• The KIPS Transactions:PartB
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• v.18B no.5
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• pp.271-278
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• 2011

Storm and flood such as torrential rains and major typhoons has often caused damages on a large scale in Korea and damages from storm and flood have been increasing by climate change and warming. Therefore, it is an essential work to maneuver preemptively against risks and damages from storm and flood by predicting the possibility and scale of the disaster. Generally the research on numerical model based on statistical methods, the KDF model of TCDIS developed by NIDP, for analyzing and predicting disaster risks and damages has been mainstreamed. In this paper, we introduced the model for prediction of damage cost from storm and flood by the neural network algorithm which outstandingly implements the pattern recognition. Also, we compared the performance of the neural network model with that of KDF model of TCDIS. We come to the conclusion that the robustness and accuracy of prediction of damage cost on TCDIS will increase by adapting the neural network model rather than the KDF model.

• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.5
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• pp.131-138
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• 2009

In this paper, a dynamic warning system to forecast inland flooding associated with typhoons and storms is described. The system is used operationally during the typhoon season to anticipate the potential impact such as inland flooding on the coastal zone of interest. The system has been developed for the use of the public and emergency management officials. Simple typhoon models for quick prediction of wind fields are implemented in a user-friendly way by using a Graphical User Interface (GUI) of MATLAB. The main program for simulating tides, depth-averaged tidal currents, wind-driven surges and currents was also vectorized for the fast performance by MATLAB. By pushing buttons and clicking the typhoon paths, the user is able to obtain real-time water level fluctuation of specific points and the flooding zone. This system would guide local officials to make systematic use of threat information possible. However, the model results are sensitive to typhoon path, and it is yet difficult to provide accurate information to local emergency managers.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.404-414
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• 2023

In this study, digital climate maps with high-resolution (1km, daily) for the period of 1981 to 2020 were produced for the use as reference data within the procedures for statistical downscaling of climate change scenarios. Grid data for the six climate variables including maximum temperature, minimum temperature, precipitation, wind speed, relative humidity, solar radiation was created over Korean Peninsula using statistical downscaling model, so-called IGISRM (Improved GIS-based Regression Model), using global reanalysis data and in-situ observation. The digital climate data reflects topographical effects well in terms of representing general behaviors of observation. In terms of Correlation Coefficient, Slope of scatter plot, and Normalized Root Mean Square Error, temperature-related variables showed satisfactory performance while the other variables showed relatively lower reproducibility performance. These digital climate maps based on observation will be used to downscale future climate change scenario data as well as to get the information of gridded agricultural weather data over the whole Korean Peninsula including North Korea.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.203-222
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• 2011

The characteristics of flood damages have been increasingly strengthened and take the form of unpredictable and unusual weather phenomena caused by climate change and climate anomalies. To prevent inundation damage caused by breach of hydraulic structure such as dam or levee, and trouble of drainage of inner basin, the prediction necessity of flood inundation area, flood risk analysis, and drawing flood risk maps have been on the rise, and the national flood risk maps have been produced. In this study, the quantitative flood vulnerability analysis was performed, which represents population living within flood-affected areas, types of economic activities, facilities affected by flood, in order to extend flood risk mapping from simple hazard concept into risk based idea. By applying it to Nakdong River basin, the flood vulnerability indices were estimated to draw flood risk maps subdivided into administrative districts. The result of this study can be applied to establish the disaster prevention measures and priority decision of disaster prevention project.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.341-341
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• 2020

서울시는 '10년, '11년, '18년의 기록적인 호우로 인해 막대한 재산피해를 기록하였다. 이로 인해 서울시는 수재해 최소화 대책의 필요성을 인지하여 방재시설물 확충 등의 구조적 대책과 함께 침수지역 예측, 호우 영향 예보와 관련된 비구조적 대책 수립을 위해 노력하고 있다. 그 일환으로 '18년에 『서울시 강한 비구름 유입경로 및 침수위험도 예측 용역』을 수행하였으며 이를 통해 레이더 기반의 비구름 이동경로 추정 기술, 침수시나리오 기반의 침수위험지역 추정기술 등을 적용한 서울시 도시침수 예측시스템을 개발하였다. 그러나 침수피해에 선제적으로 대응하기 위해서는 실시간으로 예측강우정보를 생산하고 이를 통해 침수위험지역을 추정하는 기술이 필요하다. 이에 본 연구를 통해 예측강우정보 생산 기술 적용, 예측강우정보를 이용한 실시간 침수위험지역 추정 기술 개발을 수행하여 서울시 도시침수 예측시스템을 고도화하였다. 예측강우정보의 경우 현재 기상청에서 광역 단위 호우특보 및 읍면동 단위 동네예보를 통해 제공되고 있지만, 풍수해 업무에 적용하기에는 제한적이며, 실시간 침수위험지역 추정의 경우 침수해석모델의 모의시간, 라이센스 등의 문제로 인해 한계를 보이고 있는 실정이다. 따라서 본 연구에서는 레이더 실황강우정보를 활용한 이류모델 기반의 예측강우정보 생산 기술을 적용하여 풍수해 업무 적용이 용이하도록 하였으며, 예측강우정보를 이용한 최적 침수시나리오 추정 기술 개발을 통해 실시간 침수위험지역 추정이 가능하도록 하였다. 서울시 도시침수 예측시스템은 25개 자치구를 대상으로 강우량, 호우이동경로, 침수 정보를 제공하고 있다. 강우정보는 기상청 및 SK-TechX 기반의 10분 및 1시간 단위 AWS 관측정보, 이류모델 기반 10분 단위 레이더 예측정보, 국지예보모델 기반 1시간 단위 LDAPS 예측정보를 제공하며. 호우이동경로는 레이더 실황강우정보와 LDAPS 바람장을 이용하여 서울시 및 수도권 지역의 10분 단위 1시간 예측경로를 제공한다. 침수정보는 실시간으로 레이더 예측강우정보를 이용하여 최적의 침수시나리오를 추정하여 격자 단위 상세 침수정보와 시군구 단위 침수위험지도를 제공한다. 본 시스템을 통해 실시간 침수위험지역 확인이 가능해짐에 따라 서울시의 효율적인 풍수해 업무 지원이 가능할 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.366-372
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• 2019

The PRISM model has been used to estimate precipitation in South Korea where observation data are readily available at a large number of weather station. However, it is likely that the PRISM model would result in relatively low reliability of precipitation estimates in North Korea where weather data are available at a relatively small number of weather stations. Alternatively, a hybrid method has been developed to estimate the precipitation distribution in area where availability of climate data is relatively low. In the hybrid method, Regression coefficients between the precipitation-terrain relationships are applied to a low-resolution precipitation map produced using the PRISM. In the present study, a hybrid approach was applied to North Korea for estimation of precipitation distribution at a high spatial resolution. At first, the precipitation distribution map was produced at a low-resolution (2,430m) using the PRISM model. Secondly, a deviation map was prepared calculating difference between altitudes of synoptic stations and virtual terrains produced using 270m-resolution digital elevation map (DEM). Lastly, another deviation map of precipitation was obtained from the maps of virtual precipitation produced using observation data from the synoptic weather stations and both synoptic and automated weather station (AWS), respectively. The regression equation between precipitation and terrain was determined using these deviation maps. The high resolution map of precipitation distribution was obtained applying the regression equation to the low-resolution map. It was found that the hybrid approach resulted in better representation of the effects of the terrain. The precipitation distribution map for the hybrid approach had similar spatial pattern to that for the existing method. It was estimated that the mean annual cumulative precipitation of entire territory of North Korea was 1,195mm with a standard deviation of 253mm.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.93-104
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• 2020

Climate change has emerged as a social issue, and efforts have been made to overcome it in various ways. However, climate change due to global warming is likely to accelerate further than we expected, and the associated damage is also likely to increase. This tendency is expected to continue in the future, leading to difficulties for the existing water resource management system based on historical data. The precipitation in 2020 caused property damage and loss of life due to the extreme rainfall exceeding the design rainfall with the very unusual prolonged rainy days. With this 2020 flood, we should no longer be passive in managing flood risk due to uncertainties in climate change.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.87-98
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• 2022

In recent years, frequent localized heavy rainfalls, which have a lot of rainfall in a short period of time, have been increasingly causing flooding damages. To prevent damage caused by localized heavy rainfalls, Hydrological Quantitative Precipitation Forecast (HQPF) was developed using the Local ENsemble prediction System (LENS) provided by the Korea Meteorological Administration (KMA) and Machine Learning and Probability Matching (PM) techniques using Digital forecast data. HQPF is produced as information on the impact of heavy rainfall to prepare for flooding damage caused by localized heavy rainfalls, but there is a tendency to overestimate the low rainfall intensity. In this study, we improved HQPF by expanding the period of machine learning data, analyzing ensemble techniques, and changing the process of Probability Matching (PM) techniques to improve predictive accuracy and over-predictive propensity of HQPF. In order to evaluate the predictive performance of the improved HQPF, we performed the predictive performance verification on heavy rainfall cases caused by the Changma front from August 27, 2021 to September 3, 2021. We found that the improved HQPF showed a significantly improved prediction accuracy for rainfall below 10 mm, as well as the over-prediction tendency, such as predicting the likelihood of occurrence and rainfall area similar to observation.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.37-45
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• 2008

It is expected that conditions of water resources will be changed in Korea in accordance with world wide climate change. In order to deal with this problem and find a way of minimizing the effect of future climate change, the usefulness of climate model simulation information is examined in this study. The objective of this study is to assess the applicability of GCM (General Circulation Model) information for Korean water resources management through uncertainty analysis. The methods are based on probabilistic measures of the effectiveness of GCM simulations of an indicator variable for discriminating high versus low regional observations of a target variable. The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two variables. An estimator that accounts for climate model simulation and spatial association between the GCM data and observed data is used. Atmospheric general circulation model (AGCM) simulations done by ECMWF (European Centre for Medium-Range Weather Forecasts) with a resolution of $2^{\circ}{\times}2^{\circ}$, and METRI (Meteorological Research Institute, Korea) with resolutions of $2^{\circ}{\times}2^{\circ}$ and $4^{\circ}{\times}5^{\circ}$, were used for indicator variables, while observed mean areal precipitation (MAP) data, discharge data and mean areal temperature data on the seven major river basins in Korea were used for target variables. The results show that GCM simulations are useful in discriminating the high from the low of the observed precipitation, discharge, and temperature values. Temperature especially can be useful regardless of model and season.

• 한국방재학회:학술대회논문집
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• 2011.02a
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• pp.193-193
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• 2011

본 연구에서는 산불발생인자들에 대한 정보를 각각의 요인별로 집적화하고 체계화시킴으로써 산불예방활동의 기초자료로 활용할 뿐만 아니라 산불발생 시, 산불의 거동을 예측하기 위한 자료로 활용하고자 하였다. 발생인자는 크게 연료 및 기상조건 관련 인자와 열적특성 관련 인자로 분류하고 연료 및 기상조건 관련 인자는 수종별, 부위별, 지역별, 고도별, 월별 산림연료들의 구성 요인들에 대해서 분석하였다. 수종별로는 생강나무, 초피나무, 조록싸리, 산초, 개암, 청미래, 고추나무, 철쭉, 조릿대, 털진달래 등 관목류 10개 수종과 김의털, 방아풀, 주름조개풀, 칡, 엉겅퀴 등 초본류 5개 수종 그리고 소나무, 잣나무, 리기다소나무, 해송, 구상나무, 주목 등 6개의 침엽수 및 굴참나무, 떡갈나무, 신갈나무, 갈참나무, 졸참나무, 상수리, 산개벚나무, 고채목, 개서어나무, 굴거리나무, 서어나무, 산벚나무, 때죽나무, 당단풍나무, 단풍나무 등 15개의 활엽수로 구성된 교목류를 대상으로 분석하였다. 부위별로는 생엽, 낙엽, 가지, 수피, 솔방울 등으로 구분하여 분석을 수행했으며, 지역별 구성은 강원(삼척/태백산), 경북(응봉산), 경기(용문산), 충북(월악산), 충남(계룡산), 전북(덕유산), 전남(월출산), 부산(금정산), 제주(한라산) 등 9개 지역을 대상으로 선정하였다. 고도별로는 강원도에 소재하고 있는 태백산을 중심으로 소나무와 신갈나무 생엽을 대상으로 900m, 1000m, 1100m, 1200m, 1300m, 1400m, 1500m 고도를 선정하여 분석을 수행하였다. 월별 분석데이터는 소나무 생엽의 경우, 2008년 6월부터 2010년 11월까지 매월 분석을 수행하였으며, 굴참나무 생엽의 경우에는 2008년부터 2010년까지 매년 6월부터 10월까지 생엽을 채취할 수 있는 기간 동안 분석을 수행하였다. 또한, 열적특성 관련 인자로는 착화특성(무염착화온도, 발염착화시간, 소염시간, 화염지속시간), 발열특성(총열방출량, 평균열방출률), 발연특성(총연기방출량, 최대연기밀도, 최대밀도시간) 등을 고찰하였다. 이와 같은 결과들은 산불발생인자 DB구축으로 부터 산불발생 위험도 및 동태예측의 기본 자료로 활용할 수 있을 뿐만 아니라 지역별 연료별 산림연료의 열적특성 DB로 부터 산불발생시 산불 위험도에 대한 기술정립과 응용성을 향상시킬 수 있을 것으로 사료된다. 이외에도 산림연료 종류별 열적특성을 결과를 토대로 문화재보존지역과 같이 문화적 가치가 높은 시설이나 주유소, 가스 충전소 등의 위험 시설에 대한 효과적인 보호를 위한 대처 방안을 사전에 준비할 수 있어 산불 피해에 대한 국민의 불안감을 줄일 수 있을 것으로 생각된다.