• Journal of Korea Water Resources Association
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• v.42 no.1
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• pp.51-60
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• 2009

2/3 of the Imjin River Basin area is located in North Korea, so it was hard to acquire reliable rainfall and hydrological information. This point is one of the factors that has added to flood damage. In this study, flood runoff for the river basin was simulated using hydrological radar, which is installed in an effort to reduce flood damage in the Imjin River Basin, which habitually suffers from flood damage. The feasibility of the distributed flood model was reviewed for the river basin, which is lacking in hydrological data such as rainfall and recent soil data. Based on the hydrograph, observed value was not consistent partially because of insufficient data, but peak discharge and the overall pattern showed relatively precise runoff results which can be applied in actual work.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.806-806
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• 2005

• Journal of Korea Water Resources Association
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• v.37 no.2
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• pp.145-154
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• 2004

The purpose of this study is to develop a real-time forecasting model in order to predict the flood runoff which has the nature of non-linearity and to verify applicability of neural network model for flood warning system. Developed model based on neural network, NRDFM(Neural River Discharge-Stage Forecasting Model) is applied to predict the flood discharge on Waekwann and Jindong stations in Nakdong river basin. As a result of flood forecasting on these two stations, it can be concluded that NRDFM-II is the best predictive model for real-time operation. In addition, the results of forecasting used on NRDFM-I and NRDFM-II model are not bad and these models showed sufficient probability for real-time flood forecasting. Consequently, it is expected that NRDFM in this study can be utilized as suitable model for real-time flood warning system and this model can perform flood control and management efficiently.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.5
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• pp.683-694
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• 2024

Flood control capacity enhancement measures in watersheds can be broadly categorized into structural and non-structural approaches. In this study, we propose the improvement of the flood control capacity in the Seomjin River basin through non-structural measures by optimizing the operation of the Seomjin River Dam, specifically by introducing a flexible flood season restricted water level (FSRWL). The flexible operation of FSRWL involves setting lower restricted water levels at the beginning of the flood season to increase flood control capacity and gradually raising them as the season progresses to manage flood control more effectively. As a structural measure, we examined the installation of riverside storage areas, a representative technique of nature-based solutions (NbS). Using the 2020 flood event as a case study, we analyzed the flood level reduction effects of implementing structural and non-structural measures both separately and simultaneously to identify the most effective and economical approach. The results indicate that the optimal flood prevention strategy for the main stream of the Seomjin River during the 2020 flood event involves operating the Seomjin River Dam FSRWL at EL. 190 m during the mid-flood season as a non-structural measure and installing a riverside storage area downstream of Godalgyo Bridge in Daepyeong-ri, Gokseong-gun as a structural measure.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.211-211
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• 2015

Mekong River is the world's $10^{th}$ longest river and runs through China's Yunnan province, Burma, Thailand, Laos, Cambodia and Vietnam. And Tonle Sap Lake, the largest fresh water body in Southeast Asia and the heart of Mekong River system, covers an area $2,500-3,000Km^2$ in dry season and $10,000-16,000Km^2$ in wet season. As previously noted, the water within Sap river flows from the Mekong River to Tonle Sap Lake in flood season (between June and October) and backward to Mekong River in dry season. Recently the flow regime of Sap River might be significantly affected by the development of large dams in upstream region of Mekong River. This paper aims at basic study about the large scale flood inundation of Cambodia using by CAESAR-Lisflood. CAESAR-Lisflood is a geomorphologic / Landscape evolution model that combines the Lisflood-FP 2d hydrodynamic flow model (Bates et al, 2010) with the CAESAR geomorphic model to simulate flow hydrograph and erosion/deposition in river catchments and reaches over time scales from hours to 1000's of years. This model is based on the simplified full Saint-Venant Equation so that it can simulate the interacted flow of between Mekong River and Tonle Sap Lake especially focusing on the flow direction change of Sap River by season.

• Water for future
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• v.26 no.4
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• pp.117-125
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• 1993

A flood -flow management system model of river basin has been developed in this study. The system model consists of the observation and telemetering system, the rainfall forecasting and data-bank system, the flood runoff simulation system, the dam operation simulation system, the flood forecasting simulation system and the flood warning system. The Multivariate model(MV) and Meterological-factor regression model(FR) for rainfall forecasting and the Streamflow synthesis and reservoir regulation(SSARR) model for flood runoff simulation have been adopted for the development of a new system model for flood-flow management. These models are calibrated to determine the optimal parameters on the basis of observed rainfall, streamflow and other hydrological data during the past flood periods. The flood-flow management system model with SSARR model(FFMM-SR,FFMM-SR(FR) and FFMM-SR(MV)), in which the integrated operation of dams and rainfall forecasting in the basin are considered, is then suggested and applied for flood-flow management and forecasting. The results of the simulations done at the base stations are analysed and were found to be more accurate and effective in the FFMM-SR and FFMM0-SR(MV).

• Journal of Industrial Technology
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• v.26 no.A
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• pp.129-137
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• 2006

In this research, we made a one and two-dimensional analysis of numerical data collected from the bend curvature of a bended river section. According to the result from the numerical analysis, the inflow ＆ output angle caused a water level deviation which increased with an increase of the flood discharge. From the water level deviation of our two-dimensional numerical model, we obtained the maximum slope of 6,67% when the inflow and output angle was 105 degrees and the flood discharge was 500 CMS. As for the right side, the differences with the one-dimensional numerical model were reduced when the angle was more than $90^{\circ}$. As for the left side the differences were reduced when the angle was more than $105^{\circ}$. For a river with more than 90 degrees bend curvature, a hydraulic experiment would be more appropriate than a numerical analysis.

• Journal of Korea Water Resources Association
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• v.44 no.10
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• pp.787-795
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• 2011

Extreme water events such as heavy rainfalls due to recent climate change are continually increasing and their scale has also shown an increasing trend. To overcome these natural disasters, this policy study suggests securing lateral river space as an effective method for extreme flood. To support the importance of restoration and expansion of lateral river space, Gumi upstream region of the Nakdong River basin was chosen as a target area and flood reduction analysis of the washland by using LISFLOOD model have been examined. The 500-year frequency flood was simulated for the estimation of possibly occurable flood level and it turns out that the secured lateral river space on the selected site effectively lowers about 0.53 m flood level and reduces the flood damage of the city on the lower reaches of the river. In addition, based on this result, multilateral river space securing plans were compared, and conservation easement and natural disaster insurance were suggested for sustainable and cost-effective alternatives. The costs of land purchase and conservation easement for securing the river space were also compared.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.1
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• pp.106-119
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• 2016

Flood risk map, flood damage map, disaster information map, inundation trace map are involved with the cartographic analysis of flood inundation based on prevention, preparation, restoration, response from natural disasters such as flood, flooding, etc. In this study, the analysis for channel and basin characteristics Chungju dam to Paldang dam of South han river after four river project. Flood scenario is selected to take advantage of design flood level of schematic design for river. Flood inundation of one dimensional non-uniform flow by using HEC-RAS with basin characteristics is accomplished and two dimensional unsteady flow was interpreted by using FLUMEN. Frequency analysis is carried out about each abundance of South han river for 100 year period, 200 year period and 500 year period. Flooding disaster area of 100 year period on 0.5m damage functions is 2378.8ha, 200 year period on 0.5m damage functions is 3155.2ha, 500 year period on 0.5m damage functions is 3995.3ha respectively. It will be significant data for decision making to establish inundation trace map for providing basic plan for river maintenance, land use plan, flood protection plan, application plan and getting information of flood expectation area.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.198-203
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• 2020

In this paper, we propose an artificial water level prediction system for small river flood prediction. River level prediction can be a measure to reduce flood damage. However, it is difficult to build a flood model in river because of the inherent nature of the river or rainfall that affects river flooding. In general, the downstream water level is affected by the water level at adjacent upstream. Therefore, in this study, we constructed an artificial intelligence model using Recurrent Neural Network(LSTM) that predicts the water level of downstream with the water level of two upstream points. The proposed artificial intelligence system designed a water level meter and built a server using Nodejs. The proposed neural network hardware system can predict the water level every 6 hours in the real river.