• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.4
• /
• pp.433-447
• /
• 2023

There is a growing demand for the stability of existing dams due to abnormal climate and the aging of dams. Emergency Action Plans (EAPs) for reservoir or dam failure only consider a single rainfall event. Therefore, this study simulates dam failure caused by continuous rainfall events, and proposes the establishment of EAP by selecting the optimal shelters. We define a mega rainfall event scenario caused by continuous rainfall events with 500-year frequency in the Chungju Dam watershed and estimate the mega flood. The mega flood event scenario is divided into two cases: scenario A represents the flooding case caused by discharge release from a dam, while scenario B is the case of a dam break. As a result of flood inundation analysis, the flooded damage area by the scenario A is 50.06 km² and the area by the scenario B is 6.1 times of scenario A (307.45 km²). We select optimal shelters for each administrative region in the city of Chungju, which has the highest inundation rate in the urban area. Seven shelter evaluation indicators from domestic and foreign shelter selection criteria are chosen, and Analytical Hierarchy Process (AHP) method is used to evaluate the alternatives. As a result of the optimal shelter selection, the six shelters are selected and five are schools. This study considers continuous rainfall events for inundation analysis and selection of optimal shelters. Also, the results of this study could be used as a reference for establishment of the EAP.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.2
• /
• pp.171-179
• /
• 2023

Due to man-made climate change, global abnormal weather phenomena have occurred, increasing disasters. Major developed countries(military) are preparing for disasters caused by extreme weather appearances. However, currently, disaster prevention plans and facilities have been implemented based on the frequency and intensity method based on statistical data, it is not enough to prepare for disasters caused by frequent extreme weather based on probability basis. The U.S. and British forces have been the fastest to take research and policy approaches related to climate change and the threat of disaster change, and are considering both climate change mitigation and adaptation. The South Korean military regards the perception of disasters to be storm and flood damage, and there is a lack of discussion on extreme weather and disasters due to climate change. In this study, the process of establishing disaster management systems in developed countries(the United States and the United Kingdom) was examined, and the response policies of each country(military) were analyzed using literature analysis techniques. In order to maintain tight security, our military should establish a response policy focusing on sustainability and resilience, and the following three policy approaches are needed. First, it is necessary to analyze the future operational environment of the Korean Peninsula in preparation for the environment that will change due to climate change. Second, it is necessary to discuss climate change 'adaptation policy' for sustainability. Third, it is necessary to prepare for future disasters that may occur due to climate change.

• Journal of Korea Water Resources Association
• /
• v.55 no.4
• /
• pp.257-266
• /
• 2022

Inundation damage is increasing every year due to localized heavy rain and an increase of rainfall exceeding the design frequency. Accordingly, the importance of hydraulic structures for flood control and defense is also increasing. The hydraulic structures are designed according to its purpose and performance, and the amount of flood is an important calculation factor. However, in Korea, design rainfall is used as input data for hydrological analysis for the design of hydraulic structures due to the lack of sufficient data and the lack of reliability of observation data. Accurate probability rainfall and its temporal distribution are important factors to estimate the design rainfall. In practice, the regression equation of temporal distribution for the design rainfall is calculated using the cumulative rainfall percentage of Huff's quartile method. In addition, the 6^th order polynomial regression equation which shows high overall accuracy, is uniformly used. In this study, the optimized regression equation of temporal distribution is derived using the variable selection method according to the principle of parsimony in statistical modeling. The derived regression equation of temporal distribution is verified through the significance test. As a result of this study, it is most appropriate to derive the regression equation of temporal distribution using the stepwise selection method, which has the advantages of both forward selection and backward elimination.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.4D
• /
• pp.513-521
• /
• 2008

The objective of this study is the evaluation of the impact on the construction condition due to historical observation data and IPCC SRES A2 climate change scenario. For this purpose, daily precipitation and daily mean temperature data which have been observed over the past 30 years by Korea Meteorological Administration are collected and applied. Also, A2 scenarios during 2011~2040 and 2051~2080 are used for this analysis. According to the results of trend analyses on annual precipitation and annual mean temperature, they are on the increase mostly. The available working day and the day occurred an extreme event are used as correlation indices between climate factor and construction condition. For the past observation data, linear regression and Mann-Kendall test are used to analyze the trend on the correlation index. As a result, both working day and extreme event occurrence day are increased. Likewise, for the future, variation analysis showed the similar result to that of the past and the occurrence frequency of extreme events is increased obviously. Therefore, we can project to increase flood damage potential on the construction site by climate change.

• Ecology and Resilient Infrastructure
• /
• v.10 no.4
• /
• pp.116-124
• /
• 2023

As the flood damage on small streams increase due to the increase in frequency of extreme climate events, the need to measure hydraulic data of them has increased for disaster risk management. National Disaster Management Institute, Ministry of Interior and Safety develops CADMT, a CCTV-based automatic discharge measurement technology, and operates pilot small streams to verify its performance and develop disaster risk management technology. The research selects two small streams such as the Neungmac and the Jungsunpil streams to develop the Nomograph by using the 4-Parameter Logistic method using only the observed rainfall data from the Automatic Weather System operated by the Korea Meteorological Agency closest to the small streams and discharge data collected by using the CADMT. To evaluate developed Nomograph, the research forecasts floods discharges in each small stream and compares the result with the observed discharges. As a result of the evaluations, the forecasted value is found to represent the observed value well, so if more accurate observed data are collected and the Nomograph based on it is developed in the future, the high-accuracy flood prediction and warning will be possible.

• Journal of the Korean Society of Marine Environment & Safety
• /
• v.29 no.7
• /
• pp.843-856
• /
• 2023

The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_2
• /
• pp.755-770
• /
• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.6
• /
• pp.721-733
• /
• 2023

As the frequency of extreme rainfall events increase due to climate change, climate change adaptation measures have been proposed by the central and local governments. In order to reduce flood damage in urban areas, various flood response policies, such as low impact development techniques and enhancement of the capacity of rainwater drainage networks, have been proposed. When these policies are established, regional characteristics and policy-effectiveness from the cost-benefit perspective must be considered for the flood mitigation measures. In this study, capacity enhancement of rainwater pipe networks and low impact development techniques including green roof and permeable pavement techniques are selected. And the flood reduction effect of the target watershed, Gwanak campus of Seoul National University, was analyzed using SWMM model which is an urban runoff simulation model. In addition, along with the quantified urban flooding reduction outputs, construction and operation costs for various policy scenarios were calculated so that cost-benefit analyses were conducted to analyze the effectiveness of the applied policy scenarios. As a result of cost-benefit analysis, a policy that adopts both permeable pavement and rainwater pipe expansion was selected as the best cost-effective scenario for flood mitigation. The research methodology, proposed in this study, is expected to be utilized for decision-making in the planning stage for flood mitigation measures for each region.

• Journal of the Korean Geotechnical Society
• /
• v.39 no.12
• /
• pp.23-35
• /
• 2023

The Ministry of Agriculture, Food and Rural Affairs has announced design standards for disaster-resilient greenhouses capable of resisting wind speeds with a 30-year frequency to respond to the destruction of greenhouses caused by strong winds. However, many greenhouses are still being maintained or newly installed as conventional standard facilities for the supply type. In these supply-type greenhouses, a small pile called a steel peg is used as reinforcement to resist wind-induced damage. The wind resistance of steel pegs varies depending on the soil environment and installation method. In this study, a correlation analysis was performed between the wind resistance of steel pegs installed in loam and sandy loam, using a soil hardness meter. To estimate the pull-out force of steel pegs based on soil water content and compaction, soil compaction tests and laboratory soil box and field tests were performed. The soil compaction degree was measured using a soil hardness meter that could easily confirm soil compaction. This was used to analyze the correlation between the soil compaction degree in the tests. In addition, a correlation analysis was performed between the pull-out force of steel pegs in the soil box and field. The findings of this study will be useful in predicting the pull-out force of steel pegs based on the method of steel peg installation and environmental changes.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.26 no.1
• /
• pp.63-74
• /
• 2024

In agriculture, frost can be devastating, which is why observation and forecasting are so important. According to a recent report analyzing frost observation data from the Korea Meteorological Administration, despite global warming due to climate change, the late frost date in spring has not been accelerated, and the frequency of frost has not decreased. Therefore, it is important to automate and continuously operate frost observation in risk areas to prevent agricultural frost damage. In the existing frost observation using leaf wetness sensors, there is a problem that the reference voltage value fluctuates over a long period of time due to contamination of the observation sensor or changes in the humidity of the surrounding environment. In this study, a datalogger program was implemented to automatically solve these problems. The established frost observation system can stably and automatically accumulate time-resolved observation data over a long period of time. This data can be utilized in the future for the development of frost diagnosis models using machine learning methods and the production of frost occurrence prediction information for surrounding areas.