• 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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• 2017.05a
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• pp.2-2
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• 2017

수문분석이 있어 정확한 강우량 추정 및 강우 자료의 품질은 매우 중요한 요소이다. 유출분석의 기본 입력 자료인 만큼 홍수유출 결과에도 큰 영향을 미치게 되는데, 현재 하나의 확정적인 값으로 제공되는 레이더 강우 자료는 추정과정에서 많은 오차 및 불확실성을 포함하고 있다. 강우 자료의 불확실성은 기상현상의 예측능력 한계로 인한 것으로 관측지점에서의 발생 가능한 다양한 강우시나리오의 범위를 나타낸다. 본 연구에서는 임의의 값을 추정하는데 있어 하나의 값이 아닌 가능한 값들의 범위를 정의하거나 확률분포를 표현할 수 있는 확률론적인 방법을 이용하여 레이더 강우 앙상블을 생성하고자 하였다. 2012년 남강댐 유역에 발생한 태풍 '산바', '볼라벤'을 대상으로 자료간 오차 공분산을 고려하 2012년 남강댐 유역에 발생한 태풍 '산바', '볼라벤'을 대상으로 자료간 오차 공분산을 고려하여 강우 앙상블을 생성하였으며, 레이더 강우에 내포된 불확실성 정도를 정량적으로 제시하였다. 생성된 강우 앙상블은 레이더 강우의 전체적인 편의보정뿐만 아니라 지상강우의 패턴을 잘 모의하고 있는 것으로 나타났으며, 레이더에 의해 추정한 강우의 불확실성을 잘 표현하고 있는 것으로 확인되었다. 강우 앙상블 생성 방법은 발생 가능한 다양한 강우 시나리오를 제공할 수 있으며 홍수예경보와 같은 의사 결정에 유용한 정보를 제공할 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.310-310
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• 2023

기상레이더는 강우의 공간분포를 관측하고 강우장 이동특성을 예측하여 집중호우, 태풍 등에 대비할 수 있는 시간을 확보하기 위하여 운용되고 있다. 기상레이더는 전파를 송신하고 대기 중의물체(수상체, 건물 등)에 부딪혀 되돌아오는 신호를 수신하여 강우의 양, 분포, 이동방향 등을 산정할 수 있으며 세부적으로 입체관측(volume scan)을 반복하여 고도각 별로 거리와 방위각에 따라 다양한 합성영상을 산출할 수 있는 특성이 있다. 본 연구는 구름의 수평적 분포를 파악하는데 용이하여 기존에 널리 사용된 CAPPI 합성영상과 최근 현업에서 복잡한 지형으로 인한 오차를 해소하고자 광범위하게 사용되고 있는 다중 고도각 기반 레이더 강수량(hybrid surface rainfall, HSR) 합성영상을 취득하여 수문해석을 위한 유역단위 면적강수량의 추정오차를 검토하였다. HSR 합성영상은 우리나라와 같이 산악지형이 많이 존재하는 경우 지형의 영향을 받지 않아 지면에 가장 가까운 고도각의 관측자료를 사용하므로 지상관측소 강수량과 비교한 결과에서 기존의 CAPPI 합성영상 레이더 강수량과 통계적 효율 기준을 산정하여 레이더 강수의 품질이 개선되는 것을 확인하였다. 최근 환경부에서 추진하고 있는 인공지능(AI) 홍수예보 및 가상모형(Digital Twin)을 활용하여 홍수정보를 생산 및 전달하는 과정에서 유역의 지형적 특성을 현실적으로 고려한 레이더 강수량을 사용함으로 기후변화에 따라 국지적으로 발생하는 집중호우 대응 및 과학적 홍수관리를 실현할 수 있을 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.61-61
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• 2020

최근 수문기상학 분야에서 레이더 강수량을 활용한 응용연구가 활발하게 진행되고 있다. 하지만 레이더 강수량은 대류성 및 층상형 등과 같이 강수특성을 기준으로 레이더 반사도-강수량(Reflectivity-Rainfall, Z-R) 관계식 매개변수를 시공간적으로 동일하게 적용하여 레이더 강수량을 산정하는 방법론은 지상관측 강수량과 정량적인 편의 오차(systematic error)를 발생시킬 수 있는 문제점이 있다. 본 연구는 장기간의 레이더 합성장 반사도를 활용하여 Z-R 관계식 매개변수를 산정하였으며, 이 과정에서 Bayesian 추론 기법을 도입하여 Z-R 관계식 매개변수의 불확실성을 정량화하였다. 추가적으로 편의 오차를 최소화하기 위하여 계절성을 고려한 Z-R 관계식을 산정하였다. 건기와 우기로 구분하여 산정된 Z-R 관계식 매개변수의 공간적으로 변동성과 더불어 강수의 계절적 특성에 기인하는 Z-R 관계식 매개변수의 역비례 관계를 확인하였다. 최종적으로, 제안된 방법론으로 산정된 레이더 강수장은 일반적으로 레이더 강수량 산정에 널리 이용되는 Marshall-Palmer Z-R 관계식으로 산정된 강수장에 비하여 우수한 통계지표를 제시하였다.

• Journal of Korea Water Resources Association
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• v.33 no.2
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• pp.159-167
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• 2000

The purpose of this study is to estimate the stochastic monthly runoff model for the Kunwi south station of Wi-stream basin in Nakdong river system. This model was based on the theory of Box-Jenkins multiplicative ARlMA and the state-space model to simulate changes of monthly runoff. The forecasting monthly runoff from the pair of estimated effective rainfall and observed value of runoff in the uniform interval was given less standard error then the analysis only by runoff, so this study was more rational forecasting by the use of effective rainfall and runoff. This paper analyzed the records of monthly runoff and effective rainfall, and applied the multiplicative ARlMA model and state-space model. For the P value of V AR(P) model to establish state-space theory, it used Ale value by lag time and VARMA model were established that it was findings to the constituent unit of state-space model using canonical correction coefficients. Therefore this paper confirms that state space model is very significant related with optimization factors of VARMA model.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.81-87
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• 2010

In order to calculate the accurate runoff from a basin, nonlinearity in the relationship between rainfall and runoff has to be considered. Many runoff calculation models assume the linearity in the relationship or are too complicated to be analyzed. Therefore, the storage function method has been used in the prediction of flood because of the simplicity of the model. The storage function method has five parameters with related to the basin and rainfall characteristics which can be estimated by the empirical trial and error method. To optimize these parameters, regression method or optimization techniques such as genetic algorithm have been used, however, it is not easy to optimize them because of the complexity of the method. In this study, the metamodel is proposed to estimate those model parameters. The metamodel is the combination of artificial neural network and genetic algorithm. The model is consisted of two stages. In the first stage, an artificial neural network is constructed using the given rainfall-runoff relationship. In the second stage, the parameters of the storage function method are estimated using genetic algorithm and the trained artificial neural network. The proposed metamodel is applied in the Peong Chang River basin and the results are presented.

• Journal of Korean Society on Water Environment
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• v.33 no.2
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• pp.160-169
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• 2017

The objective of this study are to analyze changes in future rainfall patterns in the Soyang-dam watershed according to the RCP 4.5 scenario of climate change. Second objective is to project peak flow and hourly sediment simulated for the future extreme rainfall events using the SWAT model. For these, accuracy of SWAT hourly simulation for the large scale watershed was evaluated in advance. The results of model calibration showed that simulated peak flow matched observation well with acceptable average relative error. The results of future rainfall pattern changes analysis indicated that extreme storm events will become more severe and frequent as climate change progresses. Especially, possibility of occurrence of large scale extreme storm events will be greater on the periods of 2030-2040 and 2050-2060. In addition, as shown in the SWAT hourly simulation for the future extreme storm events, more severe flood and turbid water can happen in the future compared with the most devastating storm event which occurred by the typhoon Ewiniar in 2006 year. Thus, countermeasures against future extreme storm event and turbid water are needed to cope with climate change.

• Journal of the Korean Geotechnical Society
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• v.34 no.4
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• pp.5-11
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• 2018

In conventional analytical solutions for rainfall-induced soil slope stability, the Green-Ampt (1911) equation for estimating the saturation depth and the Skempton & DeLory (1957) equation for calculating the infinite slope shallow failure were compared with the numerical analysis to confirm the error. In the simple evaluation of the reason of soil slope instability due to rainfall using the conventional equations, there are many errors and, overestimation or underestimation of the calculation results. In this study, the equation consisting of the results obtained from infiltration analysis on unsaturated soil slope is proposed by applying the average range of the strength parameters of the granite weathered soils, and its reliability is verified by comparing with the numerical analysis results. The developed equation can be used easily in various fields for the estimation of slope safety factor by checking the rainfall duration and saturation depth.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2745-2752
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• 2013

The tipping-bucket and weight measuring type precipitation gauge has long been used worldwide for measuring rainfall. However, the conventional gauge has observation errors and its measurement range is limited by the device's resolution. In this paper, a new type of precipitation gauge that uses an innovative method by applying a new ultrasonic flow measuring technique was developed. This is the first time this technique is being used to gauge rainfall. The prototype was tested in the laboratory designated by the Korea Laboratory Accreditation Scheme (KOLAS). The rainfall intensity condition was 20~420 mm/H and the Standard Correction System for Precipitation Gauges was used. Results of the laboratory experiment showed that the proposed gauge has a ${\pm}2%$ margin of error. Consequently, it was proven that the proposed gauge is quite accurate and reliable for measuring precipitation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.4
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• pp.57-68
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• 2001

It is matter of common knowledge to give impetus to the water resources development to cope with increasing demand and supply for the water utilization project including agricultural living and industrial water owing to the economic and civilization development in recent years. Regional design rainfall is necessary or the design of the dam reservoir levee and drainage facilities for the development of various kinds of essential waters including agricultural water. For the estimation of the regional design rainfall classification of the climatologically an geographically homogeneous regions should be preceded preferentially This study was mainly conducted to derive the optimal regionalization of the precipitation data which can be classified by the climatologically and geographically homogeneous regions all over the regions except Cheju and Wulreung islands in Korea. A total of 65 rain gauges were used to regional analysis of precipitation. Annual maximum series for the consecutive durations of 1, 3, 6, 12, 24, 36, 48 and 72hr were used for various statistical analysis. Both K-means clustering and mean annual precipitation methods are used to identify homogeneous regions all over the regions. Nine and five homogeneous regions for the precipitation were classified by the K-means clustering and mean annual methods, respectively. Finally, Five homogeneous regions were established by the trial and error method with homogeneity test using statistics of $\chi$$^2$ distribution.