• Journal of Korean Society for Geospatial Information Science
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• v.18 no.3
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• pp.37-48
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• 2010

The purpose of this paper is to evaluate how the rainfall field effect on a runoff simulation using grid radar rainfall data and ground gauge rainfall. The Gwangdeoksan radar and ground-gauge rainfall data were used to estimate a spatial rainfall field, and a hydrologic model was used to evaluate whether the rainfall fields created by each method reproduced a realistically valid spatial and temporal distribution. Pilot basin in this paper was the Naerin stream located in Inje-gun, Gangwondo, 250m grid scale digital elevation data, land cover maps, and soil maps were used to estimate geological parameters for the hydrologic model. For the rainfall input data, quantitative precipitation estimation(QPE), adjusted radar rainfall, and gauge rainfall was used, and then compared with the observed runoff by inputting it into a $Vflo^{TM}$ model. As a result of the simulation, the quantitative precipitation estimation and the ground rainfall were underestimated when compared to the observed runoff, while the adjusted radar rainfall showed a similar runoff simulation with the actual observed runoff. From these results, we suggested that when weather radars and ground rainfall data are combined, they have a greater hydrological usability as input data for a hydrological model than when just radar rainfall or ground rainfall is used separately.

• Journal of Wetlands Research
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• v.19 no.1
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• pp.112-121
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• 2017

This study proposed the quantitative precipitation estimation method using overlapped area in radar network. For this purpose, the dense rain gauges and radar network are used. As a result, we found a reflectivity bias between two radar located in different area and developed the new quantitative precipitation estimation method using the bias. Estimated radar rainfall from this method showed the apt radar rainfall estimate than the other results from conventional method at overall rainfall field.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.4
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• pp.695-704
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• 2018

The rainfall cases were identified by rainfall estimation techniques which were developed by using X - band marine radar. A digital signal converter was used to convert the signal received from the marine radar into digital reflectivity information. The ground clutter signal was removed and the errors caused by beam attenuation and beam volume changes were corrected. The reflectivity showed a linear relationship with the rain gauge rainfall. Quantitative rainfall was estimated by converting the radar signal into an cartesian coordinate system. When the rainfall was recorded more than $5mm\;hr^{-1}$ at three automatic weather stations, the rain cell distribution on the marine radar was consistent with that of the weather radar operated by Korea meteorological Adminstration.

• Journal of Korea Water Resources Association
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• v.47 no.9
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• pp.801-812
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• 2014

In this study, average rainfall of basin was estimated and compared with that obtained from Biseulsan dual polarization RADAR. And the runoffs are estimated using Vflo distribution model for Habcheon reservoir basin and Huicheon basin. In the rainfall estimation using dual polarization RADAR, the rainfall was estimated by using the specific phase difference and differential reflectivity of dual polarization RADAR variables. As a result, for all events rainfall estimation using dual polarization RADAR has the closest value to the gauge rainfall in terms of the peak rainfall and total rainfall. Also, runoff simulation results from dual polarization RADAR show the better results. It is concluded that the method using dual polarization radar can improve the accuracy more than a single polarization radar using only horizontal reflectivity.

• Journal of Korea Water Resources Association
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• v.38 no.12 s.161
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• pp.1039-1049
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• 2005

The objective of this study is to produce optimal radar-derived rainfall for hydrologic utilization. The ground clutter and beam blockage effects from Mt. Kwanak station (E.L 608m) are removed from radar reflectivities by POD analysis. The reflectivities are used to produce radar rainfall data in the form of rain rates (mm/h) by the application of the Marshall-Palmer reflectivity versus rainfall relationship. However, these radar-derived rainfall are underestimated in temporal and spatial scale compared with observed one, so it is necessary to hire a correction scheme based on the gauge-to-radar (G/R) statistical adjustment technique. The selected watershed for studying the real-time correction of radar-rainfall estimation is the Soyang dam site, which is located approximately 100km east of Kwanak radar station. The results indicate that adjusted radar rainfall with the gauge measurement have reasonal G/R ratio ranged on 0.95-1.32 and less uncertainty with that mean standard deviation of G/R ratio are decreased by $9-28\%$. Mean areal precipitation from adjusted radar rainfall are well agreed to the observed one on the Soyang River watershed. It is concluded that the real-time bias adjustment scheme is useful to estimate accurate basin-based radar rainfall for hydrologic application.

• Proceedings of the Korea Water Resources Association Conference
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• 2003.05a
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• pp.93-100
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• 2003

In order to use radar rainfall data for flood management, it is necessary to study and develop a method for optimum error correction to obtain radar rainfall values that agree closely with surface rainfall data. This paper proposes an optimum estimation method for calculating rainfall in a river basin by using data from surface raingauges and radar raingauge systems. This paper also reports on recent applications of radar raingauge systems for accurate simulation of flood discharge based on river basin rainfall values obtained from radar raingauge systems.

• Atmosphere
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• v.27 no.4
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• pp.467-481
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• 2017

A correction method of reflectivity in partial beam blockage (PBB) area is suggested, which is based on the combination of digital terrain information and self-consistency principle between polarimetric observation. First, the reflectivity was corrected by adding the radar energy loss estimated from beam blockage simulation using digital elevation model (DEM) and beam propagation geometry in standard atmosphere. The additional energy loss by unexpected obstacles and non-standard beam propagation was estimated by using the coefficient between accumulated reflectivity ($Z_H$) and differences of differential phase shift (${\Phi}_{DP}$) along radial direction. The proposed method was applied to operational S-band dual-polarization radar at Jindo and its performance was compared with those of simulation method and self-consistency method for six rainfall cases. When the accumulated reflectivity and increment of ${\Phi}_{DP}$ along radial direction are too small, the self-consistency method has failed to correct the reflectivity while the combined method has corrected the reflectivity bias reasonably. The correction based on beam simulation showed the underestimation. For evaluation of rainfall estimation, the FBs (FRMSEs) of simulation method and self-consistency principle were -0.32 (0.59) and -0.30 (0.57), respectively. The proposed method showed the lowest FB (-0.24) and FRMSE (0.50). The FB and FMSE were improved by about 18% and by 19% in comparison to those before correction (-0.42 and 0.70). We can conclude that the proposed method can improve the accuracy of rainfall estimation in PBB area.

• Journal of Korean Society on Water Environment
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• v.32 no.3
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• pp.310-317
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• 2016

It has been a big problem to estimate rainfall for the studies of mud-debris flows because the estimated rainfall from the nearest AWS (Automatic Weather Station) can tend to be quite inaccurate at individual sites. This study attempts to improve this problem through accurate rainfall depth estimation by applying an artificial neural network with radar rainfall data. For this, three models were made according to utilizing methodologies of rainfall data. The first model uses the nearest rainfall, observing the site from an ungauged site. The second uses only radar rainfall data and the third model integrates the above two models using both radar and observed rainfall at the sites around the ungauged site. This methodology was applied to the metropolitan area in Korea. It appeared as though the third model improved rainfall estimations by the largest margin. Therefore, the proposed methodology can be applied to forecast mud-debris flows in ungageed sites.

• Journal of Korea Water Resources Association
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• v.42 no.8
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• pp.659-671
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• 2009

Fuzzy c-means clustering technique is applied to improve the accuracy of G/R ratio used for rainfall estimation by radar reflectivity. G/R ratio is computed by the ground rainfall records at AWS(Automatic Weather System) sites to the radar estimated rainfall from the reflectivity of Kwangduck Mt. radar station with 100km effective range. G/R ratio is calculated by two methods: the first one uses a single G/R ratio for the entire effective range and the other two different G/R ratio for two regions that is formed by clustering analysis, and absolute relative error and root mean squared error are employed for evaluating the accuracy of radar rainfall estimation from two G/R ratios. As a result, the radar rainfall estimated by two different G/R ratio from clustering analysis is more accurate than that by a single G/R ratio for the entire range.