• Journal of Korea Water Resources Association
• /
• v.39 no.4 s.165
• /
• pp.347-362
• /
• 2006

In this study, a 2-D flood inundation model was developed to evaluate the impact of levee failure in a natural basin for flood analysis. The model was applied to analyze the inundation flow from the levee break of Gamcheon river during the typhoon Rusa on October 31 through September 1, 2002. To verify the simulated results, wide range field surveys have been performed including the collection of NGIS database, land use condition, flooded area, and flow depths. Velocity distributions and inundation depths were presented to demonstrate the robustness of the model. Model results have good agreements with the observed data in terms of flood level and flooded area. The model is able to compute maximum stage and peak discharge efficiently in channel and protected lowland. Methodology considering radar-rainfall estimation using cokriging scheme, flood-runoff and inundation analysis in this study will contribute to the establishment of the national integrated flood disaster prevention system and the river or protect lowland management system.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.201-203
• /
• 2004

We present here, some of the studies carried for estimation of rainfall over land and oceanic regions in and around South Korea. We use active and passive microwave measurements from TRMM - TMI and Precipitation Radar (PR) respectively during a typhoon even named - RUSA that took place during 30 Aug. 2002. We have followed due approach by Yao at. all (2002) and examined the performance of their algorithm using two main predictor variable, named as Scattering Index (SI) and Polarization Corrected Brightness Temperature (PCT) while using TMI data. The rainfall rate estimated using PCT and SI shows some under-estimation as compared to the AWS rainfall products from the PR in common area of overlap. A larger database thus would be used in future. To establish a new rain rate algorithm over Korean region based on the present case study.

• Journal of the Korean earth science society
• /
• v.33 no.7
• /
• pp.569-582
• /
• 2012

The heavy rainfalls caused large property damages and human casualties. For example, Changma caused 0.25 billion dollars in damages and 57 deaths and 112 missing by accompanying the torrentially convective heavy rainfall in Seoul, 2011. In addition, TY15 (Bolaven) caused a small damage by bringing a relatively small amount of rainfall and strong wind in Gwanju, 2012. The investigation and analyses of these mesoscale processes of rainfall events for different physical properties using KLAPS for weather environments of the above cases were performed. These typical and ideal meoscale systems by better and more favorable cloud systems were chosen to retrieve rain intensity from Radar and Chullian data. The quantitative rain intensities of Radar and Chullian differ greatly from the ground-based gauge values with underestimating over 50 mm/hr at the peak time of hourly maximum rain intensity about over than 85 mm/hr. However, the Radar rain intensity demonstrated approximately lower than 35 mm/hr, and the Chullian rain intensity less than 60 mm/hr for Changma in Seoul, 2011. For typhoon (TY15, Bolaven) in Gwangju, similarly, the quantitative rain intensities of Radar and Chullian differ from the ground-based gauge values. At the peak time, the hourly maximum rain intensity of ground-based gauge was more than 15 mm/hr. However, the Radar rain intensity showed lower than 5 mm/hr, and the Chullian rain intensity lower than 10 mm/hr. Regarding the above two cases of typhoon and Changma, even though Radar and Chullian rain intensities have been underestimated when compared to the ground-based rain intensity, the distributions of time scale features of both Radar and Chullian rain intensities still delineated a similar tendency of rain intensity distribution of the ground-based gauge data.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.5B
• /
• pp.429-435
• /
• 2010

This study proposed a methodology for evaluating the radar rainfall data, whose basic idea is similar to the analysis of variance in statistics. This method enables us to represent separately the error from the bias and that from the data variability. The proposed method was then applied to two storm events for its evaluation. As results, the error from the bias was found to comprises most of the raw radar data error, which becomes significantly decreased in the quality improved cases. On the other hand, the error from the data variability was rather increased due to the quality improvement procedure. The proposed methodology was found to be effective for evaluating the data quality of a storm event for steps of quality improvement, but has a limitation for comparing qualities of storm events. This limitation should be implemented for its general application.

• Journal of Digital Convergence
• /
• v.18 no.4
• /
• pp.221-228
• /
• 2020

As industrial technology advances, convenience is also being developed. Many people living in big cities are commuting using transportation such as buses, taxis, cars, etc. and enjoy leisure, so research is needed to reduce the damages caused by traffic accidents. This study deals with estimating road-level rainfall in real-time. A rainfall observation data and radar data provided by the Korea meteorological administration were collected in real-time to create an integrated database, which was estimated as road-level rainfall by universal kriging method. Besides, we conducted a study to interactively visualization of mash-up road traffic information in real-time with integrating rainfall information.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.1
• /
• pp.1-7
• /
• 2013

The interference among the rain radars and interference in the adjacent wireless station due to the spurious signals from the rain radar were analyzed in this paper. The rain radar measures the rain intensity using S-band signal. The measured data are utilized in forecasting the rainfall. The interference among the rain radars or in the adjacent wireless stations may be caused by the operation with low elevation angle and the high output power. Based on the propagation analysis of S band signal and the deduced interference protection ratio of rain radar, the interference due to the rain radar are analyzed. Also, the radiation spectrum characteristics of a rain radar are deduced from the caused interference effects by the spurious signals of the rain radar. To minimize the interference effects for adjacent wireless stations, it is required to get the rejection characteristics of spurious signals above 105 dB. In viewpoints of interference for rain radars, it is necessary to operate the rain radar with a different PRF and operation time opposite to adjacent rain radars.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.43-45
• /
• 2021

The short-term quantitative precipitation prediction (QPF) system is important socially and economically to prevent damage from severe weather. Recently, many studies for short-term QPF model applying the Deep Neural Network (DNN) has been conducted. These studies require the sophisticated pre-processing because the mistreatment of various and vast meteorological data sets leads to lower performance of QPF. Especially, for more accurate prediction of the non-linear trends in precipitation, the dataset needs to be carefully handled based on the physical and dynamical understands the data. Thereby, this paper proposes the following approaches: i) refining and combining major factors (weather radar, terrain, air temperature, and so on) related to precipitation development in order to construct training data for pattern analysis of precipitation; ii) producing predicted precipitation fields based on Convolutional with ConvLSTM. The proposed algorithm was evaluated by rainfall events in 2020. It is outperformed in the magnitude and strength of precipitation, and clearly predicted non-linear pattern of precipitation. The algorithm can be useful as a forecasting tool for preventing severe weather.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.136-136
• /
• 2017

본 연구의 목적은 이중편파 레이더 강우자료와 현재 실무에서 널이 이용되고 있는 레이더 강우보정 기법 적용에 따른 격자기반 분포형 강우-유출 모형인 KIMSTORM (KIneMatic wave STOrm Runoff Model)을 이용하여 유출해석을 수행하여 보정된 레이더 강우자료를 적용한 분포형 수문모형의 효율성을 검토하는데 있다. 남강댐 유역($2,293km^2$)을 대상으로 2014년 8월 태풍 이벤트(나크리), 2016년 10월 태풍 이벤트(차바)에 대하여 비슬산 레이더 강우자료를 사용하였다. 강우자료의 보정은 21개 지점 강우와 레이더 강우를 이용하여 조건부 합성 보정기법을 이용하였으며, 누적 강우량 그리고 면적 강우량 모두 관측치를 잘 재현함을 확인 할 수 있었다. $R^2$(coefficient of determination), ME (model efficiency), VCI (volume conservation index)를 이용하여 적용성을 평가하였다. 2016년 태풍 차바 이벤트에서의 유출 모형의 보정결과 조건부 합성 보정기법을 적용하기전 $R^2$, ME는 각각 0.75, 0.13으로 나타났고 조건부 합성 보정기법을 적용하였을 경우 각각 0.87, 0.82로 유출량 정확도가 크게 향상됨을 나타냈다. 다양한 국지성 집중호우 이벤트는 레이더 강우자료의 과대 및 과소추정을 유발하는 오차의 원인으로 조건부 합성 보정기법은 이러한 오차를 줄여 강우-유출 모형의 유출분석 결과 비교시 첨두유량 및 정량적인 면에서 실측 유량과 가깝게 모의되는 결과를 나타냈다.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.1 no.2
• /
• pp.142-150
• /
• 1999

During the past three decades after the first attempt to use satellite imagery or derived cloud products for rainfall estimation, much is known and understood concerning the scope and difficulties of satellite rainfall monitoring. After a brief general introduction this paper reviews recent progress in this field with special reference to improvement of algorithms, inter-comparison projects, integrative use of data from different sources, increasing lengths of data records and derived products, and interpretability of rainfall results. Also the paradigm of TRMM (Tropical Rainfall Measuring Mission) which is the first space mission(1997) dedicated to measuring tropical and subtropical rainfall though microwave and visible/infrared sensors, including the first spaceborne rain radar was introduced, and the potential applicability to the field of agriculture and water resources by combining satellite imagery is described.

• Journal of Korea Water Resources Association
• /
• v.53 no.6
• /
• pp.417-425
• /
• 2020

In order to predict and prevent hydrological disasters such as flood, it is necessary to accurately estimate rainfall. In this paper, an areal average rainfall estimation method using multiple elevation observation data of an electromagnetic wave rain gauge is presented. The small electromagnetic rain gauge system is a very small precipitation radar that operates at K-band with dual-polarization technology for very short distance observation. The areal average rainfall estimation method is based on the assumption that the variation in rainfall over the observation range is small because the observation distance and time are very short. The proposed method has been evaluated by comparing with ground instruments such as tipping-bucket rain gauges and a Parsivel. The evaluation results show that the methodology works fairly well for the rainfall events which are shown here.