• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2018년도 학술발표회
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• pp.155-155
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• 2018

Uncertainty in flood forecasting using a coupled meteorological and hydrological model is arisen from various sources, especially the uncertainty comes from the inaccuracy of Quantitative Precipitation Forecasts (QPFs). In order to improve the capability of flood forecast, the uncertainty estimation and mitigation are required to perform. This study is conducted to investigate and reduce such uncertainty. First, ensemble QPFs are generated by using Monte - Carlo simulation, then each ensemble member is forced as input for a hydrological model to obtain ensemble streamflow prediction. Likelihood measures are evaluated to identify feasible member. These members are retained to define upper and lower limits of the uncertainty interval and assess the uncertainty. To mitigate the uncertainty for very short lead time, a blending method, which merges the ensemble QPFs with radar-based rainfall prediction considering both qualitative and quantitative skills, is proposed. Finally, blending bias ratios, which are estimated from previous time step, are used to update the members over total lead time. The proposed method is verified for the two flood events in 2013 and 2016 in the Yeonguol and Soyang watersheds that are located in the Han River basin, South Korea. The uncertainty in flood forecasting using a coupled Local Data Assimilation and Prediction System (LDAPS) and Sejong University Rainfall - Runoff (SURR) model is investigated and then mitigated by blending the generated ensemble LDAPS members with radar-based rainfall prediction that uses McGill algorithm for precipitation nowcasting by Lagrangian extrapolation (MAPLE). The results show that the uncertainty of flood forecasting using the coupled model increases when the lead time is longer. The mitigation method indicates its effectiveness for mitigating the uncertainty with the increases of the percentage of feasible member (POFM) and the ratio of the number of observations that fall into the uncertainty interval (p-factor).

• Journal of Korean Society on Water Environment
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• 제24권3호
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• pp.345-353
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• 2008

In order to design storage-based non-point source management facilities, the aspect of statistical features of the entire precipitation time series should be considered since non-point source pollutions are delivered by continuous rainfall runoffs. The 3-parameter mixed exponential probability density function instead of traditional single-parameter exponential probability density function is applied to represent the probabilistic features of long-term precipitation time series and model urban stormwater runoff. Finally, probability density functions of water quality control basin overflow are derived under two extreme intial conditions. The 31-year continuous precipitation time series recorded in Busan are analyzed to show that the 3-parameter mixed exponential probability density function gives better resolution.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2018년도 학술발표회
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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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• 한국수자원학회 2023년도 학술발표회
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• pp.349-349
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• 2023

In recent years, urban floods have become more frequent, causing significant harm to society and resulting in substantial losses to the national economy and people's lives and property. To assess the impact of floods on people's safety and property in Seoul, annual precipitation data from 1980 to 2020 was analyzed for return periods of 5, 10, 20, 50, and 100 years. A rainfall runoff simulation model for Seoul was established using HEC-HMS and HEC-RAS models. The study revealed that at a 5-year return period, water began to accumulate in Seoul, but it was not severe. However, at a 10-year return period, the water accumulation was relatively serious, and inundation began to occur. At a 20-year return period, there was serious water accumulation and inundation in Seoul. During a 50-year return period, Seoul suffered from severe inundation in commercial areas, resulting in substantial losses to the local economy. The findings indicate that Seoul City faces high flood risks, and measures should be taken to mitigate the impact of floods on the city's residents and economy.

• Water for future
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• 제26권1호
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• pp.115-124
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• 1993

This study is to determine the critical duration of design rainfall and to utilize it for the design of detention pond with pump station. To examine the effect of the duration and temporal distribution of the design rainfall, Huff's quartile method is used for the 9 cases of durations ranging from 20 to 240 minutes with 10 years return period, and the ILLUDAS model is used for runoff analysis. The storage ration which is the ratio of maximum storage amounts to total runoff volume, is introduced to determine the critical duration of design rainfall. The duration which maximizes the storage ratio is adopted as the critical duration. This study is applied to 18 urban drainage watersheds with pump station in Seoul, of which the range of watershed area is $0.24-12.70\textrm{km}^2.$ The result of simulation shows that the duration which maximizes storage ration is 30 and 60 minutes on the whole. It is shown also that the storage ration of 2nd- and 3rd-quartile pattern is larger than that of 1st- and 4th-quartile pattern of temporal distribution. A simplified empirical formula for Seoul area is suggested by using the regression analysis between the maximum storage ration and the peak ratio, and can be utilized for the preliminary design and planning of detention pond with pump station.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2020년도 학술발표회
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• pp.117-117
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• 2020

The main objective of this study was to setup model and evaluate the model performance for streamflow simulation in Burundi using Soil and Water Assessment Tool (SWAT) model. The total area of Burundi is 27,834 ㎢. The elevation of Burundi ranges from 780 m to 2,700m. The West and East are low lands, while the Central part is high land. The topographic data (30 meters Digital Elevation Model) and land use and land cover data of Burundi were obtained respectively from Shuttle Radar Topography Mission (SRTM) and the Regional Centre for Mapping of Resources for Development (RCMRD). The soil data used was obtained from Food and Agriculture Organization (FAO). The local weather data and discharge data were provided by Burundi Hydro meteorological Service (IGEBU). Mean Areal Precipitation (MAP) and Mean Areal Temperature (MAT) were estimated. The streamflow simulation was done for the period 1980-2017. The calibration and validation of river discharge was performed at a daily time step from 2005 through 2011 as the calibration period and 2012 up to 2017 as the validation period. The findings show that streamflow decreases during Jun to September and increases during March to May and October to December.

• Journal of Korea Water Resources Association
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• 제45권11호
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• pp.1121-1130
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• 2012

Projected changes and their impacts on water quality are simulated in response to climate change stressors. CGHR (T63) simulation on the A1B scenario is converted to regional scale data using a statistical down-scaling method and applied to SWAT model to assess water quality impacts in Nakdong River basin. The results demonstrate that rainfall-runoff and pollutant loading in the future (2011~2100) will clearly increase as compared to the last 30-year average. The rate of pollutant loading increase is expected to continue its acceleration until 2040s. Runoff also shows similar patterns to the precipitation, increasing by 60%. Accordingly, the runoff increase results in escalation of pollutant loading by 35~45% for TSS and 5~20% for T-P. This phenomenon is more pronounced in the upper basin during winter and spring season.

• Journal of Korea Water Resources Association
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• 제37권11호
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• pp.929-938
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• 2004

In this study, Miho stream basin(Seokhwa water level gauging station) In Geum river, Flood control main station of Geum River Flood Control Office, is selected. Hydrologic topographical informations are calculated using WMS which is hydrologic analysis software coupled with GIS Method, and flood analysis is accomplished by HEC-1 included In WMS. To calculate the effective rainfall CN values of SCS are used. Clark, Snyder and SCS methods are selected respectively to derive unit hydrograph. This study shows the applicability of GIS techniques to runoff simulation in ungauged basin by comparing with actual measured flood hydrograph. As a results, Snyder(Tulsa) method and Clark (Herby) method is suitable to Miho stream basin. But Snyder(Tulsa) method is suitable more than Clark(Herby) method. And according to the degree of urbanization, the peak discharge has increased and the peak time has tended to decrease.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2017년도 학술발표회
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• pp.83-83
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• 2017

수자원공학에서 일강수량 모의기법은 다양한 목적으로 활용되고 있지만, 일반적으로 홍수와 가뭄의 영향을 고려할 수 있는 수공구조물의 위험도 및 신뢰성 평가 및 수자원 계획을 수립하기 위한 입력 자료생성을 목적으로 활용된다. 유역 단위의 분석시 단일 지점에 대한 강수 모의 기법을 적용할 경우 각각의 지점에서 관측된 강수 자료의 시계열 및 통계치 특성이 효과적으로 재현되지만 공간적으로 발생하는 즉, 지점 간의 종속관계를 재현하지 못하는 문제가 발생한다. 이러한 이유로 공간적인 전이 특성이 있는 가뭄 분석 및 유역내 유출량의 공간적 변동 특성 분석에 단일지점별 모의 결과를 이용할 경우 관측 자료와 상반된 공간적 변동성으로 인하여 잘못된 가뭄 및 유출 분석 결과가 도출되는 문제점이 있다. 따라서, 실제적으로 발생하는 강수 특성을 반영한 유역 단위의 홍수 및 가뭄 등의 수문 분석을 위해서는 지점간의 종속성을 반영할 수 있는 다지점 강수 모의 모형의 적용이 필수적이다. 본 연구에서는 다지점 모의에 있어서, Wilks 모형의 지점별 시변동 특성과 공간상관성 재현 능력, HMM 모형이 갖는 강수 사상별로 분포된 양적 분포 패턴 재현 능력을 복합적으로 나타낼 수 있는 새로운 다지점 일강수량 모의 모형인 기계학습 기반 범주화 기법을 이용한 다지점 일강수량 모의 모형(ML-MRS)을 개발하였다. 또한, 지점별 강수량에 적용되는 확률분포모형은 Gamma 분포로 구성된 혼합모형을 적용하여 단일 확률 분포 모형의 자료 적합 문제를 개선하였다. 모의를 통한 일강수량 시계열 자료는 일 강수자료의 통계량을 효과적으로 모의하였으며, 다지점 모형의 모의 결과를 적용한 가뭄 모의 결과 관측 자료에서 나타나는 공간적 패턴이 재현되었다. 본 모형은 시 공간적 사상을 효과적으로 재현함으로서 지역의 변동특성을 반영한 가뭄, 홍수, 기상 현상 분석 등 활용도가 매우 높을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.953-956
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• 2009

본 연구는 농업용저수지유역을 대상으로 분포형 강우-유출모형을 적용해 봄으로서 차후 본 연구대상유역의 분포형 강우유출모형을 이용한 설계홍수량 산정에 활용해 보기 위한 사전연구이다. 농업용저수지유역을 대상으로 모의하기 위하여 자동수위계를 통하여 저수지 수위자료가 주기적으로 기록되고 있는 계룡저수지 유역($15.4km^2$)을 선정하였으며, 주요 공간매개변수는 30m 격자해상도로 구축하였다. 관측유량자료는 수위-내용적-방류량 관계곡선에 의하여 수위변화에 따른 내용적 변화량을 유입량으로 가정하여 환산토록 하였으며, 곡선의 진동이 다소 작고 상태가 양호한 3개 강우사상을 대상으로 분석하였다. 대상유역의 2개 강우관측소(복룡, 반포)의 강우량을 IDW 방법에 의해 공간분포시켜 적용하였으며, 모형의 분석결과, 결정계수($R^2$)는 평균0.88, 용적보존지수(VCI)는 평균 0.14, 첨두유량의 상대오차 ($EQ_p$)는 평균 $0.11m^3/s$로 분석되었다.