• 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.

• 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.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.03a
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• pp.419-426
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• 2008

Recently, localized heavy rain due to "EL-LIO" was a kind of reason by risk of slope stability. In this paper, the behaviour of slope when localized heavy rain was studied. In order to perform this study experimental programs were performed. Experimental programs was checked filtering conditions for slope stability due to localized heavy rain. And then, investigated slope stability and fracture mechanism each other types. In the experimental study, performed changing filtering condition by embankment, through five fixing factors such as rainfall intensity, slope shape, geological condition, compaction energy and water content. According to the results of this study, behaviour of facture slope has made a shallow and narrow waterway. This waterway expanded base stone. In order to, suggested a system for slope stability examination.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2006.04a
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• pp.313-318
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• 2006

The main cause of natural disaster in Korea is meteorological phenomenon, such as typhoon, heavy rain, storm, rainstorm, heavy snow, hailstorm, overflowing of sea and so on(including thunderstroke, blast, snow damage, freezing and earthquake), and among those disasters, heavy rain takes place most often, and it occupies 80% of total disaster Especially, disaster related to slope collapse (landslide, collapse of retaining wall, burying ect.) takes place every year due to meteorological cause such as localized heavy rain, which is getting stronger. (National Institute for Prevention Disaster, 2002, Meteorological Administration) Accordingly, it is necessary to analyze the features of slope collapse related to natural disaster in Korea, and also to make up counterplan to prevent disaster. This paper will try to analyze potential areas which are susceptible to landslide regarding factors inducing landslide and heavy rain, and to evaluate the potentiality of landslide regarding local particularity of rainfall, furthermore to provide essential information for development of community such as preventing damages from landslide, construction Industry, and effective use of land.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.7
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• pp.730-735
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• 2014

This paper introduces a GP (Genetic Programming) based robust technique for the prediction of a heavy rain newsflash. The nature of prediction for precipitation is very complex, irregular and highly fluctuating. Especially, the prediction of heavy precipitation is very difficult. Because not only it depends on various elements, such as location, season, time and geographical features, but also the case data is rare. In order to provide a robust model for precipitation prediction, a nonlinear and symbolic regression method using GP is suggested. The remaining part of the study is to evaluate the performance of prediction for a heavy rain newsflash using a GP based nonlinear regression technique in Korean regions. Analysis of the feature selection is executed and various fitness functions are proposed to improve performances. The KLAPS data of 2006-2010 is used for training and the data of 2011 is adopted for verification.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.473-478
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• 2013

In this paper, we develop the Heavy Rain Advisory Decision Model based on intelligent neuro-fuzzy algorithm RBFNNs by using KLAPS(Korea Local Analysis and Prediction System) Reanalysis data. the prediction ability of existing heavy rainfall forecasting systems is usually affected by the processing techniques of meteorological data. In this study, we introduce the heavy rain forecast method using the pre-processing techniques of meteorological data are in order to improve these drawbacks of conventional system. The pre-processing techniques of meteorological data are designed by using point conversion, cumulative precipitation generation, time series data processing and heavy rain warning extraction methods based on KLAPS data. Finally, the proposed system forecasts cumulative rainfall for six hours after future t(t=1,2,3) hours and offers information to determine heavy rain advisory. The essential parameters of the proposed model such as polynomial order, the number of rules, and fuzzification coefficient are optimized by means of Differential Evolution.

• Journal of Korean Society of Water and Wastewater
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• v.32 no.6
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• pp.517-526
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• 2018

Climate adaptation strategies for water utilities including 16 water treatment plants(WTPs) in Jeju were investigated. Drought, heat wave, and heavy rain were among the most significant climate factors affecting water utilities in Jeju. Heat wave increases water temperature, which in turn increases the concentration of algae, color, and odor materials. Some adaption strategies for the heat wave can be strengthening water monitoring and introducing advanced water treatments. Heavy rain increases raw water turbidity in surface water. The 7 WTPs that take raw water from streams or springs had a maximum turbidity of less than 50 NTU under heavy rain. However, due to concerns of turbidity spike in treated water, some WTPs discontinued intaking raw water when raw water turbidity increased more than 2 NTU. They instead received treated water from other WTPs which took groundwater for water supply. This happens because of the low skills of employees. Thus, there needs to be an increase in operator competency and upgrade of water facilities for the adaption of heavy rain. To improve adaption for the drought, there should be an increase in the capacity of intake facilities of surface water as well as a decrease in water loss. In addition, water consumption per person should be decreased.

• Journal of Integrative Natural Science
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• v.14 no.4
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• pp.162-175
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• 2021

Recently, due to global warming, the average temperature of the earth has risen, and the glaciers in the Antarctic and Arctic melt, leading to a rise in sea level, which is accompanied by powerful natural disasters such as strong typhoons and tsunamis around the world. Accordingly, a precipitation in summer in Korea also increased, and changes in the form of precipitation were showed with the increase. Compared to the past, the frequency of localized heavy rain is increasing, and the damage from flooding and flooding is increasing day by day. In this study, based on the precipitation data measured in hours from May to September from 2016 to 2021 according to the change in the precipitation form, according to the nature of the torrential rain investigated the change in the summer precipitation form. In addition, the trend of localized heavy rain from 2016 to 2021 was confirmed by classifying them into two types: localized heavy rains caused by cyclones and weather front, and by typhoons and large-scale cyclones. Through this, the change in precipitation due to the climate crisis should not be viewed as a single phenomenon, it should be reflected and discussed on our life focused on scientific and technological development, and it should be used as a stepping stone for realizing a humanistic.

• Korean Journal of Remote Sensing
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• v.29 no.4
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• pp.423-441
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• 2013

On 21 September 2010, one of Chuseok holidays in Korea, localized heavy rainfalls occurred over the midwestern region of the Korean peninsula. In this study MTSAT-2 infrared and water vapor channel imagery are examined to find out some features which are obvious in each stage of the life cycle of convective cell for this heavy rain event. Also the kinematic and thermodynamic features probably associated with them are investigated. The first clouds related with the Chuseok heavy rain are detected as low-level multicell cloud (brightness temperature: $-15{\sim}0^{\circ}C$) in the middle of the Yellow sea at 1630~1900 UTC on 20 Sept., which are probably associated with the convergence at 1000 hPa. Convective cells are initiated in the vicinity of Shantung peninsula at 1933 UTC 20, which have developed around the edge of the dark region in water vapor images. At two times of 0033 and 0433 UTC 21 the merging of two convective cells happens near midwestern coast of the peninsula and then they have developed rapidly. From 0430 to 1000 UTC 21, key features of convective cell include repeated formation of secondary cell, slow horizontal cloud motion, persistence of lower brightness temperature ($-75{\sim}-65^{\circ}C$), and relatively small cloud size (${\leq}-50^{\circ}C$) of about $30,000km^2$. Radar analysis showed that this heavy rain is featured by a narrow line-shaped rainband with locally heavy rainrate (${\geq}50$ mm/hr), which is located in the south-western edge of the convective cell. However there are no distinct features in the associated synoptic-scale dynamic forcing. After 1000 UTC 21 the convective cell grows up quickly in cloud size and then is dissipated. These satellite features may be employed for very short range forecast and nowcasting of mesoscale heavy rain system.