• Journal of Korean Society of Disaster and Security
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• v.12 no.1
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• pp.11-21
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• 2019

This study assessed the risk of disaster by using QRE(Quick Risk Estimation - UNISDR Roll Model City of Basic Evaluation Tool) tools for three natural disasters and sixteen social disasters managed by the Seoul Metropolitan Government. The criteria for selecting 19 disaster types in Seoul are limited to disasters that occur frequently in the past and cause a lot of damage to people and property if they occur. We also considered disasters that are likely to occur in the future. According to the results of the QRE tools for disaster type in Seoul, the most dangerous type of disaster among the Seoul city disasters was "suicide accident" and "deterioration of air quality". Suicide risk is high and it is not easy to take measures against the economic and psychological problems of suicide. This corresponds to the Risk ratings(Likelihood ranking score & Severity rating) "M6". In contrast, disaster types with low risk during the disaster managed by the city of Seoul were analyzed as flooding, water leakage, and water pollution accidents. In the case of floods, there is a high likelihood of disaster such as localized heavy rains and typhoons. However, the city of Seoul has established a comprehensive plan to reduce floods and water every five years. This aspect is considered to be appropriate for disaster prevention preparedness and relatively low disaster risk was analyzed. This corresponds to the disaster Risk ratings(Likelihood ranking score & Severity rating) "VL1". Finally, the QRE tool provides the city's leaders and disaster managers with a quick reference to the risk of a disaster so that decisions can be made faster. In addition, the risk assessment using the QRE tool has helped many aspects such as systematic evaluation of resilience against the city's safety risks, basic data on future investment plans, and disaster response.

• Journal of the Korean earth science society
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• v.41 no.6
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• pp.588-598
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• 2020

The seafloor geology of Ieodo, a submerged volcanic island, has been poorly understood, although this place has gained considerable attention for ocean and climate studies. The main purpose of the study is to understand and elucidate types, distribution patterns and provenance of the surficial sediments in and around the Ieodo area. For this purpose, 25 seafloor sediments were collected using a box-corer, these having been analyzed for grain sizes. XRD (X-ray Diffraction) analysis of fine-grained sediments was conducted for characterizing clay minerals. The peak of Ieodo exists in the northern region, while in the southern area, shore platforms occur. The extensive platform in the south results from severe erosion by strong waves. However, the northern peak still survived from differential weathering. Grain size analyses indicated that gravels and gravelly sands with skeletons and shells were distributed predominantly on the volcanic apron and shore platform. Muddy sediments were found along the Ieodo and the adjacent deeper seafloor. Based on the analysis of clay mineral composition, illites were the most abundant in fine muds, followed by chlorites and kaolinites. The ratio plots of clay minerals for the provenance discrimination suggested that the Ieodo muds were likely to be derived from the Yangtze River (Changjiang River). As a consequence, gravels and gravelly sands with bioclastics may be supplied from the Ieodo volcanic apron by erosion processes. Wave activities might play a major role in transportation and sedimentation. In contrast, fine muds were assumed to be derived from the inflow of the Yangtze River, particularly in summer. Deposition in the Ieodo area is, therefore, probably controlled by the inflow from the Changjiang Dilute Water and summer typhoons from the south.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.66 no.2
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• pp.105-111
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• 2021

Rice lodging is an annual occurrence caused by typhoons accompanied by strong winds and strong rainfall, resulting in damage relating to pre-harvest sprouting during the ripening period. Thus, rapid estimations of the area of lodged rice are necessary to enable timely responses to damage. To this end, we obtained images related to rice lodging using a drone in Gimje, Buan, and Gunsan, which were converted to 128 × 128 pixels images. A convolutional neural network (CNN) model, a deep learning model based on these images, was used to predict rice lodging, which was classified into two types (lodging and non-lodging), and the images were divided in a 8:2 ratio into a training set and a validation set. The CNN model was layered and trained using three optimizers (Adam, Rmsprop, and SGD). The area of rice lodging was evaluated for the three fields using the obtained data, with the exception of the training set and validation set. The images were combined to give composites images of the entire fields using Metashape, and these images were divided into 128 × 128 pixels. Lodging in the divided images was predicted using the trained CNN model, and the extent of lodging was calculated by multiplying the ratio of the total number of field images by the number of lodging images by the area of the entire field. The results for the training and validation sets showed that accuracy increased with a progression in learning and eventually reached a level greater than 0.919. The results obtained for each of the three fields showed high accuracy with respect to all optimizers, among which, Adam showed the highest accuracy (normalized root mean square error: 2.73%). On the basis of the findings of this study, it is anticipated that the area of lodged rice can be rapidly predicted using deep learning.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.26 no.4
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• pp.343-355
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• 2021

Eelgrass, Zostera marina L., was widely distributed around Sinyangseopji Beach in Bangdu Bay, on the eastern coast of Jeju Island, until breakwater construction in the late 1990s resulted in its complete loss. Six experimental sites were identified for restoration of the Z. marina bed in Bangdu Bay. Using the staple method, 500 Z. marina shoots were transplanted at each site in January 2019 and 2020. The transplants, along with environmental parameters, were monitored for 10 months following transplantation. There were significant differences in underwater irradiance, water temperature, and salinity among the sites, but all were suitable for Z. marina growth. The Ulva species, an opportunistic alga, appeared in spring and accumulated during summer at all sites; however, there was no significant effect of Ulva species on the survival and growth of the eelgrass transplants. Most of the transplanted Z. marina survived, and after 3 months, the density increased by 112.5-300% due to vegetative propagation, with a rapid rate of increase observed during spring and early summer at all sites. For 1-2 months after transplanting, the Z. marina shoots showed signs of transplant shock, after which the shoot density increased at all sites, confirming that all transplants adapted well to the new environment. However, in both 2019 and 2020, during late summer to early fall, the sites experienced heavy damage from typoons (twice in 2019 and three times in 2020) that hit Bangdu Bay. The transplants at two sites located in the center of Bangdu Bay were completely destroyed, but those at three sites located to the west of the bay showed a 192-312% increase in density. Thus, we confirmed that the Bangdu Bay Z. marina bed can be restored, with the highest probability of success for Z. marina restoration on the western side of Bangdu Bay, which is protected from typhoons.

• Journal of Korea Water Resources Association
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• v.54 no.11
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• pp.903-913
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• 2021

In the flood season, the measurement of the river discharge has many restrictions due to reasons such as budget, manpower, safety, convenience in measurement and so on. In particular, when heavy rain events occur due to typhoons, etc., it is difficult to measure the amount of flood due to the above problems. In order to improve this problem, in this study, a method was developed that can measure the river discharge in a flood season simply and safely in a short time with minimal manpower by combining the functions of a drone and a surface velocity doppler radar. To overcome the mechanical limitations of drones caused by weather issues such as wind and rainfall derived from the measurement of the river discharge using the conventional drone, we developed a drone with P56 grade dustproof and waterproof performance, stable flight capability at a wind speed of up to 36 km/h, and a payload weight of up to 10 kg. Further, to eliminate vibration which is the most important constraint factor in the measurement with a surface velocity doppler radar, a damper plate was developed as a device that combines a drone and a surface velocity Doppler radar. The velocity meter DSVM (Dron and Surface Veloctity Meter using doppler radar) that combines the flight equipment with the velocity meter was produced. The error of ±3.5% occurred as a result of measuring the river discharge using DSVM at the point of Geumsan-gun (Hwangpunggyo) located at Bonghwang stream (the first tributary stream of the Geum River). In addition, when calculating the mean velocity from the measured surface velocity, the measurement was performed using ADCP simultaneously to improve accuracy, and the mean velocity conversion factor (0.92) was calculated by comparing the mean velocity. In this study, the discharge measured by combining a drone and a surface velocity meter was compared with the discharge measured using ADCP and floats, so that the application and utility of DSVM was confirmed.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1095-1105
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• 2021

The advancement of dam operation is further required due to the upcoming rainy season, typhoons, or torrential rains. Besides, physical models based on specific rules may sometimes have limitations in controlling the release discharge of dam due to inherent uncertainty and complex factors. This study aims to forecast the water level of the nearest station to the dam multi-timestep-ahead and evaluate the availability when it makes a decision for a release discharge of dam based on LSTM (Long Short-Term Memory) of deep learning. The LSTM model was trained and tested on eight data sets with a 1-hour temporal resolution, including primary data used in the dam operation and downstream water level station data about 13 years (2009~2021). The trained model forecasted the water level time series divided by the six lead times: 1, 3, 6, 9, 12, 18-hours, and compared and analyzed with the observed data. As a result, the prediction results of the 1-hour ahead exhibited the best performance for all cases with an average accuracy of MAE of 0.01m, RMSE of 0.015 m, and NSE of 0.99, respectively. In addition, as the lead time increases, the predictive performance of the model tends to decrease slightly. The model may similarly estimate and reliably predicts the temporal pattern of the observed water level. Thus, it is judged that the LSTM model could produce predictive data by extracting the characteristics of complex hydrological non-linear data and can be used to determine the amount of release discharge from the dam when simulating the operation of the dam.

• Atmosphere
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• v.33 no.2
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• pp.223-246
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• 2023

This paper summarized the research papers on weather extremes that occurred in the Republic of Korea, which were published in the domestic and foreign journals during 1963~2022. Weather extreme is defined as a weather phenomenon that causes serious casualty and property loss; here, it includes typhoon, heavy rain, drought, heat wave, cold surge, heavy snow, and strong gust. Based on the 2011~2020 statistics in Korea, above 80% of property loss due to all natural disasters were caused by typhoons and heavy rainfalls. However, the impact of the other weather extremes can be underestimated rather than we have actually experienced; the property loss caused by the other extremes is hard to be quantitatively counted. Particularly, as global warming becomes serious, the influence of drought and heat wave has been increasing. The damages caused by cold surges, heavy snow, and strong gust occurred over relatively local areas on short-term time scales compared to other weather hazards. In particularly, strong gust accompanied with drought may result in severe forest fires over mountainous regions. We hope that the present review paper may remind us of the importance of weather extremes that directly affect our lives.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.4
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• pp.1-15
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• 2023

This research intended to reveal the special characteristics of the vegetation structure and the tendency of change of -landfill slope districts, which are reclaimed land, through an investigationsinto the presently existent vegetation and plant community structure of the World Cup Park landfill slope district. For the analysis of changes in vegetation, this study compared the results of field surveys in 1999, 2003, 2005, 2007, 2008, 2012, 2016, and 2021. For the investigation into the plant community structure, a field investigation was carried out in 2021 with six fixed investigation districts designated in 1999 as subjects. To analyze the change in the plant community structure, the past data on the population, the number of the species, and the species diversity by the layer in 2021 were compared and analyzed in the landfill slope district, which is reclaimed land. The changes of the vegetation distribution and the power had been affected by typhoons (Kompasu). Above the plantation foundation, which had been dry and poor, Salix koreensis, marsh woody plants that had formed the community, decreased greatly. The Robinia pseudoacacia community, after the typhoon in 2010, decreased in the number of species and population. Afterward, it showed a tendency to rebound. Regarding the Ailanthus altissima-Robinia pseudoacacia-Paulownia tomentosa community, the number of the species and the population had shown a change similar to the Robinia pseudoacacia community. The Paulownia tomentosa and the Ailanthus altissima have been culled. The slope was predicted as a Future Robinia pseudoacacia forest. The Salix pseudolasiogyne community has been transitioning to a Robinia pseudoacacia forest. Only some enumeration districts, the Robinia pseudoacacia forests and the Salix pseudolasiogyne, had been growing. However, most had been in been declining. It was predicted that this community will be maintained as a Robinia pseudoacacia forest in the future. As these vegetation communities are the representative vegetation of the landfill slope districts, which is reclaimed land, there is a need to understand the ecosystem changes of the community through continuous monitoring. The results of this research can be utilized as a basic material for the vegetation restoration of reclaimed land.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.25 no.4
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• pp.117-131
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• 2020

Although most species in genus Zostera inhabit shallow coastal areas and bays with weak wave energy, the Asian eelgrass, Zostera asiatica is distributed in deep water depth (8-15 m) unlike other seagrasses on the eastern coast of Korea. To examine factors limiting distribution Z. asiatica in relatively deep coastal areas, a transplantation experiment was conducted on October 2011, in which Z. asiatica shoots were transplanted from the reference site (donor meadow, ~9 m) to the shallow transplant site (~3 m). We compared shoot density, morphology, and productivity of Z. asiatica as well as environmental factors (underwater irradiance, water temperature, and nutrients) between the reference and transplant sites from October 2011 to September 2012. Shoot density and shoot height of transplants dramatically decreased within a few months after transplantation, but were similar with Z. asiatica in the reference site during spring. Shoot productivity were significantly higher in the transplant site than in reference site because of high light availability and nutrient concentrations. Transplants showed photoacclimatory responses such as higher rETR_max and E_k and lower photosynthetic efficiency in the transplant site than those in the reference site. Most of Z. asiatica transplant in the shallow transplant site disappeared in summer, which may be due to the high wave energy and physical damages induced by typhoons (TEMBIN and SANBA) in August and September 2012. According to the results of this study, Z. asiatica could not survive in shallow areas despite of more favorable light and nutrient conditions. Thus, Z. asiatica may restrictively occur in deep areas to avoid the intense physical stresses in the shallow area on the east coast of Korea.