• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.74-74
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• 2015

최근 홍수의 특성과 피해 양상은 과거와는 다르게 변화하고 있으며, 급격한 도시화로 인하여 기존 하천유역의 저류 능력이 감소하였으며 이러한 한계를 극복하기 위하여 이미 외국에서는 대심도 터널을 활용한 홍수재해 관리방안이 오래전부터 활용되어 왔다. 본 연구에서는 대심도 터널의 유입구, 수직갱, 감세지, 배수터널과 같은 시설물 중 대심도 터널 설계 시 수직 유입구를 통해 유입되는 유량의 에너지를 완화하고 효과적으로 배수 할 수 있도록 중요한 역할을 하는 감세지의 효율적인 깊이 산정을 위하여 수리모형실험을 실시하였으며, 모형은 Froude 상사법칙을 사용하여 원형의 1/18크기로 제작하였다. 본 연구에서 실시한 감세지 모형의 깊이는 0.278 m(원형 5.0 m), 0.417 m(원형 7.5 m)이며, 각 감세지 깊이별 수직 유입구 3개소(저지수직구1, 저지수직구2, 고지수직구) 및 5가지의 유량 CASE에 대하여 감세지 바닥면 압력을 비교?분석 하였다. 수직 유입구 3개소의 설계조건에 따른 감세지 깊이별 바닥면 압력 분포 평가를 실시한 결과 저지수직구1의 감세지 깊이 0.278 m(원형 5.0m)에서는 최대 압력이 4번 지점에서 $0.075kg/cm^2$(원형 1.30 MPa)이 측정 되었으며, 0.417 m(원형 7.5m)에서는 최대 압력이 1번지점에서 $0.089kg/cm^2$(원형 1.54MPa)이 측정되었다. 또한 저지수직구2의 감세지 깊이 0.278 m(원형 5.0 m)에서는 최대 압력이 1번 지점에서 $0.074kg/cm^2$(원형 1.28 MPa)이 측정 되었으며, 0.417 m(원형 7.5 m)에서는 최대 압력이 2번지점에서 $0.088kg/cm^2$(원형 1.52 MPa)이 측정되었다. 고지수직구의 감세지 깊이 0.278 m(원형 5.0 m)에서는 최대 압력이 3번 지점에서 $0.082kg/cm^2$(원형 1.42 MPa)이 측정 되었으며, 0.417 m(원형 7.5 m)에서는 최대 압력이 1번지점에서 $0.092kg/cm^2$(원형 1.59 MPa)이 측정되었다. 본 연구에서 실시한 수리모형실험의 결과 저유량에서 고유량으로 갈수록 최대압력지점은 반시계방향으로 움직이는 것을 알 수 있으며, 이는 수직 유입구의 설계조건에 따른 수직갱에서의 회전수차에 의하여 발생하는 것으로 분석하였다. 따라서 적절한 감세지 깊이 산정을 위해서 대심도터널의 수직 유입구(유입구형태, 수직갱)의 평가가 함께 유기적으로 이루어져야 할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.337-337
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• 2017

가뭄은 일반적으로 강수량의 부족에 기인하며, 수자원의 이용 및 관리에 큰 영향을 미치는 자연재해이다. 2013년부터 2015년까지 우리나라의 연 평균 강수량은 각각 1,162mm, 1,173mm, 948mm로 평년대비 89.0%, 89.8%, 72.1%의 적은 강수를 보였다. 이는 마른장마, 평년보다 적게 발생한 태풍 등의 영향 인 것으로 판단되며 이러한 강수의 부족으로 인해 전국적으로 가뭄이 빈번하게 발생하였다. 이에 가뭄의 대처방안에 대한 관심이 증대되었고, 가뭄을 정량적으로 표현하고자 하는 연구들이 진행되었다. 가뭄은 크게 수문학적, 기상학적, 농업적 가뭄으로 구분되며 각각의 기준에 따라 다양한 변수들을 이용한 지표들이 개발되었다. 개발된 가뭄 지표는 가뭄을 평가하고 대비하기 위한 의사결정에 유용한 자료로 사용되고 있다. 농업적 가뭄은 강우부족, 실제와 잠재증발산량의 차이, 토양수분 부족, 저수지 또는 지하수위의 저하 등 농작물의 생육과 수확량에 직접적인 영향을 미치는 특성들을 고려하여 평가해야 하며, 이러한 특성들을 고려한 가뭄 지수로는 저수지 가뭄지수(RDI), 토양수분지수(SMI), 통합농업가뭄지수(IADI) 등이 개발되었다. 저수지 가뭄지수는 가뭄발생의 위험과 크기를 순별 가용저수량의 빈도를 이용하여 나타낸 가뭄 지표이다. 따라서 가뭄 지표를 산정하는데 사용된 자료의 기간에 따라 그 값의 차이가 존재한다. 본 연구에서는 각각 10개년, 20개년, 30개년 기간의 백산저수지 농업지구 저수량 자료를 사용하여 2011년부터 2015년까지의 저수지 가뭄지수를 산정하였으며 이를 각각 비교하였다. 2006년부터 2015년까지 10개년 기간의 자료를 사용하여 산정한 가뭄지수는 2012년 ~ 2015년에 가뭄을 나타내고 있었고 특히, 2015년 6월 상순과 중순의 가뭄지수가 -4.1으로 가장 심한 가뭄을 나타내었다. 1996년부터 2015년까지 20개년 기간의 자료를 사용하여 산정한 가뭄지수는 2012 ~ 2015년에 가뭄을 나타내며 2015년 6월 상순과 중순의 가뭄지수는 각각 -0.9, -1.0으로 10개년의 기간을 사용하였을 때보다 완화된 모습을 보였다. 1986년부터 2015년까지 30개년 기간의 자료를 사용하여 산정한 가뭄지수는 2011년부터 2015년까지 가뭄을 나타내고 있었으며, 2015년 6월 상순과 중순의 경우 각각 -1.7, -1.0으로 20개년 자료를 사용하였을 때보다 심한 가뭄을 나타내지만, 10개년 자료를 사용하였을 때보다 완화된 가뭄을 나타내었다. 백산저수지의 경우 2011년부터 2015년까지 가뭄이 발생하였으나, 용수공급이 불가능 할 정도의 가뭄이 발생하지는 않은 것으로 조사되었으며, 30개년 자료를 사용한 가뭄지수가 이와 가장 근사한 가뭄정도를 나타내고 있다. 이는 저수량자료의 기간이 크면 빈도값의 신뢰성이 높아지기 때문인 것으로 판단되며 저수지 가뭄지수의 경우 저수량 자료가 누적될수록 좀 더 정확한 가뭄상황을 표현할 수 있을 것으로 판단된다.

• Journal of Korean Society of Disaster and Security
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• v.14 no.3
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• pp.17-27
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• 2021

In this study, classification models were built using machine learning techniques that can classify the soil creep risk into three classes from A to C (A: risk, B: moderate, C: good). A total of six machine learning techniques were used: K-Nearest Neighbor, Support Vector Machine, Logistic Regression, Decision Tree, Random Forest, and Extreme Gradient Boosting and then their classification accuracy was analyzed using the nationwide soil creep field survey data in 2019 and 2020. As a result of classification accuracy analysis, all six methods showed excellent accuracy of 0.9 or more. The methods where numerical data were applied for data training showed better performance than the methods based on character data of field survey evaluation table. Moreover, the methods learned with the data group (R1~R4) reflecting the expert opinion had higher accuracy than the field survey evaluation score data group (C1~C4). The machine learning can be used as a tool for prediction of soil creep if high-quality data are continuously secured and updated in the future.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.533-544
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• 2018

Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.

• 재활복지
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• v.20 no.1
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• pp.1-22
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• 2016

This research aimed to examine the problems in a current national emergency management system that does not consider the disabled in the face of manmade catastrophes and natural disasters, and to conduct an expert opinion survey to explore the direction of disabled-inclusive public disaster management system. As a result of the analysis, the respondents of the survey revealed a need for a designated government department for disaster management systems for the disabled and the experts preferred the Ministry of Public Safety and Security (50%) than the Ministry of Health and Welfare (37.5%). However, 12.5% of the surveyed experts perceived cooperation between the two Ministries, rather than selecting a certain ministry, as necessary to establish a disaster management system for the disabled. Additionally, the experts recognized the response period (43.8%) of the disaster management life cycle to be the most important phase. Thus, at the disaster response period, the experts suggested utilizing an emergency alarm system to effectively rescue the disabled in the face of disaster. Based on this discussion, the paper explores ways to establish a disabled-inclusive public disaster management system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.793-800
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• 2018

It is necessary to determine an optimal design frequency for establishing stable flood control against frequent flood disasters. Depending on the importance of river and regional characteristics, design return periods are suggested from at least 50 years up to 200 years for river design. However, due to the wide range of applications, it is not desirable to reflect the geographical and flood control characteristics of river. In this study, Bayes theory was applied to seven evaluation factors to determine the optimal design return period of rivers in Chungcheongnam-do; urbanization flooded area, watershed area, basin coefficient, slope, water system and stream order, range of backwater effect, abnormal rainfall occurrence frequency. The potential flood damage (PFD) capacity was estimated considering climate change and the appropriate design return period was determined by analyzing the capacity of each district. We compared the design return periods of 382 rivers in Chungcheongnam-do with the existing design return periods. The number of rivers that were upgraded from the existing return period were 65, which have relatively large flooding areas and have large PFDs. Whereas, the number of rivers that were downgraded were 169.

• The Journal of Engineering Geology
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• v.29 no.1
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• pp.23-35
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• 2019

Landslides occur due to heavy rainfall in the summer season. Some of water may infiltrate into the ground; it causes a high saturation condition capable of causing a landslide. Soil properties are crucial in estimating slope stability and debris flow occurrence. The main study areas are Gwanaksan, Suraksan and Bukhansan (Mountain) in Seoul. A total of 44 soil samples were taken from the study area; and a series of geotechnical tests were performed. Physical and mechanical properties were obtained and compared based on region. As a result, among well-graded soils, they are classified as a clayey sand. Coarse-grained and fine-grained contents are approximately 95% and 5%, respectively, with very low amount of clay content. Density, liquid limit and dry unit weight are ranged in $2.62{\sim}2.67g/cm^3$, 27.93~38.15% and $1.092{\sim}1.814g/cm^3$. Cohesion and internal friction angle are 4 kPa and $35^{\circ}$ regardless of mountain area. Coefficient of permeability is varied between $3.07{\times}10^{-3}{\sim}4.61{\times}10^{-2}cm/sec$; it means that it results in great seepage. Permeability is inversely proportional to the uniformity coefficient and is proportional to the effective particle size. In the formal case, there was a difference by mountain area, while in the latter, the tendency was almost similar.

• Journal of the Korea Institute of Construction Safety
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• v.3 no.1
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• pp.32-40
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• 2020

In this study, an application was developed to reduce the work between labor and safety managers and to hire better workers when hiring workers. With the expected increase in foreign workers in the future, the number of illegal workers will also increase. As a result, accident and on-site management are becoming more difficult due to insufficient information collection of workers. Therefore, it was possible to secure on-site safety through an application that could collect accurate information and reduce the time of information exchange between safety managers and labor managers. In addition, the application was designed to help the safety manager identify the faithful workers more quickly when re-employment of the day laborers if many day laborers were assessed and filled out as they were. This anticipates the expected effect of shortening the construction period. The current application collected necessary information through an interview with the site manager. If the company collects more information needed in the field and has big data than it has collected necessary information so far, it will be highly competitive in the market as it can improve the completeness of applications by establishing opinions and reflecting information accordingly.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.675-686
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• 2021

This study investigated the ground displacement occurring in a slope below a waste-rock dumping site and estimated the likelihood of a disaster due to a landslide. To start with, photogrammetry was conducted by unmanned aerial vehicles (UAVs) to investigate the size and extent of the ground displacement. From April 2019 to July 2020, the average error rate of the five UAV surveys was 0.011-0.034 m, and an elevation change of 2.97 m occurred due to the movement of the soil layer. Only some areas of the slope showedelevation change, and this was believed to be due to thegroundwater generated during rainfall rather than the effect of the waste-rock load at the top. Sensitivity analysis for LS-RAPID simulation was performed, and the simulation results were compared and analyzed by applying a digital elevation model (DEM) and a digital surface model (DSM)as terrain data with 10 m, 5 m, and 4 m grids. When data with high spatial resolution were used, the extent of the sedimentation of landslide material tended to be excessively expanded in the DEM. In contrast, in the result of applying a DSM, which reflects the topography in detail, the diffusion range was not significantly affected even when the spatial resolution was changed, and the sedimentation behavior according to the river shape could be accurately expressed. As a result, it was concluded that applying a DSM rather than a DEM does not significantly expand the sedimentation range, and results that reflect the site situation well can be obtained.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.901-912
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• 2022

The frequency of disasters is increasing due to global climate change, and unusual heavy rains and rainy seasons are occurring in Korea. Periodic monitoring and rapid detection are important because these weather conditions can lead to drought and flooding, causing secondary damage. Although research using optical images is continuously being conducted to determine the waterbody, there is a limitation in that it is difficult to detect due to the influence of clouds in order to detect floods that accompany heavy rain. Therefore, there is a need for research using synthetic aperture radar (SAR) that can be observed regardless of day or night in all weather. In this study, using Sentinel-1 SAR images that can be collected in near-real time as open data, the UNet model among deep learning algorithms that have recently been used in various fields was applied. In previous studies, waterbody detection studies using SAR images and deep learning algorithms are being conducted, but only a small number of studies have been conducted in Korea. In this study, to determine the applicability of deep learning of SAR images, UNet and the existing algorithm thresholding method were compared, and five indices and Sentinel-2 normalized difference water index (NDWI) were evaluated. As a result of evaluating the accuracy with intersect of union (IoU), it was confirmed that UNet has high accuracy with 0.894 for UNet and 0.699 for threshold method. Through this study, the applicability of deep learning-based SAR images was confirmed, and if high-resolution SAR images and deep learning algorithms are applied, it is expected that periodic and accurate waterbody change detection will be possible in Korea.