• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.7
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• pp.845-857
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• 2020

Compound coastal disasters are a type of natural disaster featuring both internal and external flooding due to rises in sea-level, torrential rains, typhoons, and tsunamis. The, incidence and scale of damage from such disasters is increasing. This aim of this study was to review the current laws and systems managing the phenomenon of the coastal complex disaster, and to derive recommendations for improvements to manage and prevent them. In this study, the Framework Act on the Management of Disasters and Safety, the Countermeasures against Natural Disasters Act, the National Land Planning and Utilization Act, the Coast Management Act, the River Act, and the Sewerage Act were reviewed, with focus on the district-zoning system designated by ministries for the management of natural disasters along the coast. Through a comparison of the purpose and nature of the laws, spatial scope, and management resources, it was judged that it would be desirable to comprehensively manage compound coastal disasters based on the Countermeasures Against Natural Disasters Act. In order to overcome the limitations of the current system and to derive specific measures to improve laws and systems, a questionnaire survey on detailed factors was conducted targeting experts in natural disaster management. The results indicated that it is necessary to improve the current system or introduce a new system for the management of coastal complex disasters, with integrated management of land and sea areas through the installation and operation of integrated decision-making governance by related ministries such as MOIS, MOLIT, MOF, and ME.

• 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.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1195-1204
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• 2021

Recently, local torrential rain have become more frequent and severe due to abnormal climate conditions, causing a surge in human and properties damage including infrastructures along the river. In this study, water surface elevation prediction algorithm was developed using the LSTM (Long Short-term Memory) technique specialized for time series data among Machine Learning to estimate and prevent flooding of the facilities. The study area is Jamsu Bridge, the study period is 6 years (2015~2020) of June, July and August and the water surface elevation of the Jamsu Bridge after 3 hours was predicted. Input data set is composed of the water surface elevation of Jamsu Bridge (EL.m), the amount of discharge from Paldang Dam (m³/s), the tide level of Ganghwa Bridge (cm) and the number of tweets in Seoul. Complementary data were constructed by using not only structured data mainly used in precedent research but also unstructured data constructed through wordcloud, and the role of unstructured data was presented through comparison and analysis of whether or not unstructured data was used. When predicting the water surface elevation of the Jamsu Bridge, the accuracy of prediction was improved and realized that complementary data could be conservative alerts to reduce casualties. In this study, it was concluded that the use of complementary data was relatively effective in providing the user's safety and convenience of riverside infrastructure. In the future, more accurate water surface elevation prediction would be expected through the addition of types of unstructured data or detailed pre-processing of input data.

• Journal of the Korean Recycled Construction Resources Institute
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• v.10 no.3
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• pp.276-284
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• 2022

In this study, performance evaluation and rheological characteristics were analyzed for recycling the fine powder of nuclear power plant dismantled waste concrete as a solidifying agent for radioactive waste disposal. The radioactive concrete fine powder was used to prepare a simulated sample, and the test specimen was prepared using Di-water, CoCl₂, and 1 mol CsCl aqueous solution as mixing water. Regardless of the aggregate mixing ratio and the type of mixing water, it satisfies the performance standard of 3.45 MPa for compressive strength at 28 days of age. All specimens satisfied the criteria for submersion strength, and the thermal cycle compressive strength satisfies the criteria for all specimens except Plain-50. As a result of evaluating the rheological properties of the solidifying agent, it was found that the increase in the aggregate mixing rate decreased the yield stress and plastic viscosity. The leaching index for cobalt and cesium of all specimens was 6 or higher, which satisfies the standard. In order to secure the stable performance of the solidifying agent, it is considered effective to use 40 % or less of the aggregate component in the solidifying agent.

• Journal of Environmental Impact Assessment
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• v.31 no.6
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• pp.409-422
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• 2022

Riverine wetlands are an important element of the river ecosystem and account for approximately 38% of the inland wetlands surveyed so far. The Shincheon Wetland located in Mangyeong River is also a channel wetland as the flow rate is slowed by the constructed weirs, leading to sediment accumulation. To identify the conservation value and ecological characteristics of Shincheon Wetland, its vegetation and plant diversity were identified using a phytosociological method, and a total of 45 vegetation-related datasets were collected. Overall, 24 plant communities, comprising a total of 153 taxa (49 families, 117 genera, 146 species, 2 subspecies, 5 varieties) were identified. The plant with the highest appearance rate in the communities was Humulus japonicus Siebold & Zucc. In addition, annual herb species, including Rumex crispus L., Bromusjaponicus Thunb., Erigeron annuus (L.) Pers., and Artemisia indica Willd. were frequently observed to be growing in the secondary grassland. Naturalized plants were surveyed in the 38 taxa; the urbanization index was 10.3% and the naturalized index was 24.8%. Plant communities were largely classified into submerged vegetation, floating and floating-leaved vegetation, annual and biennial vegetation, perennial herb vegetation, and woody vegetation. The distribution of plant communities reflecting various habitats, including the lentic and lotic zone maintaining a constant water depth, littoral zone experiencing intermittent water level fluctuations, and dry floodplain environment was also confirmed. Overall, plant community development plays an important role in the habitat for wild animals; therefore, it is expected to positively impact biodiversity enhancement.

• Journal of Korea Water Resources Association
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• v.55 no.12
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• pp.1065-1076
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• 2022

The purpose of this study was to investigate the effect of the expansion and withering of Salix subfragilis communities on the water quality in Namgang Dam reservoir. The distribution area of the Salix subfragilis communities was 0.12 km² in 2003 for the first time, but it was 3.58 km² in 2019, which has increased rapidly by about 30 times in 16 years. However, in 2013, the distribution area has decreased by 0.17 km² due to long-term immersion in high turbidity, and self-thinning in Salix subfragilis communities. The lake characteristics of reservoir showed a combination of lake type and river type in terms of average water depth, watershed area/lake surface area ratio, water residence time, flushing rate, and stratification. From the result of analyzing long-term changes in lake water quality, COD, TP, and chlorophyll-a in Salix subfragilis communities were significantly larger than those in the three points located in the central part of reservoir. In particular, the fact that the value of chlorophyll-a showed the maximum value in winter rather than summer, unlike the trend of the three points in the Namgang Dam water quality monitoring network, is thought to have occurred internally rather than externally. It can be estimated that one cause of this deterioration of the water quality in Namgang Dam reservoir is the huge amount of nutrients generated in the decomposition process of by-products such as fallen leaves, branches and withered trees in Salix subfragilis communities.

• Journal of the Korean GEO-environmental Society
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• v.23 no.3
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• pp.15-22
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• 2022

This study aims to observe the swelling representative rocks in Korea and to suggest improvements in the use of test methods and prior analysis in relation to the weathering of rocks. The swelling test and analysis were performed on the drilling cores obtained for the ground investigation at the domestic highway construction site. For the method of determining the absorption expansion index of rocks, the method proposed in "Standard Methods for Sample Collection and Specimen Preparation" of ISRM and Korean Rock Engineers Standard Rock Test Method was used. The specimen for the measurement of the expansion displacement was cylindrical with a height of 10 cm and a diameter of 5 cm. The existing swelling analysis method evaluates the sensitivity to weathering by using the maximum expansion displacement, but since the classification by bedrock grade is unclear, it is reasonable to use the rate of change of the expansion displacement according to the immersion time. It is necessary to conduct an experiment to distinguish between weathering and fault deterioration. In addition, long-term weathering prediction technology for each cancer type is needed through the expansion displacement analysis of the chemical weathering stage.

• Journal of Wetlands Research
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• v.24 no.1
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• pp.25-37
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• 2022

Climate change is becoming increasingly unpredictable. This has led to changes in various systems such as ecosystems, human life and hydrological cycles. In particular, the recent unpredictable climate change frequently causes extreme droughts and torrential rains, resulting in complex water resources disasters that cause water pollution due to inundation and retirement rather than primary disasters. SWAT was used as a watershed model to analyze future runoff and pollutant loads. The climate scenario analyzed the RCP4.5 climate scenario of the Meteorological Agency standard scenario (HadGEM3-RA) using the normal quantitative mapping method. Runoff and pollutant load analysis were performed by linkage simulation of climate scenario and watershed model. Finally, the results of application and verification of linkage model and analysis of future water quality change due to climate change were presented. In this study, we simulated climate change scenarios using artificial neural networks, analyzed changes in water temperature and turbidity, and compared the results of dams with artificial neural network results through W2 model, a reservoir water quality model. The results of this study suggest the possibility of applying the nonlinearity and simplicity of neural network model to Hapcheon dam water quality prediction using climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.333-342
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• 2022

Due to climate change, increased heavy rainfalls result in flood damage every year. To investigate the storm-runoff reduction effects of Low Impact Development (LID), this study performed runoff analyses using the U.S. Environmental Protection Agency (EPA) Storm Water Management Model (SWMM) for past and future representative storm events of the Yongdu Rainwater Pumping Station basin. As a result, the infiltration loss for representative future rainfalls increased by 3.17 %, and the surface runoff and peak runoff rate increased significantly by 32.50 %, and 128.77 %, respectively. To reduce the increased surface runoff and peak runoff rates, this study investigated the applicability of LID approaches, including a permeable pavement, green roof, and rain garden, by adjusting the LID parameters and the ratio of installation area. We identified the ranges of LID parameters that decreased peak runoff rate and surface runoff, and increased infiltration. In addition, when the application ratio of permeable pavement, green roof, and rain garden was 2:1:3, best performance was attained, leading to a reduction of peak runoff of 26.85 %, infiltration loss 12.01 %, surface runoff 15.11 %, and storage 509.47 %. Based on analyzing the effect of storm runoff reductions for various return periods, it was found that as the return period increased, the proportion of peak runoff and surface runoff increased and the proportion of infiltration loss and storage decreased.