• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.4
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• pp.19-29
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• 2007

This study compares various ground-truth designs of radar rainfall using rain-gauge data sets from Korea Meteorological Administration (KMA), AWS and Ministry of Construction and Transportation (MOCT). These Rain-gauge data sets and the Mt. Gwanak radar rainfall data for the same period were compared, and then the differences between two observed rainfall were evaluated with respect to the amount of bias. Additionally this study investigated possible differences in bias due to different storm characteristics. The application results showed no distinct differences between biases from three rain-gauge data sets, but some differences in their statistical characteristics. In overall, the design bias from MOCT was estimated to be the smallest among the three rain-gauge data sets. Among three storm events considered, the jangma with the highest spatial intermittency showed the smallest bias.

• 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.

• Journal of Korea Water Resources Association
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• v.34 no.5
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• pp.415-426
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• 2001

After Disaster Impact Assessment(DIA) Program was particed, the wide variety of hydrological data are estimated by introducing the concept of critical storm duration to calculate the stormwater impoundments as the alternative of increasing runoff due to many developments. Critical storm duration is varied by a lot of hydraulic structures, drainage characteristics, temporal distribution of design rainfall, return period, and runoff models. In this study the methods of estimating the proper volume to design the stormwater impoundments are proposed to determine the required volume by comparing and analyzing the maximum stormwater impoundments in accordance with the impoundment volume and rainfall duration by using the concept of storage ratio presented in the existing studies. The methods of determining the critical storm duration of design rainfall which cause the maximum load from the runoff hydrograph will be studied as analyzing rainfall-runoff using the various runoff models and observed data.

• Journal of the Korean Society of Hazard Mitigation
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• v.4 no.3 s.14
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• pp.33-41
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• 2004

The purpose of this study is to analyze the relationship between El Nino phenomena and the monthly rainfall variations of Seoul city which is composed of 30 year data during $1967{\sim}1996$. In this study, the monthly rainfall data at Seoul city is analyzed by applying an intervention model. As it is unavailable to get the data of El Nino phenomena, the point of intervention have been decided from the literature survey of the data observed to be the years of 1972, 1976, 1979, 1982, 1986 and 1991. As a results the El Nino was revealed more significant to the monthly rainfall at Seoul. In addition, monthly rainfall varied between the maximum 53.41mm and the minimum 2.50mm. To prevented future natural disaster, long term water planning and management is requied in consideration El $Nin\tilde{o}$.

• Journal of Korean Society on Water Environment
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• v.30 no.2
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• pp.212-219
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• 2014

In this study, a land pollutant load calculation method in TMDLs was improved to consider climate change scenarios. In order to evaluate the new method, future change in rainfall patterns was predicted by using SRES A1B climate change scenarios and then post-processing methods such as change factor (CF) and quantile mapping (QM) were applied to correct the bias between the predicted and the observed rainfall patterns. Also, future land pollutant loads were estimated by using both the bias corrected rainfall patterns and the enhanced method. For the results of bias correction, both methods (CF and QM) predicted the temporal trend of the past rainfall patterns and QM method showed future daily average precipitation in the range of 1.1~7.5 mm and CF showed it in the range of 1.3~6.8 mm from 2014 to 2100. Also, in the result of the estimation of future land pollutant loads using the enhanced method (2020, 2040, 2100), TN loads were in the range of 4316.6~6138.6 kg/day and TP loads were in the range of 457.0~716.5 kg/day. However, each result of TN and TP loads in 2020, 2040, 2100 was the same with the original method. The enhanced method in this study will be useful to predict land pollutant loads under the influence of climate change because it can reflect future change in rainfall patterns. Also, it is expected that the results of this study are used as a base data of TMDLs in case of applying for climate change scenarios.

• Atmosphere
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• v.22 no.4
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• pp.387-400
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• 2012

This study aims at examining the sensitivity of numerical simulations to the resolution of initial and boundary data, and to an application of WRF (Weather Research and Forecasting) 3DVAR (Three Dimension Variational data Assimilation). To do this, we ran the WRF model by using GDAS (Global Data Assimilation System) FNL (Final analyses) and the KLAPS (Korea Local Analysis and Prediction System) analyses as the WRF's initial and boundary data, and by using an initial field made by assimilating the radar data to the KLAPS analyses. For the sensitivity experiment, we selected a heavy rainfall case of 21 September 2010, where there was localized torrential rain, which was recorded as 259.5 mm precipitation in a day at Seoul. The result of the simulation using the FNL as initial and boundary data (FNL exp) showed that the localized heavy rainfall area was not accurately simulated and that the simulated amount of precipitation was about 4% of the observed accumulated precipitation. That of the simulation using KLAPS analyses as initial and boundary data (KLAPC exp) showed that the localized heavy rainfall area was simulated on the northern area of Seoul-Gyeonggi area, which renders rather difference in location, and that the simulated amount was underestimated as about 6.4% of the precipitation. Finally, that of the simulation using an initial field made by assimilating the radar data to the KLAPS using 3DVAR system (KLAP3D exp) showed that the localized heavy rainfall area was located properly on Seoul-Gyeonggi area, but still the amount itself was underestimated as about 29% of the precipitation. Even though KLAP3D exp still showed an underestimation in the precipitation, it showed the best result among them. Even if it is difficult to generalize the effect of data assimilation by one case, this study showed that the radar data assimilation can somewhat improve the accuracy of the simulated precipitation.

• Journal of Korea Water Resources Association
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• v.38 no.11
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• pp.963-972
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• 2005

This study searched the criterion of AMC with respect to the rainfall amount for the periods of antecedent 5 to 2 days. This criterion was decided as the rainfall amount with which the frequency of the observed CN(I) and CN(III) events being categorized as the true CN(I) and CW(III) become highest. Among four cases considered, the cases with antecedent 4 and 5 days provided a reasonable results, but the others not due to limited rainfall events available. For both cases with antecedent 4 and 5 days, the frequency of AMC-II increases, but that of AMC-III decreases significantly to become a more reasonable distribution. Among the cases with antecedent 4 and S days, the latter seems to be better as the occurrence of AMC-II and the relative frequency of CN(I) are higher. If adopting the rainfall amount of antecedent 5 days for the AMC, the criteria for AMC-I and AMC-III for the Jangpyung subbasin becomes 22 mm and 117 mm, respectively.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.281-289
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• 2019

In this study, the typhoon damage forecasting model was developed for southern inland district. The typhoon damage in the inland district is caused by heavy rain and strong winds, variables are many and varied, but the damage data of the inland district are not enough to develop the model. The hydrological data related to the typhoon damage were hour maximum rainfall amount which is accumulated 3 hour interval, the total rainfall amount, the 1-5 day anticipated rainfall amount, the maximum wind speed and the typhoon center pressure at latitude 33° near the Jeju island. The Multivariate Analysis such as cluster Analysis considering the lack of damage data and principal component analysis removing multi-collinearity of rainfall data are adopted for the damage forecasting model. As a result of applying the developed model, typhoon damage estimated and observed values were up to 2.2 times. this is caused it is difficult to estimate the damage caused by strong winds and it is assumed that the local rainfall characteristics are not considered properly measured by 69 ASOS.

• Korean Journal of Environmental Biology
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• v.23 no.1
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• pp.57-63
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• 2005

The phytoplankton community, environmental factors, and rainfall were investigated from July to October in 2001 and 2003 on Dam site in Daechung Reservoir. The monthly average rainfall in the investigated period were 91.3 and 265.3 mm in 2001 and 2003, respectively. The maximum chlorophyll a concentration was observed higher at 131.5 ㎍ L/sup -1/ in 2003 than at 45.4 ㎍ L/sup -1/ in 2001. The cyanobacterial number in 2001 was counted up to over 200,000 cells mL/sup -1/, which was much higher than the maximum number of 49,000 cells mL/sup -1/ in 2003. The relative abundance of cyanobacteria in the phytoplankton community was about 97% in 2001 and 74% in 2003. Microcystis spp. were absolutely dominant species in 2001, while a couple of cyanobacteria such as Oscillatoria spp., Phormidium spp. Chroococcus spp. and Microcystis spp. were dominant species in 2003. Consequently, it seemed that rainfall affected the diversity of phytoplankton species and decreased the density of bloom-forming cyanobacteria.

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.735-743
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• 2017

With growing concerns about ever-increasing anthropogenic greenhouse gas emissions, it is crucial to enhance preparedness for unprecedented extreme weathers that can bring catastrophic consequences. In this study, we proposed a stochastic framework that considers uncertainty in weather forecasts for flood analyses. First, we calibrated a simple rainfall-runoff model against observed hourly hydrographs. Then, using probability density functions of rainfall depths conditioned by 6-hourly weather forecasts, we generated many stochastic rainfall depths for upcoming 48 hours. We disaggregated the stochastic 6-hour rainfalls into an hourly scale, and input them into the runoff model to quantify a probabilistic range of runoff during upcoming 48 hours. Under this framework, we assessed two rainfall events occurred in Bocheong River Basin, South Korea in 2017. It is indicated actual flood events could be greater than expectations from weather forecasts in some cases; however, the probabilistic runoff range could be intuitive information for managing flood risks before events. This study suggests combining deterministic and stochastic methods for forecast-based flood analyses to consider uncertainty in weather forecasts.