• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.1525-1530
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• 2008

최근의 기상이변 및 집중호우 등에 대응하기 위해 기존 다목적댐 상류지역에 대한 홍수를 저감시키고, 용수공급, 퇴사 및 탁수저감, 부유물 차단 및 레크레이션 등 기존댐의 효용 증진과 그 가치를 제고하기 위하여 다목적댐 상류에 소규모댐 설치 필요성이 커지고 있다. 따라서 본 연구에서는 소양강, 충주, 횡성, 안동, 임하, 합천, 남강, 밀양, 대청, 용담, 섬진강, 주암(본,조), 부안, 보령, 장흥 등 전국의 다목적댐 15개소의 상류 하천 및 유역을 대상으로 국내외 사례를 조사하여 소규모댐의 정의, 역할, 기능 및 효과를 제시하고 소규모댐의 필요성 및 사업의 타당성을 정립하며, 상류 소규모댐 개발 가능지점 선정을 위하여 댐별 특성을 고려한 수문현황, 환경기초현황 등의 문헌조사와 이를 토대로 도상검토 및 현장조사를 통한 홍수조절, 상류 용수공급, 퇴사, 탁수, 부유물, 레크레이션 등의 소규모댐의 필요성을 제시하여 지자체 및 지역의견 수렴후 개발지점을 선정하는 것이다. 개발지점 선정을 위하여 이수부문 및 치수부문으로 조사목적을 구분하였으며, 이수부분은 인구 현황 및 상수도 이용실태 등을 각 댐별 관련보고서 및 현황 자료를 조사 분석하여 개발의 필요성 및 지점을 결정하였고, 치수부분은 홍수피해액, 수해상습지 및 재해위험지구 등을, 소규모댐의 설치 목적별로 지표들을 핵함수를 이용한 비매개변수적 확률밀도함수법으로 지수화하여 우선순위를 결정하였다.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.5
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• pp.149-158
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• 2010

Recent rainfall patterns in Korea show that both of the total amount of rainfall and the total number of heavy rain days have been increased. Therefore, the damage resulted from flood disaster has been dramatically increased in Korea. The purpose of the present study is to analyze flooding in an urban area using SWMM linked with FLUMEN. The study area is Suyeong-Mangmi lowland area, Busan, Korea. Suyeong-Mangmi lowland area have been a flooding hazard zone since 1995. The last flooding cases of this area occurred on July 7th and 16th, 2009, and the later flooding case was analyzed in this study. The first step of computation is calculating flow through storm sewers using the urban runoff simulation model of SWMM. The flooding hydrographs are used in the inundation analysis model of FLUMEN. The results of inundation analysis were compared with the real flooding situation of the study area. The real maximum inundation depth was guessed by 1.0 m or more on July 16th. The computation yields the maximum inundation depth of 1.2 m and the result was somewhat overestimated. The errors may be resulted from the runoff simulation and incapability of simulation using FLUMEN for flow into buildings. The models and procedures used in this study can be applied to analysis of flooding resulted from severe rainfall and insufficiency of drainage capacity.

• Journal of Wetlands Research
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• v.13 no.1
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• pp.1-11
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• 2011

A chronic drought stress has been imposed during non-rainy season(from winter to spring) since 1990s. We faced the most significant water crisis in 2001, and the drought was characterized by sultry weather and severe drought on a national scale. It has been widely acknowledged that the drought related damage is 2-3 times serious than floods. In the list of the world's largest natural disaster compiled by NOAA, 4 of the top 5 disasters are droughts. And according to the analysis from the NDMC report, the drought has the highest annual average damage among all the disasters. There was a very serious impact on the economic such as rising consumer price during the 2001 spring drought in Korea. There has been flood prevention measures implemented at national-level but for mitigation of droughts, there are only plans aimed at emergency (short-term) restoration rather than the comprehensive preventive measures. In addition, there is a lack of a clear set of indicators to express drought situation objectively, and therefore it is important and urgent to begin a systematic study. In this study, a nonstationary downscaling model using RCM based climate change scenario was first applied to simulate precipitation, and the simulated precipitation data was used to derive Standardized Precipitation Index (SPI). The SPI under climate change was used to evaluate the spatio-temporal variability of drought through principal component analysis at three different time scales which are 2015, 2045 and 2075. It was found that spatio-temporal variability is likely to modulate with climate change.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

• Journal of the Korea Institute of Building Construction
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• v.20 no.2
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• pp.137-145
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• 2020

The recent bridge construction projects demand thorough and systematic safety and risk management, due to the increase of risk factors following the introduction of new and complex construction methods and technologies. Among many types of damages that can occur in bridge construction projects, the damages to third parties who are not directly related to the existing property of the contractor construction project can also bring about critical loss in the project in order to compensate the damages. Therefore, risks that could be caused by the loss occurred to indemnify the third party damages should be clearly analyzed, although there are not subsequent amount of studies focusing on the issue. Based on the past record of insurance payment from domestic insurance companies for bridge construction projects, this study aimed to analyze the risk factors of bridge construction for loss caused to compensate the third-party damages happened in actual bridge construction projects and to develop a quantified and numerical predictive loss model. In order to develop the model, the loss ratio was selected as the dependent variable; and among many analyzed independent variables, the superstructure, foundation, flood, and ranking of contractors were the four significant risk factor variables that affect the loss ratio. The results produced can be used as an essential guidance for balanced risk assessment, supplementing the existing analysis on material losses in bridge construction projects by taking into account the third-party damage and losses.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.278-280
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• 2007

우리나라는 지난 94년간 1.5도 상승하여 전지구 온난화추세를 상회하였다. 기온뿐만 아니라 강수량 역시 변화하였는데 변동폭이 크기는 하나 장기적으로 증가하는 경향으로 20세기초에 비해 상대적으로 기온이 높고 강수량도 많은 특성을 보인다. 평균적인 기후변화추이와 더불어 특히 최근 10년($1996{\sim}2005$년)은 1850년 이후 지구평균기온이 가장 높았던 기간으로, 세계적으로 열파, 홍수, 가뭄, 태풍 등 기상이변에 의한 인명과 재산 피해, 생물종의 멸종 등 사회경제적 피해가 막대하였다. 우리나라 역시 폭염, 호우등의 빈번한 출현으로 급격해지는 온난화추세 영향을 반영하였는데 이러한 기후 변화양상을 파악하기 위하여 우리나라의 최근 10년간 기후 특성과 계절별 현상일수의 변화를 분석하였다. 최근 10년(1996-2005년) 우리나라 기후변화의 특성을 보면 우리나라(15개 관측지점자료)는 평균기온이 과거 30년$(1971{\sim}2000)$ 평균대비 $0.6^{\circ}C$ 상승하였다. 계절별로 봄은 평년대비 $0.7^{\circ}C$, 여름은 $0.4^{\circ}C$, 가을은 $0.6^{\circ}C$, 겨울은 $0.7^{\circ}C$ 상승하여 봄과 겨울의 상승폭이 가장 크다. 연강수량은 30년 평균대비 최근 10년 강수량은 11% 증가하였고 특히 여름은 증가폭이 가장 커서 18% 증가하였다. 계절에 따라 다양한 기상현상의 변화도 나타났다. 3월 이후에 나타나는 늦서리의 종료일은 평균적으로 3월 말경에 나타났는데 최근 10년에는 3월 중순으로 2주 앞당겨졌고 이 추세는 특히 1993년 이후 뚜렷하다. 늦서리의 발생일수도 평균 4일 정도 줄었다. 일평균기온 $20^{\circ}C$이상인 날은 평년에 비해 최근 10년 동안 약 2일 증가하여 여름 시작시기가 빨라지고 있음을 알 수 있다. 일최저기온이 25도 이상인 열대야는 평년대비 최근 10년간 연간발생일수가 1.3일 증가하였으나 일최고기온 $35^{\circ}C$ 이상인 날의 수는 오히려 감소하는 경향을 보인다. 이것은 여름철 강수량이 증가하고, 호우발생빈도, 특히 8월의 강수일수가 증가하고 있다는 것과 밀접한 관련이 있다. 여름과 가을에 우리나라에 영향을 미치는 태풍의 수는 뚜렷한 추세를 보이지 않으나, 2002년 루사, 2003년 매미로 인하여 각각 6조원, 4조원 이상의 막대한 피해가 발생하였다. 태풍에 의한 피해액은 GDP 대비 약 0.9%(태풍 루사)로 최근 경제상장률과 비교해 보면, 상당한 비율을 차지한다. 우리나라에 영향을 미치는 태풍은 연근해의 해수면 온도가 높아지면 세기가 강해질 가능성이 높다. 폭설과 한파일수도 평년대비 최근 10년 감소하였고 일최저기온이 영하 $10^{\circ}C$ 이하인 날도 연간 발생일수가 감소하였다. 최근 10년간 우리나라 기후의 변화특성은 기온상승과 더불어 서리종료일이 앞당겨지고 열대야가 증가하고 폭설, 한파, 겨울철 일최저기온 영하 10도 이하인 날의 감소 등이 나타나고, 여름철 재해의 원인인 호우일수는 증가하는 추세이다. 앞으로 지구온난화는 가속화될 것으로 전망되고 이로 인한 피해규모도 커질 것으로 예상된다. 최근 우리나라에서 나타나는 기후변화의 추이를 감안할 때, 기후변화에 대한 장기적인 대비책을 마련하여 이로 인한 부정적인 영향을 감소시키기 위하여 국가차원의 체계적인 대응이 필요하다.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.

• Journal of Korean Society of Forest Science
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• v.39 no.1
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• pp.1-34
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• 1978

On July 8, 1977, 432mm of precipitation which is the largest daily storm in Korea fell on the city of Anyang where a nearby suburban community of Seoul. Average storm intensities of 90mm per hour were recorded during the period from 1900~2200 hours on this date. Area of landslides triggered by this storm is about 96 hectares resulting from 1,876 places within about 12,600 hectares of the watershed studied. These hazards injured hundreds of human lives and took 122 human lives. Rail and highway systems were disrupted and about 30 hectares of rice paddies were washed away and hundreds of hectares were inundated. About 500 houses were destroyed. The objectives of this study are (a) to describe the problem areas, identifying critical factors causing the landslide hazards including earth and stone-debris avalanches, (b) suggest measures which might enhance the effectiveness of stabilization measures, and (c) also suggest the landslide and flood damage prevention methods from the point view of the upper-watershed conservation techniques in Anyang hollow-basin.

• Korean Journal of Mineralogy and Petrology
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• v.36 no.2
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• pp.135-145
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• 2023

Aggregate is used to produce stable materials like concrete and asphalt and is fundamental to meet the social needs of housing, industry, road, energy and health. A total of 42.35 billion tons of aggregate were produced in 2021 worldwide, an increase of 0.91% compared to the previous year. Among them, 2 billion tons were produced in China, India, European Union and United States, making up to 71.75% of the share. South Korea has witnessed a constant increase in aggregate production, overtaking Mexico and Japan for seventh place with 390 million tons and 0.85% of the share. The industrial sand and gravel produced globally amounted to 352.66 million tons. The top seven countries with the highest production were China, United States, Netherlands, Italy, India, Turkey and France, and their production exceeded 10 million tons and held a share of 74.69%. Exports of natural rock recorded $21.68 billion in 2021, increased by $2.3 billion compared to the previous year, while exports of artificial rock increased by $2.66 billion to $13.59 billion. Exports of sand reached $1.71 billion with United States, Netherlands, Germany and Belgium being the four countries with the highest exports of sand. The four countries exported more than $100 million in sand and took up 57.70% of the total amount. Exports of gravel totaled $2.75 billion, with China, Norway, Germany, Belgium, France and Austria in the lead, making up to 48.30% of the total share. The aggregate quarry started to surge in the 1950s due to the change in people's lifestyle such as population growth, urbanization and infrastructure delvelopment. Demand for aggregate is also skyrocketing to prevent land reclamation and flood caused by sea-level rise. Demand for aggregate, which was around 24 gigatons in 2011, is expected to double to 55 gigatons in 2060. However, it is likely that aggregate extraction will heavily damage the ecosystem and the world will eventually face a shortage of aggregate followed by tense social conflict.

• Journal of the Korea Institute of Building Construction
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• v.20 no.1
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• pp.83-91
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• 2020

The recent bridge construction projects is demanded more sophisticated risk management measures and loss forecasts to brace for risk losses from an increase in the trend of bridge construction. This study aims to analyze the risk factors that caused the loss of material in actual bridge construction and to develop a quantified predictive loss model, based on the past record of insurance payment by major domestic insurance companies for bridge construction projects. For the development of quantitative bridge construction loss model, the dependent variable was selected as the loss ratio, i.e., the ratio of insurance payout divided by the total project cost, while the independent variable adopted 1) Technical factors: superstructure type, foundation type, construction method, and bridge length 2) Natural hazards: typhoon and flood 3) Project information: construction period and total project cost. Among the selected independent variables, superstructure type, construction method, and project period were shown to affect the ratio of bridge construction losses. The results of this study can provide government agencies, bridge construction design and construction and insurance companies with the quantitative damage prediction and risk assessment services, using risk indicators and loss prediction functions derived from the findings of this study and can be used as a guideline for future basic bridge risk assessment development research.