• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.755-765
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• 2013

This study developed a real-time dam's hydrologic variables prediction model (DHVPM) and evaluated its performance for simulating historical dam inflow and outflow in the Chungju dam basin. The DHVPM consists of the Sejong University River Forecast (SURF) model for hydrologic modeling and an autoreservoir operation method (Auto ROM) for dam operation. SURF model is continuous rainfall-runoff model with data assimilation using an ensemble Kalman filter technique. The four extreme events including the maximum inflow of each year for 2006~2009 were selected to examine the performance of DHVPM. The statistical criteria, the relative error in peak flow, root mean square error, and model efficiency, demonstrated that DHVPM with data assimilation can simulate more close to observed inflow than those with no data assimilation at both 1-hour lead time, except the relative error in peak flow in 2007. Especially, DHVPM with data assimilation until 10-hour lead time reduced the biases of inflow forecast attributed to observed precipitation error. In conclusion, DHVPM with data assimilation can be useful to improve the accuracy of inflow forecast in the basin where real-time observed inflow are available.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.294-294
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• 2019

The system for predicting flood of river at Flood Control Office is made up of a rainfall-runoff model and FLDWAV model. This system is mainly operating to predict the excess of the flood watch or warning level at flood forecast points. As the demand for information of the management and operation of riverside, which is being used as a waterfront area such as parks, camping sites, and bike paths, high-level forecasts of watch and warning at certain points are required as well as production of lowland flood forecast information that is used as a waterfront within the river. In this study, a technology to produce flood forecast information in lowland areas of the river used as a waterfront was developed. Based on the results of the 1D hydraulic analysis, a model for performing spatial operations based on high resolution grid was constructed. A model was constructed for Andong district, and the inundation conditions and level were analyzed through a virtual outflow scenarios of Andong and Imha Dam.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.2
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• pp.215-226
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• 2018

The purpose of this study is to improve the accuracy of the urban runoff and drainage network analysis by using the observed water level in the drainage network. To do this, sensitivity analysis for major parameters of SWMM (Storm Water Management Model) was performed and parameters were calibrated. The sensitivity of the parameters was the order of the roughness of the conduit, the roughness of the impervious area, the width of the watershed, and the roughness of the pervious area. Six types of scenarios were set up according to the number and types of parameter considering four parameters with high sensitivity. These scenarios were applied to the Seocho-3/4/5, Yeoksam, and Nonhyun drainage basins, where the serious flood damage occurred due to the heavy rain on 21 July, 2013. Parameter optimization analysis based on PEST (Parameter ESTimation) model for each scenario was performed by comparing observed water level in the conduits. By analyzing the accuracy of each scenario, more improved simulation results could be obtained, that is, the maximum RMSE (Root Mean Square Error) could be reduced by 2.41cm and the maximum peak error by 13.7%. The results of this study will be helpful to analyze volume of the manhole surcharge and forecast the inundation area more accurately.

• Journal of Korea Water Resources Association
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• v.33 no.6
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• pp.701-709
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• 2000

Integrated storage function model (ISFM) is applied to some rainfall-runoff events of the selected basins in Korea to show validity of the proposed model. Comparing the numerical results of the model with the field measurements, the simulated hydrographs and peak flood discharges for the most part showed good agreements, except the occurrence time of the peak discharges which showed a bit discrepancy, and they showed it was very hard to have a sufficient lead-time to forecast the flood when the upstream inflow of the channel reach was more dominant than the inflow from the residual watershed of the channel.hannel.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.115-122
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• 1992

Stochastic rainfall-runoff process model which is mainly used in real-time streamflow forecasting is Transfer Function(TF) model that has a simple structure and can be easy to formulate state-space model. However, in order to forecast the streamflow accurately in real-time using the TF model, it is not only necessary to determine accurate structure of the model but also required to reduce forecasting error in early stage. In this study, after introducing 5-day Antecedent Precipitation Index (API5), which represents the initial soil moisture condition of the watershed, by using the threshold concept, the TF models in each API5 are identified by Box-Jenkins method and the results are compared with each other.

• Proceedings of the KSRS Conference
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• v.2
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• pp.973-976
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• 2006

The oscillations of the Caspian Sea level represent a result of mutually related hydrometeorological processes. The change in the tendency of the mean sea level variations that occurred in the middle 1970s, when the long-term level fall was replaced by its rapid and significant rise, represents an important indicator of the changes in the natural regime of the Caspian Sea. Therefore, sea level monitoring and long-term forecast of the sea level changes represent an extremely important task. The aim of this presentation is to show the experience of application of satellite altimetry methods to the investigation of seasonal and interannual variability of the sea level, wind speed and wave height, water dynamics, as well as of uplift of the Earth’s crust in different parts of the Caspian Sea and Kara-Bogaz-Gol Bay. Special attention is given to estimates of the Volga River runoff derived from satellite altimetry data. The work is based on the 1992-2005 TOPEX/Poseidon (T/P) and Jason-1 (J-1) data sets.

• Journal of Korean Society for Geospatial Information Science
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• v.11 no.3 s.26
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• pp.35-40
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• 2003

In these days, damages from localized heavy rain or typhoon are increase and people are making constant effort to work out countermeasures. Especially, by apply GIS with prompt extraction of information and objective analysis, we could demonstrate more effectively. For that reason, in this research we make the connection between rainfall-runoff model and HEC-RAS which calculate automatically and inquire out the dangerous zone easier way by describing the result with the connection between the Map Object and MFC. Most of all, this research will be very useful to forecast and prepare the disaster because it could plot plane figures, longitudinal sections and cross sections at the same time to help understand the damaged situation.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.147-147
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• 2018

In this article, we use an open source software library: TensorFlow, developed for the purposes of conducting very complex machine learning and deep neural network applications. However, the system is general enough to be applicable in a wide variety of other domains as well. The proposed model based on a deep neural network model, LSTM (Long Short-Term Memory) to predict the river water level at Okcheon Station of the Guem River without utilization of rainfall - forecast information. For LSTM modeling, the input data is hourly water level data for 15 years from 2002 to 2016 at 4 stations includes 3 upstream stations (Sutong, Hotan, and Songcheon) and the forecasting-target station (Okcheon). The data are subdivided into three purposes: a training data set, a testing data set and a validation data set. The model was formulated to predict Okcheon Station water level for many cases from 3 hours to 12 hours of lead time. Although the model does not require many input data such as climate, geography, land-use for rainfall-runoff simulation, the prediction is very stable and reliable up to 9 hours of lead time with the Nash - Sutcliffe efficiency (NSE) is higher than 0.90 and the root mean square error (RMSE) is lower than 12cm. The result indicated that the method is able to produce the river water level time series and be applicable to the practical flood forecasting instead of hydrologic modeling approaches.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.425-425
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• 2022

동아시아 지역은 몬순 영향으로 계절적인 수자원 변동성이 매우 크고 홍수 및 가뭄과 같은 수재해 피해가 빈번히 발생하고 추세이다. 본 연구에서는 동아시아의 수자원 관리에 활용하기 위해 수문 모형 중 하나인 WRF-Hydro (Weather Research and Forecast and Model Hydrological modeling extension package) 모형을 구축하였다. WRF-Hydro 모형은 미국 NCAR (National Center for Atmospheric Research)에서 개발된 커뮤니티형 고해상도 예측모델로 미국 등에서 활발히 사용되고 있으나, 동아시아 지역에 적용된 연구는 없다. 따라서 모형의 동아시아 적용 가능성에 대한 불확실성이 높다. 본 연구에서는 WRF-Hydro 모형을 0.25°의 공간해상도로 동아시아 대상으로 구축하였고, 기상 및 지면 특성과 유역자료를 활용한 머신러닝 방법으로 파라미터 보정을 시행하여 2006년부터 2015년까지 구동하였다. 머신러닝을 통해 지역특성이 고려된 WRF-Hydro 모형은 표면유출, 보수깊이, 표면 거칠기, 표면 기울기와 같은 매개변수를 보정하였다. 모형 평가를 위해 GRDC (Global Runoff Database Center (GRDC), GLDAS (Global Land Data Assimilation System), ESA-CCI (European Space Agency Climate Change Initiative), MODIS (Moderate Resolution Imaging Spectroradiometer)에서 제공하는 관측 유출량, 토양수분, 증발산량을 비교, 분석하여 동아시아 적용 적절성에 대해 검토하였다.

• Journal of Korea Water Resources Association
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• v.51 no.1
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• pp.11-18
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• 2018

The climate change impacts on hydrological components and water balance in Jeju Island were evaluated using multiple climate models and watershed model, SWAT-K. To take into account the uncertainty of the future forecast data according to climate models, climate data of 9 GCMs were utilized as weather data of SWAT-K for future period (2010-2099). Using the modeling results of the past (1992-2013) and the future period, the hydrological changes of each year were analyzed and the precipitation, runoff, evapotranspiration and recharge were increasing. Compared with the past, the change in the runoff was the largest (up to 50% increase) and the evapotranspiration was relatively small (up to 11% increase). Monthly results show that the amount of evapotranspiration and the amount of recharge are greatly increased as the amount of precipitation increases in August and September, while the amount of evapotranspiration decreases in the same period. January and December showed the opposite tendency. As a result of analyzing future water balance changes, the ratio of runoff, evapotranspiration, and recharge to rainfall did not change much, but compared to the past, the runoff rate increased up to 4.3% in the RCP 8.5 scenario, while the evapotranspiration rate decreased by up to 3.5%. Based on the results of other researchers and this study, it is expected that rainfall and runoff will increase gradually in the future under the assumption of present climate change scenarios. Especially summer precipitation and runoff are expected to increase. As a result, the amount of groundwater recharge in Jeju Island will increase.