• 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.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.851-859
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• 2019

The COMS satellites take image of the Korean Peninsula every 15 minutes, but due to the limitations of the observational channels, they tend to underestimate when estimating rainfall. In this study, we developed satellite-based rainfall estimation technology using COMS and GPM that can be used in the heavy rain on the Korean Peninsula. The time resolution and spatial resolution of COMS satellites and GPM satellites were matched to improve accuracy using GPM IMERG data. As a result, it showed that the number of correlations with the ASOS observations was more than 0.7, enabling the estimation of rainfalls that are more accurate than the estimates of rainfall by COMS satellites. It is believed that the application of the subsequent satellite(GK-2A) will provide more accurate rainfall estimation information in the future. Therefore, we expect greater utilization in disaster management for the ungauged areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.783-791
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• 2018

The biased estimation of low density rainfall network and radar rainfall has limited application to extreme rainfall in a small area. To improve this, more rainfall information needs to be produced. In this study, we analyzed the applicability of the vehicle rainfall sensor developed and used recently. The developed rainfall sensor was attached to the vehicle to observe the rainfall according to the movement of the vehicle. The analytical method used time series and average rainfall values for observations of rainfall sensors and nearby rainfall stations. The results show that the trend of observed values according to rainfall events shows a certain pattern. It is analyzed that it is caused by various causes such as the difference between the observation position of the rainfall sensor and the nearby rainfall station, the moving speed of the vehicle, and the rainfall observation method. This result shows the possibility of rainfall observation using a rainfall sensor for a vehicle, and it is possible to observe rainfall more precisely through experiments and improvement of rainfall sensors in various conditions in the future.

• Proceedings of the KSRS Conference
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• v.2
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• pp.884-887
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• 2006

This paper focuses on minimizing flood damage in the Yeongdeok basin of South Korea by establishing a flood prediction model based on a geographic information system (GIS), remote sensing, and geomorphoclimatic instantaneous unit hydrograph (GcIUH) techniques. The GIS database for flash flood prediction was created using data from digital elevation models (DEMs), soil maps, and Landsat satellite imagery. Flood prediction was based on the peak discharge calculated at the sub-basin scale using hydrogeomorphologic techniques and the threshold runoff value. Using the developed flash flood prediction model, rainfall conditions with the potential to cause flooding were determined based on the cumulative rainfall for 20 minutes, considering rainfall duration, peak discharge, and flooding in the Yeongdeok basin.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.3
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• pp.141-152
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• 2017

This paper presents a technical method for flood estimation based on satellite rainfall and satellite rainfall correction method for watersheds lacking measurement data. The study area was the Sebou Watershed, Morocco. The Integrated Flood Analysis System(IFAS) and Grid-based Rainfall-Runoff Model(GRM) were applied to estimate watershed runoff. Daily rainfall from ground gauges and satellite-derived hourly data were used. In the runoff simulation using satellite rainfall data, the composites of the daily gauge rainfall and the hourly satellite data were applied. The Shuttle Radar Topographic Mission Digital Elevation Model(SRTM DEM) with a 90m spatial resolution and 1km resolution data from Global map land cover and United States Food and Agriculture Organization(US FAO) Harmonized World Soil Database(HWSD) were used. Underestimated satellite rainfall data were calibrated using ground gauge data. The simulation results using the revised satellite rainfall data were $5,878{\sim}7,434m^3/s$ and $6,140{\sim}7,437m^3/s$ based on the IFAS and GRM, respectively. The peak discharge during flooding of Sebou River Watershed in 2009~2010 was estimated to range from $5,800m^3/s$ to $7,500m^3/s$. The flood estimations from the two hydrologic models using satellite-derived rainfall data were similar. Therefore, the calibration method using satellite rainfall suggested in this study can be applied to estimate the flood discharge of watersheds lacking observational data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.528-530
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• 2003

We present here, some of the studies carried for estimation of rainfall over land and oceanic regions in and around South Korea. We use active and passive microwave measurements from TRMM ? TMI and Precipitation Radar (PR) respectively during a typhoon even named ? RUSA that took place during 30 Aug. 2002. We have followed due approach by Yao at. all (2002) and examined the performance of their algorithm using two main predictor variable, named as Scattering Index (SI) and Polarization Corrected Brightness Temperature (PCT) while using TMI data. The rainfall fnus estimated using PST and SI shows some Underestimation as compared to the 2A25 rainfall products from the PR in common area of overlap. A larger database thus would be used in future. To establish a new rain rate algorithm over Korean region based on the present case study.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.390-390
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• 2019

Application of Hidden Markov Model (HMM) to the hydrological time series would be an innovative way to identify extreme rainfall events in a series. Even though the optimum number of hidden states can be identify based on maximizing the log-likelihood or minimizing Bayesian information criterion. However, occasionally value for the log-likelihood keep increasing with the state which gives false identification of the optimum hidden state. Therefore, this study attempts to identify optimum number of hidden states for Colombo station, Sri Lanka as fundamental approach to identify frequency and percentage of extreme rainfall events for the station. Colombo station consisted of daily rainfall values between 1961 and 2015. The representative station is located at the wet zone of Sri Lanka where the major rainfall season falls on May to September. Therefore, HMM was ran for the season of May to September between 1961 and 2015. Results showed more or less similar log-likelihood which could be identified as maximum for states between 4 to 7. Therefore, measure of central tendency (i.e. mean, median, mode, standard deviation, variance and auto-correlation) for observed and simulated daily rainfall series was carried to each state to identify optimum state which could give statistically compatible results. Further, the method was applied for the second major rainfall season (i.e. October to February) for the same station as a comparison.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.4
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• pp.57-66
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• 2016

Harmonized World Soil Database (HWSD) including the global soil information has been implemented to the runoff analysis in many watersheds of the world. However, its accuracy can be a critical issue in the modeling because of the limitation the low resolution reflecting the physical properties of soil in a watershed. Accordingly, this study attempted to assess the effect of HWSD in modeling by comparing parameters of the rainfall-runoff model using HWSD with the detailed soil map. For this, Grid based Rainfall-runoff Model (GRM) was employed in the Hyangseok watershed. The results showed that both of two soil maps in the rainfall-runoff model are able to well capture the observed runoff. However, compared with the detailed soil map, HWSD produced more uncertainty in the GRM parameters related to soil depth and hydraulic conductivity during the calibrations than the detailed soil map. Therefore, the uncertainty from the limited information on soil texture in HWSD should be considered for better calibration of a rainfall-runoff model.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.857-865
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• 2013

Extreme rainfall causes heavy losses in human life and properties. Hence many works have been done to predict extreme rainfall by using extreme value distributions. In this study, we use a generalized extreme value distribution to derive the posterior predictive density with hierarchical Bayesian approach based on the data of Seoul area from 1973 to 2010. It becomes clear that the probability of the extreme rainfall is increasing for last 20 years in Seoul area and the model proposed works relatively well for both point prediction and predictive interval approach.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.1-13
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• 2011

This study is to analyze the relationship between rainfall and water level using the measured data. During the rainfall event from September 9 to September 12, 2010, the rainfall and water level data were measured from automatic weather systems and automatic water level measurement systems which have been installed throughout Gangwon province. The result showed that the relationship between rainfall and peak flow change was different by basin and tributary. It is expected that this study will help to build a plan for preventing disasters and rainfall-runoff models for the river basins in Gangwon province.