• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.157-157
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• 2019

This study derived the Flood-Inducing-Rainfall (FIR) and the Flood-Inducing-Runoff (FIRO) from the radar-gage composite data to be used as the basis of the flood warning initiation for the urban area of Seoul. For this, we derived the rainfall depth-duration relationship for the 261 flood events at 239 watersheds during the years 2010 and 2011 based on the 10-minute 1km-1km radar-gauge composite rainfall field. The relationship was further refined by the discrete ranges of the proportion of the flooded area in the watershed (FP) and the coefficient variation of the rainfall time series (CV). Then, the slope of the straight line that contains all data points in the depth-duration relationship plot was determined as the FIR for the specified range of the FP and the CV. Similar methodology was applied to derive the FIRO, which used the runoff depths that were estimated using the NRCS Curve Number method. We found that FIR and FIRO vary at the range of 37mm/hr-63mm/hr and the range of 10mm/hr-42mm/hr, respectively. The large variability was well explained by the FP and the CV: As the FP increases, FIR and FIRO increased too, suggesting that the greater rainfall causes larger flooded area; as the rainfall CV increases, FIR and FIRO decreased, which suggests that the temporally concentrated rainfall requires less total of rainfall to cause the flood in the area. We verified our result against the 21 flood events that occurred for the period of 2012 through 2015 for the same study area. When the 5 percent of the flooded area was tolerated, the ratio of hit-and-miss of the warning system based on the rainfall was 44.2 percent and 9.5 percent, respectively. The ratio of hit-and-miss of the warning system based on the runoff was 67 percent and 4.7 percent, respectively. Lastly, we showed the importance of considering the radar-gauge composite rainfall data as well as rainfall and runoff temporal variability in flood warning system by comparing our results to the ones based on the gauge-only or radar-only rainfall data and to the one that does not account for the temporal variability.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.253-256
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• 1996

Rainfall is one of the major and complicated elements of hydrologic system. Accurate prediction of rainfall is very important to mitigate storm damage. The neural network is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. In this dissertation, rainfall predictions by the neural network theory were presented. A multi-layer neural network was constructed. The network learned continuous-valued input and output data. The network was used to predict rainfall. The online, multivariate, short term rainfall prediction is possible by means of the developed model. A multidimensional rainfall generation model is applied to Seoul metropolitan area in order to generate the 10-minute rainfall. Application of neural network to the generated rainfall shows good prediction. Also application of neural network to 1-hour real data in Seoul metropolitan area shows slightly good predictions.

• Journal of Korea Water Resources Association
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• v.37 no.5
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• pp.425-435
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• 2004

Mainly, observed maximum rainfall has been evaluated by point rainfall, but actually it should be considered by means of average areal rainfall. Average areal rainfall is an estimated value computed through DAD(rainfall Depth-Area-Duration) analysis. By using this value, an average and maximum areal rainfall according to area-duration relationship could be computed. In this study, we assume that the whole Korea region is hydrologically homogeneous, and then analyze using the storm-centered DAD(moving-area DAD) method for the past century data. From this analysis, we evaluate the yearly variation of observed maximum areal rainfall through area-duration relationship. And we also construct an IDF(rainfall Intensity-Duration-Frequency) curve by using the annual time series data which is composed of maximum areal rainfall. The characteristics of IDF and observed maximum areal rainfall is also evaluated.

• Magazine of the Korean Society of Agricultural Engineers
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• v.24 no.1
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• pp.63-72
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• 1982

To maintain an optimum condition for the plant growth on upland soil, the irrigation planning after the natural rainfall should be given enormous considerations on the rainfall effectiveness. This study has been intended to develop the computer model for estimating the effec- tiveness of the rainfall. The computer model should also estimated the infiltration due to the rainfall and the soil moisture deficiency at the root zone of the plant. For this purpose, the experiments of infiltration using rainfall simulator and the observations of the change of soil moisture content before and after rainfall were carried out. Needed input data for the developed model include final infiltration capacity and field capacity of the soil, porosity of the top soil, root depth of the plant, rainfall intensity and duration, and the Horton's decay coefficient. Among the needed input data for the developed model, final infiltration capacity and Horton's decay coefficient were determined by the experiments of infiltration. And from the result of the experiments, it is found that there is a great correlation between initial infiltration capacity and initial moisture content. And it is also found that the infiltration due to rainfall can be estimated with the Horton's equation. The developed model was tested by the experimental data with two rainfall intensities. Tests were conducted on the different root depths at each rainfall. Observed and estimated effective rainfalls were found to have great correlation. The result of the experiments showed that the effectiveness of the rainfall were 100%, so the comparisons were conducted by the comsumption rates of infiltration at each depth. The developed model can be also used for estimating the deficiency of rainfall, if the rainfall is not sufficient to the needed soil moisture. But, test was not carried out.

• Journal of Wetlands Research
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• v.13 no.2
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• pp.189-197
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• 2011

This paper reviewed application of data-driven method, distance-weighted method(IDWM, IEWM, CCWM, ANN), and radar data method estimated of missing raifall data. To evaluate these methods, statistics was compared using radar and station rainfall data from Imjin-river basin. The range of RMSE values calculated for CCWM, ANN was 1.4 to 1.79mm, and the range of RMSE values estimated data used for radar rainfall data was 0.05 to 2.26mm. Spatial characteristics is considered to Radar rainfall data rather than station rainfall data. Result suggest that estimated data used for radar data can impove estimation of missing raifall data.

• Journal of Korea Water Resources Association
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• v.36 no.2
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• pp.237-249
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• 2003

Wind effects on a rain gauge can cause a significant underestimation of rainfall depths and contribute to the inconsistency in rainfall data. To revise the rainfall data requires the study about calculation of deficiency percentages of rain catch. There are few studies which reflect the variation of wind speed. in this study, the raindrop terminal velocity is quantified according to the particle size of rainfall. The model for calculating deficiency percentages of rain catch according to the particle size of rainfall is examined by experimentation. Experimentation shows that deficiency percentages of rain catch have no relationship with rainfall intensity and affected by raindrop diameter. In conclusion, the estimated deficiency percentages of rain catch coincided with the experimental results and can be used as recommended adjustment factors.

• Journal of Wetlands Research
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• v.12 no.1
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• pp.51-61
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• 2010

Changes in climate have largely increased concentrated heavy rainfall, which in turn is causing enormous damages to humans and properties. Therefore, it is important to understand the spatial-temporal features of rainfall. In this study, RADAR rainfall was used to calculate gridded areal rainfall which reflects the spatial-temporal variability. In addition, Kalman-filter method, a stochastical technique, was used to combine ground rainfall network with RADAR rainfall network to calculate areal rainfall. Thiessen polygon method, Inverse distance weighting method, and Kriging method were used for calculating areal rainfall, and the calculated data was compared with adjusted areal RADAR rainfall measured using the Kalman-filter method. The result showed that RADAR rainfall adjusted with Kalman-filter method well-reproduced the distribution of raw RADAR rainfall which has a similar spatial distribution as the actual rainfall distribution. The adjusted RADAR rainfall also showed a similar rainfall volume as the volume shown in rain gauge data. Anseong-Cheon basin was used as a study area and the RADAR rainfall adjusted with Kalman-filter method was applied in $Vflo^{TM}$ model, a physical-based distributed model, and ModClark model, a semi-distributed model. As a result, $Vflo^{TM}$ model simulated peak time and peak value similar to that of observed hydrograph. ModClark model showed good results for total runoff volume. However, for verifying the parameter, $Vflo^{TM}$ model showed better reproduction of observed hydrograph than ModClark model. These results confirmed that flood runoff simulation is applicable in domestic settings(in South Korea) if highly accurate areal rainfall is calculated by combining gauge rainfall and RADAR rainfall data and the simulation is performed in link to the distributed hydrological model.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.233-240
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• 2004

Most of hydrological analyses in the field of water resources are launched by gathering and analyzing rainfall data. Several methods have been developed to estimate areal rainfall from point rainfall data and to fill missing or ungaged data. Thiessen and Reciprocal Distance Squared(RDS) methods whose parameters are only dependent on inter-station distance are classical work in hydrology, but these techniques do not provide a continuous representation of the hydrologic process involved. In this study, kriging technique was applied to rainfall analysis in Nakdong river basin in order to complement the defects of these classical methods and to reflect spatial characteristics of regional rainfall. After spatial correlation and semi-variogram analyses were performed to perceive regional rainfall property, kriging analysis was performed to interpolate rainfall data for each grid Thus, these procedures were enable to estimate average rainfall of subbasins. In addition, poor region of rainfall observation was analyzed by spatial interpolation error for each grid and mean error for each subbasin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.35 no.2
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• pp.319-326
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• 2015

Rainfall data is necessary component for water resources design and flood warning system. Most analysis are used long-term hourly data of surface synoptic stations from the Meteorological Administration, Ministry of land, Infrastructure and Transport and others. However, It will be used minutely data of more high density automatic weather stations than surface synoptic stations expecting to increase the frequency of heavy precipitation. But minutely data has a problem about quality of rainfall data by auto observation. This study analyzed about quality control method using automatic weather station's minutely rainfall data of meteorological administration. It was performed assessment of the quality control that was classified quality control of miss Data, outlier data and rainfall interpolation. This method will be utilized when hydrological analysis uses minute rainfall data.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.6
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• pp.113-120
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• 2008

This study analyzed the spatial correlograms of minutely rainfall data with respect to various accumulation times. A bivariate mixed lognormal distribution was applied for rainfall modelling. A total of 26 minutely rainfall data sets from rain gauge stations in the central part of Korean peninsula were analyzed, also repeated for several storm types like Jang-Ma, typhoon and convective storms for their comparison. The accumulation times 1, 2, 3, 5, 10, 30 and 60 minutes were considered in this study. As results, it was found that the minutely rainfall data available was not good enough for estimating minutely rainfall intensity at ungaged locations. It seems more practical to use the hourly rainfall data with much higher rain gauge density, if proper methods for interpolation and data dis-aggregation are provided.