• 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.454-458
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• 2018

홍수예보 정보는 인명 및 재산 피해를 예방하기 위한 중요한 기능을 수행하고 있다. 현재 제공되고 있는 홍수예보 정보는 본류 및 일부 주요지천에 설치된 수위관측소(홍수예보지점)에 국한되어 제공되고 있다. 또한 제공되는 홍수예보 정보는 주의보 및 경보 수위로 하천내의 친수시설 및 범람 위험에 대한 홍수예보 정보를 제공하지 못하고 있다. 따라서 영산강 수계의 홍수예보 정보제공 효율성을 높이기 위해서 기존에 제공되었던 주의보 및 경보 수위에 대하여 국가 위기경보단계별 기준을 적용하여 아래 표와 같이 4단계의 홍수예보정보를 제공할 수 있는 기준을 제시하였다. 제시된 개선 사항을 영산강 수계 수위관측소에 적용하여 친수시설 및 범람 위험에 대한 추가정보를 제공할 수 있도록 하였다. 또한 관측소별로 과거 수위자료를 수집하고 발생 빈도를 산정하여 홍수예보 정보제공에 활용함으로써 보다 효율적인 홍수예보 정보제공이 가능하도록 하였다. 본 연구에서는 일부 홍수예보지점에서 제공되는 홍수예보 정보(주의보 및 경보)를 개선하고 친수시설 및 범람 위험에 대한 추가 정보를 제공하여 홍수로 인한 인명 및 재산 피해를 경감할 수 있을 것으로 판단된다. 하지만 제시된 홍수예보 정보제공 방안은 수위관측소 주변을 대상으로 단순 측량에 의해 산정된 방법으로 향후에는 하천 전체를 공간적 개념으로 적용한 홍수예보 정보제공 방안에 대한 연구가 수행될 필요가 있다.

• 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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• 2021.06a
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• pp.347-347
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• 2021

국내 호우 및 태풍으로 인한 홍수피해는 전체 자연재해 피해액 중 90%에 달할 정도로 심각하다. 홍수 피해는 국내의 기후적 특성으로 인해 매년 반복될 뿐만 아니라 최근엔 기후변화로 인해 강우 패턴이 변함에 따라 홍수 대응에 대한 새로운 해결책이 요구되는 상황이다. 이러한 니즈에 맞춰 국내의 홍수 관리 기술 및 제도도 빠르게 발전해왔다. 기술적으로는 수문 관측 밀도, 자료의 축적, 전송, 분석기법 등이 상당한 수준에 이르고 있다. 다만, 단기 강우 예측, 고도화된 홍수해석모형, GIS와의 연계 등이 홍수 예경보 시스템과 실무에 직접적으로 활용되기 위해서는 아직 개발기술에 대한 실용화 연구 및 적용검증이 필요하다. 뿐만 아니라, 제도적으로도 「수자원의 조사·계획 및 관리에 관한 법률 및 시행규칙」을 통해 하천구역 및 그 배후지역에서 홍수로 인명과 재산에 대한 피해가 예상될 경우 홍수 예경보를 실시하도록 하고 있다. 그러나 최근 도달시간이 짧아 홍수선행예보시간이 확보되지 못하는 경우 등이 발생하며 홍수특보 기준에 대한 보완의 필요성이 제기되고 있다. 본 연구에서는 충분한 선행예보시간 확보 및 신속한 홍수대응을 위하여 홍수발생 및 예경보 발령 사례를 분석하고자 한다. 현재 홍수특보 발령 기준은 홍수위험정도에 따라 홍수주의보 또는 홍수경보로 구분하여 발령하도록 하고 있다. 홍수위험정도의 기준은 일반적으로 수위 또는 유량을 기준으로 하고 있으며, 이를 기준수위라고 정의하여 관리하고 있다. 본 연구에서는 홍수특보지점별 사례를 통해 지점의 지형적 특성, 기준수위, 기준수위에 도달시간을 종합적으로 분석하였다. 분석결과를 바탕으로 기존의 홍수특보를 효과적으로 운영하고 홍수피해를 저감하기 위해 고려해야 할 요소를 제시하였다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.442-442
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• 2022

고해상도 시공간적 격자 형태의 레이더 강수는 돌발홍수(flash flood)와 같은 기상재해에 대비하기 위하여 실시간 예측정보로 활용된다. 그러나 대부분의 레이더 강수는 과소 추정되는 경향이 있어 정량적인 보정 과정인 QPE (Quantitative Precipitation Estimation)가 필요하다. 일반적으로 레이더 강수자료 보정은 지점 관측자료를 활용하지만, 본 연구에서는 지상 강수량 기반의 고해상도 격자 강수자료를 생산하여 레이더 강수자료와 직접적으로 비교하고자 한다. 이에 고도와 지형적 특성을 고려한 PRISM(Precipitation-elevation Regressions on Independent Slopes Model) 방법을 사용하여 고해상도 격자기반의 자료를 생성하였다. PRISM 방법은 고도와 지리정보를 독립변수로 갖는 회귀모형 기반의 기후인자 추정 모형이다. 생산된 고해상도 격자 강수자료와 레이더 강수자료를 QPF (Quantitative Precipitation Forecast) 모델의 입력자료로 사용하여 예측결과를 비교하였다. 해당 QPF 모델은 이류(advection)와 확률론적 섭동(stochastic perturbation)을 기반으로 하며, 강수 앙상블 자료를 생산한다. QPF 모델에 대해 투 트랙(two-track) 방법으로 생산된 예측정보를 통해 레이더 강수자료의 격자별 후처리 보정이 가능할 것으로 판단된다.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.196-200
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• 2024

Weather forecasting is considered to be of utmost important among various important sectors such as flood management and hydro-electricity generation. Although there are various numerical methods for weather forecasting but majority of them are reported to be Mechanistic computationally demanding due to their complexities. Therefore, it is necessary to develop and build models for accurately predicting the weather conditions which are faster as well as efficient in comparison to the prevalent meteorological models. The study has been undertaken to forecast various atmospheric parameters in the city of Bangalore using Naïve Bayes algorithms. The individual parameters analyzed in the study consisted of wind speed (WS), wind direction (WD), relative humidity (RH), solar radiation (SR), black carbon (BC), radiative forcing (RF), air temperature (AT), bar pressure (BP), PM₁₀ and PM_2.5 of the Bangalore city collected from Air Quality Monitoring Station for a period of 5 years from January 2015 to May 2019. The study concluded that Naive Bayes is an easy and efficient classifier that is centered on Bayes theorem, is quite efficient in forecasting the various air pollution parameters of the city of Bangalore.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.14-30
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• 2015

This paper attempted to analyze the hydraulic effects that the dredging can take as an alternative to reduce possible damages of flooding due to the overflow of river levee in meandering rivers, where riverbed aggradation, seepage and erosion may occur. In order to make a hydraulic analysis in a section of meandering rivers, a two-dimensional hydraulic analysis model, RMA-2, was selected. The GIS was applied to construct two-dimensional finite element grids to consider the hydraulic conditions before and after dredging. The water surface elevations, depths, velocities, and tractive forces were compared before and after the dredging. The difference of water surface elevation between the inside and outside of river was turned out to be the maximum value of 0.58m under the design flood condition. It could be evaluated that the tractive force at the bank decreased about 42 to 67% on average for all the sections. These results could give valuable information that the dredging of the stream channel at the meandering sections decreased the risk of overflow, seepage and erosion of the banks. The methodologies given in this study will contribute to mitigating the flood damages in the surrounding farmlands.

• Journal of Korea Water Resources Association
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• v.57 no.5
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• pp.333-346
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• 2024

High-resolution medium-range streamflow prediction is crucial for sustainable water quality and aquatic ecosystem management. For reliable medium-range streamflow predictions, it is necessary to understand the characteristics of forcings and to effectively utilize weather forecast data with low spatio-temporal resolutions. In this study, we presented a comparative analysis of medium-range streamflow predictions using the distributed hydrological model, WRF-Hydro, and the numerical weather forecast Global Data Assimilation and Prediction System (GDAPS) in the Geumho River basin, Korea. Multiple forcings, ground observations (AWS&ASOS), numerical weather forecast (GDAPS), and Global Land Data Assimilation System (GLDAS), were ingested to investigate the performance of streamflow predictions with highresolution WRF-Hydro configuration. In terms of the mean areal accumulated rainfall, GDAPS was overestimated by 36% to 234%, and GLDAS reanalysis data were overestimated by 80% to 153% compared to AWS&ASOS. The performance of streamflow predictions using AWS&ASOS resulted in KGE and NSE values of 0.6 or higher at the Kangchang station. Meanwhile, GDAPS-based streamflow predictions showed high variability, with KGE values ranging from 0.871 to -0.131 depending on the rainfall events. Although the peak flow error of GDAPS was larger or similar to that of GLDAS, the peak flow timing error of GDAPS was smaller than that of GLDAS. The average timing errors of AWS&ASOS, GDAPS, and GLDAS were 3.7 hours, 8.4 hours, and 70.1 hours, respectively. Medium-range streamflow predictions using GDAPS and high-resolution WRF-Hydro may provide useful information for water resources management especially in terms of occurrence and timing of peak flow albeit high uncertainty in flood magnitude.

• Journal of Korea Water Resources Association
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• v.41 no.12
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• pp.1219-1230
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• 2008

Stream inflows induced by flood runoffs have a higher density than the ambient reservoir water because of a lower water temperature and elevated suspended sediment(SS) concentration. As the propagation of density currents that formed by density difference between inflow and ambient water affects reservoir water quality and ecosystem, an understanding of reservoir density current is essential for an optimization of filed monitoring, analysis and forecast of SS and nutrient transport, and their proper management and control. This study was aimed to quantify the characteristics of inflow density current including plunge depth($d_p$) and distance($X_p$), separation depth($d_s$), interflow thickness($h_i$), arrival time to dam($t_a$), reduction ratio(${\beta}$) of SS contained stream inflow for different flood magnitude in Daecheong Reservoir with a validated two-dimensional(2D) numerical model. 10 different flood scenarios corresponding to inflow densimetric Froude number($Fr_i$) range from 0.920 to 9.205 were set up based on the hydrograph obtained from June 13 to July 3, 2004. A fully developed stratification condition was assumed as an initial water temperature profile. Higher $Fr_i$(inertia-to-buoyancy ratio) resulted in a greater $d_p,\;X_p,\;d_s,\;h_i$, and faster propagation of interflow, while the effect of reservoir geometry on these characteristics was significant. The Hebbert equation that estimates $d_p$ assuming steady-state flow condition with triangular cross section substantially over-estimated the $d_p$ because it does not consider the spatial variation of reservoir geometry and water surface changes during flood events. The ${\beta}$ values between inflow and dam sites were decreased as $Fr_i$ increased, but reversed after $Fr_i$>9.0 because of turbulent mixing effect. The results provides a practical and effective prediction measures for reservoir operators to first capture the behavior of turbidity inflow.

• Journal of Ocean Engineering and Technology
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• v.33 no.6
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• pp.590-596
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• 2019

Numerous deaths and substantial property damage have occurred recently due to frequent disasters of the highest intensity according to the abnormal climate, which is caused by various problems, such as global warming, all over the world. Such large-scale disasters have become an international issue and have made people aware of the disasters so they can implement disaster-prevention measures. Extensive information on disaster prevention actively has been announced publicly to support the natural disaster reduction measures throughout the world. In Japan, diverse developmental studies on disaster prevention systems, which support hazard map development and flood control activity, have been conducted vigorously to estimate external forces according to design frequencies as well as expected maximum frequencies from a variety of areas, such as rivers, coasts, and ports based on broad disaster prevention data obtained from several huge disasters. However, the current reduction measures alone are not sufficiently effective due to the change of the paradigms of the current disasters. Therefore, in order to obtain the synergy effect of reduction measures, a study of the establishment of an integrated system is required to improve the various disaster prevention technologies and the current disaster prevention system. In order to develop a similar typhoon search system and establish a disaster prevention infrastructure, in this study, techniques will be developed that can be used to forecast typhoons before they strike by using artificial intelligence (AI) technology and offer primary disaster prevention information according to the direction of the typhoon. The main function of this model is to predict the most similar typhoon among the existing typhoons by utilizing the major typhoon information, such as course, central pressure, and speed, before the typhoon directly impacts South Korea. This model is equipped with a combination of AI and DNN forecasts of typhoons that change from moment to moment in order to efficiently forecast a current typhoon based on similar typhoons in the past. Thus, the result of a similar typhoon search showed that the quality of prediction was higher with the grid size of one degree rather than two degrees in latitude and longitude.