• Journal of Korea Water Resources Association
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• v.49 no.1
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• pp.19-28
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• 2016

The objective of this study is the generation of the gridded flash flood index using the gridded hydrologic components of TOPLATS land surface model and statistic flash flood index model. The accuracy of this method is also examined in this study. The study area is the national capital region of Korea, and 38 flash flood damages had occurred from 2009 to 2012. The spatio-temporal resolutions of land surface model are 1 h and 1 km, respectively. The gridded meteorological data are generated using the inverse distance weight method with automatic weather stations (AWSs) of Korea Meteorological Administration (KMA). The hydrological components (e.g., surface runoff, soil water contents, and water table depth) of cells corresponding to the positions of 38 flood damages reasonably respond to the cell based hourly rainfalls. Under the total rainfall condition, the gridded flash flood index shows 71% to 87% from 4 h to 6 h in the lead time based on the rescue request time and 42% to 52% of accuracy at 0 h which means that the time period of the lead time is in a limited rescue request time. From these results, it is known that the gridded flash flood index using the cell based hydrological components from land surface model and the statistic flash flood index model have a capability to predict flash flood in the mountainous area.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.605-612
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• 2006

In this study(II), The developed rainfall forecast model was applied to the NakDong River Basin for the heavy rainfall on 6th to 16th of August in 2002. The results demonstrated that the rainfall forecasts of 3 hours lead time showed good agreement with observed data. The inundation aspect of simulation depends on actual levee failure in the same basin. Rainfall forecasts were used for flood amount computation in the target watershed. Also the flood amount in the target watershed was used on boundary condition for flood inundation simulation in a protected lowland and a river. The results of simulation are consistent with actuality inundation traces and flood level data of the target watershed. This study provides practical applicability of satellite data in rainfall forecast of extreme events such as heavy rainfall or typhoon. Also this study presented an advanced integrated model of rainfall, runoff, and inundation analysis which can be applicable for flood disaster prevention and mitigation.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.17-27
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• 2020

The objective of this study was to assess the flood probability based on temporal distribution of forecasted-rainfall in Cheongmicheon watershed. In this study, 6-hr rainfalls were disaggregated into hourly rainfall using the Multiplicative Random Cascade (MRC) model, which is a stochastic rainfall time disaggregation model and it was repeated 100 times to make 100 rainfalls for each storm event. The watershed runoff was estimated using the Clark unit hydrograph method with disaggregated rainfall and watershed characteristics. Using the peak discharges of the simulated hydrographs, the probability distribution was determined and parameters were estimated. Using the parameters, the probability density function is shown and the flood probability is calculated by comparing with the design flood of Cheongmicheon watershed. The flood probability results differed for various values of rainfall and rainfall duration. In addition, the flood probability calculated in this study was compared with the actual flood damage in Cheongmicheon watershed (R² = 0.7). Further, this study results could be used for flood forecasting.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.981-992
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• 2023

Due to recent global climate change, the scale of flood damage is increasing as rainfall is concentrated and its intensity increases. Rain on a scale that has not been observed in the past may fall, and long-term rainy seasons that have not been recorded may occur. These damages are also concentrated in ASEAN countries, and many people in ASEAN countries are affected, along with frequent occurrences of flooding due to typhoons and torrential rains. In particular, the Bandung region which is located in the Upper Chitarum River basin in Indonesia has topographical characteristics in the form of a basin, making it very vulnerable to flooding. Accordingly, through the Official Development Assistance (ODA), a flood forecasting and warning system was established for the Upper Citarium River basin in 2017 and is currently in operation. Nevertheless, the Upper Citarium River basin is still exposed to the risk of human and property damage in the event of a flood, so efforts to reduce damage through fast and accurate flood forecasting are continuously needed. Therefore, in this study an artificial intelligence-based river flood water level forecasting model for Dayeu Kolot as a target station was developed by using 10-minute hydrological data from 4 rainfall stations and 1 water level station. Using 10-minute hydrological observation data from 6 stations from January 2017 to January 2021, learning, verification, and testing were performed for lead time such as 0.5, 1, 2, 3, 4, 5 and 6 hour and LSTM was applied as an artificial intelligence algorithm. As a result of the study, good results were shown in model fit and error for all lead times, and as a result of reviewing the prediction accuracy according to the learning dataset conditions, it is expected to be used to build an efficient artificial intelligence-based model as it secures prediction accuracy similar to that of using all observation stations even when there are few reference stations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.3
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• pp.127-137
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• 1992

For the real-time control of a multi-purpose reservoir in case of a storm, it is absolutely necessary to forecast accurate flood inflows through a good rainfall-runoff model by calibrating the parameters with the on-line rainfall and water level data transmitted by the telemetering systems. To calibrate the parameters of a runoff model. the trial and error method of manual calibration has been adopted from the subjective view point of a model user. The object of this study is to develop a automatic calibration method using an optimization technique. The pattern-search algorithm was applied as an optimization technique because of the stability of the solution under various conditions. The object function was selected as the sum of the squares of differences between observed and fitted ordinates of the hydrograph. Two historical flood events were applied to verify the developed technique for the automatic calibration of the parameters of the storage-function rainfall-runoff model which has been used for the flood control of the Soyanggang multi-purpose reservoir by the Korea Water Resources Corporation. The developed method was verified to be much more suitable than the manual method in flood forecasting and real-time reservoir controlling because it saves calibration time and efforts in addition to the better flood forecasting capability.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.171-182
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• 2006

In this study, rainfall-runoff analysis was performed for Yongdam watershed($930km^2$) using KOWACO flood analysis model based on Storage Function Method as lumped hydrologic model and Vflo which was developed for real-time flood prediction by University of Oklahoma. The results shows that, the hydrographs of lumped and distributed model with uncalibrated parameters which estimated from physical or experimental relationship show significant biases from observed hydrographs. However, the hydrograph at Cheoncheon site from the distributed model follows the actual hydrograph to an extent that no more calibration is necessary. It encourages that distributed model can have advantages for application in real-time flood forecasting as physically based distributed hydrologic model which can construct event-independent basin parameter group.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Water for future
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• v.25 no.4
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• pp.109-119
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• 1992

The purpose of this study is to develop real-time streamflow forecasting models in order to manage effectively the flood warning system and water resources during the storm. The stochastic system models of the rainfall-runoff process using in this study are constituted and applied the Recursive Least Square and the Instrumental Variable-Approximate Maximum Likelihood algorithm which can estimate recursively the optimal parameters of the model. Also, in order to improve the performance of streamflow forecasting, initial values of the model parameter and covariance matrix of parameter estimate errors were evaluated by using the observed historical data of the hourly rainfall-runoff, and the accuracy and applicability of the models developed in this study were examined by the analysis of the I-step ahead streamflow forecasts.

• Journal of Korea Water Resources Association
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• v.46 no.6
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• pp.655-666
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• 2013

Lately, intensity and frequency of natural disasters such as flood are increasing because of abnormal climate. Casualties and property damages due to large-scale floods such as Typhoon Rusa in 2002 and Typhoon Maemi in 2003 rapidly increased, and these show the limits of the existing disaster prevention measures and flood forecasting systems regarding irregular climate changes. In order to efficiently respond to extraordinary flood, it is important to provide effective countermeasures through an inundation model that can accurately simulate flood inundation patterns. However, the existing flood inundation analysis model has problems such as excessive take of analysis time and accuracy of the analyzed results. Therefore, this study conducted a flood inundation analysis by using the Gerris flow solver that uses quadtree grid, targeting the Baeksan Levee in the Nakdong River Basin that collapsed because of a concentrated torrential rainfall in August, 2002. Through comparisons with the FLUMEN model that uses unstructured grid among the existing flood inundation models and the actual flooded areas, it determined the applicability and efficiency of the quadtree grid-based flood inundation model of the Gerris flow solver.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.09a
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• pp.711-713
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• 2005