• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.275-275
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• 2021

A fixed Z-R relationship approach, such as the Marshall-Palmer relationship, for an entire year and for different seasons can be problematic in cases where the relationship varies spatially and temporally throughout a region. From this perspective, this study explores the use of long-term radar reflectivity for South Korea to obtain a nationwide calibrated Z-R relationship and the associated uncertainties within a Bayesian regression framework. This study also investigates seasonal differences in the Z-R relationship and their roles in reducing systematic error. Distinct differences in the Z-R parameters in space are identified, and more importantly, an inverse relationship between the parameters is clearly identified with distinct regimes based on the seasons. A spatially structured pattern in the parameters exists, particularly parameter α for the wet season and parameter β for the dry season. A pronounced region of high values during the wet and dry seasons may be partially associated with storm movements in that season. Finally, the radar rainfall estimates through the calibrated Z-R relationship are compared with the existing Z-R relationships for estimating stratiform rainfall and convective rainfall. Overall, the radar rainfall fields based on the proposed modeling procedure are similar to the observed rainfall fields, whereas the radar rainfall fields obtained from the existing Marshall-Palmer Z-R relationship show a systematic underestimation. The obtained Z-R relationships are validated by testing the predictions on unseen radar-gauge pairs in the year 2018, in the context of cross-validation. The cross-validation results are largely similar to those in the calibration process, suggesting that the derived Z-R relationships fit the radar-gauge pairs reasonably well.

• Journal of The Korean Society of Agricultural Engineers
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• v.48 no.5
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• pp.3-15
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• 2006

The purpose of the study is to determine grid cell of radar relationship, and to promote the radar data on hydrology field. The study region is the Chungjudam basin with a drainage area of $6,648km^{2}$ located within the 260 km circle under the DWSR-88C C-band umbrella(Kwanak Mt Radar). Grid cell was produced to extract radar reflectivity and rainfall data of the same time and point using Arc-view software package. The grid cell size is to estimate mean correlation coefficient for $1km{\times}1km,\;2km{\times}2km,\;3km{\times}3km$ grid. The result of mean correlation coefficient showed good result(0.57) for the $1km{\times}1km$ grid cell. The 32 rainfall stations Z-R relationship was estimated in Chungjudam basin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1B
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• pp.7-14
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• 2006

The radar relationship was estimated for the selected rainfall event at Yeongchun station within Chungjudam basin where the discharge record was the range of from 1,000 CMS to 9,000 CMS. By calibrating the rainfall coefficient parameter estimated by radar relationship in small hydrology basin, rainfall with the topography properties was calculated. Three different rainfall estimation methods were compared:(1) radar relationship method (2) Thiessen method (3) Isohyetal method (4) Inverse distance method. Basin model was built by applying HEC-GeoHMS which uses digital elevation model to extract hydrological characteristic and generate river network. The proposed basin model was used as an input to HEC-HMS to build a runoff model. The runoff estimation model applying radar data showed the good result. It is proposed that the radar data would produce more rapid and accurate runoff forecasting especially in the case of the partially concentrated rainfall due to the atmospheric change. The proposed radar relationship could efficiently estimate the rainfall on the study area(Chungjudam basin).

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.813-826
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• 2018

Recently, weather radar system has been widely used for effectively monitoring near real-time weather conditions. The radar rainfall estimates are generally relies on the Z-R equation that is an indirect approximation of the empirical relationship. In this regards, the bias in the radar rainfall estimates can be affected by spatial-temporal variations in the radar profile. This study evaluates the uncertainty of the Z-R relationship while considering the rainfall types in the process of estimating the parameters of the Z-R equation in the context of stochastic approach. The radar rainfall estimates based on the Bayesian inference technique appears to be effective in terms of reduction in bias for a given season. The derived Z-R equation using Bayesian model enables us to better represent the hydrological process in the rainfall-runoff model and provide a more reliable forecast.

• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.41-45
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• 2006

A disdrometer has been used to determine Z-R relationships for the weather radar, which is unique coastal radar operating regularly in western tropical south Atlantic. Rainfall rates were divided into the stratiform rain and the convective rain on the basis of $10\;mm\;h^{-1}$. The Z-R relationship for the stratiform class was similar to the general one since the convective clouds did not developed and two classes of the rain rate were mixed.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.789-792
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• 2004

This study aims to detect only voids and estimate the cross-sectional size and thickness of voids using radar. A new method based on radar image processing is carried out with various void sizes and depths. The regression relationship between void size which has different depth and the amplitude characteristics of the radar return is considered in a new method of this research. For the purpose of examining; this regression relationship, experiments with change of void depth, surface area and thickness were carried out. Finally, the threshold value for image processing which aims to represent only voids to be fitted size (width) can be obtained. As the results, a proposed method in this study has a possibility of detecting only voids and estimating void size and thickness with good accuracy.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.332-335
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• 2008

Newly developing SAR (Synthetic Aperture Radar) sensors commonly include high resolution X-band those data are expected to contribute various applications. Recent few studies are presenting potential of X-band SAR data in forest related application. This study tried to investigate the relationship between forest stand parameters and multi-band SAR normalized backscattering. Multi-band SAR data was radiometric corrected to compare signal from different forest stand condition. Then correlation coefficients were estimated between attribute of forest stand map and normalized backscattering coefficients. Although overall correlation coefficients are not high, only X-band shows strong relationship with DBH class than other bands. The signal of C- and L-band is composed of a large number of discrete tree components such as leaves, stems, even background soil. In forest, strength of radar backscattering is affected by complex parameters. Further study might be considered more various forest stand parameters such as canopy density, stand height, volume, and biomass.

• Journal of the Korean earth science society
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• v.33 no.7
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• pp.596-607
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• 2012

The R-Z relationship is one of important error factors to determine the accuracy of radar rainfall estimation. In this study, we have explored the effect of the R-Z relationships derived from disdrometer data in estimating the radar rainfall. The heavy rain event that produced flooding in St-Remi, Quebec, Canada has been occurred. We have tried to investigate the severity of rain for this event using high temporal (2.5 min) and spatial resolution ($1^{\circ}$ by 250 m) radar data obtained from the McGill S-band radar. Radar data revealed that the heavy rain cells pass directly over St-Remi while the coarse raingauge network was not sufficient to detect this rain event. The maximum 30 min (1 h) accumulation reaches about 39 (42) mm in St-Remi. During the rain event, the two disdrometers (POSS; Precipitation Occurrence Sensor System) were available: One used for the reflectivity calibration by comparing disdrometer Z and radar Z and the other for deriving disdrometric R-Z relationships. The result shows the significant improvement with the disdrometric reflectivity-dependent R-Z relationships against the climatological R-Z relationship. The bias in radar rain estimation is reduced from +12% to -2% and the root-mean squared error from 16 to 10% for daily accumulation. Using the estimated radar rainfall rate with disdrometric R-Z relationships, the flood event was well captured with proper timing and amount.

• 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.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.589-601
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• 2019

Various applications of radar rainfall data have been actively employed in the field of hydro-meteorology. Since radar rainfall is estimated by using predefined reflectivity-rainfall intensity relationships, they may not have sufficient reproducibility of observations. In this study, a generalized linear model is introduced to better capture the Z-R relationship in the context of bias correction within a Bayesian regression framework. The bias-corrected radar rainfall with the generalized linear model is more accurate than the widely used mean field bias correction method. In addition, we analyzed variability of the bias correction parameters under various geomorphological conditions such as the height of the weather station and the separation distance from the radar. The identified relationship is finally used to derive a regionalized formula which can provide bias correction factors over the entire watershed. It can be concluded that the bias correction parameters and regionalized method obtained from this study could be useful in the field of radar hydrology.