Kyoung-Jun Kim

Sampling Error of Areal Average Rainfall due to Radar Partial Coverage

Areal average rainfall is important as it is used as an input for most rainfall-runoff analysis in Hydrology and Water Resources. Different from traditional methods of using rain gauge data, the use of radar rainfall for the estimation of areal average rainfall is very straightforward. However, in some cases with severe terrain blockages, the value of the incomplete radar information is of serious concern. This study investigated this problem and derived an equation for estimating the error involved in the areal average rainfall due to partial radar coverage of a basin or sub-basin. When only partial radar information is available, the sampling error decreases with increasing radar coverage and the number of radar bin clusters. As an application example, this study considered the Han River Basin with its rainfall observations using the Ganghwa rain radar. Among a total of 24 mid-sized sub-basins in the Han River Basin evaluated, only five sub-basins were fully covered by the radar and three were totally uncovered. The remaining 16 sub-basins were covered partially by radar leading to incomplete radar information. The results show that the sampling error ranged from several % to tens % of standard deviation of the areal average rainfall depending on the relative areal radar coverage.

Synthesis of Radar Measurements and Ground Measurements using the Successive Correction Method(SCM)

This study investigated the application of the successive correction method(SCM), a simple data assimilation method, for synthesizing the radar and rain gauge data. First, the number of iteration and influence radius for the SCM application were decided based on their sensitivity analysis. Also, for the evaluation of synthetic rainfall, the distributed rainfall field using the dense rainfall gauge network was assumed to be the true one. The synthetic rainfall field based on the SCM was also compared quantitatively with the one based on the co-Kriging frequently used nowadays. As the results, the SCM, a simple and economical data assimilation method, was found to secure the accuracy and statistical characteristics of the co-Kriging application.

On Ground-Truth Designs of Radar Rainfall Using Rain Gauge Rainfall

This study theoretically compared three possible methods for the ground-truth, that is three ground-truth designs of radar rainfall using the rain gauge rainfall. Theoretical results derived are first applied to the rainfall field generated by the Waymire-Gupta-Rodriguez Iturbe(WGR) model, and then to the Mt. Gwanak radar data using the rain gauge data from MOCT within the radar range of observation. Overall application results were found to be similar to those from theoretical studies, also those from the application to the WGR rainfall field. In conclusion, the ground-truth design using only positive(+) rainfalls from both radar and rain gauges causes serious design bias to be inappropriate as a ground-truth design.

Decision of minimum rain gauge density in a combined radar-rain gauge rainfall observation system: a case study of the Imjin River Basin, Korea

This study reviews combined rainfall observation using both radar and rain gauges. Sampling error theory is introduced and applied to an evaluation of the rain gauge network of the upstream region of the Imjin River Basin in North Korea. Under the assumption that the Ganghwa Radar is properly calibrated, an additional 13 rain gauges (including the eight that are currently in operation) is deemed sufficient to secure the quality of rainfall observation with 37 rain gauges without radar.

Effect of Zero Measurements on the Spatial Correlation Structure of Rainfall

In this study, the effect of zero measurements on the spatial correlation function of rainfall is analyzed for the quantification of a rainfall field. The use of a bivariate mixed distribution function made it possible to analyze and compare the spatial correlation functions for these three different data sets: only the positive measurements at both gauge locations, positive measurements at either one or both gauge locations, and all measurements including zero at both locations. As an example, the spatial correlation functions are derived for the Geum River Basin, Korea and evaluated for the wet and dry seasons, respectively. Results show that the effect of zero measurements on spatial correlation structures is significant during the wet season, when the inter-station correlations were estimated significantly lower than those during the dry season. It was also found that only the case considering positive measurements are valid for the quantification of rainfall field. Even during the wet season, the inter-station correlation coefficients derived by considering the zero measurements show their high variability along with many abnormally looking high estimates, which made the quantification of the spatial correlation function become very ambiguous.

Analysis on Characteristics of Orographic Effect about the Rainfall Using Radar Data: A Case Study on Chungju Dam Basin

This study analyzed the characteristics of orographic effect using radar data for the Chungju dam basin. First, independent rainfall events were selected by applying the IETD (Interevent Time Definition) and rainfall threshold. Among those independent rainfall events, rather strong events were selected to decide the occurrence condition of orographic effect. Also, the average reflectivity was calculated for the entire period and for the period of storm center, and the change in reflectivity was analyzed by comparing the average reflectivity to that in the mountain area. Important rainfall factors were selected and applied to the logistic regression model to decide the occurrence condition of orographic effect. Summarizing the results is as follows. First, evaluation of the radar data along the passing line of a storm showed the increase of radar reflectivity in the mountain area. Second, the result of logistic regression analysis showed that the orographic effect in the Chungju Dam Basin mostly occurred when the rainfall intensity was higher than 4 mm/hr, the storm velocity was lower than 4 km/hr, and the approach angle was .

Analysis of Flood Runoff Characteristics due to Rainfall Pattern Change: Comparison of Applications to Small and Medium Size Basins

본 연구에서는 강우의 특성변화가 유출 특성에 미치는 영향을 파악하기 위하여 구형펄스모형으로 모의시킨 강우를 선형저수지 모형과 Nash 모형에 유출모의하여 그 유출량에 대한 확률밀도함수와 강우의 확률 밀도함수를 비교하였다. 이를 통해 강우의 발생빈도, 강우강도, 지속시간이 유출에 어떻게 기여하는지에 대하여 파악하였다. 소규모 유역과 중규모 유역에 대한 영향을 분석하기 위하여 두 개의 대상유역을 선정하였다. 그 결과 강우의 발생빈도, 강우강도, 지속시간의 변화에 대하여 유출량이 다양한 특성을 보이는 것을 확인 할 수 있었으며, 이는 향후 기후변화에 대한 영향을 평가하는데 적용될 수 있을 것이라 판단된다. 【In this study, the probability density functions (PDFs) of the rainfall generated by PRPM(Poisson Rectangular Pulse Model) and the runoff simulated by SLRM(Single Linear Reservoir Model) and Nash model, were compared to find out the changes of runoff characteristics due to the change of rainfall characteristics. Effect of rainfall frequency, Intensity, and duration on runoff were evaluated using the PDFs derived. Two basin, small and midium-sized ones, were also selected to find out the effect of basin size. As the results, we found that the arrival time, the intensity, and the duration of rainfall differently influence the runoff characteristics, which could be applied to evaluate the effect of climate change.】