• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.334-334
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• 2022

Improvement of old-fashioned rain gauge systems for automatic, timely, continuous, and accurate precipitation observation is highly essential for weather/climate prediction and natural hazards early warning, since the occurrence frequency and intensity of heavy and extreme precipitation events (especially floods) are recently getting more increase and severe worldwide due to climate change. Although rain gauge accuracy of 0.1 mm is recommended by the World Meteorological Organization (WMO), the traditional rain gauges in both weighting and tipping bucket types are often unable to meet that demand due to several existing technical limitations together with higher production and maintenance costs. Therefore, we aim to introduce a newly developed and cost-effective hybrid rain gauge system at 0.1 mm accuracy that combines advantages of weighting and tipping bucket types for continuous, automatic, and accurate precipitation observation, where the errors from long-term load cells and external environmental sources (e.g., winds) can be removed via an automatic drainage system and artificial intelligence-based data quality control procedure. Our rain gauge system consists of an instrument unit for measuring precipitation, a communication unit for transmitting and receiving measured precipitation signals, and a database unit for storing, processing, and analyzing precipitation data. This newly developed rain gauge was designed according to the weather instrument criteria, where precipitation amounts filled into the tipping bucket are measured considering the receiver's diameter, the maximum measurement of precipitation, drainage time, and the conductivity marking. Moreover, it is also designed to transmit the measured precipitation data stored in the PCB through RS232, RS485, and TCP/IP, together with connecting to the data logger to enable data collection and analysis based on user needs. Preliminary results from a comparison with an existing 1.0-mm tipping bucket rain gauge indicated that our developed rain gauge has an excellent performance in continuous precipitation observation with higher measurement accuracy, more correct precipitation days observed (120 days), and a lower error of roughly 27 mm occurred during the measurement period.

• Journal of environmental and Sanitary engineering
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• v.19 no.2
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• pp.45-50
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• 2004

To investigate the epilithic diatom community and water quality of the Osan stream, water samples were collected from the eight stations from April to September 2003. Sampling was two times before and after heavy rain. Total 52 diatom were identified and divided into 12 saproxenosus taxa, 6 saprophilous taxa and 34 indifferent taxa, respectively. The DAIpo values higher after heavy rain than before that. According to tolerance degree to the organic water pollution, all sampling stations ranged from $\alpha$-oligosaprobic to $\alpha$-mesosaprobic. Thus, the result indicates that the water quality of Osan stream is gradually improved by heavy rain.

• Journal of Integrative Natural Science
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• v.4 no.3
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• pp.229-237
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• 2011

Today they use a weather radar with spatially high resolution in predicting rainfall intensity and utilizing the information for super short-range forecast in order to make predictions of such severe meteorological phenomena as heavy rainfall and snow. For a weather radar, they use the Z-R relation between the reflectivity factor(Z) and rainfall intensity(R) by rainfall particles in the atmosphere in order to estimate intensity. Most used among the various Z-R relation is $Z=200R^{1.6}$ applied to stratiform rain. It's also used to estimate basic rainfall intensity of a weather radar run by the weather center. This study set out to compare rainfall intensity between the reflectivity of a weather radar and the ground rainfall of ASOS(Automatic Surface Observation System) by analyzing many different cases of heavy rain, analyze the errors of different weather radars and identify their problems, and investigate their applicability to nowcasting in case of severe weather.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05b
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• pp.1161-1166
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• 2002

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.1
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• pp.1-11
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• 1999

In this work, a theoretical model has been formulated which allows the study of the scavenging efficiencies of aerosol particles by the rain drops. Aerosol particles are scavenged by the simultaneous brownian diffusion, interception and inertial impaction force. In addition the calculations based on the collision efficiency model are carried out for the collision of aerosol particles with diameter range 0.01~30 $mu extrm{m}$ and rain drops with diameter 0.02$\times$$2^{n/3}$(n=1, 2, …, 17)cm. The results indicate that: (1) the below-cloud scavenging affects mainly the coarse particles (＞3 ${\mu}{\textrm}{m}$), the fine particles remaining almost unchanged; (2) the scavenging efficiencies by below-cloud in the heavy rain (rain intensity, 10 mm/hr) surpass the efficiency found in the drizzle rain (rain intensity, 1 mm/hr).

• Journal of Ecology and Environment
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• v.32 no.3
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• pp.197-206
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• 2009

Benthic macroinvertebrate communities were collected from six different sites in the Dobong Stream in Seoul, Korea to investigate spatial and temporal changes in benthic macroinvertebrate communities in response to natural disturbances such as floods and droughts. We collected samples monthly or semimonthly with a Surber net ($30cm{\times}30cm$), and measured environmental factors, including stream temperature, discharge, width, conductivity, dissolved oxygen and pH at each sampling site. Benthic macro invertebrates were strongly affected by floods as well as droughts. In addition, benthic macroinvertebrate communities displayed different responses to the onset of the rainy season in summer 2006 and 2007, apparently due to differences in the intensity and amount of precipitation. Chironomids were particularly sensitive to heavy rain. Floods and droughts also affected the proportions of functional feeding groups during the survey period: the proportion of scrapers was high right after heavy rains, while the proportion of predators tended to increase in intermittent-type streams as the riffle zone decreased. Finally, although species richness and abundance were strongly influenced by heavy rain, they recovered to background levels for within one month, and varied consistently among stream types, indicating habitat stability.

• 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.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.113-117
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• 2020

Images were taken under various weather such as rain, haze, snow often show low visibility, which can dramatically decrease accuracy of some tasks in computer vision: object detection, segmentation. Besides, previous work to enhance image usually downsample the image to receive consistency features but have not yet good upsample algorithm to recover original size. So, in this research, we jointly implement removal streak in heavy rain image and super resolution using a deep network. We put forth a 2-stage network: a multi-model network followed by a refinement network. The first stage using rain formula in the single image and two operation layers (addition, multiplication) removes rain streak and noise to get clean image in low resolution. The second stage uses refinement network to recover damaged background information as well as upsample, and receive high resolution image. Our method improves visual quality image, gains accuracy in human action recognition task in datasets. Extensive experiments show that our network outperforms the state of the art (SoTA) methods.

• Journal of the Korean earth science society
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• v.35 no.2
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• pp.115-130
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• 2014

The growing possibility of the disaster due to severe weather calls for disaster prevention and water management measures in South Korea. In order to prevent a localized heavy rain from occurring, the rainfall must be observed and predicted quantitatively. In this study, we developed an adjustment algorithm to estimate the radar precipitation applying to the local gauge correction (LGC) method which uses geostatistical effective radius of errors of the radar precipitation. The effective radius was determined from the errors of radar rainfall using geostatistical method, and we adjusted radar precipitation for four heavy rainfall events based on the LGC method. Errors were decreased by about 40% and 60% in adjusted hourly rainfall accumulation and adjusted total rainfall accumulation for four heavy rainfall events, respectively. To estimate radar precipitation for localized heavy rain events in summer, therefore, we believe that it was appropriate for this study to use an adjustment algorithm, developed herein.

• Journal of Wetlands Research
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• v.17 no.1
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• pp.38-44
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• 2015

In Korea, most rainfall events occur during summer which then leads to an increasing concern regarding high influx of non-point source pollutants since the pollutant loadings from these non-point sources are very significant. In particular, the first flush of roof-harvested rainfall is said to contain the most highest concentration of nutrients and heavy metals. Accordingly, it is important to develope the possible water quality management options in treating the contaminants and considering reclaimed water reuse. The rain garden could be one of suitable alternatives in addressing this issue. In this study, the development of an effective adsorption media and its application to a lab-scale rain garden was tested to evaluate the removal rate of various nutrient and organic matter (TN, TP, CODcr), and heavy metals (Cu, Cd, Pb). Results showed that carbonized peatmoss produced at higher temperature have better adsorption capacity as compared to the one produced at a lower temperature. When the carbonized peatmoss was applied as rain garden media, the highest removal of TN, TP, and CODcr was observed compared to no carbonized peatmoss applied rain garden. Therefore, this study showed that the carbonized peatmoss would be effectively applied to the rain garden for removing nutrients and heavy metals from roof-harvested rainwater.