can be explained by the model. TSS, DO, EC, NO₃^-, NO₂^-, and COD were the most significant contributing parameters (p values << 0.05) in turbidity prediction. The present study can help with decision-making on the management and monitoring of the water quality of the dam, which is the primary source of drinking water in this region.

• Journal of Korea Water Resources Association
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• v.56 no.9
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• pp.529-541
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• 2023

Due to the growing concern over forecasting extreme weather events such as droughts caused by climate change, there has been a rising interest in seasonal meteorological forecasts that offer ensemble predictions for the upcoming seven months. Nonetheless, limited research has been conducted in South Korea, particularly in assessing their effectiveness at the catchment-scale. In this study, we assessed the accuracy of ECMWF's seasonal forecasts (including precipitation, temperature, and evapotranspiration) for the period of 2011 to 2020. We focused on 12 multi-purpose reservoir catchments and compared the forecasts to climatology data. Continuous Ranked Probability Skill Score method is adopted to assess the forecast skill, and the linear scaling method was applied to evaluate its impact. The results showed that while the seasonal meteorological forecasts have similar skill to climatology for one month ahead, the skill decreased significantly as the forecast lead time increased. Compared to the climatology, better results were obtained in the Wet season than the Dry season. In particular, during the Wet seasons of the dry years (2015, 2017), the seasonal meteorological forecasts showed the highest skill for all lead times.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.173-184
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• 2023

Due to climate change, algal blooms frequently occur not only in Korea but also around the world, and the risk of toxicity of harmful algae has recently been issued. It is known that the representative harmful algae, cyanobacteria, are caused by the intersection of three factors: water temperature, residence time, and nutrients. In this study, water quality simulation was carried out using EFDC, a three-dimensional numerical model, to analyze the variations in water quality due to the decrease of residence time according to the opening of Yeongju Dam in Naeseong-Cheon. In fact, the concentration of chlorophyll-a in Yeongju Dam in the summer of 2021 was significant, exceeding the 'algae warning' for a long time based on the previous algae warning system. On the other hand, as a result of performing the simulation under the condition that the dam gate was completely opened, the concentration of chlorophyll-a was mostly reduced below the 'algae warning' level during the simulation period. It was confirmed that reducing the residence time by restoring the flow of Naeseong-Cheon is a way to immediately reduce algae in Yeongju Dam.

• Journal of the Korean Institute of Gas
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• v.27 no.2
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• pp.7-15
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• 2023

The electric submersible pump (ESP) has been operating in production wells around the world because of its high applicability and operational efficiency among artificial lift techniques. When operating an ESP in a reservoir, variables such as temperature, pressure, gas/oil ratio, and flow rate are factors that affect ESP performance. In particular, free gas in the production fluid is a major factor that reduces the life and operational efficiency of ESP. This study presents the flow loop system which can implement the performance and damage tests of ESP considering field operating conditions to quantitatively analyze the variables that affect ESP performance. The developed apparatus in an integrated system that can diagnose the failure and causes of ESP, and detect leak of tubing by linking ESP and tubing as one system. In this study, the flow conditions for stable operation of ESP were identified through single phase and two phase flow experiments related to evaluation for the performance of ESP. The results provide the basic data to develop the failure prediction and diagnosis program of ESP, and are expected to be used for real-time monitoring for optimal operating conditions and failure diagnosis for ESP operation.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.88-88
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• 2021

최근 수자원과 수질관리 분야에 자료기반 머신러닝 모델과 딥러닝 모델의 활용이 급증하고 있다. 그러나 딥러닝 모델은 Blackbox 모델의 특성상 고전적인 질량, 운동량, 에너지 보존법칙을 고려하지 않고, 데이터에 내재된 패턴과 관계를 해석하기 때문에 물리적 법칙을 만족하지 않는 예측결과를 가져올 수 있다. 또한, 딥러닝 모델의 예측 성능은 학습데이터의 양과 변수 선정에 크게 영향을 받는 모델이기 때문에 양질의 데이터가 제공되지 않으면 모델의 bias와 variation이 클 수 있으며 정확도 높은 예측이 어렵다. 최근 이러한 자료기반 모델링 방법의 단점을 보완하기 위해 프로세스 기반 수치모델과 딥러닝 모델을 결합하여 두 모델링 방법의 장점을 활용하는 연구가 활발히 진행되고 있다(Read et al., 2019). Process-Guided Deep Learning (PGDL) 방법은 물리적 법칙을 반영하여 딥러닝 모델을 훈련시킴으로써 순수한 딥러닝 모델의 물리적 법칙 결여성 문제를 해결할 수 있는 대안으로 활용되고 있다. PGDL 모델은 딥러닝 모델에 물리적인 법칙을 해석할 수 있는 추가변수를 도입하며, 딥러닝 모델의 매개변수 최적화 과정에서 Cost 함수에 물리적 법칙을 위반하는 경우 Penalty를 추가하는 알고리즘을 도입하여 물리적 보존법칙을 만족하도록 모델을 훈련시킨다. 본 연구의 목적은 대청호의 수심별 수온을 예측하기 위해 역학적 모델과 딥러닝 모델을 융합한 PGDL 모델을 개발하고 적용성을 평가하는데 있다. 역학적 모델은 2차원 횡방향 평균 수리·수질 모델인 CE-QUAL-W2을 사용하였으며, 대청호를 대상으로 2017년부터 2018년까지 총 2년간 수온과 에너지 수지를 모의하였다. 기상(기온, 이슬점온도, 풍향, 풍속, 운량), 수문(저수위, 유입·유출 유량), 수온자료를 수집하여 CE-QUAL-W2 모델을 구축하고 보정하였으며, 모델은 저수위 변화, 수온의 수심별 시계열 변동 특성을 적절하게 재현하였다. 또한, 동일기간 대청호 수심별 수온 예측을 위한 순환 신경망 모델인 LSTM(Long Short-Term Memory)을 개발하였으며, 종속변수는 수온계 체인을 통해 수집한 수심별 고빈도 수온 자료를 사용하고 독립 변수는 기온, 풍속, 상대습도, 강수량, 단파복사에너지, 장파복사에너지를 사용하였다. LSTM 모델의 매개변수 최적화는 지도학습을 통해 예측값과 실측값의 RMSE가 최소화 되로록 훈련하였다. PGDL 모델은 동일 기간 LSTM 모델과 동일 입력 자료를 사용하여 구축하였으며, 역학적 모델에서 얻은 에너지 수지를 만족하지 않는 경우 Cost Function에 Penalty를 추가하여 물리적 보존법칙을 만족하도록 훈련하고 수심별 수온 예측결과를 비교·분석하였다.

• Journal of Korea Water Resources Association
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• v.46 no.12
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• pp.1235-1247
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• 2013

This study is to evaluate the climate change impact on future storage behavior of Chungju dam($2,750{\times}10^6m^3$) and the regulation dam($30{\times}10^6m^3$) using SWAT(Soil Water Assessment Tool) model. Using 9 years data (2002~2010), the SWAT was calibrated and validated for streamflow at three locations with 0.73 average Nash-Sutcliffe model Efficiency (NSE) and for two reservoir water levels with 0.86 NSE respectively. For future evaluation, the HadCM3 of GCMs (General Circulation Models) data by scenarios of SRES (Special Report on Emission Scenarios) A2 and B1 of the IPCC (Intergovernmental Panel on Climate Change) were adopted. The monthly temperature and precipitation data (2007~2099) were spatially corrected using 30 years (1977~2006, baseline period) of ground measured data through bias-correction, and temporally downscaled by Change Factor (CF) statistical method. For two periods; 2040s (2031~2050), 2080s (2071~2099), the future annual temperature were predicted to change $+0.9^{\circ}C$ in 2040s and $+4.0^{\circ}C$ in 2080s, and annual precipitation increased 9.6% in 2040s and 20.7% in 2080s respectively. The future watershed evapotranspiration increased up to 15.3% and the soil moisture decreased maximum 2.8% compared to baseline (2002~2010) condition. Under the future dam release condition of 9 years average (2002~2010) for each dam, the yearly dam inflow increased maximum 21.1% for most period except autumn. By the decrease of dam inflow in future autumn, the future dam storage could not recover to the full water level at the end of the year by the present dam release pattern. For the future flood and drought years, the temporal variation of dam storage became more unstable as it needs careful downward and upward management of dam storage respectively. Thus it is necessary to adjust the dam release pattern for climate change adaptation.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.39-50
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• 2019

This study aims to assess the influence of climate change on the hydrological cycle at a basin level in North Korea. The selected model for this study is MRI-CGCM 3, the one used for the Coupled Model Intercomparison Project Phase 5 (CMIP5). Moreover, this study adopted the Spatial Disaggregation-Quantile Delta Mapping (SDQDM), which is one of the stochastic downscaling techniques, to conduct the bias correction for climate change scenarios. The comparison between the preapplication and postapplication of the SDQDM supported the study's review on the technique's validity. In addition, as this study determined the influence of climate change on the hydrological cycle, it also observed the runoff in North Korea. In predicting such influence, parameters of a runoff model used for the analysis should be optimized. However, North Korea is classified as an ungauged region for its political characteristics, and it was difficult to collect the country's runoff observation data. Hence, the study selected 16 basins with secured high-quality runoff data, and the M-RAT model's optimized parameters were calculated. The study also analyzed the correlation among variables for basin characteristics to consider multicollinearity. Then, based on a phased regression analysis, the study developed an equation to calculate parameters for ungauged basin areas. To verify the equation, the study assumed the Osipcheon River, Namdaecheon Stream, Yongdang Reservoir, and Yonggang Stream as ungauged basin areas and conducted cross-validation. As a result, for all the four basin areas, high efficiency was confirmed with the efficiency coefficients of 0.8 or higher. The study used climate change scenarios and parameters of the estimated runoff model to assess the changes in hydrological cycle processes at a basin level from climate change in the Amnokgang River of North Korea. The results showed that climate change would lead to an increase in precipitation, and the corresponding rise in temperature is predicted to cause elevating evapotranspiration. However, it was found that the storage capacity in the basin decreased. The result of the analysis on flow duration indicated a decrease in flow on the 95th day; an increase in the drought flow during the periods of Future 1 and Future 2; and an increase in both flows for the period of Future 3.

• Journal of the Korean Society for Marine Environment & Energy
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• v.11 no.4
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• pp.181-190
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• 2008

To response climate change and Kyoto protocol and to reduce greenhouse gas emissions, marine geological storage of $CO_2$ is regarded as one of the most promising option. Marine geological storage of $CO_2$ is to capture $CO_2$ from major point sources(eg. power plant), to transport to the storage sites and to store $CO_2$ into the marine geological structure such as deep sea saline aquifer. To design a reliable $CO_2$ marine geological storage system, it is necessary to perform numerical process simulation using thermodynamic equation of state. The purpose of this paper is to compare and analyse the relevant equations of state including ideal, BWRS, PR, PRBM and SRK equation of state. To evaluate the predictive accuracy of the equation of the state, we compared numerical calculation results with reference experimental data. Ideal and SRK equation of state did not predict the density behavior above $29.85^{\circ}C$, 60 bar. Especially, they showed maximum 100% error in supercritical state. BWRS equation of state did not predict the density behavior between $60{\sim}80\;bar$ and near critical temperature. On the other hand, PR and PRBM equation of state showed good predictive capability in supercritical state. Since the thermodynamic conditions of $CO_2$ reservoir sites correspond to supercritical state(above $31.1^{\circ}C$ and 73.9 bar), we conclude that it is recommended to use PR and PRBM equation of state in designing of $CO_2$ marine geological storage process.

• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.60-66
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• 2006

Three differing sandstones, two synthetic and one field sample, have been tested ultrasonically under a range of confining pressures and pore pressures representative of in-situ reservoir pressures. These sandstones include: a synthetic sandstone with calcite intergranular cement produced using the CSIRO Calcite In-situ Precipitation Process (CIPS); a synthetic sandstone with silica intergranular cement; and a core sample from the Otway Basin Waarre Formation, Boggy Creek 1 well, from the target lithology for a trial $CO_2$ pilot project. Initial testing was carried on the cores at "room-dried" conditions, with confining pressures up to 65 MPa in steps of 5 MPa. All cores were then flooded with $CO_2$, initially in the gas phase at 6 MPa, $22^{\circ}C$, then with liquid-phase $CO_2$ at a temperature of $22^{\circ}C$ and pressures from 7 MPa to 17 MPa in steps of 5 MPa. Confining pressures varied from 10 MPa to 65 MPa. Ultrasonic waveforms for both P- and S-waves were recorded at each effective pressure increment. Velocity versus effective pressure responses were calculated from the experimental data for both P- and S-waves. Attenuations $(1/Q_p)$ were calculated from the waveform data using spectral ratio methods. Theoretical calculations of velocity as a function of effective pressure for each sandstone were made using the $CO_2$ pressure-density and $CO_2$ bulk modulus-pressure phase diagrams and Gassmann effective medium theory. Flooding the cores with gaseous phase $CO_2$ produced negligible change in velocity-effective stress relationships compared to the dry state (air saturated). Flooding with liquid-phase $CO_2$ at various pore pressures lowered velocities by approximately 8% on average compared to the air-saturated state. Attenuations increased with liquid-phase $CO_2$ flooding compared to the air-saturated case. Experimental data agreed with the Gassmann calculations at high effective pressures. The "critical" effective pressure, at which agreement with theory occurred, varied with sandstone type. Discrepancies are thought to be due to differing micro-crack populations in the microstructure of each sandstone type. The agreement with theory at high effective pressures is significant and gives some confidence in predicting seismic behaviour under field conditions when $CO_2$ is injected.