• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.438-438
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• 2021

우리나라의 수질오염총량관리제도는 수계 내 모든 유역을 관리대상으로 동일 기준유량 조건에 동일한 대상물질로 관리하고 있지만, 본류는 지류의 영향을 받고 있으며 지류는 사람이 거주하는 지역 인근에 있어 본류 수질에 직접적인 영향을 미치고 있다. 이는 지류의 시급한 개선이 필요한 오염물질의 실질적인 관리가 어려워 이를 개선하기 위해 오염도가 높은 지류의 총량관리를 위한 지류총량제도의 추가 도입이 필요한 실정이다. 본 연구에서는 지류총량제 시행에 따른 효과를 예측하기 위해 팔당수계 유역을 소유역 단위로 분할하고 HSPF 모형을 적용하여 팔당수계 소유역 지류에서의 수질 변화 양상이 본류에 미치는 영향을 분석하였다. 연구대상지역은 팔당수계 중권역 유역(남한강 하류 유역, 경안천 유역, 북한강 하류 유역)으로 구분하고 유역 유출 및 수질 모델링은 지류하천을 포함하는 57개 소유역을 대상으로 수행하였다. 입력자료는 공간자료(표고, 경사, 토지이용, 토양도 등)와 기상자료(춘천, 양평, 이천, 수원관측소)는 2008년~2018년의 강수량, 최고기온, 최저기온, 평균풍속, 평균습도 등의 시단위 자료를 사용하였다. 모의결과, BOD는 남한강 하류유역의 주요 지천 유역인 복하천, 양화천, 청미천 및 흑천 유역에서 0.54~0.56mg/L의 범위로 주변 유역보다 높게 나타났으며, 경안천 유역은 경안천 유역의 중·하류 유역에서 2.63~4.22mg/L의 범위로 높게 나타났고, 북한강 유역은 조종천 하류 및 북한강 상류 유역에서 1.36~3.31mg/L의 범위로 주변 유역보다 높게 나타났다. T-P는 남한강 하류 유역은 주요 지천 유역인 복하천, 양화천, 청미천 유역에서 0.07~0.19mg/L의 범위로 주변 유역보다 높게 나타났고, 남한강 하류 유역의 중간 지점 유역인 한강(E1, E2, E4, E6)에서 높게 나타났다. 경안천 유역은 중·하류 유역의 좌안측 유역인 경안(A4, A3, B2, B1, F9)에서 0.1~0.14mg/L의 범위로 높게 나타났으며, 북한강 유역은 전체 유역에서 0.06mg/L 이하로 남한강 하류 및 경안천 유역보다 전반적으로 낮게 나타났다. 이와 같이 지류총량관리에 HSPF 모형의 적용은 가능하였으나 HSPF 모형을 이용한 소유역 단위의 유량 및 수질 예측을 위해서는 기존의 유량 및 수질 관측망을 소유역 단위로 좀 더 정밀하게 계획하는 것이 필요하다고 판단된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.159-167
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• 2010

The purpose of this study is to get the adjusted radar rainfalls by ANN(Artificial Neural Network) method. In the case of radar rainfall, it has an advantage of spatial distribution characteristics of rainfall while point rainfall has an advantage at the point. Therefore we adjusted the radar rainfall by ANN method considering the advantages of two rainfalls of radar and point. This study constructed two ANN models of Model I and Model II for radar rainfall adjustment. We collected the three rainfall events and adjusted the radar rainfall for Anseong-cheon basin. The two events were inputted into the Modeland Model to derive the optimum parameters and the rest event was used for validation. The adjusted radar rainfalls by ANN method and the raw radar rainfall were used as the input data of ModClark model which is a semi-distributed model to simulate the runoff. As the results of the simulation, the runoff by raw radar rainfall were overestimated but the peak time and peak runoff from the adjusted rainfall by ANN were well fitted to the observed hydrograph.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.721-728
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• 2023

Agricultural drought is triggered by a depletion of moisture content in the soil, which hinders photosynthesis and thus increases carbon dioxide (CO₂) concentrations in the atmosphere. The aim of this study is to analyze the relationship between soil moisture (SM) and vegetation activity toward quantifying CO₂ concentration in the atmosphere. To this end, the MODerate resolution imaging spectroradiometer (MODIS), an optical multispectral sensor, was used to evaluate two regions in South Korea for validation. Vegetation activity was analyzed through MOD13A1 vegetation indices products, and MODIS gross primary productivity (GPP) product was used to calculate the CO₂ flux based on its relationship with respiration. In the case of SM, it was calculated through the method of applying apparent thermal inertia (ATI) in combination with land surface temperature and albedo. To validate the SM and CO₂ flux, flux tower data was used which are the observed measurement values for the extreme drought period of 2014 and 2015 in South Korea. These two variables were analyzed for temporal variation on flux tower data as daily time scale, and the relationship with vegetation index (VI) was synthesized and analyzed on a monthly scale. The highest correlation between SM and VI (correlation coefficient (r) = 0.82) was observed at a time lag of one month, and that between VI and CO₂ (r = 0.81) at half month. This regional study suggests a potential capability of MODIS-based SM, VI, and CO₂ flux, which can be applied to an assessment of the global view of the agricultural drought by using available satellite remote sensing products.

• Journal of the Korean Institute of Gas
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• v.27 no.4
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• pp.19-26
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• 2023

Earthquakes are one of the most important disasters affecting underground structures. Urban gas underground pipes may cause safety problems of structures in the event of an earthquake. Since Korea began digital observation, the number of earthquakes has been steadily increasing. The seismic design standard for urban gas pipes was established in 2008, but it is difficult to estimate the impact of pipes in the event of an earthquake based on the installation of pipes. In this study, structural analysis was performed on PE (polyethylene pipe) pipes and PLP (polyethylene coated steel pipe) pipes, which are mainly used as buried pipes in Korea, according to environmental and pipe variables in the event of an earthquake. This study sought to find the variables of the most vulnerable buried pipe by modeling pipes through Computer Aided Engineering (CAE) and generating displacement on the ground. Through this study, it was confirmed that the larger the elastic modulus of the soil, the deeper the buried depth, the smaller the tube diameter, and the higher the pressure, the more PLP pipes are affected by earthquakes than PE. Based on these results, the vulnerable points of buried urban gas pipes are inferred and used for special inspections of buried pipes in the event of an earthquake.

• Journal of Korean Society of Disaster and Security
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• v.16 no.4
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• pp.75-84
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• 2023

Many developing countries face challenges in estimating long-term discharge due to the lack of hydrological data for water supply planning, making it difficult to establish a rational water supply plan for decision-making on water distribution. The study area, the Bandung region in Indonesia, is experiencing rapid urbanization and population concentration, leading to a severe shortage of freshwater. The absence of water reservoir prediction methods has resulted in a water supply rate of approximately 20%. In this study, we aimed to propose an approach for predicting water reservoirs in developing countries by analyzing water safety and potential water supply using the MODSIM (Modified SIMYLD) network model. To assess the suitability of the MODSIM model, we applied the unit hydrograph method to calculate long-term discharge based on 19 years of discharge data (2002-2020) from the Pataruman observation station. The analysis confirmed alignment with the existing monthly optimal operation curve. The analysis of power plant capacity revealed a difference of approximately 0.30% to 0.50%, and the water intake safety at the Pataruman point showed 1.64% for Q95% flow and 0.47% for Q355 flow higher. Operational efficiency, compared to the existing reservoir optimal operation curve, was measured at around 1%, confirming the potential of using the MODSIM network model for water supply evaluation and the need for water supply facilities.

• The Journal of the Acoustical Society of Korea
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• v.43 no.3
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• pp.293-304
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• 2024

In this paper, efficient and reliable methodologies for conducting sea trials to evaluate the performance of hull-mounted sonar systems is discussed. These systems undergo performance verification during ship construction via sea trials. However, the evaluation procedures often lack detailed consideration of variabilities in detection performance due to seabed topography, seasonal factors. To resolve this issue, temperature and salinity structure data were collected from 1967 to 2022 using ARGO floats and ocean observers data. The paper proposes an efficient and reliable sea trial method incorporating Bellhop modeling. Furthermore, a machine learning model applying a Physics-Informed Neural Networks was developed using the acquired data. This model predicts the sound speed profile at specific points within the sea trial area, reflecting seasonal elements of performance evaluation. In this study, we predicted the seasonal variations in sound speed structure during sea trial operations at a specific location within the trial area. We then proposed a strategy to account for the variability in detection performance caused by seasonal factors, using results from Bellhop modeling.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.3
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• pp.135-142
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• 2016

The aim of this study was to confirm the improvement of efficiency for temperature estimation at 0600 and 1500 LST by using a simple method for estimating temperature lapse rate modulated by the amount of clouds in comparison with the case adopting the existing single temperature lapse rate ($-6.5^{\circ}C/km$ or $-9^{\circ}C/km$). A catchment of the 'Hadong Watermark2,' which includes Hadong, Gurye, and Gwangyang was selected as the area for evaluating the practicality of the temperature lapse rate estimation method. The weather data of 0600 and 1500 LST at 12 weather observation sites within the catchment were collected during the entire year of 2015. Also, the 'sky condition' of digital forecast products of KMA in 2015 ($5{\times}5km$ lattice resolution) were overlapped with the catchment of the 'Hadong Watermark2,' to calculate the spatial average value within the catchment, which were used to simulate the 0600 and 1500 LST temperature lapse rate of the catchment. The estimation errors of the temperatures at 0600 LST were ME $-0.39^{\circ}C$ and RMSE $1.45^{\circ}C$ in 2015, when applying the existing temperature lapse rate. Using the estimated temperature lapse rate, they were improved to ME $-0.19^{\circ}C$ and RMSE $1.32^{\circ}C$. At 1500 LST, the effect of the improvements found from the comparison between the existing temperature lapse rate and the estimated temperature lapse rate were minute, because the estimated lapse rate of clear days is not very different from the existing lapse rate. However, the estimation errors of the temperatures at 1500 LST during cloudy days were improved from ME $-0.69^{\circ}C$, RMSE $1.54^{\circ}C$ to ME $-0.51^{\circ}C$, RMSE $1.19^{\circ}C$.

• Journal of the Korean earth science society
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• v.27 no.2
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• pp.159-176
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• 2006

Geographic factors and mathmatical location of the Korean Peninsula have great influences on the variation patterns and appearances over a period of ten days of summer precipitation. In order to clarify the influence of several climate factors on precise climate classification in the middle part region of the Korea, weather entropy and the information ratio were calculated on the basis of information theory and of the data of 25 site observations. The data used for this study are the daily precipitation phenomenon over a period of ten days of summer during the recent thirteen years (1991-2003) at the 25 stations in the middle part region of the Korea. It is divided into four classes of no rain, $0.1{\sim}10.0mm/day,\;10.1{\sim}30.0mm/day$, 30.1mm over/day. Their temporal and spatial change were also analyzed. The results are as follows: the maximum and minimum value of calculated weather entropy are 1.870 bits at Chuncheon in the latter ten days of July and 0.960 bits at Ganghwa during mid September, respectively. And weather entropy in each observation sites tends to be larger in the beginning of August and smaller towards the end of September. The largest and smallest values of weather representative ness based on information ratio were observed at Chungju in the beginning of June and at Deagwallyeong towards the end of July. However, the largest values of weather representativeness came out during the middle or later part of September when 15 sites were adopted as the center of weather forecasting. The representative core region of weather forecasting and climate classification in the middle part region of the Korea are inside of the triangle region of the Buyeo, Incheon, and Gangneung.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.437-448
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• 2016

Some previous researches suggested a transit trip destination inference method by constructing trip chains with incomplete(missing destination) smart card dataset obtained on the entry fare control systems. To explore the feasibility of the transit trip destination inference method, the transit trip chains are constructed from the pre-paid smart card tagging data collected in Busan on October 2014 weekdays by tracing the card IDs, tagging times(boarding, alighting, transfer), and the trip linking distances between two consecutive transit trips in a daily sequences. Assuming that most trips in the transit trip chains are linked successively, the individual transit trip destination zones are inferred as the consecutive linking trip's origin zones. Applying the model to the complete trips with observed OD reveals that about 82% of the inferred trip destinations are the same as those of the observed trip destinations and the inference error defined as the difference in distance between the inferred and observed alighting stops is minimized when the trip linking distance is less than or equal to 0.5km. When applying the model to the incomplete trips with missing destinations, the overall destination missing rate decreases from 71.40% to 21.74% and approximately 77% of the destination missing trips are the single transit trips for which the destinations can not be inferable. In addition, the model remarkably reduces the destination missing rate of the multiple incomplete transit trips from 69.56% to 6.27%. Spearman's rank correlation and Chi-squared goodness-of-fit tests showed that the ranks for transit trips of each zone are not significantly affected by the inferred trips, but the transit trip distributions only using small complete trips are significantly different from those using complete and inferred trips. Therefore, it is concluded that the model should be applicable to derive a realistic transit trip patterns in cities with the incomplete smart card data.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.106-120
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• 2006

Natural or man-made disaster has been expected to be one of the potential themes that can integrate human geography and physical geography. Typhoons like Rusa and Maemi caused great loss to insurance companies as well as public sectors. We have implemented a natural disaster management system for a private insurance company to produce better estimation of hazards from high wind as well as calculate vulnerability of damage. Climatic gauge sites and addresses of contract's objects were geo-coded and the pressure values along all the typhoon tracks were vectorized into line objects. National GIS topog raphic maps with scale of 1: 5,000 were updated into base maps and digital elevation model with 30 meter space and land cover maps were used for reflecting roughness of land to wind velocity. All the data are converted to grid coverage with $1km{\times}1km$. Vulnerability curve of Munich Re was ad opted, and preprocessor and postprocessor of wind velocity model was implemented. Overlapping the location of contracts on the grid value coverage can show the relative risk, with given scenario. The wind velocities calculated by the model were compared with observed value (average $R^2=0.68$). The calibration of wind speed models was done by dropping two climatic gauge data, which enhanced $R^2$ values. The comparison of calculated loss with actual historical loss of the insurance company showed both underestimation and overestimation. This system enables the company to have quantitative data for optimizing the re-insurance ratio, to have a plan to allocate enterprise resources and to upgrade the international creditability of the company. A flood model, storm surge model and flash flood model are being added, at last, combined disaster vulnerability will be calculated for a total disaster management system.