• Title/Summary/Keyword: Heavy Rain Damage

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A Study on Effect of Repair and Improvement for Irrigation Facilities on Heavy Rain Damage (수리시설개보수사업이 호우피해에 미치는 효과 분석)

  • Lim, Cheong-Ryong;Yi, Hyang-mi;Lee, Seok-Joo
    • Journal of Korean Society of Rural Planning
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    • v.24 no.1
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    • pp.61-66
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    • 2018
  • The purpose of this study is to identify the factors related to the heavy rain damage and to identify effect of repair and improvement for irrigation facilities on heavy rain damages. The results of the analysis are as follows. First, the imbalance of precipitation became worse over time from using the coefficient of variation. Second, the analysis using Spearman correlation coefficient shows positive relationship between heavy rain damage amount and precipitation amount, and negative correlation between heavy rain damage amount and repair and improvement for irrigation facilities cost. Third, the analysis of the panel regression model shows that the negative impact of the repair and improvement for irrigation facilities cost on the heavy rain damage, which means that the increase of the repair and improvement for irrigation facilities cost can reduce the heavy rain damage.

An improvement on the Criteria of Special Weather Report for Heavy Rain Considering the Possibility of Rainfall Damage and the Recent Meteorological Characteristics (최근 기상특성과 재해발생이 고려된 호우특보 기준 개선)

  • Kim, Yeon-Hee;Choi, Da-Young;Chang, Dong-Eon;Yoo, Hee-Dong;Jin, Gee-Beom
    • Atmosphere
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    • v.21 no.4
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    • pp.481-495
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    • 2011
  • This study is performed to consider the threshold values of heavy rain warning in Korea using 98 surface meteorological station data and 590 Automatic Weather System stations (AWSs), damage data of National Emergency Management Agency for the period of 2005 to 2009. It is in need to arrange new criteria for heavy rain considering concept of rainfall intensity and rainfall damage to reflect the changed characteristics of rainfall according to the climate change. Rainfall values from the most frequent rainfall damage are at 30 mm/1 hr, 60 mm/3 hr, 70 mm/6 hr, and 110 mm/12 hr, respectively. The cumulative probability of damage occurrences of one in two due to heavy rain shows up at 20 mm/1 hr, 50 mm/3 hr, 80 mm/6 hr, and 110 mm/12 hr, respectively. When the relationship between threshold values of heavy rain warning and the possibility of rainfall damage is investigated, rainfall values for high connectivity between heavy rain warning criteria and the possibility of rainfall damage appear at 30 mm/1 hr, 50 mm/3 hr, 80 mm/6 hr, and 100 m/12 hr, respectively. It is proper to adopt the daily maximum precipitation intensity of 6 and 12 hours, because 6 hours rainfall might be include the concept of rainfall intensity for very-short-term and short-term unexpectedly happened rainfall and 12 hours rainfall could maintain the connectivity of the previous heavy rain warning system and represent long-term continuously happened rainfall. The optimum combinations of criteria for heavy rain warning of 6 and 12 hours are 80 mm/6 hr or 100 mm/12 hr, and 70 mm/6 hr or 110 mm/12 hr.

Development of 1ST-Model for 1 hour-heavy rain damage scale prediction based on AI models (1시간 호우피해 규모 예측을 위한 AI 기반의 1ST-모형 개발)

  • Lee, Joonhak;Lee, Haneul;Kang, Narae;Hwang, Seokhwan;Kim, Hung Soo;Kim, Soojun
    • 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.

Investigation of Characteristics and States of Natural Disasters for Water Resources Disasters Control in Gyeongsangnam-do (경상남도 수자원재해관리를 위한 자연재해현황과 피해특성조사)

  • Park Jong-Kil;Jang Eun-Suk;Choi Hyo-Jin
    • Journal of Environmental Science International
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    • v.14 no.6
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    • pp.621-627
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    • 2005
  • It is analysised the causes and extent of damage of natural disasters through the investigating of natural disaster states occurred in Gyeongsangnam-do. The data for this study were based on disaster annual report between 1987 and 2003. Especially, the data between 1993 and 2003 were used for the analysis in Gyeongsangnam-do area. A typhoon and a heavy rain were the major causes of the natural disasters in Gyeongsangnam-do. For all that the extent of damage by a heavy rain was twice as much as that of a typhoon, Gyongsangnam-do suffered heavy damage from a typhoon. So, special attentions should be paid to establish prevention plans for that in this area. Also, half of the natural disasters were occurred between July and August, the intensive prevention plans for the summer season are needed.

Damage Types of Levee and its Maintenance and Repair (제방의 손상 유형 및 보수보강)

  • Moon, Dae-Ho
    • Proceedings of the Korean Geotechical Society Conference
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    • 2010.09a
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    • pp.144-169
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    • 2010
  • In 2002, property loss caused by failure or leakage of existing river levee structures was about 1.8 trillion in Korean Won, and furthermore in which damages of river structures are getting more severe due to characteristics of extremely extraordinary rain such as torrential rain in the locality or guerrilla heavy rain. In this regards, this paper collects and analyzes those damage records and costs for repair by statistic method, and moreover categorizes the causes of failure, erosion and overtopping of levee structures in large and small scale rivers threatened frequently by typhoon and heavy rainfall. It is believed that the results from the analyses can be used as a basic source in developing criteria of standards for design, construction, maintenance and inspection(or diagnosis) of hydraulic structures such as levee and drain conduit.

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Cause Analysis of 2006 Concentrated Heavy Rain Which Occurred in InJe-Gun (2006년 인제군 집중호우의 원인 분석)

  • Bae, Sun-Hak
    • Journal of the Korean association of regional geographers
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    • v.13 no.4
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    • pp.396-408
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    • 2007
  • Natural disasters occurred in Inje and Pyeongchang in 2006 show that unusual changes of weather, which Korean Peninsula has not experienced before, are becoming quite common phenomenon nowadays. In future we have to proceed in the direction of preventing such disasters so as to minimize the damage, by analyzing character and cause of various disasters whenever necessary, performing modeling in simulated real world, and applying the results in disaster prevention policy next year. Applying GIS in this process, the best information for decision-making can be offered. This study has also progressed proceeding from such point of view. The results of this study show that local concentrated heavy rain, caused by the primary topographical factor in the Sulak mountain region, was the main cause of flood disaster occurred in Inje-Gun area in July of 2006. Local concentrated heavy rain is greatly affected by topography. Namely, if there is a mountainous region behind, the area opposite to the direction of rain clouds motion will have high possibility of local concentrated heavy rain.

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The Analysis of Student's Acts within Limits When Encountering Natural Disasters caused by the Degree of Environmental Sensibility of School Facilities according to Natural Disaster Damage: Focusing on High-schools in Seoul Metropolitan Area (재해시 학교시설의 환경적 지각 정도에 따른 학생의 활동제한의 분석: 수도권 고등학교를 중심으로)

  • Min, Chang-Kee
    • Journal of the Korean Institute of Educational Facilities
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    • v.13 no.4
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    • pp.31-42
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    • 2006
  • This study is about an analysis of the relation between the degree of cognition of student's acts within limits when coping with several types of disaster and the degree of cognition of damage by disasters in the method of multiple regression analysis. The dependent variable is the degree of cognition of student's acts within limits and the independent variable is the degree of cognition of damage by disasters such as heavy snow, typhoon, heavy rain, heat, and yellow sand. A survey of graduates of metropolitan area high-schools has found that there are no difference between girls and boys of the degree of cognition of student's acts within limits when coping with disasters. This study finds that the independent variable, which are playgrounds, animals and plants, streets and roads, altitude and incline, gives positive effect to the degree of cognition of student's acts within limits when coping with typhoon or heavy rain in order. The study also finds that the degree of cognition of student's acts within limits when coping with heavy snow is affected positively by streets and roads, playgrounds, altitude and incline in order. It also shows that there are factors that has an effect to the degree of cognition of student's acts within limits when coping with yellow sand and heat. This study proposes suggestions to facility plans based on these facts discovered.

Development of Regression Models Resolving High-Dimensional Data and Multicollinearity Problem for Heavy Rain Damage Data (호우피해자료에서의 고차원 자료 및 다중공선성 문제를 해소한 회귀모형 개발)

  • Kim, Jeonghwan;Park, Jihyun;Choi, Changhyun;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.38 no.6
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    • pp.801-808
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    • 2018
  • The learning of the linear regression model is stable on the assumption that the sample size is sufficiently larger than the number of explanatory variables and there is no serious multicollinearity between explanatory variables. In this study, we investigated the difficulty of model learning when the assumption was violated by analyzing a real heavy rain damage data and we proposed to use a principal component regression model or a ridge regression model after integrating data to overcome the difficulty. We evaluated the predictive performance of the proposed models by using the test data independent from the training data, and confirmed that the proposed methods showed better predictive performances than the linear regression model.

Statistical Techniques to Derive Heavy Rain Impact Level Criteria Suitable for Use in Korea (통계적 기법을 활용한 한국형 호우영향도 기준 산정 연구)

  • Lee, Seung Woon;Kim, Byung Sik;Jung, Seung Kwon
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.563-569
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    • 2020
  • Presenting the impact of meteorological disasters departs from the traditional weather forecasting approach for meteorological phenomena. It is important to provide impact forecasts so that precautions against disruption and damage can be taken. Countries such as the United States, the U.K., and France already conduct impact forecasting for heavy rain, heavy snow, and cold weather. This study improves and applies forecasts of the impact of heavy rain among various weather phenomena in accordance with domestic conditions. A total of 33 impact factors for heavy rain were constructed per 1 km grids, and four impact levels (minimal, minor, significant, and severe) were calculated using standard normal distribution. Estimated criteria were used as indicators to estimate heavy rain risk impacts for 6 categories (residential, commercial, utility, community, agriculture, and transport) centered on people, facilities, and traffic.

The Meteorological Disaster Analysis for the Natural Disaster Mitigation in the Korean Peninsula (자연재해 저감을 위한 한반도 피해 현황 분석)

  • Park, Jong-Kil;Choi, Hyo-Jin;Jung, Woo-Sik
    • 한국방재학회:학술대회논문집
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    • 2007.02a
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    • pp.319-322
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    • 2007
  • This study aims to find the characteristics of damage and states of natural disasters at the Korean Peninsula from 1985 to 2004. Using the data of Statistical yearbook of calamities issued by the National Emergency Management Agency and Annual Climatological Report issued by the Korea Meteorological Administration. we have analyzed the cause, elements, and vulnerable regions for natural disasters. Major causes of natural disaster at Korean Peninsula are four, such as a heavy rain, heavy rain typhoon, typhoon, storm snow, and storm. The frequency of natural disaster is the highest from June to September. The period from December to March also shows high frequency. The total amount of damage is high during the summer season(Jul.-Sept). The period from January to March shows relatively high amount of damage due to storm and storm snow The areas of Gangwon-do, Gyeongsangnam-do and Gyeongsangbuk-do are classified the vulnerable region for the natural disasters. By establishing mitigation plans which fit the type and characteristics of disaster for each region, damage from disaster can be reduced with efficient prevention activities.

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