• Journal of Climate Change Research
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• v.1 no.2
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• pp.109-120
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• 2010

Heat wave is a disaster, which increases morbidity and mortality in temperate regions. Climate model results indicate that both intensity and frequency of heat wave in the future will be increased. This study shows the result about relationship between excess mortality and offensive airmass in 7 metropolitan cities, and an operational Heat-Health Warning System (HHWS) in Korea. Using meteorological observations, the Spatial Synoptic Classification (SSC) has been used to classify each summer day from 1982 to 2007 into specific airmass categories for each city. Through the comparative study analysis of the daily airmass type and the corresponding daily mortality rate, Dry Tropical (DT), and Moist Tropical plus (MT+) were identified as the most offensive airmasses with the highest rates of mortality. Therefore, using the multiple linear regression, forecast algorithm was produced to predict the number of the excess deaths that will occur with each occurrence of the DT and MT+ days. Moreover, each excess death forecast algorithm was implemented for the system warning criteria based on the regional acclimatization differences. HHWS will give warnings to the city's residents under offensive weather situations which can lead to deterioration in public health, under the climate change.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.1
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• pp.9-18
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• 2019

The intensity and the number of days of high temperature occurrence are also high and record heat occurred. In addition, the global warming phenomenon is intensifying globally, and especially in South Korea, the urban heat island phenomenon is also occurring due to rapid urbanization due to rapid industrial development. As the temperature of the city rises, it causes problems such as the comfort of the residential living and the cooling load. In this study, the cool roof performance is evaluated according to the roof color to reduce these problems. Unlike previous studies, UAV(Unmanned Aerial Vehicle) thermal infrared camera was used to obtain the surface temperature (white, grey, green, blue, brown, black) according to the rooftop color by remote sensing technique. As a result, the surface temperature of white color was $11{\sim}20^{\circ}C$ lower than other colors. Also air conditioning temperature of white color was $1.5{\sim}4.4^{\circ}C$ lower than other colors and the digital thermometer of white color was about $1.5{\sim}3.5^{\circ}C$ lower than other colors. It was confirmed that the white cool roof performance is the best, and the UAV and the thermal infrared camera can confirm the cool roof performa.

• Journal of Korea Water Resources Association
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• v.51 no.spc
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• pp.1127-1134
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• 2018

According to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), climate change increases the frequency of abnormal weather phenomenon. As the frequency of abnormal weather phenomenon increases, frequency of disasters related to water resources such as floods and droughts also increases. Drought is the main factor that directly affects water supply. Recently, the intensity of drought and the frequency of drought occurrence have increased in Korea. So, there is a need for water resource securing technology for stable water supply. Korean Water Plan mentioned that water reserves concept is necessary for stable water supply. Most multi-purpose reservoirs in Korea have emergency storage in addition to conservation storage used for water supply. However, there is no clear use standard for emergency storage. This study investigated the use of reservoir reserves for stable water supply. In order to consider the climate change impact, the AR5-based hydrological scenario was used as inflow data for the reservoir simulation model. Reservoir simulations were carried out in accordance with the utilization conditions of emergency storage and water supply adjustment standard. The optimal reserves for each multi-purpose reservoirs was estimated using simulation results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.23 no.5
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• pp.84-95
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• 2019

This paper reports the process of seismic fragility analysis for the rahman-type continuous bridge system. The target structure was the five span highway bridge with maximum pier hight of 72m. OpenSees software was used for the nonlinear time history analysis. In this study, 50 ground motions are considered for nonlinear time history analysis. For each ground motion, PGA was scaled from 0.1g to 2.0g with intervals of 0.1g in order to consider a wide range of the seismic intensity measure. In addition, yield displacement and ultimate displacement of each pier were calculated through section analysis. Based on the result of non linear time history analysis and section analysis, damage condition of target bridge was classified according to the definition of damage condition proposed by Barbat et al. As a result, it was predicted that Extensive Damage occurred at P1 when 0.731 g earthquake occurred in the longitudinal direction. Based on the seismic fragility analysis results, it is found that the probability of occurrence of Extensive Damage in the 4,800 - year period earthquake was about 4.2%. Therefore the target bridge has enough safety for earthquake.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.277-286
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• 2021

Background: As trade increases, the influx of various alien species and their spread to new regions are prevalent and no longer a special problem. Anthropogenic activities and climate changes have made the distribution of alien species out of their native range common. As a result, alien species can be easily found anywhere, and they have nothing but only a few differences in intensity. The prevalent distribution of alien species adversely affects the ecosystem, and a strategic management plan must be established to control them effectively. To this end, hot spots and cold spots were analyzed according to the degree of distribution of invasive alien plants, and major environmental factors related to hot spots were found. We analyzed the 10,287 distribution points of 126 species of alien plants collected through the national survey of alien species by the hierarchical model of species communities (HMSC) framework. Results: The explanatory and fourfold cross-validation predictive power of the model were 0.91 and 0.75 as AUC values, respectively. The hot spots of invasive plants were found in the Seoul metropolitan area, Daegu metropolitan city, Chungcheongbuk-do Province, southwest shore, and Jeju island. Generally, the hot spots were found where the higher maximum temperature of summer, precipitation of winter, and road density are observed, but temperature seasonality, annual temperature range, precipitation of the summer, and distance to river and sea were negatively related to the hot spots. According to the model, the functional traits accounted for 55% of the variance explained by the environmental factors. The species with higher specific leaf areas were more found where temperature seasonality was low. Taller species preferred the bigger annual temperature range. The heavier seed mass was only preferred when the max temperature of summer exceeded 29 ℃. Conclusions: In this study, hot spots were places where 2.1 times more alien plants were distributed on average than non-hot spots (33.5 vs 15.7 species). The hot spots of invasive plants were expected to appear in less stressful climate conditions, such as low fluctuation of temperature and precipitation. Also, the disturbance by anthropogenic factors or water flow had positive influences on the hot spots. These results were consistent with the previous reports about the ruderal or competitive strategies of invasive plants instead of the stress-tolerant strategy. The functional traits are closely related to the ecological strategies of plants by shaping the response of species to various environmental filters, and our result confirmed this. Therefore, in order to effectively control alien plants, it is judged that the occurrence of disturbed sites in which alien plants can grow in large quantities is minimized, and the river management of waterfronts is required.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1091-1104
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• 2022

Climate change is predicted to increase the frequency and intensity of rainfall worldwide, and the pattern is changing due to inundation damage in urban areas due to rapid urbanization and industrialization. Accordingly, the impact assessment of climate change is mentioned as a very important factor in urban planning, and the World Meteorological Organization (WMO) is emphasizing the need for an impact forecast that considers the social and economic impacts that may arise from meteorological phenomena. In particular, in terms of traffic, the degradation of transport systems due to urban flooding is the most detrimental factor to society and is estimated to be around £100k per hour per major road affected. However, in the case of Korea, even if accurate forecasts and special warnings on the occurrence of meteorological disasters are currently provided, the effects are not properly conveyed. Therefore, in this study, high-resolution analysis and hydrological factors of each area are reflected in order to suggest the depth of flooding of urban floods and to cope with the damage that may affect vehicles, and the degree of flooding caused by rainfall and its effect on vehicle operation are investigated. decided it was necessary. Therefore, the calculation formula of rainfall-immersion depth-vehicle speed is presented using various machine learning techniques rather than simple linear regression. In addition, by applying the climate change scenario to the rainfall-inundation depth-vehicle speed calculation formula, it predicts the flooding of urban rivers during heavy rain, and evaluates possible traffic network disturbances due to road inundation considering the impact of future climate change. We want to develop technology for use in traffic flow planning.

• Journal of the Korean Society of Radiology
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• v.16 no.4
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• pp.471-476
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• 2022

The purpose of this study was to study the probability of cancer occurrence due to photoneutron dose exposure of the colon and thyroid gland, which are normal organs, in 3D CRT, IMRT 5 portals, and IMRT 9 portals, which are radiotherapy methods for prostate cancer. The total prescribed dose for prostate cancer was 6600 cGy, 220 cGy per dose, and 30 divided irradiations were applied for the total number of times. After setting up the Rando phantom on the treatment table (couch) of the medical linear accelerator used in the experiment, an optically stimulated luminescence albedo neutron dosimeter was placed on the corresponding area of the large intestine and thyroid gland of the phantom for measurement. During 3D CRT of prostate cancer, the probability of secondary cancer due to photoneutron dose to the colon and thyroid gland, which are normal organs, was 1.8 per 10,000 people. And IMRT 5 portals were 8.7 per 10,000 people, which was about 5 times larger than 3D CRT. IMRT 9 portals derived the result that there is a probability that 1.2 people per 1,000 people will develop cancer. Based on this study, the risk of secondary radiation exposure due to the dose of photoneutrons generated during radiation therapy is studied, and it is thought that it will be used as useful data for radiation protection in relation to the stochastic effect of radiation in the future.

• 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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.3B
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• pp.269-276
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• 2010

Climatic disasters are globally soaring due to recent acceleration of global warming. Especially the occurrence frequency of heavy rainfalls is increasing since the rainfall intensity is increasing due to the change of rainfall pattern, This study proposed the non-stationary frequency analysis for estimating design rainfalls in a design target year, considering the change of rainfall pattern through the climatic change scenario. The annual rainfalls, which are regionally downscaled from the BCM2 (A2 scenario) and NCEP data using a K-NN method, were used to estimate the parameters of a probability distribution in a design target year, based on the relationship between annual mean rainfalls and distribution parameters. A Gumbel distribution with a probability weighted method was used in this study. Seoul rainfall data, which are the longest observations in Korea, were used to verified the proposed method. Then, rainfall data at 7 stations, which have statistical trends in observations in 2006, were used to estimate the design rainfalls in 2020. The results indicated that the regional annual rainfalls, which were estimated through the climate change scenario, significantly affect on the design rainfalls in future.