• 한국농공학회지
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• 제32권3호
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• pp.47-55
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• 1990

An adaptive algorithm was applied to forecast daily stream flows in real time using rainfall data. A three-component tank model was selected to simulate the flows and its time-variant parameters were self-calibrated with updated data using a parameter optimization scheme, golden section search method. The resulting adaptive model, APTANK, was applied to six watersheds, ranging from 0.47 to 33.62 km$^2$ size and the simulated daily streamflows were compared with the measured. The simulation results were in good agreement with the field data. APTANK is found to be applied to real-time flow simulation purposes such as a tool for irrigation water resources management and operations. The model is particularly good to simulate streamflows on dry days as compared to wet days having runoff-induced precipitation.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2001년도 학술발표회 논문집(I)
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• pp.383-388
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• 2001

• 농업과학연구
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• 제37권1호
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• pp.105-112
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• 2010

The objective of this study is to develop a standardized model for analyzing water balances in large scaled water basin by considering agricultural water districts, and to evaluate the hydrological feasibility of applying this model to several water districts such as Nonbul, Geumbok, Daejeon 1, Daejeon 2, and Cheonggang in Geum river basin. Ten types of stream network were considered in developed model. Using this model, streamflows were simulated by major stations and water balances were analyzed by water districts. Simulated streamflows and measured streamflows were compared at check stations such as Gapcheon and Bugang stations in which Nash and Schcliffe's model efficiencies were 0.633, 0.902, respectively. This results showed its applicabilities to national water resources plan, rural water development plan, and total maximum daily load plan in Korea.

• 한국수자원학회논문집
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• 제42권2호
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• pp.161-168
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• 2009

본 연구에서는 팔당댐 지점을 중심으로 상류에 위치하고 있는 소양강, 충주 다목적댐 운영에 따른 빈도홍수량의 거동변화를 분석하고자 하였다. 이를 연구하기 위해서는 동일기간의 댐운영 여부에 따른 두 계열(조절유량, 비조절 유량)의 홍수량 자료를 합리적으로 획득하는 것이 무엇보다 중요하다. 홍수량 산정을 위해서는 단기 강우-유출모형을 이용해야 하지만, 계산의 어려움과 유역의 비선형으로 인해 그 결과를 증명하기 매우 어려운 현실이다. 따라서 상대적으로 유역면적이 클수록 일유량과 홍수량의 관계가 비교적 일정한 경향을 보인다는 점에 착안하여, 장기유출모형인 SWAT-K를 이용하여 댐운영 여부에 따른 두 계열의 일유량을 모의하였다. 일유량과 홍수량의 상관관계로 모의된 일유량을 홍수량으로 유도한 후, 댐운영 여부에 따른 빈도홍수량의 변화특성을 파악하였다. 홍수빈도분석을 위해 사용된 분포는 Extreme Type-I이며, 매개변수 추정은 L-moment 방법을 이용하였다. 연구결과에 따르면, 소양강, 충주 두 다목적댐 운영이 이루어지지 않은 상황에 대한 팔당댐 지점에서의 100년 빈도홍수량에 비하여, 소양강댐, 충주댐, 소양강과 충주댐의 운영유무에 따른 3가지 시나리오에 대한 빈도홍수량은 각각 91, 83, 71 % 규모로 분석되었다. 본 연구는 유역면적이 상대적으로 넓은 유역에서 댐운영 여부에 따른 빈도홍수량의 변화를 파악할 수 있는 새로운 시도였다. 이는 일유량 자료의 이용 및 분석에 있어 이수적인 측면뿐만 아니라 치수적인 측면에서의 활용성을 높일 것으로 판단된다.

• 한국수자원학회논문집
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• 제39권3호
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• pp.253-259
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• 2006

기존의 거의 모든 수문학적 연구에 있어서, 시스템의 특성을 파악한 뒤 예측을 실시하는 표준접근법이 채택되어왔다. 그러나 최근 들어 시스템의 특성분석에 앞서 예측을 실시하고, 상태공간 매개변수가 시스템의 특성분석단계가 아닌 예측단계에서 평가되는 가역접근법이 제안되었다. 본 연구에서는 최근에 제안된 가역접근법과 기존에 널리 적용되어온 표준접근법을 이론적 카오스 시계열과 Idaho주 Bear강의 일유출량 자료에 적용함으로써, 가역접근법의 적용성을 검토하고 카오스 시계열의 특성을 알아보았으며, 카오스이론이 적용된 비선형 예측기법으로는 부분근사화 기법을 이용하였다. 카오스 특성 분석을 통해, 이론적 카오스 시계열과 Idaho주 Bear강의 일유출량 시계열 자료 모두에서 카오스 특성이 나타남을 알 수 있었다. 200일에 대한 1, 3, 5일 예측 결과, 가역접근법이 표준접근법에 비해 우수함을 알 수 있었다.

• 물과 미래
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• 제25권3호
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• pp.105-113
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• 1992

본연구는 홍수기의 일단위 하천유출량을 예측하기 위한 방법으로 인공지능의 구현 모형으로 사용되고 있는 신경회로망이론을 도입하여 실수문계에 적용하고 그 결과를 제시하는 것이다. 강우-유출과정으로 형성되는 수문계의 동적거동을 입출력패턴으로 보아서 모형을 구성하는 유니트의 비선형 응답특성에 따라 네트워크의 상호 결합강도를 조정하여 시스템의 매개변수를 반복추정하는 방법으로 시스템을 특정 평가하였다. 일강우와 일유량의 과거 관측치를 신경회로망 모형의 순전파알고리즘으로 학습시켜 추정된 매개변수를 이용하여 하천유출량을 예측하였고 그 결과를 관측된 유량과 비교하기 위하여 통계학적으로 분석하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 1992년도 수공학연구발표회논문집
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• pp.411-418
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• 1992

The purpose of this study is to develop dynamic-stochastic models that can forecast the inflow into reservoir during low/drought periods and flood periods. For the formulation of the models, the discrete transfer function is utilized to construct the deterministic characteristics, and the ARIMA model is utilized to construct the stochastic characteristics of residuals. The stochastic variations and structures of time series on hydrological data are examined by employing the auto/cross covariance function and auto/cross correlation function. Also, general modeling processes and forecasting method are used the model building methods of Box and Jenkins. For the verifications and applications of the developed models, the Chungju multi-purpose reservoir which is located in the South Han river systems is selected. Input data required are the current and past reservoir inflow and Yungchun water levels. In order to transform the water level at Yungchon into streamflows, the water level-streamflows rating curves at low/drought periods and flood periods are estimated. The models are calibrated with the flood periods of 1988 and 1989 and hourly data for 1990 flood are analyzed. Also, for the low/drought periods, daily data of 1988 and 1989 are calibrated, and daily data for 1989 are analyzed.

• Korean Journal of Hydrosciences
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• 제4권
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• pp.1-9
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• 1993

It is a major objective for the management and operation of water resources system to forecast streamflows. The applicability of artificial neural network model to hydrologic system is analyzed and the performance is compared by statistical method with observed. Multi-layered perception was used to model rainfall-runoff process at Pyung Chang River Basin in Korea. The neural network model has the function of learning the process which can be trained with the error backpropagation (EBP) algorithm in two phases; (1) learning phase permits to find the best parameters(weight matrix) between input and output. (2) adaptive phase use the EBP algorithm in order to learn from the provided data. The generalization results have been obtained on forecasting the daily and hourly streamflows by assuming them with the structure of ARMA model. The results show validities in applying to hydrologic forecasting system.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회 논문집
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• pp.143-148
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• 2005

The main purpose of this study is to suggest and evaluate an operational method for assessing the potential impact of climate change on hydrologic components and water resources of regional scale river basins. The method, which uses large scale climate change information provided by a state of the art general circulation model(GCM) comprises a statistical downscaling approach and a spatially distributed hydrological model applied to a river basin located in Korea. First, we construct global climate change scenarios using the YONU GCM control run and transient experiments, then transform the YONU GCM grid-box predictions with coarse resolution of climate change into the site-specific values by statistical downscaling techniques. The values are used to modify the parameters of the stochastic weather generator model for the simulation of the site-specific daily weather time series. The weather series fed into a semi-distributed hydrological model called SLURP to simulate the streamflows associated with other water resources for the condition of $2CO_2$. This approach is applied to the Yongdam dam basin in southern part of Korea. The results show that under the condition of $2CO_2$, about $7.6\% of annual mean streamflow is reduced when it is compared with the observed one. And while Seasonal streamflows in the winter and autumn are increased, a streamflow in the summer is decreased. However, the seasonality of the simulated series is similar to the observed pattern and the analysis of the duration cure shows the mean of averaged low flow is increased while the averaged wet and normal flow are decreased for the climate change.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2000년도 학술발표회 발표논문집
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• pp.384-389
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• 2000

A artificial neural network model was developed to analyze and forecast the flow fluctuation at small streams in the Balan watershed. Backpropagation neural networks were found to perform very well in forecasting daily streamflows. In order to deal with slow convergence and an appropriate structure, two algorithms were proposed for speeding up the convergence of the backpropagation method, and the Bayesian Information Criterion(BIC) was proposed for obtaining the optimal number of hidden nodes. From simulations using daily flows at the HS#3 watershed of the Balan Watershed Project, which is 412,5 ㏊ in size and relatively steep in landscape, it was found that those algorithms perform satisfactorily.