• 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 Animal Science and Technology
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• v.65 no.4
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• pp.792-803
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• 2023

This study aimed to assess the impact of weather events on the sorghum-sudangrass hybrid (Sorghum bicolor L.) cultivar production trend in the central inland region of Korea during the monsoon season, using time series analysis. The sorghum-sudangrass production data collected between 1988 and 2013 were compiled along with the production year's weather data. The growing degree days (GDD), accumulated rainfall, and sunshine duration were used to assess their impacts on forage production (kg/ha) trend. Conversely, GDD and accumulated rainfall had positive and negative effects on the trend of forage production, respectively. Meanwhile, weather events such as heavy rainfall and typhoon were also collected based on weather warnings as weather events in the Korean monsoon season. The impact of weather events did not affect forage production, even with the increasing frequency and intensity of heavy rainfall. Therefore, the trend of forage production for the sorghum-sudangrass hybrid was forecasted to slightly increase until 2045. The predicted forage production in 2045 will be 14,926 ± 6,657 kg/ha. It is likely that the damage by heavy rainfall and typhoons can be reduced through more frequent harvest against short-term single damage and a deeper extension of the root system against soil erosion and lodging. Therefore, in an environment that is rapidly changing due to climate change and extreme/abnormal weather, the cultivation of the sorghum-sudangrass hybrid would be advantageous in securing stable and robust forage production. Through this study, we propose the cultivation of sorghum-sudangrass hybrid as one of the alternative summer forage options to achieve stable forage production during the dynamically changing monsoon, in spite of rather lower nutrient value than that of maize (Zea mays L.).

• Journal of Korea Water Resources Association
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• v.51 no.3
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• pp.221-233
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• 2018

Recently, the flood damage by the localized heavy rainfall and typhoon have been frequently occurred due to the climate change. Accurate rainfall forecasting and flood runoff estimates are needed to reduce such damages. However, the uncertainties are involved in guage rainfall, radar rainfall, and the estimated runoff hydrograph from rainfall-runoff models. Therefore, the purpose of this study is to identify the uncertainty of rainfall by generating a probabilistic radar rainfall ensemble and confirm the uncertainties of hydrological models through the analysis of the simulated runoffs from the models. The blending technique is used to estimate a single integrated or an optimal runoff hydrograph by the simulated runoffs from multi rainfall-runoff models. The radar ensemble is underestimated due to the influence of rainfall intensity and topography and the uncertainty of the rainfall ensemble is large. From the study, it will be helpful to estimate and predict the accurate runoff to prepare for the disaster caused by heavy rainfall.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.1
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• pp.76-84
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• 2014

Heavy Rainfall event accompanying with Mesoscale Convective Systems(MCSs) inducing flash flooding and Kimpo and Inchon International Airport closing over Seoul metropolitan area was investigated this study. This heavy rainfall event was occurred through the synoptic scale boundary of North Pacific Subtropical high, Typhoon and also can predicted by proper analysis of various forecasting parameters such as abundant moisture, instabilities, and synoptic/mesoscale forcing.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.2
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• pp.40-47
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• 2014

Heavy Rainfall event accompanying with Mesoscale Convective Systems(MCSs) inducing flash flooding and Muan and Kunsan Airport closing over Jeollabuk-do area was investigated this study. Comparing to previous study(I), this heavy rainfall event was characterized by much abundant moisture from Typhoon, strong conditional convective instability, and cluster type MCSs. It almost impossible to make accurate forecasting of precipitation amounts and life cycle of MCSs unless proper analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.5
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• pp.1129-1136
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• 1994

A point heavy rainfall process is physically modeled. It uses meteorological variables at the ground level as its inputs. The components of the model are parameterized based on well established observations and the previous studies of cloud physics. Particular emphasis is placed on the efficiency of accretion. So we adopt the modified skew-symmetric model for hydrometeor size distribution function that is suitable for the heavy rain cloud. The dominant parameters included in the model are estimated by the optimization technique. The rainfall intensity is predicted by the model with the medium values of estimated parameters.

• Journal of Industrial Technology
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• v.31 no.A
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• pp.87-94
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• 2011

This paper is results of analyzing characteristics of landslides occurred in Wonju, Gangwondo, around July, 16 in 2006, caused by heavy rainfall and antecedent precipitation by two typhoons of Ewiniar and Bilis. The main causes of landslides were antecedent precipitation during July 8 to 15, resulting in weakening grounds by increasing the degree of saturation previously, and the heavy rainfall during July 15 to 16. Most of landslides in natural slopes were transitional failures occurred along the boundary between the residual weathered soil in shallow depth and the hard mother rock. From results of conclusive analyses regarding 28 sites in Wonju region where landslides occurred, the slope length of landslide, the slope width, and the slope area were less than 50m with 71% of frequency, 20m with 79% of frequency and $300m^2$ of 64% of frequency respectively. The average value of slope angle was $35^{\circ}$. The most probable direction of slope was found to be north because of topography and advancing direction of seasonal rain front.

• The Journal of Engineering Geology
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• v.15 no.4 s.42
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• pp.435-445
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• 2005

Landslides induced by heavy rainfall from typhoon 'Rusa' in 2002 and typhoon 'Meami' in 2003 were investigated at Samcheok area, and the relationship between landslides and rainfall on that area was analyzed. The average annual rainfall at Samcheok area is generally $1,200mm\~1,300mm$. However, the average annual rainfall at samcheok for 2003 and ton was increased more than 2,000mm because of typhoon 'Rusa' and typhoon 'Meami'. The number of landslides and the landslides area are largely occurred in a area of the relatively high maximum hourly rainfall and 2days cumulative rainfall. Therefore, it confirmed that landslides are directly depended on the hourly rainfall and the cumulative rainfall. The landslides at Samcheok area induced by heavy rainfall due to typhoon are more influenced by the maximum hourly rainfall at the landslide occurrence day. In order to predict a rational landslide size, a new method included the maximum hourly rainfall and the landslide area in a traditional way was proposed. As the result of applying the new proposed method, the landslide size at Samcheok area is involved in the large scale landslide.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.4
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• pp.526-533
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• 2014

In this study, we introduce design methodology to develop a guidance for issuing heavy rainfall warning by using both RBFNNs(Radial basis function neural networks) and SVR(Support vector regression) model, and then carry out the comparative studies between two pattern classifiers. Individual classifiers are designed as architecture realized with the aid of optimization and pre-processing algorithm. Because the predictive performance of the existing heavy rainfall forecast system is commonly affected from diverse processing techniques of meteorological data, under-sampling method as the pre-processing method of input data is used, and also data discretization and feature extraction method for SVR and FCM clustering and PSO method for RBFNNs are exploited respectively. The observed data, AWS(Automatic weather wtation), supplied from KMA(korea meteorological administration), is used for training and testing of the proposed classifiers. The proposed classifiers offer the related information to issue a heavy rain warning in advance before 1 to 3 hours by using the selected meteorological data and the cumulated precipitation amount accumulated for 1 to 12 hours from AWS data. For performance evaluation of each classifier, ETS(Equitable Threat Score) method is used as standard verification method for predictive ability. Through the comparative studies of two classifiers, neuro-fuzzy method is effectively used for improved performance and to show stable predictive result of guidance to issue heavy rainfall warning.

• Atmosphere
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• v.14 no.1
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• pp.24-43
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• 2004

This paper describes the detailed characteristics of heavy rainfall events occurred in Chungcheong province on 15 and 16 April and from 6 to 8 August 2002 based on the analysis of raingauge rainfall rate and radar reflectivity from the METRI's X-band Weather Radar located in Cheongju. A synoptic analysis of the case is carried out, first, and then the analysis is devoted to seeing how the radar observes the case and how much information we obtain. The highly resolved radar reflectivity of horizontal and vertical resolutions of 1 km and 500 m, respectively shows a three-dimensional structure of the precipitating system, in a similar sequence with the ground rainfall rate. The radar echo classification algorithm for convective/stratiform cloud is applied. In the convectively-classified area, the radar reflectivity pattern shows a fair agreement with that of the surface rainfall rate. This kind of classification using radar reflectivity is considered to be useful for the precipitation forecasting. Another noteworthy aspect of the case includes the effect of topography on the precipitating system, following the analysis of the surface rainfall rate, topography, and precipitating system. The results from this case study offer a unique opportunity of the usefulness of weather radar for better understanding of structural and variable characteristics of flash flood-producing heavy rainfall events, in particular for their improved forecasting.