• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.71-71
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• 2012

현재 전 세계적으로 극한강우의 발생빈도가 점차 높아지고 있으며 홍수량 또한 강도가 커지고 있는 것이 현실이다. 하지만 과거의 홍수발생 빈도에 따라 설계된 홍수방어시설들이 점차 한계를 보이고 있으므로 이를 대비하기위한 구조적 대책뿐만 아니라 홍수피해 발생 가능지역에 사전 예경보를 시행하는 비구조적 대책마련 또한 필요하다. 기존의 홍수예측은 확정적인 하나의 유량예측값만을 제공함으로써 신속하고 편리하였지만 이에 대한 불확실성이 큰 경우 예상치 못한 큰 인적 물적 피해를 가져올 수 있다. 이처럼 확률론적 홍수예측의 필요성이 대두되어 지면서 유럽이나 미국등 선진국에서는 EFFS(European Flood Forecasting System)과 NWSRFS(National Water Service River Forecast System)같이 이미 확률론적 홍수예측에 대한 연구 및 기술개발이 활발하게 진행되어지고 있다. 하지만 홍수예측의 확률론적 접근에 있어서는 많은 불확실성들이 내포되어 있으므로 예측시스템에서 생성된 앙상블 유량예측 결과의 신뢰도 분석과 올바른 불확실성 정보의 제공이 필요하다. 본 연구는 확률론적 홍수예측 방법을 국내에 적용시켜서 기상청의 예측시스템 KLAPS(Korea Local Analysis and Prediction System), MAPLE(McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation), UM(Unified Model) 그리고 MOGREPS(Met Office Global Regional Ensemble Prediction System)으로부터 생성된 기상앙상블을 현재 국토해양부 홍수통제소에서 사용하고 있는 강우-유출모형인 저류함수모형(Storage Function Method)의 입력 자료로 사용한다. 확률론적 홍수예측에서 오는 불확실성을 분석하기 위해서 첫 번째로 제공되는 기상예측 시스템의 시 공간적 스케일 및 대상유역의 공간특성에 따라 어떠한 형태로 전파되어지는지를 분석하였다. 두 번째는 각각의 예측시스템들이 선행기간(Lead time)에 따라 불확실성의 특성이 어떻게 나타나게 되는지를 확인하였다. 이러한 불확실성의 특성을 정확하게 파악하게 된다면 예측에 있어서 현재 갖고 있는 문제점들로부터 개선해 나가야 할 방향을 제시해주어 향후연구에 유용하게 활용될 수 있을 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.449-453
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• 2007

Has been being operated since 1974, recently, the flood forecasting and warning system is applied in almost all the rivers in Korea, and the Storage Function Method(SFM) is used for flood routing. The SFM which was presented by Toshimitsu Kimura(1961) routes floods in channels and basins with the storage function as the basic equation. A watershed is devided into two zone, runoff and percolation area and Runoff is occured when cumulated rainfall is not exceed saturation rainfall, but exceed, runoff is occured from percolation area, too. Runoff area is given and not changed, runoff ratio is constant. In routing process, runoff from runoff and percolation area is routed seperately with nonlinear cenceptual reservior having same characteristics and it is unreasonable assumption. Modified SFM is proposed with storage function and continuity Equation which has no assumption for routing process and effective rainfall is calculated by SCS Method. For Wi Stream, comparision of Kimura and Modified SFM is conducted and It could be seen that Modified SFM is more improvemental and easily applicable method.

• Journal of Korea Water Resources Association
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• v.40 no.7
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• pp.523-532
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• 2007

It has been operated since 1974, recently, the flood forecasting and warning system is applied in almost all the rivers in Korea, and the Storage Function Method (SFM) is used for flood routing. The SFM which was presented by Toshimitsu Kimura (1961) routes floods in channels and basins with the storage function as the basic equation. A watershed is divided into two zone, runoff and percolation area and runoff from runoff area is occurred when cumulated rainfall is not exceed saturation point, but exceed runoff is occurred from percolation area, too. Runoff area is given and not changed, runoff ratio is constant. In routing Process, runoff from runoff and percolation area is routed seperately with nonlinear conceptual reservoir having the same characteristics and it is unreasonable assumption. A modified SFM is proposed with storage function and continuity equation which has no assumption for routing process and effective rainfall is calculated by SCS Method. For Wi-stream, comparison of Kimura and the modified SFM is conducted, and it could be seen that the modified SFM is more improvable and applicable method easily by reducing the parameters.

• Journal of Korea Water Resources Association
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• v.51 no.2
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• pp.165-174
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• 2018

The model using time series data can be considered as a flood forecasting model of a small river due to its efficiency for model development and the advantage of rapid simulation for securing predicted time when reliable data are obtained. Transfer Function Noise (TFN) model has been applied hourly flood forecast in Italy, and UK since 1970s, while it has mainly been used for long-term simulations in daily or monthly basis in Korea. Recently, accumulating hydrological data with good quality have made it possible to simulate hourly flood prediction. The purpose of this study is to assess the TFN model applicability that can reflect exogenous variables by combining dynamic system and error term to reduce prediction error for tributary rivers. TFN model with hourly data had better results than result from Storage Function Model (SFM), according to the flood events. And it is expected to expand to similar sized streams in the future.

• Journal of Korea Water Resources Association
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• v.39 no.12 s.173
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• pp.1013-1022
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• 2006

Urban flooding is usually caused by the surcharge of storm sewers. For this reason, previous studies on urban flooding are mainly concentrated on the simulation of urban drainage systems. However these approaches that find the pipes which have insufficient drainage capacity are very approximate and unreasonable ways in establishing both flood prevention and flood-loss reduction planning. In this study, a two-dimensional model linked the existing ILLUDAS model is developed to calculate the accurate and resonable solution about urban flood inundation and it is verified by using the simulation of July 2001 flood in Seoul. In the urban area with a small difference of ground elevations, the two-dimensional flood propagation phases must be considered to make a accurate analysis for inundated area and depth. The result of this study can be used to construct fundamental data for a flood control plan and establish a urban flood forecasting/warning system.

• Journal of Korea Water Resources Association
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• v.42 no.2
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• pp.131-139
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• 2009

The weather accidents by global warming effect are increasing rapidly whole world. Flood forcasting system and hydrological database are operated by almost all the countries in the world. An objective of this study is to research revised methods of missing rainfall data and find more effective revised method for this operating system. 194 rainfall data of the Han river basin is used. Arithmetic average method, coefficient of correlation weighting method and inverse distance weighting method are compared to estimate revised methods. The result from the analysis shows that coefficient of correlation weighting method is best quantitatively among the 3 methods.

• 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.

• Korean Journal of Hydrosciences
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• v.6
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• pp.81-98
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• 1995

A linear reservoir rainfall-runoff system was developed as a rainfall-runoff event simulation model. It was achieved from large modification of runoff function method. There are six parameters in the model. Hydrologic losses consist of some quantity of initial loss and some ratio of rainfall intensity followed by initial loss. The model has analytical routing equations. Hooke and Jaeves algorithm was used for model calibration. Parameters were estimated for flood events from '84 to '89 at Seomyeon and Munmak stream gauges, and the trends of major parameters were analyzed. Using the trends, verifications were performed for the flood event in September 1990. Because antecedent rainfalls affect initial loss, future researches are required on such effects. The estimation method of major parameters should also be studied for real-time forecasting.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.157-161
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• 2009

In recent years, there is a remarkable progress in ICTs (Information and Communication Technologies), and then many attempts to apply ICTs to other industries are being made. In the field of disaster managements, ICTs such as RFID (Radio Frequency IDentification) and USN (Ubiquitous Sensor Network) are used to provide safe environments. Actually, various types of early warning systems using USN are now widely used to monitor natural disasters such as floods, landslides and earthquakes, and also to detect human-caused disasters such as fires, explosions and collapses. These early warning systems issue alarms rapidly when a disaster is detected or an event exceeds prescribed thresholds, and furthermore deliver alarm messages to disaster managers and citizens. In general, these systems consist of a number of various sensors and measure real-time stream data, which requires an efficient and rapid data processing technique. In this study, an event-driven architecture (EDA) is presented to collect event effectively and to provide an alert rapidly. A publish/subscribe event processing method to process simple event is introduced. Additionally, a complex event processing (CEP) technique is introduced to process complex data from various sensors and to provide prompt and reasonable decision supports when many disasters happen simultaneously. A basic concept of CEP technique is presented and the advantages of the technique in disaster management are also discussed. Then, how the main processing methods of CEP such as aggregation, correlation, and filtering can be applied to disaster management is considered. Finally, an example of flood forecasting and early alarm system in which CEP is incorporated is presented It is found that the CEP based on the EDA will provide an efficient early warning method when disaster happens.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.2B
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• pp.145-152
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• 2006

In the present study, a nonlinear model of rainfall-runoff process using Artficial Neural networks(ANNs) which have no consideration on the physical parameter for the basin was developed at Naju station which is the main stream of Yeongsan-river, and Sunam station which is the main stream of Hwangryong-river. The result from the model of ANN_NJ_9 at the Naju station revealed the best result of the rainfall-runoff process, while the model of ANN_SA_9 for the Sunam station. Also, GUI_FFS developed in the research showed the $R^2$ of more than 0.98 between the observed and predicted values using the rainfall and runoff in the respective stations. Therefore, the GUI_FFS might be expected that it can play a role for the high reliability to operate and manage the water resources and the design of river plan more efficiently in the future.