• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1543-1547
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• 2007

지금까지 돌발홍수는 주로 강우의 시공간적인 특성들을 고려한 기후학적 측면에서 관심을 가지고 연구가 진행되어 왔을 뿐 유출의 시각에서 돌발홍수를 평가하기 위한 노력은 매우 미흡하였다고 할 수 있다. 본 연구의 목적은 Bhaskar 등(2000)의 연구를 우리나라에 적용하여 유출수문곡선에 의해 돌발홍수를 설명하고, 다른 홍수사상과 돌발홍수 사상을 구별하고자 하는데 있다. 즉, 유출수문곡선의 특성을 이용해 홍수사상에 대한 돌발홍수지수(flash flood index)를 산정함으로써 돌발홍수의 심각성 정도를 정량화하고자 하였다. 이를 위해 본 논문에서는 한강유역의 과거 101개의 홍수사상에 대해 돌발홍수의 상대심도(relative severity)를 파악하기 위하여 돌발홍수지수를 산정하였으며 또한, 2006년 7월의 집중호우에 의해 발생한 홍수사상의 돌발홍수 심도를 시공간적으로 정량화하였다. 분석 결과, 한강유역의 다른 지역에 비해 강원도 지역의 홍수 유출수문곡선들이 돌발홍수 심도를 크게 나타내었으며 중랑천 등과 같은 도시유역에서도 돌발심도가 크게 나타남을 확인 할 수 있었다. 2006년 7월 집중호우에 의한 한강유역의 돌발홍수지수를 7월 전반기, 중반기 그리고 하반기로 나누어 시공간적 공간분포를 분석한 결과, 7월 전반기의 경우 서울 주변지역의 돌발심도가 크게 나타났으며 7월 중반기의 경우 강원도 지역의 돌발홍수 심도가 크게 나타났다.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.857-871
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• 2013

The interest in rainfall observation and forecasting using remote sensing method like RADAR (Radio Detection and Ranging) and satellite image is increased according to increased damage by rapid weather change like regional torrential rain and flash flood. In this study, the basin runoff was calculated using adaptive neuro-fuzzy technique, one of the data driven model and MAPLE (McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation) forecasted precipitation data as one of the input variables. The flood estimation method using neuro-fuzzy technique and RADAR forecasted precipitation data was evaluated. Six rainfall events occurred at flood season in 2010 and 2011 in Chungju Reservoir basin were used for the input data. The flood estimation results according to the rainfall data used as training, checking and testing data in the model setup process were compared. The 15 models were composed of combination of the input variables and the results according to change of clustering methods were compared and analysed. From this study was that using the relatively larger clustering radius and the biggest flood ever happened for training data showed the better flood estimation. The model using MAPLE forecasted precipitation data showed relatively better result at inflow estimation Chungju Reservoir.

• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.407-424
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• 2004

Using geomorphoclimatic unit hydrograph(GCUH), we estimated the fitness to calculate the mountainous area discharge and flash flood trigger rainfall(FFTR). First, we compared the GCUH peak discharge with the existing report using the design storm at the Dukcheon basin. Second, we compared the HEC-HMS(Hydrologic Engineering Center-Hydrologic Modeling System) model and GCUH with the observed discharge using the real rainfall events at the Taesu stage gage. Third, GCUH and NRCS(Natural Resources Conservation Service) were used for calculating FFTR and proper calculation method was shown. At the Dukcheon basin, the comparison result of using design storm was shown in Table 11, and it was not in excess of 1.1, except for the 30 year return period. In case of real rainfall events, the result was shown in Table 12, and GCUH discharges were all larger than the HEC-HMS model discharges, and they were very similar to the observed data at the Taesu stage gage. In this study, we found that GCUH was a very proper method in the calculation of mountainous discharge. At the Dukcheon basin, FFTR was 12.96 mm in the first 10 minutes when the threshold discharge was 95.59 $m^3$/sec.

• Journal of Korean Society for Geospatial Information Science
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• v.16 no.1
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• pp.23-32
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• 2008

According to recent frequent local flash flood due to climate change, the very short-term rainfall forecast using remotely sensed rainfall like radar is necessary to establish. This research is to evaluate the feasibility of GIS-based distributed model coupled with radar rainfall, which can express temporal and spatial distribution, for multipurpose dam operation during flood season. $Vflo^{TM}$ model was used as physically based distributed hydrologic model. The study area was Yongdam dam basin ($930\;km^2$) and the 3 storm events of local convective rainfall in August 2005, and the typhoon.Ewiniar.and.Bilis.collected from Jindo radar was adopted for runoff simulation. Distributed rainfall consistent with hydrologic model grid resolution was generated by using K-RainVieux, pre-processor program for radar rainfall. The local bias correction for original radar rainfall shows reasonable results of which the percent error from the gauge observation is less than 2% and the bias value is $0.886{\sim}0.908$. The parameters for the $Vflo^{TM}$ were estimated from basic GIS data such as DEM, land cover and soil map. As a result of the 3 events of multiple peak hydrographs, the bias of total accumulated runoff and peak flow is less than 20%, which can provide a reasonable base for building operational real-time short-term rainfall-runoff forecast system.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.256-256
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• 2021

Saint-Venant 방정식은 수평규모가 수심규모보다 큰 천수흐름을 기술하는 수리동역학 모형으로 지난 수십년간 공학적 분야에서 널리 이용되어 왔다. 최근에도 기후변화에 따른 도시 홍수의 위기 증대로 홍수위기관리의 관심이 높아짐에 따라 홍수파(flood wave), 도시침수(urban inundation), 돌발홍수(flash flood) 등의 신속한 예측을 위한 Saint-Venant 방정식의 연구가 활발히 진행되고 있다. 그러나 도시와 같은 인공구조물이 즐비한 상황에서 천수흐름을 해석하는 고전적인 수치해법들은 다양한 불연속 지형들의 존재로 인하여 불안정하며 지배방정식의 정해로 수치해가 잘 수렴하지 않는 문제가 있다. 지난 수년간 이를 해결하기 위해 불연속한 지형을 안정적으로 해결할 수 있는 수치기법의 연구가 진행되어 왔으나, 정해로의 수렴성, 정확성에 관하여 연구가 부족한 실정이다. 본 연구는 수치해법의 주요 구조를 구성하는 Saint-Venant 방정식의 불연속한 지형조건에 대한 리만 문제의 정해를 연구하였다. 쌍곡선형 시스템의 특징을 고려하여 요소파들(elementary waves)의 공식을 유도하였는데, 질량과 에너지의 보존법칙에 위배되지 않으며 운동량이송부의 비선형성과 지형의 불연속에 의한 비엄격성을 고려할 수 있는 조건을 제시하였다. 또한, 유도된 요소파들을 바탕으로 L-M & R-M 커브이론(Han et al. 2014)을 사용할 수 있는 조건과 당위성을 증명하였고, 이를 바탕으로 Saint-Venant 방정식의 정해법을 구성하였다. 리만문제의 다양한 초기조건들을 바탕으로 모든 경우의 정해 구조를 조사하였고, 이를 통해 불연속 지형에 대한 Saint-Venant 지배방정식의 정해가 다수해를 갖을 수 있음을 보였으며, 이를 근사할 수 있는 수치기법의 전략을 소개하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.338-340
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• 2021

Among the recent natural disasters, flood damage is concentrated in the summer, leading to casualties or property damage due to the typhoon's rainy season. Much research is being done to reduce this damage. In this paper, we design and implement a system that detects paths and provides them to users using shortest-distance algorithms in the event of such sudden flooding. The proposed system uses QGIS to detect paths using topographical data that generated tracks and pointers. In addition, other shortest paths are detected and provided to users when sudden flooding occurs during evacuation to routes detected through scenarios. Therefore, it is assumed that the proposed system will allow users to safely evacuate from the risk of future disaster safety accidents.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.3
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• pp.52-67
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• 2008

Recently, frequent occurrence of flash floods caused by climactic change has necessitated prompt and quantitative prediction of precipitation. In particular, the usability of rainfall radar that can carry out real-time observation and prediction of precipitation behavior has increased. Moreover, the use of distributed hydrological model that enables grid level analysis has increased for an efficient use of rainfall radar that provides grid data at 1km resolution. The use of distributed hydrologic model necessitates grid-type spatial data about target basins; to enhance reliability of flood runoff simulation, the use of visible and precise data is necessary. In this paper, physically based $Vflo^{TM}$ model and ModClark, a quasi-distributed hydrological model, were used to carry out flood runoff simulation and comparison of simulation results with data from Imjin River Basin, two-third of which is ungauged. The spatial scope of this study was divided into the whole Imjin River basin area, which includes ungauged area, and Imjin River basin area in South Korea for which relatively accurate and visible data are available. Peak flow and lag time outputs from the two simulations of each region were compared to analyze the impact of uncertainty in topographical parameters and soil parameters on flood runoff simulation and to propose effective methods for flood runoff simulation in ungauged regions.

• Journal of Korean Society of Disaster and Security
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• v.6 no.3
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• pp.19-27
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• 2013

Along with green growth era in the 21st century and with the increasing economic, social, and cultural stabilization, people expect absolute freedom from the drought and flood and long for ecological exchange in the waterfront as a part of the living base at the same time. In order to match the changes in social demand, the focus on the river management policy urgently requires a comprehensive river management that considers the nature's environmental and ecological aspects as well as a new disaster prevention approach that grows out of existing simple flood prevention. Therefore, this thesis provides feasible solutions by suggesting the following findings to maintain and manage rivers to be harmonized with the natural environment considering disaster prevention aspects. It is necessary to change the river management policy and integrated river basin management, to control the river management lead by the central government and to promote close-to-nature river management approach for environmentally sound and sustainable development.

• Journal of Korea Water Resources Association
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• v.48 no.12
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• pp.995-1009
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• 2015

Weather radar rainfall data has been recognized for making valuable contributions to short-term flood forecasting and management over the past decades. There are several advantages to better monitoring rainfall in ungauged area compared to ground-based rain gauges with which spatial patterns of the rainfall are not effectively identified. Hence, this study aims to develop a new scheme to forecast spatio-temporal rainfall field. The proposed model was based on an advection scheme to track wind patterns and velocity. The results showd a promising forecasting skill with quantitative and qualitative measures. It was confirmed that the forecasted rainfall may be effectively used an input data for a distributed hydrological model.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.31-31
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• 2023

During December 2022, the northeast monsoon, which dominates the south and the Gulf of Thailand, had significant rainfall that impacted the lower southern region, causing flash floods, landslides, blustery winds, and the river exceeding its bank. The Golok River, located in Narathiwat, divides the border between Thailand and Malaysia was also affected by rainfall. In flood management, instruments for measuring precipitation and water level have become important for assessing and forecasting the trend of situations and areas of risk. However, such regions are international borders, so the installed measuring telemetry system cannot measure the rainfall and water level of the entire area. This study aims to predict 72 hours of water level and evaluate the situation as information to support the government in making water management decisions, publicizing them to relevant agencies, and warning citizens during crisis events. This research is applied to machine learning (ML) for water level prediction of the Golok River, Lan Tu Bridge area, Sungai Golok Subdistrict, Su-ngai Golok District, Narathiwat Province, which is one of the major monitored rivers. The eXtreme Gradient Boosting (XGBoost) algorithm, a tree-based ensemble machine learning algorithm, was exploited to predict hourly water levels through the R programming language. Model training and testing were carried out utilizing observed hourly rainfall from the STH010 station and hourly water level data from the X.119A station between 2020 and 2022 as main prediction inputs. Furthermore, this model applies hourly spatial rainfall forecasting data from Weather Research and Forecasting and Regional Ocean Model System models (WRF-ROMs) provided by Hydro-Informatics Institute (HII) as input, allowing the model to predict the hourly water level in the Golok River. The evaluation of the predicted performances using the statistical performance metrics, delivering an R-square of 0.96 can validate the results as robust forecasting outcomes. The result shows that the predicted water level at the X.119A telemetry station (Golok River) is in a steady decline, which relates to the input data of predicted 72-hour rainfall from WRF-ROMs having decreased. In short, the relationship between input and result can be used to evaluate flood situations. Here, the data is contributed to the Operational support to the Special Water Resources Management Operation Center in Southern Thailand for flood preparedness and response to make intelligent decisions on water management during crisis occurrences, as well as to be prepared and prevent loss and harm to citizens.