• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.207-221
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• 2014

Recently, due to global warming, climate change has affected short time concentrated local rain and unexpected heavy rain which is increasingly causing life and property damage. Therefore, this paper studies the characteristic of localized heavy rain and flash flood in Nakdong basin study area by applying Data Mining method to predict flood and constructing water level predicting model. For the verification neural network from Data Mining method and hydraulic flood routing was used for flood from July 1989 to September 1999 in Nakdong point and Iseon point was used to compare flood level change between observed water level and SAM (Slope Area Method). In this research, the study area was divided into three cases in which each point's flood discharge, water level was considered to construct the model for hydraulic flood routing and neural network based on artificial intelligence which can be made from simple input data used for comparison analysis and comparison evaluation according to actual water level and from the model.

• Journal of Korea Water Resources Association
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• v.38 no.6 s.155
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• pp.485-494
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• 2005

It is very important to analyze the correlation between discharge and water quality. The observation of discharge and water quality are effective at same point as well as same time for real time management. But no less significant is the fact that there are some of real time water quality monitoring stations far from the T/M water stage. Pyeongchanggang station is one of them. In this case, it need to observe accurate discharge data, and to develop forecasting program or system using real time data. In this paper, discharge on Pyeongchanggang station was calculated by developed runoff neural network model, and compared with discharge using WMS(Watershed Modeling System) model. WMS shows better results when peak discharge is small and hydrograph is smooth. Forecasted discharge of neural network model have achieved the highest overall accuracy of specific discharge and WMS. Neural network model forecast change of discharge well on unrecored station.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1653-1661
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• 2022

In this study, the classification of cold water and normal water based on Geo-Kompsat 2A images was performed. Daily mean surface temperature products provided by the National Meteorological Satellite Center (NMSC) were used, and convolution neural network (CNN) deep learning technique was applied as a classification algorithm. From 2019 to 2022, the cold water occurrence data provided by the National Institute of Fisheries Science (NIFS) were used as the cold water class. As a result of learning, the probability of detection was 82.5% and the false alarm ratio was 54.4%. Through misclassification analysis, it was confirmed that cloud area should be considered and accurate learning data should be considered in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.500-504
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• 2008

The objective of this paper is to evaluate the feasibility of using an optimization model as a effective way to search conjunctive operation scheme to meet two conditions; one is to minimize the electric cost for pumping and another is to meet the water demand for satisfying customers. The feasibility is confirmed as comparing the best combinations of pumps between multi-regional water supply networks from multiple sources which are obtained through an optimization modeling and EPAnet modeling. KModsim model, a network optimization model, was used to determine conjunctive operation scheme in the pipe system. KModsim, based on Lagrangian Relaxation algorithm, is useful for modeling network system and obtaining simultaneously pump combination and water allocation with given input option such as energy unit cost supplying from a source into a consumer, operating pumping combination. This study develops the procedure of determining optimal conjunctive operation scheme with using KModsim model. As a study region, the water supplying systems of the Geojae-city in the Geongsang Namdo Province was selected and investigated. The EPAnet hydraulic simulation result(Ryu et al, 2007, KSWW) gave input data for optimization model; energy unit price(won/$m^3$), water service available area etc.. It was assured that the combination of pump operation through optimum conjunctive operation is to be optimum scheme to obtain the best economic water allocation with comparison to the hydraulic simulation result such as electric cost and pump combination cases. The results obtained through the study are as follows. First, It was found that a well-allocated water supply scheme, the best combination of pump operation through optimum joint operation, promises to save the electric cost and satisfy all operational goals such as stability and revenues during the period. Second, an application of KModSim, a network model, gave the amount of water allocation from each source to a consumer with consideration of economic supply. Finally, in a service area available to supply through conjunctive operation of existing inter-regional water supply networks within short distance, a conjunctive operation is useful for determining each transmission pipeline's service area and maximizing the effectiveness of optimizations in pumping operation time.

• Proceedings of the Korea Water Resources Association Conference
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• 1998.05a
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• pp.97-102
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• 1998

• Proceedings of the Korea Water Resources Association Conference
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• 1998.05a
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• pp.179-184
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• 1998

• Journal of Korean Society on Water Environment
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• v.23 no.5
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• pp.697-704
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• 2007

This study proposes an integrated technique of Genetic Algorishim (GA) and Geographic Information System (GIS) for designing the water quality monitoring networks. To develop solution scheme of the integrated system, fitness functions are defined by the linear combination of five criteria which stand for the operation objectives of water quality monitoring stations. The criteria include representativeness of a river system, compliance with water quality standards, supervision of water use, surveillance of pollution sources and examination of water quality changes. The fitness level is obtained through calculations of the fitness functions and input data from GIS. To find the most appropriate parameters for the problems, the sensitivity analysis is performed for four parameters such as number of generations, population sizes, probability of crossover, and probability of mutation. Using the parameters resulted from the sensitivity analysis, the developed system proposed 110 water quality monitoring stations in the Nakdong River. This study demonstrates that the integrated technique of GA and GIS can be utilized as a decision supporting tool in optimized design for a water quality monitoring network.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.1389-1396
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• 2008

The recent Sichuan earthquake(2008) in China and Iwate-Miyazaki earthquake(2008) in Japan give Korea peninsula warning that it is no more safety zone against damage by earthquake events. So, rapid and appropriate countermeasures for dam operation and management against earthquake are needed. In Korea earthquake design standard(MOCT, 1997) has been revised after Kobe earthquake. Installation of seismometer and monitoring of earthquake for special class dams is requlated in dam aseismic design standard(MOCT, 2001). Accelerometer installation project for existing dams has been carrying out by K-water to establish an earthquake network for dam safety. Real-time dam earthquake monitoring network has also been developed to detect an earthquake efficiently and to warn to dam administrators as soon as possible. In this study, dam real-time earthquake monitoring system developed by K-water was introduced and applicability of real earthquake record measured by this system to dam safety management was illustrated.

• International Journal of Computer Science & Network Security
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• v.21 no.1
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• pp.201-206
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• 2021

The significance of high-quality development and green total factor productivity has attracted widespread attention and research, while few studies on green total factor productivity that considers the use of water resources have been conducted in the context of water shortages and water stress. In this study, the green total factor productivity of water use from 2005 to 2015 in mainland China is evaluated based on the global Malmquist-Luenberger productivity index. Results show that: (1) China's green total factor productivity of water use has been improving since 2005 with an annual global Malmquist-Luenberger productivity index of 1.0104. (2) At the regional level, the eastern zone in mainland China owns the highest green total factor productivity of water use, while that in the intermediate zone ranks last. (3) The green total factor productivity of water use in the southern region (1.0113) significantly higher than that in the northern region (1.0095), and also higher than the national average level in the same period. BPC index has been the most important incluencing factor of green total factor productivity of water use at both national level and regional level since 2011.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.245-249
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• 2005

The numerical simulation of a two-phase flow In a discrete fracture network model is presented in this paper, The purpose of this work is to consider density-driven flows induced by the density difference between hot autochthonous heavy brines and injected cold water. Mechanical consequences of high pressure waves on the fracture permeability and heat exchanges between fluids and rock matrix are neglected in this study. The finite volume method is employed to discretize spatially and the system is solved by using an IMPES(Implicit Pressure-Explicit Saturation) scheme. In order to solve the strong non-linearity of the system, the Newton-Raphson algorithm is used. The well-known Buckeley-Leverett problem is adapted to validate results calculated from the model and a relatively good agreement is obtained.