• Title/Summary/Keyword: heavy rainfall

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Concentration Rise of Fine Particle according to Resuspended Dust from Paved Roads after Sudden Heavy Rain in Busan (부산 도심지역 기습 폭우 후 형성된 도로면 토사의 재비산에 의한 미세먼지 농도 상승)

  • Jeon, Byung-Il
    • Journal of Environmental Science International
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    • v.25 no.5
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    • pp.705-713
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    • 2016
  • This study investigates the concentration sudden rise in fine particle according to resuspended dust from paved roads after sudden heavy rain in Busan on August 25, 2015. The localized torrential rainfall in Busan area occurred as tropical airmass flow from the south and polar airmass flow from north merged. Orographic effect of Mt. Geumjeong enforced rainfall and it amounted to maximum 80 mm/hr at Dongrae and Geumjeong region in Busan. This heavy rain induced flood and landslide in Busan and the nearby areas. The sudden heavy rain moved soil and gravel from mountainous region, which deposited on paved roads and near roadside. These matters on road suspended by an automobile transit, and increased fine particle concentration of air. In addition outdoor fine particle of high concentration flowed in indoor by shoes, cloths and air circulation.

Instability Analysis of Road Landfill Slope during Heavy Rainfall (호우시 도로성토사면의 사면불안정 분석)

  • Kim, Young-Muk;Park, Hyang-Keun;Chol, Mun-Hee
    • Journal of the Korean GEO-environmental Society
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    • v.5 no.3
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    • pp.41-50
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    • 2004
  • The study of seepage behavior is very important to slope stability of road landfill for heavy rainfall season. This study is done to propose more stable of road landfill based on analysis of seepage behavior and slope stability for some cases of road landfill. The selected sections of collapsed road landfill are most general case of road landfill, a case is landfill on the ground area and another case is on the slope area. The results of this study is summarized as follows. It is founded that the road landfill on the ground area is increased saturation region due to rainfall infiltration, and the seepage behavior of road landfill is solved by theory of unsaturated flow. The road landfill is more unstable due to rainfall infiltration at the slope surface, especially during heavy rainfall. The case of road landfill on the slope area is analyzed in consideration of slope surface infiltration, and it is founded that the slope instability is increased because of rainfall infiltration. The drain layer located on the original ground which made by more permeable materials could be good action of slope stability in the case of road landfill on the slope area.

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An Evaluation of Landslide Probability by Maximum Continuous Rainfall in Gangwon, Korea (강원지역의 최대연속강우량에 의한 산사태 발생가능성 평가)

  • Yang, In-Tae;Park, Jae-Kook;Jeon, Woo-Hyun;Chun, Ki-Sun
    • Journal of Korean Society for Geospatial Information Science
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    • v.15 no.4
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    • pp.11-20
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    • 2007
  • Most natural disasters in Korea are caused by meteorological natural phenomena, which include storms, heavy rains, heavy snow, hail, tidal waves, and earthquakes. Rainfall is the most frequent cause of disasters and accounts for about 80% of all disasters. Particularly in recent years, Korea has seen annual occurrences of natural disasters associated with landslides (slope and retaining wall collapse and burying) due to meteorological causes from the increasing intensity of heavy rains including local heavy rainfalls. In Korea, it is critical to analyze the characteristics of landslides according to rainfall characteristics and to take necessary and proper measures for them. This study assessed the possibility of landslides in the Gangwon region with a geographic information system by taking into account the inducer factors of landslides and the maximum continuous rainfall of each area. It also analyzed areas susceptible to landslides and checked the distribution of landslide-prone areas by considering the rainfall characteristics of those areas.

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Prediction of Landslides Occurrence Probability under Climate Change using MaxEnt Model (MaxEnt 모형을 이용한 기후변화에 따른 산사태 발생가능성 예측)

  • Kim, Hogul;Lee, Dong-Kun;Mo, Yongwon;Kil, Sungho;Park, Chan;Lee, Soojae
    • Journal of Environmental Impact Assessment
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    • v.22 no.1
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    • pp.39-50
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    • 2013
  • Occurrence of landslides has been increasing due to extreme weather events(e.g. heavy rainfall, torrential rains) by climate change. Pyeongchang, Korea had seriously been damaged by landslides caused by a typhoon, Ewiniar in 2006. Moreover, the frequency and intensity of landslides are increasing in summer due to torrential rain. Therefore, risk assessment and adaptation measure is urgently needed to build resilience. To support landslide adaptation measures, this study predicted landslides occurrence using MaxEnt model and suggested susceptibility map of landslides. Precipitation data of RCP 8.5 Climate change scenarios were used to analyze an impact of increase in rainfall in the future. In 2050 and 2090, the probability of landslides occurrence was predicted to increase. These were due to an increase in heavy rainfall and cumulative rainfall. As a result of analysis, factors that has major impact on landslide appeared to be climate factors, prediction accuracy of the model was very high(92%). In the future Pyeongchang will have serious rainfall compare to 2006 and more intense landslides area expected to increase. This study will help to establish adaptation measure against landslides due to heavy rainfall.

An intercomparison of GMS image data and observed rainfall data (GMS 영상자료와 관측강수량 자료의 비교)

  • 서애숙;이미선;김금란;이희훈
    • Korean Journal of Remote Sensing
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    • v.10 no.1
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    • pp.1-14
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    • 1994
  • The purpose of this study is to find the relationship between GMS image data and hourly observed rainfalls data. Heavy rainfall cases over South Korea on 10th September 1990 and on 29th July 1993 were selected for studying of the relationship between the image data and reinfalls. First, image data were converted to TBB(Temperature of Black Body) and albedo and then these values were extracted for the pixels closest to the surface observation station to correlate with the rainfall data. Horizontal distribution of TBB and albedo tells roughly rainfall regions. The correlation between rainfall and TBB is found to be very low in quantitative analysis. The weak relationship between the brighter albedo and the higher rainfall probability is observed. This study suggests that the TBB values are useful in classifying rain areas and for heavy rainfalls the albedo values are more useful than the TBB. Low linear correlation between the fields may be attributed to the neglect of cloud types in this study.

Analyzed Change of Soil Characteristics by Rainfall and Vegetation (강우 및 식생에 의한 토질특성 변화 분석)

  • Lee, Moon-Se;Kim, Kyeong-Su;Song, Young-Suk;Ryu, Je-Cheon
    • The Journal of Engineering Geology
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    • v.19 no.1
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    • pp.33-41
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    • 2009
  • In this study, some changes of soil characteristics in a field were analyzed to investigate the effect of heavy rainfall during rainy season. The heavy rainfalls were often induced geohazards like landslides. To do this, the reaching rainfall in the ground surface was investigated according to a condition of vegetation, and the change of soil characteristics induced by infiltrating rainfall was analyzed. The study site is a natural terrain located in Daedeok Science Complex. This site has same geology and soil condition whereas it has different vegetable condition. The rainfall records during the rainy season of 2006 and 2007 were selected. The rainfall records are based on the measuring date from Daejeon Regional Meteorological Administration adjacent to the study site. Also, the rainfall records according to the condition of vegetation were measured using rainfall measuring device made by ourselves. The soil tests were carried out about soil specimen sampled before and after rainfall, and then the change of soil characteristics related to rainfall and vegetation were analyzed. As the result, the density of vegetation was influenced by reaching rainfall quantity in the ground surface, and its influence intensity was decreased with rainfall intensity and rainfall duration. Also, it shows that degree of saturations, water contents, liquidities and shear resistances are directly influenced by heavy rainfalls.

The Runoff Characteristics due to Heavy Rainfall in Mountainous River (산지하천의 집중강우에 따른 유출특성에 관한 연구)

  • Kang, Sang-Hyeok;Choi, Jong-In;Park, Jong-Young
    • Spatial Information Research
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    • v.15 no.2
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    • pp.159-167
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    • 2007
  • In this study, we investigated the application of extending the Huff's method to design discharge being used at present up to the event of concentrated rainfall. As our field study site, we selected Odae Cheon basin in Pheongchang, which was affected by concentrated rainfall in July 2006. Actual concentrated rainfall and design rainfall derived from the Huff's method were used to calculate the discharge and storm water levels, which were compared with the directly measured water-level marks of storm discharges. The results showed that the peak storm discharge from the torrential rainfall was twice higher than the design rainfall. The short term discharges from concentrated rainfall closely corresponded to the rainfall discharges of 150 years storm frequency.

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The Development of a Rainfall Correction Technique based on Machine Learning for Hydrological Applications (수문학적 활용을 위한 머신러닝 기반의 강우보정기술 개발)

  • Lee, Young-Mi;Ko, Chul-Min;Shin, Seong-Cheol;Kim, Byung-Sik
    • Journal of Environmental Science International
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    • v.28 no.1
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    • pp.125-135
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    • 2019
  • For the purposes of enhancing usability of Numerical Weather Prediction (NWP), the quantitative precipitation prediction scheme by machine learning has been proposed. In this study, heavy rainfall was corrected for by utilizing rainfall predictors from LENS and Radar from 2017 to 2018, as well as machine learning tools LightGBM and XGBoost. The results were analyzed using Mean Absolute Error (MAE), Normalized Peak Error (NPE), and Peak Timing Error (PTE) for rainfall corrected through machine learning. Machine learning results (i.e. using LightGBM and XGBoost) showed improvements in the overall correction of rainfall and maximum rainfall compared to LENS. For example, the MAE of case 5 was found to be 24.252 using LENS, 11.564 using LightGBM, and 11.693 using XGBoost, showing excellent error improvement in machine learning results. This rainfall correction technique can provide hydrologically meaningful rainfall information such as predictions of flooding. Future research on the interpretation of various hydrologic processes using machine learning is necessary.

A study on the adsorption characteristic and safety assessment of railway subsoil material (철도 노반 재료의 중금속 흡착특성과 안전성에 관한 연구)

  • Paek, Seoungbong;Gil, Kyungik
    • Journal of Wetlands Research
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    • v.17 no.2
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    • pp.146-154
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    • 2015
  • Domestic railway industry has grown in numbers, scale of railway ndustrial and operation because was focused on an environmentally sustainable transportation. However, it is not enough to treat and prevent heavy metals which occur as the railway operation increases. The heavy metals occurred when the operating railway and it will be flow into water system with rainfall effluent during rainfall. will flow out along with the rainfall effluent when rainfall comes. In case of a railway bridge, In particular, heavy metals were flow into the water system without any treatment from railway bridges where located nearby rivers and lakes. So, rainfall effluent from railway facilities was occurred pollution of water system. For the prevent of heavy metal runoff during rainfall, the adsorptivity of material in railway roadbed is important.In this study, adsorptivity of gravel which is main gravel and blast-furnace slag were conducted adsorption test and deducted Freundlich's and Langmuir's isothermal adsorption equations. Safety as railway subbase course material was evaluated using modeling. As a result, absorption amount of slag, Cd and Cu, was shown higher than gravel and Pb along with Zn showed higher absorption amount of gravel. However, absorption amount of slag was shown higher than gravel used as railway subbase course material as time passes by. Absorption features had more suitable determination coefficient of heavy metals in warm absorption type such as Langnmuir compared to warm absorption type like Freundlich. To add, they showed less transformation by about 10% compared to gravel in safety evaluation through modeling. This is a railway subbase course material that prevents water outflow of heavy metal thus we can know slag is needed to be used.

A Study on the Causes of Steep Slope Failure induced Heavy Rainfall (집중호우시 급경사지 붕괴발생 원인분석 연구)

  • Ryu, Ji Hyeob;Lim, Ik Hyen;Hwang, Eui Jin
    • Journal of Korean Society of societal Security
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    • v.4 no.1
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    • pp.67-74
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    • 2011
  • This paper was to examine the causes of steep slope failure during the season of heavy rainfall. For the purpose, the paper carefully analyzed the sites of steep slope failure, which happened in July 2009. The direct cause of steep slope failure was much related to heavy rainfall during summer. The paper continued to verify that additional causes include the malfunction of diverse waterways, the slope design without considering weathering soils and related characteristics, the lack of the waterway size, the intrusion of plant roots, the reinforced technique without considering slope conditions, etc.

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