• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2010년도 추계 학술발표회
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• pp.253-262
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• 2010

In this study, localized heavy rainfall occurred during the collapse of steep slopes adjacent to the construction site and to ensure the safety of residents to build an early warning system was performed. Forecast/Alert range was estimated based on vulnerability landslide map and past disaster history. And established a critical line in consideration of the characteristics of local rainfall and operating a snake line, the study calculated causing and non-causing points. Also, be measured in real-time analysis of rainfall data in conjunction with the system before the steep slope failure occurred forecast/Alert System is presented.

• Geomechanics and Engineering
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• 제33권1호
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• pp.77-89
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• 2023

This study aims to establish the correlations between variables related to a slope during rainfall and factor of safety (FOS) and displacement using a coupling analysis method that is designed to consider both in rainfall conditions. With the recent development of measurement technologies, the approach of using the measurement data in the field has become easier. Particularly, they have been obtained in tests to determine the real-time safety and movement of a slope; however, a specific method has not been finalized. In addition, collected measurement data for recognizing the FOS and displacement in real-time with a specific relevance is difficult, and risks of uncertainty, such as in soil parameters and time, exist. In this study, the correlations between various slope-related variables (i.e., rainfall intensity, rainfall duration, angle of the slope, and mechanical properties including strength parameters of selected three types of soil; loamy sand, silt loam, sand) and the FOS and displacement are analyzed in order of seepage analysis, slope stability analysis and slope displacement analysis. Moreover, the methodology of coupling analysis is verified and a fundamental understanding of the factors that need to be considered in real-time observations is gained. The results show that the contributions of the abovementioned variables vary according to the soil type. Thus, the tendency of the displacement also differs by the soil type and variables but not same tendency with FOS. The friction angle and cohesion are negative while the rainfall duration and rainfall intensity are positive with the displacement. This suggests that understanding their correlations is necessary to determine the safety of a slope in real-time using displacement data. Additionally, databases considering rainfall conditions and a wide range of soil characteristics, including hydraulic and mechanical parameters, should be accumulated.

• 한국습지학회지
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• 제14권3호
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• pp.385-397
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• 2012

격자 기반의 물리적 분포형 모형은 유역의 물리적 매개변수와 격자 형식의 공간 및 수문자료를 이용해서 유출해석을 수행한다. 본 연구에서는 격자 기반의 물리적 분포형 강우-유출 모형인 GRM(Grid based Rainfall-runoff Model)의 실시간 유출해석 모듈인 GRM RT(Real Time)를 이용해서 실시간 유출해석 시스템을 개발하였다. 실시간으로 수신되는 기상레이더 자료를 기상청의 실시간 AWS 자료를 이용하여 보정한 후 유출해석에 적용하며, 수위관측소 자료로부터 생성되는 유량자료를 이용해서 유출모형을 실시간 보정한다. 본 연구에서는 실시간 유출해석 시스템 구축을 위해서 필요한 데이터베이스를 설계 및 구현하였으며, 분포형 모형과 레이더 자료를 이용한 실시간 유출해석 절차를 정립하였다. 또한 개발된 시스템의 성능을 평가하고 실시간 모형보정에 대한 적용성을 평가하였다. 소양강댐 상류에 위치한 내린천 수위관측소 유역을 대상으로 실시간 유출해석 시스템을 적용하고 그 결과를 평가하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.194-198
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• 2005

Although the rainstorm causes local damage on large scale, it is difficult to predict the movement of the rainstorm exactly. In order to reduce the rainstorm damage of the rainstorm, it is necessary to analyze the path of the rainstorm using various statistical methods. In addition, efficient time interval of rainfall observation for the analysis of the rainstorm movement can be derived by applying various statistical methods to rainfall data. In this study, the rainstorm tracking using statistical method is performed for various types of rainfall data. For the tracking of the rainstorm, the methods of temporal distribution, inclined Plane equations, and cross correlation were applied for various types of data including electromagnetic rainfall gauge data and AWS data. The speed and direction of each method were compared with those of real rainfall movement. In addition, the effective time interval of rainfall observation for the analysis of the rainstorm movement was also investigated for the selected time intervals 10, 20, 30, 40, 50, and 60 minutes. As a result, the absolute relative errors of the method of inclined plane equations are smaller than those of other methods in case of electromagnetic rainfall gauges data. The absolute relative errors of the method of cross correlation are smaller than those of other methods in case of AWS data. The absolute relative errors of 30 minutes or less than 30 minutes are smaller than those of other time intervals.

• 한국농공학회논문집
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• 제59권2호
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• pp.69-79
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• 2017

In this study, we developed real-time urban stream discharge forecasting model using short-term rainfall forecasts data simulated by a regional climate model (RCM). The National Centers for Environmental Prediction (NCEP) Climate Forecasting System (CFS) data was used as a boundary condition for the RCM, namely the Global/Regional Integrated Model System(GRIMs)-Regional Model Program (RMP). In addition, we make ensemble (ESB) forecast with different lead time from 1-day to 3-day and its accuracy was validated through temporal correlation coefficient (TCC). The simulated rainfall is compared to observed data, which are automatic weather stations (AWS) data and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA 3B43; 3 hourly rainfall with $0.25^{\circ}{\times}0.25^{\circ}$ resolution) data over midland of Korea in July 26-29, 2011. Moreover, we evaluated urban rainfall-runoff relationship using Storm Water Management Model (SWMM). Several statistical measures (e.g., percent error of peak, precent error of volume, and time of peak) are used to validate the rainfall-runoff model's performance. The correlation coefficient (CC) and the Nash-Sutcliffe efficiency (NSE) are evaluated. The result shows that the high correlation was lead time (LT) 33-hour, LT 27-hour, and ESB forecasts, and the NSE shows positive values in LT 33-hour, and ESB forecasts. Through this study, it can be expected to utilizing the real-time urban flood alert using short-term weather forecast.

• 한국지리정보학회지
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• 제20권3호
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• pp.12-26
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• 2017

본 연구의 목적은 물리적 분포형 강우-유출 모형인 GRM(Grid based Rainfall-runoff Model)과 마이크로소프트 Azure(Microsoft cloud computing service)를 이용하여 낙동강 유역의 유출해석시스템을 개발하고, Azure의 가상머신(VM, Virtual Machine) 설정에 따른 시스템 실행시간을 평가하는 것이다. 이를 위해서 낙동강 유역을 20개의 소유역으로 구분하고, 각 소유역에 대해서 GRM 모형을 구축하였다. 각 유역의 유출해석은 상하류 위상관계를 유지하면서 독립된 프로세스로 실행된다. 실시간 유출해석을 위해 국토교통부의 실시간 강우레이더 자료와 댐방류량 자료를 이용한다. 유출해석시스템은 Azure에서 실행되며, 유출해석 결과는 웹을 통해서 가시화 된다. 연구결과 실시간 수문자료 수신서버와 유출해석 계산서버(Azure) 및 사용자 PC가 연계된 낙동강 실시간 유출해석시스템을 개발할 수 있었다. 유출해석을 위한 전산장비는 하드디스크와 메모리 보다는 CPU의 성능에 크게 의존하는 것으로 평가되었다. 유출해석시의 디스크 입출력(I/O)과 계산 프로세스를 분산함으로써 입출력과 계산 병목을 각각 감소시킬 수 있었고, 실행시간을 단축시킬 수 있었다. 본 연구의 결과는 고해상도의 공간 및 수문 자료를 활용하는 분포형 모형을 이용한 대유역 유출해석시스템을 구축하기 위한 기술로 활용될 수 있을 것이다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2017년도 학술발표회
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• pp.194-194
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• 2017

Flooding is one of the most serious and frequently occurred natural disaster at many regions around the world. Especially, under the climate change impact, it is more and more increasingly trend. To reduce the flood damage, flood forecast and its accuracy analysis are required. This study is conducted to analyze the accuracy of the real-time flood forecasting of a coupled meteo-hydrological model for the Han River basin, South Korea. The LDAPS (Local Data Assimilation and Prediction System) products with the spatial resolution of 1.5km and lead time of 36 hours are extracted and used as inputs for the SURR (Sejong University Rainfall-Runoff) model. Three statistical criteria consisting of CC (Corelation Coefficient), RMSE (Root Mean Square Error) and ME (Model Efficiency) are used to evaluate the performance of this couple. The results are expected that the accuracy of the flood forecasting reduces following the increase of lead time corresponding to the accuracy reduction of LDAPS rainfall. Further study is planed to improve the accuracy of the real-time flood forecasting.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.183-183
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• 2021

Deep learning methods and their application have become an essential part of prediction and modeling in water-related research areas, including hydrological processes, climate change, etc. It is known that application of deep learning leads to high availability of data sources in hydrology, which shows its usefulness in analysis of precipitation, runoff, groundwater level, evapotranspiration, and so on. However, there is still a limitation on microclimate analysis and prediction with deep learning methods because of deficiency of gauge-based data and shortcomings of existing technologies. In this study, a real-time rainfall prediction model was developed from a sky image data set with convolutional neural networks (CNNs). These daily image data were collected at Chung-Ang University and Korea University. For high accuracy of the proposed model, it considers data classification, image processing, ratio adjustment of no-rain data. Rainfall prediction data were compared with minutely rainfall data at rain gauge stations close to image sensors. It indicates that the proposed model could offer an interpolation of current rainfall observation system and have large potential to fill an observation gap. Information from small-scaled areas leads to advance in accurate weather forecasting and hydrological modeling at a micro scale.

• 한국농공학회논문집
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• 제59권3호
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• pp.29-39
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• 2017

In this study, the GPM (Global Precipitation Mission) IMERG (Integrated Multi-satellitE retrievals for GPM) rainfall data was verified and evaluated using ground AWS (Automated Weather Station) and radar in order to investigate the availability of GPM IMERG rainfall data. The SPI (Standardized Precipitation Index) was calculated based on the GPM IMERG data and also compared with the results obtained from the ground observation data for the Hoengseong Dam and Yongdam Dam areas. For the radar data, 1.5 km CAPPI rainfall data with a resolution of 10 km and 30 minutes was generated by applying the Z-R relationship ($Z=200R^{1.6}$) and used for accuracy verification. In order to calculate the SPI, PERSIANN_CDR and TRMM 3B42 were used for the period prior to the GPM IMERG data availability range. As a result of latency verification, it was confirmed that the performance is relatively higher than that of the early run mode in the late run mode. The GPM IMERG rainfall data has a high accuracy for 20 mm/h or more rainfall as a result of the comparison with the ground rainfall data. The analysis of the time scale of the SPI based on GPM IMERG and changes in normal annual precipitation adequately showed the effect of short term rainfall cases on local drought relief. In addition, the correlation coefficient and the determination coefficient were 0.83, 0.914, 0.689 and 0.835, respectively, between the SPI based GPM IMERG and the ground observation data. Therefore, it can be used as a predictive factor through the time series prediction model. We confirmed the hydrological utilization and the possibility of real time drought monitoring using SPI based on GPM IMERG rainfall, even though results presented in this study were limited to some rainfall cases.

• 대한토목학회논문집
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• 제30권4B호
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• pp.347-359
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• 2010

실시간 홍수예측시스템의 구성에서 장래 강우 양상(지속기간, 강우강도 등)에 대한 가정으로 인하여 홍수예측의 신뢰성을 높이기 어려웠다는 점을 해결하기 위하여 현재까지의 강우, 현재수위 및 상류지역의 수위를 기반으로 홍수를 예측할 수 있는 간단한 웹기반모형을 구성하였다. 대상유역인 대전광역시의 도심하천 구간에서 각 수위 및 강우관측소들 간의 자료들을 활용하고, 현재까지의 관측 자료들을 이용하여 최대 2시간 후의 수위변화를 예측할 수 있는 회귀분석 모형을 구성하였다. 자료의 전송은 MS-Excel 2007을 기반으로 하여 금강홍수통제소와 국가수자원관리 종합정보홈페이지의 강우 및 수위자료를 실시간으로 읽어오는 방식으로 자료를 연결하였다. 각각의 선행시간에 대하여 예측한 결과 실제 실측치를 예측하는 과정에서 표준편차가 최대 5 cm, 평균 표준편차가 1~4 cm에 머무르고 있는 점 및 수정 결정계수의 값이 대부분 0.95 이상을 나타내는 점 등을 살펴보면 전체적으로 예보모형이 안정적으로 운영이 되고 있음을 알 수 있었다. 다만 본 회귀모형의 특성이 유역반응의 정상성을 가정하여 구성된 것을 감안한다면 어느 정도 기간까지 정상성을 유지할 수 있는가의 문제 및 시계열분석 기법의 적용은 추후 연구가 더욱 필요할 것으로 보인다.