• Journal of Korea Water Resources Association
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• v.41 no.11
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• pp.1153-1162
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• 2008

The use of radar rainfall for hydrological appraisal has been a challenge due to the limitations in raw data generation followed by the complex analysis needed to come up with precise data interpretation. In this study, RAIDOM (RAdar Image DigitalizatiOn Method) has been developed to convert synthetic radar CAPPI(Constant Altitude Plan Position Indicator) image data from Korea Meteorological Administration into digital format in order to come up with a more practical and useful radar image data. RAIDOM was used to examine a severe local rainstorm that occurred in July 2006 as well as two other separate events that caused heavy floods on both upper and mid parts of the HanRiver basin. A distributed model was developed based on the available radar rainfall data. The Flood Hydrograph simulation has been found consistent with actual values. The results show the potentials of RAIDOM and the distributed model as tools for flood prediction. Furthermore, these findings are expected to extend the usefulness of radar rainfall data in hydrological appraisal.

• International Union of Geodesy and Geophysics Korean Journal of Geophysical Research
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• v.26 no.1
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• pp.15-29
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• 1998

The numerical simulation of heavy precipitation event occurred in the central Korean Peninsula on July 26-28, 1996 was performed using the fine mesh model. ARPS (Advanced Regional Prediction System) developed by the CAPS (Center for Analysis and Prediction of Storms). Usually, the heavy rainfalls occurred at late July in the Korean Peninsula were difficult to predict, and showed very strong rainfall intensity. As results, they caused a great loss of life and property. As it usual, this case was unsuccessful to predict the location of rain band and the precipitation intensity with the coarse-mesh model. The same case was, however, simulated well with fine-mesh storm-scale model, ARPS. Moisture band at 850 hPa appeared along the Changma Front in the area of China through central Korea passed Yellow Sea. Also the low-level jet at 700 hPa existed in the Yellow Sea through central Korea and they together offered favorable condition to induce heavy rainfall in that area. The convective activities developed to a meso-scale convective system were observed at near the Yangtze River and moved to the central Korean Peninsula. Furthermore, the intrusion of warm and moist air, origninated from typhoon, into the Asia Continent might result in heavy rainfall formation through redistribution of moisture and heat. In the vertical circulation, the heavy rainfall was formed between the upper- and low-level jets, especially, the entrance region of the upper-level jet above the exit the region of the low-level jet. The low level convergence, the upper level divergence and the strong vertical wind were organized to the very north of the low level jet and concentrated on tens to hundreds km horizontal distance. These result represent the upper- and low-level jets are one of the most important reasons on the formation of heavy precipitation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5B
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• pp.267-272
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• 2012

To reduce the flood risk caused by unexpected heavy rainfall, many prediction methods for flood have been developed. A major constituent of flood prediction is an accurate rainfall estimation which is an input of hydrologic models. In this study, a regional-scale weather model which can provide relatively longer lead time for flood mitigation compared to the Nowcasting based on radar system will be introduced and applied to the Chongmi river basin located in central part of South Korea. The duration of application of a regional weather model is from July 11 to July 23 in 2006. The estimated rainfall amounts were compared with observations from rain gauges (Sangkeuk, Samjook, and Sulsung). For this rainfall event at Chongmi river basin, Thomson and Kain-Frisch Schemes for microphysics and cumulus parameterization, respectively, were selected as optimal physical conditions to present rainfall fall amount in terms of Mean Absolute Relative Errors (MARE>0.45).

• Journal of information and communication convergence engineering
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• v.14 no.3
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• pp.153-162
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• 2016

Microwave and millimeter waves are considered suitable frequency ranges for diverse applications. The prediction of rain attenuation required the 1-min rainfall rate distribution, particularly for data obtained locally from experimental measurement campaigns over a given location. Rainfall rate data acquired from Korea Meteorological Administration (KMA) for nine major sites are analyzed to investigate the statistical stability of the cumulative distribution of rainfall rate, as obtained from a 10-year measurement. In this study, we use the following rain rate conversion techniques: Segal, Burgueno et al., Chebil and Rahman, exponential, and proposed global coefficient methods. The performance of the proposed technique is tested against that of the existing rain rate conversion techniques. The nine sites considered for the average 1-min rain rate derivation are Gwangju, Daegu, Daejeon, Busan, Seogwipo, Seoul, Ulsan, Incheon, and Chuncheon. In this paper, we propose a conversion technique for a suitable estimation of the 1-min rainfall rate distribution.

• Magazine of the Korean Society of Agricultural Engineers
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• v.20 no.3
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• pp.4724-4731
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• 1978

Using hydrometric data from an upland river in North Wales, a relationship between rate of river flow and water stored within the catchment area (catchment storage) is assumed to exist, and is evaluated from an analysis of winter recession curves. This storage/river flow relationship, when combined with water balance equations, produces a set of equations which may be used for "routing" input of rainfall through a storage with defined outflow characteristics, providing a straightforward method of flood prediction and analysis from rainfall data. Recorded and predicted flood hydrographs are compared, and the effectiveness and limitations of the method are considered. The development of a complete mathematical model, embodying the storage/river flow relationship, and suitable for generation of continuous run-off records from rainfall and evaporation data, is also considered.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.335-339
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• 2001

The Tropical Rainfall Measuring Mission(TRMM) Satellite was launched in November 1997, carrying into orbit the first space-borne Precipitation Radar(PR). The purpose of this study is to identify the relationship between TRMM/PR and AWS raingage data, and test the possibility to apply storm runoff prediction. Four TRMM/PR data in 1999 for Yongdam watershed was adopted and made a simple linear regression equation using AWS data. By using the equation, the storm runoff was estimated with the adjusted rainfall. TRMM/PR rainfall and runoff was overall underestimated by the carry-over effect of rainfall error and SCS-CN value selection.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.188-188
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• 2017

Rainfall is an important input to hydrological models. The accuracy of hydrological studies for water resources and floods management depend primarily on the estimation of rainfall. Thailand is among the countries that have regularly affected by floods. Flood forecasting and warning are necessary to prevent or mitigate loss and damage. Merging near real time satellite-based precipitation estimation with relatively high spatial and temporal resolutions to ground gauged precipitation data could contribute to reducing uncertainty and increasing efficiency for flood forecasting application. This study tested the applicability of satellite-based rainfall for water resources management and flood forecasting. The objectives of the study are to assess uncertainty associated with satellite-based rainfall estimation, to perform bias correction for satellite-based rainfall products, and to evaluate the performance of the bias-corrected rainfall data for the prediction of flood events. This study was conducted using a case study of Thai catchments including the Chao Phraya, northeastern (Chi and Mun catchments), and the eastern catchments for the period of 2006-2015. Data used in the study included daily rainfall from ground gauges, telegauges, and near real time satellite-based rainfall products from TRMM, GSMaP and PERSIANN CCS. Uncertainty in satellite-based precipitation estimation was assessed using a set of indicators describing the capability to detect rainfall event and efficiency to capture rainfall pattern and amount. The results suggested that TRMM, GSMaP and PERSIANN CCS are potentially able to improve flood forecast especially after the process of bias correction. Recommendations for further study include extending the scope of the study from regional to national level, testing the model at finer spatial and temporal resolutions and assessing other bias correction methods.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Journal of Environmental Science International
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• v.20 no.12
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• pp.1541-1551
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• 2011

This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1209-1212
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• 2007

Urban flooding with surcharges in sewer system was investigated because of unexpected torrential storm events these days, causing significant amounts of human and economic damages. Although there are limitations in forecasting and preventing natural disasters, integrated urban flooding management system using the SWMM(Storm Water Management Model) engine and Web technology will be an effective tool in securing safety in operating rubber-tired transportation system. In this study, the study area, located in Chuncheon, Kangwon province, was selected to evaluate the applicability of the SWMM model in forecasting urban flooding due to surcharges in sewer system The catchment are 21.10 ha in size and the average slope is 2% in lower flat areas. Information of subcatchment, conjunctions, and conduits was used as the SWMM interface to model surface runoff generation, water distribution through the sewer system and amount of water overflow. Through this study, the applicability of the SWMM for urban flooding forecasting was investigated and probability distribution of storm events module was developed to facilitate urban flooding prediction with forecasted rainfall amounts. In addition, this result can be used to the establishment of disaster management system for rainfall safety of rubber-tired tram in the future.