• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.111-116
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• 2004

We surveyed the coastal structure damages due to the typhoon 'Mae-mi' which heavily struck Korean peninsula in September 12, 2003. The survey revealed the typhoon induced high tides and strong winds were the main causes especially in Busan areas. Though some experimental real time coastal monitoring stations captured the typhoon movements at the critical time, more systematic and complete systems should be implemented to save human lives and properties from huge typhoon disasters.

• Journal of Ocean Engineering and Technology
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• v.18 no.2
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• pp.25-32
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• 2004

We surveyed the coastal structure damage created by typhoon ‘Maemi’, which heavily struck the Korean peninsula on September 12, 2003. The survey revealed that high tides and strong winds induced by the typhoon were the main causes of the coastal damage, especially in the Busan areas. Though some experimental real-time coastal monitoring stations captured the typhoon movements at the critical time, more systematic and complete system should be implemented to save human lives and property from huge typhoon disasters.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.165-166
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• 2006

Recently, after Wide Area Outage of the North-Eastern United States occurred, many countries started to be concerned about WAMS (Wide Area Monitoring System), and Korean power system also experienced Wide Area outage according to typhoon Mae-Mi, and Haenam-Jeju HVDC line fault. Since it is too difficult to detect a symptom based on SCADA or EMS, a defense system of electric power infrastructure has required. In this research, the designed and developed system processes the time synchronized real time power system information based on GPS and shows the 2D/3D monitoring viewer using the phasor data and the results of three algorithms.

• Journal of Korean Society on Water Environment
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• v.24 no.2
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• pp.185-194
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• 2008

There is increased soil erosion potential at highland agricultural crop fields because of its topographic characteristics and site-specific agricultural management practices performed at these areas. The agricultural upland fields are usually located at the sloping areas, resulting in higher soil loss, pesticides, and nutrients in case of torrential rainfall events or typhoon, such as 2002 Rusa and 2003 MaeMi. At the highland agricultural fields, the soil reconditioning have been performed every year to decrease damage by continuous cropping and pests. Also it has been done to increase crop productivity and soil fertility. The increased amounts of soil used for soil reconditioning are increasing over the years, causing significant impacts on water quality at the receiving water bodies. In this study, the field investigation was done to check soil reconditioning status for potato, carrot, and cabbage at the Doam-dam watershed. With these data obtained from the field investigation, the Soil and Water Assesment Tool (SWAT) model was used to simulate the soil loss reduction with environment-friendly and agronomically enough soil reconditioning. The average soil reconditioning depth for potato was 34.3 cm, 48.3 cm for carrot, and 31.2 cm for cabbage at the Doam-dam watershed. These data were used for SWAT model runs. Before the SWAT simulation, the SWAT ArcView GIS Patch, developed by the Kangwon National University, was applied because of proper simulation of soil erosion and sediment yield at the sloping watershed, such as the Doam-dam watershed. With this patch applied, the Coefficient of Determination ($R^2$) value was 0.85 and the Nash-Sutcliffe Model Efficiency (EI) was 0.75 for flow calibration. The $R^2$ value was 0.87 and the EI was 0.85 for flow validation. For sediment simulation, the $R^2$ value was 0.91 and the EI was 0.70, indicating the SWAT model predicts the soil erosion processes and sediment yield at the Doam-dam watershed. With the calibrated and validated SWAT for the Doam-dam watershed, the soil erosion reduction was investigated for potato, carrot, and cabbage. For potato, around 19.3 cm of soil were over applied to the agricultural field, causing 146% of more soil erosion rate, approximately 33.3 cm, causing 146% of more soil erosion for carrot, and approximately 16.2 cm, causing 44% of more soil erosion. The results obtained in this study showed that excessive soil reconditioning are performed at the highland agricultural fields, causing severe muddy water issues and water quality degradation at the Doam-water watershed. The results can be used to develop soil reconditioning standard policy for various crops at the highland agricultural fields, without causing problems agronomically and environmentally.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.1
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• pp.83-93
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• 2020

East Asia, which includes China, Japan, Korea, and Mongolia, is highly impacted by hydroclimate extremes such drought, flood, and typhoon recent year. In 2017, more than 18.5 million hectares of crops have been damaged in China, and Korea has suffered economic losses as a result of severe drought. Satellite-derived rainfall products are becoming more accurate as space and time resolution become increasingly higher, and provide an alternative means of estimating ground-based rainfall. In this study, we verified the availability of rainfall products by comparing widely used satellite images such as Climate Hazards Groups InfraRed Precipitation with Station (CHIRPS), Global Precipitation Climatology Centre (GPCC), and Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) with ground stations in East Asia. Also, the satellite-based rainfall products were used to calculate the Standardized Precipitation Index (SPI). The temporal resolution is based on monthly images and compared with the past 30 years data from 1989 to 2018. The comparison between rainfall data based on each satellite image products and the data from weather station-based weather data was shown by the coefficient of determination and showed more than 0.9. Each satellite-based rainfall data was used for each grid and applied to East Asia and South Korea. As a result of SPI analysis, the RMSE values of CHIRPS were 0.57, 0.53 and 0.47, and the MAE values of 0.46, 0.43 and 0.37 were better than other satellite products. This satellite-derived rainfall estimates offers important advantages in terms of spatial coverage, timeliness and cost efficiency compared to analysis for drought assessment with ground stations.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1037-1051
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• 2020

The accurate monitoring and forecasting of the intensity of tropical cyclones (TCs) are able to effectively reduce the overall costs of disaster management. In this study, we proposed a multi-task learning (MTL) based deep learning model for real-time TC intensity estimation and forecasting with the lead time of 6-12 hours following the event, based on the fusion of geostationary satellite images and numerical forecast model output. A total of 142 TCs which developed in the Northwest Pacific from 2011 to 2016 were used in this study. The Communications system, the Ocean and Meteorological Satellite (COMS) Meteorological Imager (MI) data were used to extract the images of typhoons, and the Climate Forecast System version 2 (CFSv2) provided by the National Center of Environmental Prediction (NCEP) was employed to extract air and ocean forecasting data. This study suggested two schemes with different input variables to the MTL models. Scheme 1 used only satellite-based input data while scheme 2 used both satellite images and numerical forecast modeling. As a result of real-time TC intensity estimation, Both schemes exhibited similar performance. For TC intensity forecasting with the lead time of 6 and 12 hours, scheme 2 improved the performance by 13% and 16%, respectively, in terms of the root mean squared error (RMSE) when compared to scheme 1. Relative root mean squared errors(rRMSE) for most intensity levels were lessthan 30%. The lower mean absolute error (MAE) and RMSE were found for the lower intensity levels of TCs. In the test results of the typhoon HALONG in 2014, scheme 1 tended to overestimate the intensity by about 20 kts at the early development stage. Scheme 2 slightly reduced the error, resulting in an overestimation by about 5 kts. The MTL models reduced the computational cost about 300% when compared to the single-tasking model, which suggested the feasibility of the rapid production of TC intensity forecasts.