• Water for future
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• v.52 no.8
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• pp.34-36
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• 2019

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.129-138
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• 2023

This study attempted to analyze the comparative advantage in terms of disaster safety costs in verifying the effectiveness and economic feasibility of the high-performance water-bulwark system in the pole tunnel, which was recently promoted as a part of the acceleration of vehicles. The tunnel to be analyzed was divided into a short tunnel(Anyang, Cheonggye) and a long tunnel(Suraksan, Sapaesan). As a result, it was analyzed that 25% of the improvement effect would occur if one lane was secured by applying the Water-Bulwark System. It was analyzed that this is because the time value cost, which accounts for a large proportion of the traffic congestion cost of short tunnels and pole tunnels, differs depending on the congestion time and traffic volume, not the length of the tunnel.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.94-97
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• 2007

This study aims to find the characteristics of damage and states of natural disasters at Gimhae, Gyeongsangnam-do from 1985 to 2004. Using the data of Statistical yearbook of calamities issued by the National Emergency Management Agency and Annual Climatological Report issued by the Korea Meteorological Administration. we have analyzed the cause, elements, and vulnerable regions for natural disasters. Major causes of natural disaster at Gimhae are four, such as a heavy rain, heavy rain typhoon, typhoon, storm snow, and storm. The cause of disaster recorded the most amount of damage is typhoon. The areas of Hallim-myeon, Sangdong-myeon, and Saengnim-myeon are classified the vulnerable region for the natural disasters in Gimhae. Therefore, it seems necessary to build natural disaster mitigation plan each cause of disaster to control water resources and to reduce damage for these areas.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1245-1254
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• 2020

In this study, the limitations of the existing water level detection algorithm using CCTV images were recognized and the water level detection algorithm was improved by applying the Region growing technique. It applied three techniques (Horizontal projection profile, Texture analysis, and Optical flow) to estimate the water area, and the results were analyzed in a comprehensive analysis to select the initial water area. The water level was then continuously detected by the Region growing technique, referring to the initial water area. As a result, it was possible to confirm that the exact level of water was detected without being affected by environmental factors compared to the existing level detection algorithm, which had frequent mis-detection phenomena depending on the surrounding environmental factors. In addition, the water level was detected in the video showing flooded roads in urban areas, not in the video of the river. These results are believed to be able to supplement the difficulty of monitoring at all times with limited manpower by automatically detecting the level of water through numerous CCTV footage installed throughout the country, and to contribute to laying the foundation for preventing disasters caused by torrential rains and typhoons in advance.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.809-818
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• 2019

The Republic of Korea is very vulnerable to damage from storm and flood due to the rainfall phenomenon in summer and the topography of the narrow peninsula. The damage is recently getting worse because of the concentration rainfall. The accurate damage information production and analysis is required to prepare for future disaster. In this study, we analyzed the water surface area changes of Byeokjeong, Sajeom, Subu and Boryeong using Sentinel-1 satellite imagery. The surface area of the Sentinel-1 satellite, taken from May 2015 to August 2019, was preprocessed using RTC and image binarization using Otsu. The water surface area of reservoir was compared with the storage capacity from WAMIS and RIMS. As a result, Subu and Boryeong showed strong correlations of 0.850 and 0.941, respectively, and Byeokjeong and Sajeom showed the normal correlation of 0.651 and 0.657. Thus, SAR satellite imagery can be used to objective data as disaster management.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.963-973
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• 2019

This study reviews a urban flooding risk criteria estimation model to predict risk criteria in areas where flood risk criteria are not precalculated by using watershed characteristic data and limit rainfall based on damage history. The risk criteria estimation model was designed using Support Vector Machine, one of the machine learning algorithms. The learning data consisted of regional limit rainfall and watershed characteristic. The learning data were applied to the SVM algorithm after normalization. We calculated the mean absolute error and standard deviation using Leave-One-Out and K-fold cross-validation algorithms and evaluated the performance of the model. In Leave-One-Out, models with small standard deviation were selected as the optimal model, and models with less folds were selected in the K-fold. The average accuracy of the selected models by rainfall duration is over 80%, suggesting that SVM can be used to estimate flooding risk criteria.

• Korean Journal of Remote Sensing
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• v.38 no.6_3
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• pp.1761-1775
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• 2022

Due to unpredictable climate change, the frequency of occurrence of water-related disasters and the scale of damage are also continuously increasing. In terms of disaster management, it is essential to identify the damaged area in a wide area and monitor for mid-term and long-term forecasting. In the field of water disasters, research on remote sensing technology using Synthetic Aperture Radar (SAR) satellite images for wide-area monitoring is being actively conducted. Time-series analysis for monitoring requires a complex preprocessing process that collects a large amount of images and considers the noisy radar characteristics, and for this, a considerable amount of time is required. With the recent development of cloud computing technology, many platforms capable of performing spatiotemporal analysis using satellite big data have been proposed. Google Earth Engine (GEE)is a representative platform that provides about 600 satellite data for free and enables semi real time space time analysis based on the analysis preparation data of satellite images. Therefore, in this study, immediate water disaster damage detection and mid to long term time series observation studies were conducted using GEE. Through the Otsu technique, which is mainly used for change detection, changes in river width and flood area due to river flooding were confirmed, centered on the torrential rains that occurred in 2020. In addition, in terms of disaster management, the change trend of the time series waterbody from 2018 to 2022 was confirmed. The short processing time through javascript based coding, and the strength of spatiotemporal analysis and result expression, are expected to enable use in the field of water disasters. In addition, it is expected that the field of application will be expanded through connection with various satellite bigdata in the future.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.149-149
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• 2022

Accurate quantitative evaluation of baseflow contribution to streamflow is imperative to address seasonal drought vulnerability, flood occurrence and groundwater management concerns for efficient and sustainable water resources management in watersheds. Several baseflow separation algorithms using recursive filters, graphical method and tracer or chemical balance have been developed but resulting baseflow outputs always show wide variations, thereby making it hard to determine best separation technique. Therefore, the current global shift towards implementation of artificial intelligence (AI) in water resources is employed to compare the performance of deep learning models with conventional hydrograph separation techniques to quantify baseflow contribution to streamflow of Piney River watershed, Tennessee from 2001-2021. Streamflow values are obtained from the USGS station 03602500 and modeled to generate values of Baseflow Index (BI) using Web-based Hydrograph Analysis (WHAT) model. Annual and seasonal baseflow outputs from the traditional separation techniques are compared with results of Long Short Term Memory (LSTM) and simple Gated Recurrent Unit (GRU) models. The GRU model gave optimal BFI values during the four seasons with average NSE = 0.98, KGE = 0.97, r = 0.89 and future baseflow volumes are predicted. AI offers easier and more accurate approach to groundwater management and surface runoff modeling to create effective water policy frameworks for disaster management.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.210-210
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• 2022

This study evaluates Japan's Official Development Assistance (ODA) projects in Thailand from 2011 to 2013 by deploying the Sendai Framework for Disaster Risk Reduction (SFDRR) and the Organization for Economic Cooperation Development (OECD) evaluation criteria. Special attention is placed on disaster-related development assistance activities of Japan through reviewing long-term impacts of the projects. The Japan International Cooperation Agency (JICA) has played a crucial role in transferring Japan's experiences on disaster risk management to developing countries, including Thailand. The study highlights two flood risk management projects in Thailand with the support of JICA after the 2011 floods, namely the Project for the Comprehensive Flood Management Plan for the Chao Phraya River Basin and the Project for Flood Countermeasures for Thailand Agriculture Sector. The case studies demonstrate that the projects were efficiently and effectively conducted for meeting Thailand's needs and requirements. JICA provided multi-hazards risk analysis through scientific data as well as local knowledge. However, achievements of the project did not last for long because of a lack of Thai stakeholders' commitment and JICA's post-project management. It is concluded that a development agency should consider impacts and sustainability of flood risk management projects more carefully from the stage of planning, and the practical application of the knowledge, and technologies should also be monitored progressively after the completion of the project.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.25-36
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• 2021

This study analyzed the causes of flood accidents, such as isolation and lost footing accidents in Dorimcheon, to provide legal and institutional improvements. For cause analysis, Field Investigation, Stakeholder Interview, Report, manual, Law et al. Review, Analysis of water level change characteristics, automatic alarm issuance standard level analysis, and evacuation time according to river control were evaluated. Dorimcheon has the characteristics of a typical urban river, which is disadvantageous in terms of water control. In addition, the risk of flood accidents is high because the section where fatal accidents occur forms sharply curved channels. Tripping and isolation accidents occur in the floodplain watch and evacuation stage, which is the stage before the flood watch and warning is issued. Because floodplain evacuation is issued only when the water level rises to the floodplain, an immediate response according to the rainfall forecast is essential. Furthermore, considering that the rate of water level rise is up to 2.62 cm/min in Sillimgyo 3 and Gwanakdorimgyo, sufficient evacuation time is not secured after the floodplain watch is issued. Considering that fatal accidents occurred 0.46 m below the standard water level for the flood watch, complete control is very important, such as blocking the entry of rivers to prevent accidents. Based on these results, four improvement measures were suggested, and it is expected to contribute to the prevention of Tripping and Isolation Accidents occurring in rivers.