• Journal of Convergence for Information Technology
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• v.10 no.10
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• pp.115-122
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• 2020

Due to the climate change, torrential rain downpours unprecedentedly, and urban areas repeatedly suffer from the inundation damages, which cause miserable loss of property and life by flooding. Two major reasons of urban flooding are river inundation and inland submergence. However, most of previous studies ignored the comprehensive mechanism of those two factors, and showed discrepancy and inadequacy due to the linear summation of each analysis result. In this study, river inundation and inland flooding were analyzed at the same time. Petrov-stabilizing scheme was adopted to capture the shock wave accurately by which river inundation can be modularized. In addition, flux-blocking alrotithm was introduced to handle the wet and dry phenomena. Sink/source terms with EGR (Exponentially Growth Rate) concept were incorporated to the shallow water equations to consider inland flooding. Comprehensive simulation implementing inland flooding and river inundation at the same time produced satisfactory results because it can reflect the counterbalancing and superposition effects, which provided accurate prediction in flooding analysis.

• Spatial Information Research
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• v.20 no.1
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• pp.9-18
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• 2012

South Korea has many landslides caused by heavy rains during summer time recently and the landslides continue to cause damages in many places. These landslides occur repeatedly each year, and the frequency of landslides is expected to increase in the coming future due to dramatic global climate change. In Korea, 81.5% of the population is living in urban areas and about 1,055 million people are living in Seoul. In 2011, the landslide that occurred in Seocho-dong killed 18 people and about 9% of Seoul's area is under the same land conditions as Seocho-dong. Even the size of landslide occurred in a city is small, but it is more likely to cause a big disaster because of a greater population density in the city. So far, the effort has been made to identify landslide vulnerability and causes, but now, the new dem and arises for the prediction study about the areal extent of disaster area in case of landslides. In this study, the diffusion model of the landslide disaster area was established based on Cellular Automata(CA) to analyze the physical diffusion forms of landslide. This study compared the accuracy with the Seocho-dong landslide case, which occurred in July 2011, applying the SCIDDICA model and the CAESAR model. The SCIDDICA model involves the following variables, such as the movement rules and the topographical obstacles, and the CAESAR model is also applied to this process to simulate the changes of deposition and erosion.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.1
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• pp.760-767
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• 2020

Sustainable growth of hydroelectric power plants is expected in consideration of climate change and energy security. However, hydroelectric power plants always have a risk of water hammer damage, and safety assurance is very important. The water hammer phenomenon commonly occurs during operations such as rapid opening and closing of the valves and pump/turbine shutdown in pipe systems, which is more common in cases of emergency shutdown. In this study, a computational numerical model was developed using the MOC-FDM scheme to reflect the mechanism of water hammer occurrence. The proposed model was implemented in boundary conditions such as reservoir, pipeline, valve, and pump/turbine conditions and then applied to simulate hypothetical case studies. The analysis results of the model were verified using the analysis results at the main points of the pipe systems. The model produced reasonably good performance and was validated by comparison with the results of the SIMSEN package model. The model could be used as an efficient tool for the safety assessment of hydroelectric power plants based on accurate prediction of transient behavior in the operation of hydropower facilities.

• Journal of Korea Water Resources Association
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• v.51 no.6
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• pp.503-514
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• 2018

In recent, the hydrological regime of the Mekong river is changing drastically due to climate change and haphazard watershed development including dam construction. Information of hydrologic feature like streamflow of the Mekong river are required for water disaster prevention and sustainable water resources development in the river sharing countries. In this study, runoff simulations at the Kratie station of the lower Mekong river are performed using SWAT (Soil and Water Assessment Tool), a physics-based hydrologic model, and LSTM (Long Short-Term Memory), a data-driven deep learning algorithm. The SWAT model was set up based on globally-available database (topography: HydroSHED, landuse: GLCF-MODIS, soil: FAO-Soil map, rainfall: APHRODITE, etc) and then simulated daily discharge from 2003 to 2007. The LSTM was built using deep learning open-source library TensorFlow and the deep-layer neural networks of the LSTM were trained based merely on daily water level data of 10 upper stations of the Kratie during two periods: 2000~2002 and 2008~2014. Then, LSTM simulated daily discharge for 2003~2007 as in SWAT model. The simulation results show that Nash-Sutcliffe Efficiency (NSE) of each model were calculated at 0.9(SWAT) and 0.99(LSTM), respectively. In order to simply simulate hydrological time series of ungauged large watersheds, data-driven model like the LSTM method is more applicable than the physics-based hydrological model having complexity due to various database pressure because it is able to memorize the preceding time series sequences and reflect them to prediction.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.105-116
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• 2011

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, the exact relationship and the spatial variability analysis of hydrometeorological elements and characteristic factors is critical elements to reduce the uncertainty in rainfall -runoff model. In this study, radar rainfall grid resolution and grid resolution depending on the topographic factor in rainfall - runoff models were how to respond. In this study, semi-distribution of rainfall-runoff model using the model ModClark of Inje, Gangwon Naerin watershed was used as Gwangdeok RADAR data. The completed ModClark model was calibrated for use DEM of cell size of 30m, 150m, 250m, 350m was chosen for the application, and runoff simulated by the RADAR rainfall data of 500m, 1km, 2km, 5km, 10km from 14 to 17 on July, 2006. According to the resolution of each grid, in order to compare simulation results, the runoff hydrograph has been made and the runoff has also been simulated. As a result, it was highly runoff simulation if the cell size is DEM 30m~150m, RADAR rainfall 500m~2km for peak flow and runoff volume. In the statistical analysis results, if every DEM cell size are 500m and if RADAR rainfall cell size is 30m, relevance of model was higher. Result of sensitivity assessment, high index DEM give effect to result of distributed model. Recently, rainfall -runoff analysis is used lumped model to distributed model. So, this study is expected to make use of the efficiently decision criteria for configurated models.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.2
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• pp.97-108
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• 2012

A Lagrangian particle tracking model coupled with the ECOM3D were used to study on the behavior of fresh water released from the Namgang Dam in terms of residence time in Kangjin Bay, South Sea, Korea. Model was calibrated until skill cores for elevation, velocity, temperature and salinity are satisfied over 85%. In the numerical simulation, particles were released in 1 hour time interval from the northern boundary. The different patterns of particle trajectory are identified under the varying dynamics from tidal to density-driven current. The average residence time of total particles are approximately 65.9 hours in the entire Kangjin Bay. The average residence time were increased from 55~65 to 70~80 hours during maximum discharge period. Discharge rate of fresh water and average residence time in the Kangjin Bay is high correlated with correlation coefficient over 0.81.

• Journal of Korea Water Resources Association
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• v.34 no.5
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• pp.511-519
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• 2001

Global warming has begun since the industrial revolution and it is getting worse recently. Even though the increase of greenhouse gases such as $CO_2$is thought to be the main cause for glogal warming, its impact on global climate has not been revealed clearly in rather quantitative manners. The objective of this research is to predict the hydrological environment changes in the Daechung Dam basin due to the global warming. A mesoscale atmospheric/hydrologic model (IRSHAM96 model) is used to predict the possible changes in precipitation and temperature in the Daechun Dam basin. The simulation results of IRSHAM96 model and a conceptual water balance model are used to analyze the changes in soil moisture, evapotranspiration and runoff in the Daechung Dam basin. From the simulation results using the water balance model for 1x$CO_2$and 2x$CO_2$situations, it has been found that the runoff would be decreased in dry season, but increased in wet season due to the global warming. Therefore, it is predicted that the frequency of drought and flood occurrences in the Daechung Dam basin would be increased in 2x$CO_2$condition.

• Journal of Korea Water Resources Association
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• v.41 no.3
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• pp.293-303
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• 2008

Reservoir turbidity flows degrade the efficiency and sustainability of water supply system in many countries located in monsoon climate region. A decision support system called RTMMS aimed to assist reservoir operations was developed for the real time monitoring, modeling, and management of turbidity flows induced by flood runoffs in Daecheong reservoir. RTMMS consists of a real time data acquisition module that collects and stores field monitoring data, a data assimilation module that assists pre-processing of model input data, a two dimensional numerical model for the simulation of reservoir hydrodynamics and turbidity, and a post-processor that aids the analysis of simulation results and alternative management scenarios. RTMMS was calibrated using field data obtained during the flood season of 2004, and applied to real-time simulations of flood events occurred on July of 2006 for assessing its predictive capability. The system showed fairly satisfactory performance in reproducing the density flow regimes and fate of turbidity plumes in the reservoir with efficient computation time that is a vital requirement for a real time application. The configurations of RTMMS suggested in this study can be adopted in many reservoirs that have similar turbidity issues for better management of water supply utilities and downstream aquatic ecosystem.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.1
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• pp.128-136
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• 2008

Recently, the unusual climate change is happening from the global warming in the whole world, the Korean peninsula is also no exception. It is predicted by many researchers that, in the near future, the Super-Typhoon of overwhelming power will occur due to rising temperatures on the sea surface around the Korean peninsula. In this study, numerical simulation has been performed with the Super-Typhoons which combined route of Typhoon Maemi with typhoon conditons of Hurricane Katrina (New Oleans in U.S.A, 2005), Typhoon Durian (philippine, 2006) and Typhoon Vera (Ise Bay in Japan, 1959) at Busan and Gyeongnam coastal area which has been badly damaged due to storm surge every year. From the numerical results, it is revealed that the storm surge heights of the Super-Typhoons are higher than that of Maemi, specially the storm surge height in the case of Katrina is about 4 times larger. So, it can be pointed out that the construction of countermeasures against disasters are very important in order to prepare against an attack of the Super-Typhoons.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.4
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• pp.23-32
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• 2019

Increasing crop production with the same amount of resources is essential for enhancing the economy in agriculture. The first prerequisite is to understand relationships between the resources. The concept of WEF (Water-Energy-Food) nexus analysis was first introduced in 2011, which helps to interpret inter-linkages among the resources and stakeholders. The objective of this study was to analyze energy-water nexus in greenhouse cultivation by estimating reference evapotranspiration and heating load. For the estimation, this study used the physical model to simulate the inside temperature of the agricultural greenhouse using heating, solar radiation, ventilated and transferred heat losses as input variables. For estimating reference evapotranspiration and heating load, Penman-Monteith equation and seasonal heating load equation with HDH (Heating Degree-Hour) was applied. For calibration and validation of simulated inside temperature, used were hourly data observed from 2011 to 2012 in multi-span greenhouse. Results of the simulation were evaluated using $R^2$, MAE and RMSE, which showed 0.75, 2.22, 3.08 for calibration and 0.71, 2.39, 3.35 for validation respectively. When minimum setting temperature was $12^{\circ}C$ from 2013 to 2017, mean values of evapotranspiration and heating load were 687 mm/year and 2,147 GJ/year. For $18^{\circ}C$, Mean values of evapotranspiration and heating load were 707 mm/year and 5,616 GJ/year. From the estimation, the relationship between water and heat energy was estimated as 1.0~2.6 GJ/ton. Though additional calibrations with different types of greenhouses are necessary, the results of this study imply that they are applicable when evaluating resource relationship in the greenhouse cultivation complex.