• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.695-707
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• 2010

The frequency and size of typhoon and local severe rainfall are increasing due to the climate change and the damage also increasing from typhoon and severe rainfall. The flood forecasting and warning system to reduce the damage from typhoon and severe rainfall needs forecasted rainfall using radar data and short-term rainfall forecasting model. For this reason, this study examined the applicability of short-term rainfall forecast using translation model with weather radar data to point out that the utilization of flood forecasting in Korea. This study estimated the radar rainfall using Least-square fitting method and estimated rainfall was used as initial field of translation model. The translation model have verified accuracy of forecasted radar rainfall through the comparison of forecasted radar rainfall and observed rainfall quantitatively and qualitatively. Almost case studies showed that accuracy is over 0.6 within 4 hours leading time and mean of correlation coefficient is over 0.5 within 1 hours leading time in Kwanak and Jindo radar site. And, as the increasing the leading time, the forecast accuracy of precipitation decreased. The results of the calculated Mean Area Precipitation (MAP) showed forecast rainfall tend to be underestimated than observed rainfall but the correlation coefficient more than 0.5. Therefore it showed that translation model could be accurately predicted the rainfall relatively. The present results indicate that possibility of translation model application of Korea just within 2 hours leading forecasted rainfall.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.294-294
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• 2019

The system for predicting flood of river at Flood Control Office is made up of a rainfall-runoff model and FLDWAV model. This system is mainly operating to predict the excess of the flood watch or warning level at flood forecast points. As the demand for information of the management and operation of riverside, which is being used as a waterfront area such as parks, camping sites, and bike paths, high-level forecasts of watch and warning at certain points are required as well as production of lowland flood forecast information that is used as a waterfront within the river. In this study, a technology to produce flood forecast information in lowland areas of the river used as a waterfront was developed. Based on the results of the 1D hydraulic analysis, a model for performing spatial operations based on high resolution grid was constructed. A model was constructed for Andong district, and the inundation conditions and level were analyzed through a virtual outflow scenarios of Andong and Imha Dam.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.22-25
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• 2005

The 10 Year Implementation Plan for a Global Earth Observation System of Systems (GEOSS), which was endorsed at the Third Earth Observation Summit in Brussels in February, 2005, emphasizes the importance of data management facilities for diverse and large-volume Earth Observation data from inhomogeneous information sources. A three year research plan for addressing this key target of GEOSS has just approved as the first step by the Japanese government. The goals of this research are, (1) to develop a data management core system consisting of data integration and information fusion functions and interoperability and information service functions; (2) to establish data and information flows between data providers and users; (3) to promote application studies of data integration and information fusion, especially in the fields of weather forecasting, flood forecasting, agricultural management, and climate variability and changes. The research group involves leading scientists on information science and technology, who have been developing giant data archive servers, storage area networks, metadata models, ontology for the earth observations. They are closely cooperating with scientists on earth sciences, water resources management, and agriculture, and establishing an effective collaborative research framework.

• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.573-579
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• 2009

The performance of Rainfall-Runoff Forecasting System (RRFS), the watershed management model for the Geum river basin, is evaluated based on the agreement between the simulated and observed hydrographs and the behavioral characteristics of the flow-duration curves. As a result, the simulated hydrographs are well agreed with the observed ones except high flow discharges. It is inferred that most of the errors in the simulated hydrographs are due to the misestimation of agricultural water use in $2^{nd}$ quarter and the discrepancy of the peak discharges in $3^{rd}$ quarter. It is however judged that RRFS would give the reliable runoff hydrographs from the point of view of continuous model application. And simulated flow-duration curves and flow-duration coefficients are also similar to the observed ones except flood flow region. From the above result it is confirmed that the construction of Yongdam dam improves the state of flow-duration curve at the Gongjoo station.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.347-354
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• 2021

In the past few years, various damages have occurred in the vicinity of rivers due to flooding. In order to alleviate such flood damage, structural and non-structural measures are being established, and one of the important non-structural measures is to establish a flood warning system. In general, in order to establish a flood warning system, the water level of the flood alarm reference point is set, the critical flow corresponding thereto is calculated, and the warning precipitation amount corresponding to the critical flow is calculated through the Geomorphological Instantaneous Unit Hydrograph (GIUH) rainfall-runoff model. In particular, when calculating the critical flow, various studies have calculated the critical flow through the Manning formula. To compare the adequacy of this, in this study, the critical flow was calculated through the HEC-RAS model and compared with the value obtained from Manning's equation. As a result of the comparison, it was confirmed that the critical flow calculated by the Manning equation adopted excessive alarm precipitation values and lead a very high flow compared to the existing design precipitation. In contrast, the critical flow of HEC-RAS presented an appropriate alarm precipitation value and was found to be appropriate to the annual average alarm standard. From the results of this study, it seems more appropriate to calculate the critical flow through HEC-RAS, rather than through the existing Manning equation, in a situation where various river projects have been conducted resulting that most of the rivers have been surveyed.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.310-310
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• 2021

지난 수년간 하천 인근에서 홍수로 인하여 다양한 피해가 발생하고 있다. 이러한 홍수피해를 경감하기위해 구조적 비구조적 대책들을 세우고 있으며, 중요한 비구조적 대책 중의 하나가 홍수경보시스템을 구축하는 것이다. 일반적으로 홍수경보시스템을 구축하기 위하여 홍수경보기준지점의 수위를 설정하며 이에 대응하는 한계유량을 산출하고 GIUH 강우-유출모형을 통하여 한계유량에 대응하는 경보강수량을 산정하는 방식을 택하고 있다. 특히 한계유량을 산출하는 경우, 다양한 연구에서 Manning 공식을 통하여 한계유량을 산출하고 있다. 이에 대한 적정성을 비교하기 위해 본 연구에서는 HEC-RAS모형을 통하여 한계유량을 계산하였고 Manning식에서 나온 값과 비교하였다. 비교결과 Manning식에서 산출된 한계유량은 과다한 경보 강수량 값을 채택하고 기존 설계강수량에 비해 매우 큰 값임을 확인할 수 있었다. 이에 비해 HEC-RAS의 한계 유량값은 적정한 경보강수량 값을 제시하였고 연평균알람기준에도 적정함을 알 수 있었다. 본 연구 결과를 통해, 현재 다양한 하천사업이 이루어져 대부분의 하천의 측량이 이루어진 상황에서 기존의 Manning식에 의한 한계유량 산출보다는 HEC-RAS를 통하여 한계유량을 산정해야하는 것이 보다 적정해 보인다.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.80-88
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• 2020

This paper describes the development trends and service provision examples of disaster occurrence and spread prediction technology for various disasters such as tsunamis, floods, and fires. In terms of fires, we introduce the WIFIRE system, which predicts the spread of large forest fires in the United States, and the Metro21: Smart Cities Institute project, which predicts the risk of building fires. This paper describes the development trends in tsunami prediction technology in the United States and Japan using artificial intelligence (AI) to predict the occurrence and size of tsunamis that cause great damage to coastal cities in Japan, Indonesia, and the United States. In addition, it introduces the NOAA big data platform built for natural disaster prediction, considering that the use of big data is very important for AI-based disaster prediction. In addition, Google's flood forecasting system, domestic and overseas earthquake early warning system development, and service delivery cases will be introduced.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• Water for future
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• v.27 no.3
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• pp.145-158
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• 1994

The 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 Jeeves algorithm was used to 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 '90 flood event. Because antecedent fainfalls affect initial loss, future researches are required on such effects. The estimation method of major parameters should also be studied for real-time forecasting.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.379-379
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• 2017

과거에는 하천 범람으로 인한 홍수피해가 많았으나 최근에는 도시화로 인한 불투수면적의 증가로 홍수도달시간의 단축 및 노면수의 배수불량으로 인한 내수 홍수피해가 많아졌다. 이러한 변화는 도시하천의 홍수예보에 밀접한 관련이 있으며 관련된 분석 모형 및 연계방안 또한 매우 중요하게 되었다. 일반적으로 하천에 대한 유출해석 모형으로 HEC-RAS((Hydrologic Engineering Center-River Analysis System)가 주로 사용되고 있으나 현재와 같이 도심지 하천에서는 내배수의 특성을 고려한 SWMM(Storm Water Management Model)을 사용한다. 또는 이 두모형의 연계를 통해 유출해석을 진행하기도 한다. 최근 HEC-RAS와 SWMM모형이 최신 버전을 공개하였다. HEC-RAS의 경우 2016년 9월 5.0.3버전을 출시하며 1D뿐만 아닌 2D의 모의도 가능하도록 기능을 개선하였으며 SWMM의 경우 2016년 09월 07일 5.1.011버젼이 공개되었다. 본 연구에서는 공개된 최신 모형을 도림천 지역에 적용하여 도림천 지역에 적합한 모형 및 연계 방법을 찾아보려 한다. 이를 통해 최적의 도시홍수예보 시스템을 구성하기 위한 모형 및 연계방안의 조사와 가장 합리적인 도시홍수 시스템의 구성방안을 제시하고자 한다.