• Journal of Wetlands Research
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• v.14 no.4
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• pp.571-580
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• 2012

This study is on the purpose of leading Geomorphoclimatic Instantaneous Unit Hydrograph(GcIUH) by using GIS Techniques, and estimating trigger rainfall for predicting flash flood in Seolmacheon catchment, mountain river watershed. This study leads GcIUH by using GIS techniques, calculates NRCS-CN values for effective rainfall rate, and analyzes 2011 main rainfall events using estimated GcIUH. According to the results, the case of Memorial bridge does not exceed the amount of threshold runoff, however, the case of Sabang bridge shows that simulated peak flow, approximately $149.4m^3/s$, exceeds the threshold runoff. To estimate trigger rainfall, this study determines the depth of 50 year-frequency designed flood amount as a threshold water depth, and estimates trigger rainfall of flash flood in consideration of duration. Hereafter, this study will analyze various flood events, estimate the appropriateness of trigger rainfall as well as threshold runoff through this analysis, and develop prototype of Flash Flood Prediction System which is considered the characteristics of mountain river watershed on the basis of this estimation.

• Journal of Wetlands Research
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• v.20 no.4
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• pp.446-457
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• 2018

Forecasting of flood wave travel time is very important in terms of river management and operation. Recently, the hydrological environment of has changed due to the construction of multi-function weir in the river. It is necessary to analyze flood wave travel time, including hydraulic structures in the channel. The flood wave travel time according to the discharge and downstream water level operating conditions was analyzed using HEC-RASver5.0.3 which is capable a two-dimentional analysis. This study showed nonlinear characteristics of flood wave travel times due to increase of discharge and operating conditions. The results of this study will be helpful for the operation of multi-function weir as well as the river operation.

• KCID journal
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• v.17 no.2
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• pp.28-34
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• 2010

This study re-exams hydrologic stability on spillway outlet capacity of agricultural reservoirs using hydrologic data with current rainfall condition instead of project hydrologic data applied at design on Backgok reservoir located in Chungbuk province. It is concluded that Backgok reservoir is not hydrologically stable and therefore structural measures including the extension of spillway and non structural measures should be taken. Continuous basic plan for river maintenance including additional bank reinforcement to bottom river shall be carried out. Due to high peak flood with more than 290% compared to 200 year frequency probability flood which was design standard of the past in view of the results of calculating PMF according to revised design standard for reservoirs, there could a problem for securing rationality in case of applying PMF with design flood. Therefore, hydrological stability, construction, and maintenance cost shall be synthetically studied and reasonal application shall be made if the decision is made on applying PMF with design flood.

• Land and Housing Review
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• v.5 no.3
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• pp.203-214
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• 2014

The purpose of this paper is to introduce two integrated urban development projects in Japan that take full advantage of flood-control reservoirs: the Tetsugakudo Park Collective Housing Development Project and the Koshigaya Lake Town Project. The former project - implemented cooperatively by the Tokyo metropolitan government in charge of river management, Shinjuku and Nakano wards (in Tokyo) responsible for park management, and the Urban Renaissance Agency, a housing project developer - set a significant precedent for three-dimensional river use by realizing the three-dimensional integrated development of a flood control reservoir, a park, and collective housing. The Koshigaya Lake Town Project, launched as a drastic storm water management measure for a low-lying area often plagued by flooding, has achieved a sustainable coexistence between the waterfront environment and the urban living environment, with an artificial flood-control reservoir as the core for urban development. This project is fully committed to environmental coexistence through the optimal use of local environmental resources, with the cooperation of the central government, Saitama Prefecture and Koshigaya City.

• Proceedings of the Korea Water Resources Association Conference
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• 2004.05b
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• pp.62-71
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• 2004

There are 109 A class rivers in Japan. One purpose of river management is to reduce the flooding. For this purpose, government provides the information to public, as flood forecasting, rainfall forecasting and estimate the runoff magnitude to avoid the flood and inundation. In this paper, we introduce current situation of flood forecasting and rainfall forecasting in Japan, and we describe how to use the information of flood forecasting and rainfall forecasting in conjunction with current strategy for river management.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1427-1431
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• 2007

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.2
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• pp.13.2-20
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• 1995

An water balance model was formulated to simulate the change in water levels at the estuary reservoir from sluice gate releases and the inflow hydrographs, and an one-di- mensional flood routing model was formulated to simulate temporal and spatial varia- tions of flood hydrographs along the estuarine river. Flow rates through sluice gates were calibrated with data from the estuary dam, and the results were used for a water balance model, which did a good job in predicting the water level fluctuations. The flood routing model which used the results from two hydrologic models and the water balance model simulated hydrographs that were in close agreement with the observed data. The flood forecasting model was found to be applicable to real-time forecasting of water level fluc- tuations with reasonable accuracies.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.79-87
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• 1994

A real-time flood forecasting system(FLOFS) was developed for the real-time and predictive determination of flood discharges and stages, and to aid in flood management decisions in the Keum River Estuary Dam. The system consists of three subsystems : data subsystem, model subsystem, and user subsystem. The data subsystem controls and manages data transmitted from telemetering systems and simulated by models. The model subsystem combines various techniques for rainfall-runoff modeling, tidal-level forecasting modeling, one-dimensional unsteady flood routing, Kalman filtering, and autoregressivemovingaverage(ARMA) modeling. The user subsystem in a menu-driven and man-machine interface system.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.669-673
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• 2008

In this study, the new methodology which combines Kohonen self-organizing map(KSOM) neural networks model and the conventional neural networks models such as feedforward neural networks model and generalized neural networks model is introduced to forecast flood stage in Nakdong river, Republic of Korea. It is possible to train without output data in KSOM neural networks model. KSOM neural networks model is used to classify the input data before it combines with the conventional neural networks model. Four types of models such as SOM-FFNNM-BP, SOM-GRNNM-GA, FFNNM-BP, and GRNNM-GA are used to train and test performances respectively. From the statistical analysis for training and testing performances, SOM-GRNNM-GA shows the best results compared with the other models such as SOM-FFNNM-BP, FFNNM-BP, and GRNNM-GA and FFNNM-BP shows vice-versa. From this study, we can suggest the new methodology to forecast flood stage and construct flood warning system in river basin.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.179-179
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• 2015

Citarum River is one of the important river in West Java, Indonesia. During the rainy season, flood happens almost every year in Upper Citarum Watershed, hence, it is necessary to establish the countermeasure in order to prevent and mitigate flood damages. Since the lack of hydrological data for the modelling is common problem in this area, it is difficult to prepare the countermeasures. Therefore, we used Rainfall-Runoff-Inundation (RRI) Model developed by Sayama et al. (2010) as the hydrological and inundation modelling for evaluating the inundation case happened in Upper Citarum Watershed, West Java, Indonesia and the satellite based information such as rainfall (GSMaP), landuse and so on instead of the limited hydrological data. In addition, 3 arc-second HydroSHEDS Digital Elevation Model (DEM) is used. To verify the model, the observed data of Nanjung water stage gauging station and the daily observation data are used. Simulated inundation areas are compared with the flood extent figure from Upper Citarum Basin Flood Management Project (UCBFM).