• 제목/요약/키워드: daily streamflow

검색결과 137건 처리시간 0.023초

부분계측 및 미계측 유역에서 기준유량 산정 방법 비교 연구 (Comparative Study on Evaluating Standard Flow in Partially Gauged and Ungauged Watershed)

  • 김경훈;김정민;정현기;임태효;김성민;김용석;서미진
    • 한국물환경학회지
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    • 제35권6호
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    • pp.481-496
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    • 2019
  • The Ministry of Environment has measured streamflow at eight-day intervals for the estimation of standard flow of the Total Maximum Daily Loads (TMDL) system. This study identified the availability of the partially measured the eight-day interval data for estimating standard flow and found the optimal extension techniques of standard flow. The study area was selected for the Nakbon-A watershed in the Nakdong River, and four streamflow record extension techniques of standard flow were considered: extension, percentile, drainagearea, and regional regression methods. The flow duration curve (FDC) using the eight-day interval streamflow data indicated very high Nash and Sutcliffe Efficiency (NSE) values above 90 % from FDC-II to FDC-VII compared to FDC-VIII, the standard FDC. This result demonstrates that FDC using daily data of three-six cumulative years could represent standard FDC fairly well. For the streamflow record extension techniques of standard flow, the percentile method was selected as the optimal alternative, showing the minimal difference from FDC-VIII. These results validate the availability of the eight-day interval streamflow data in the standard flow estimation and the application of extension techniques. It seems that these results could reduce the uncertainty of partially measured streamflow data for water quantity and quality management.

인공신경망 이론을 이용한 소유역에서의 장기 유출 해석 (Forecasting Long-Term Steamflow from a Small Waterhed Using Artificial Neural Network)

  • 강문성;박승우
    • 한국농공학회지
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    • 제43권2호
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    • pp.69-77
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    • 2001
  • An artificial neural network model was developed to analyze and forecast daily steamflow flow a small watershed. Error Back propagation neural networks (EBPN) of daily rainfall and runoff data were found to have a high performance in simulating stremflow. The model adopts a gradient descent method where the momentum and adaptive learning rate concepts were employed to minimize local minima value problems and speed up the convergence of EBP method. The number of hidden nodes was optimized using Bayesian information criterion. The resulting optimal EBPN model for forecasting daily streamflow consists of three rainfall and four runoff data (Model34), and the best number of the hidden nodes were found to be 13. The proposed model simulates the daily streamflow satisfactorily by comparison compared to the observed data at the HS#3 watershed of the Baran watershed project, which is 391.8 ha and has relatively steep topography and complex land use.

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Assessment of streamflow variation considering long-term land-use change in a watershed

  • Noh, Joonwoo;Kim, Yeonsu;Yu, Wansik;Yu, Jisoo
    • 농업과학연구
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    • 제48권3호
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    • pp.629-642
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    • 2021
  • Land-use change has an important role in the hydrologic characteristics of watersheds because it alters various hydrologic components such as interception, infiltration, and evapotranspiration. For example, rapid urbanization in a watershed reduces infiltration rates and increases peak flow which lead to changes in the hydrologic responses. In this study, a physical hydrologic model the soil and water assessment tool (SWAT) was used to assess long-term continuous daily streamflow corresponding to land-use changes that occurred in the Naesungchun river watershed. For a 30-year model simulation, 3 different land-use maps of the 1990s, 2000s, and 2010s were used to identify the impacts of the land-use changes. Using SWAT-CUP (calibration and uncertainty program), an automated parameter calibration tool, 23 parameters were selected, optimized and compared with the daily streamflow data observed at the upstream, midstream and downstream locations of the watershed. The statistical indexes used for the model calibration and validation show that the model performance is improved at the downstream location of the Naesungchun river. The simulated streamflow in the mainstream considering land-use change increases up to -2 - 30 cm compared with the results simulated with the single land-use map. However, the difference was not significant in the tributaries with or without the impact of land-use change.

CMIP5 기반 하천유량 예측을 위한 딥러닝 LSTM 모형의 최적 학습기간 산정 (Estimation of Optimal Training Period for the Deep-Learning LSTM Model to Forecast CMIP5-based Streamflow)

  • 천범석;이태화;김상우;임경재;정영훈;도종원;신용철
    • 한국농공학회논문집
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    • 제64권1호
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    • pp.39-50
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    • 2022
  • In this study, we suggested the optimal training period for predicting the streamflow using the LSTM (Long Short-Term Memory) model based on the deep learning and CMIP5 (The fifth phase of the Couple Model Intercomparison Project) future climate scenarios. To validate the model performance of LSTM, the Jinan-gun (Seongsan-ri) site was selected in this study. We comfirmed that the LSTM-based streamflow was highly comparable to the measurements during the calibration (2000 to 2002/2014 to 2015) and validation (2003 to 2005/2016 to 2017) periods. Additionally, we compared the LSTM-based streamflow to the SWAT-based output during the calibration (2000~2015) and validation (2016~2019) periods. The results supported that the LSTM model also performed well in simulating streamflow during the long-term period, although small uncertainties exist. Then the SWAT-based daily streamflow was forecasted using the CMIP5 climate scenario forcing data in 2011~2100. We tested and determined the optimal training period for the LSTM model by comparing the LSTM-/SWAT-based streamflow with various scenarios. Note that the SWAT-based streamflow values were assumed as the observation because of no measurements in future (2011~2100). Our results showed that the LSTM-based streamflow was similar to the SWAT-based streamflow when the training data over the 30 years were used. These findings indicated that training periods more than 30 years were required to obtain LSTM-based reliable streamflow forecasts using climate change scenarios.

가역접근법을 이용한 일유출량 자료의 비선형 예측 (Nonlinear Forecasting of Daily Runoff Using Inverse Approach Method)

  • 이배성;정동국;정태성;이상진
    • 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.

DAWAST 모형의 개선 (Improvement of the DAWAST Model)

  • 이재면;김태철
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2002년도 학술발표회 발표논문집
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    • pp.249-252
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    • 2002
  • This model is the daily streamflow model of the Korean watersheds has been developed to simulate the daily streamflow with the data of daily rainfall and pan evaporation. Parameters of this model are the water balance parameters composed Umax, Lmax, FC, CP, and CE and the routing parameters composed $U_i,\;k_1\;and\;k_2$. Among these parameters, CE value is applied one fixed value during the year and coefficient of initial ion K is empirically determined by 0.2. The object of this research is to improve the DAWAST model by application of the monthly value of CE for evapotranspiration and the revised K value for the initial abstraction.

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DAWAST모형을 이용한 아노하유역의 일 유출량 추정(수공) (Estimation of Daily Streamflow for the Yalu Watershed by DAWAST Model)

  • 김태철;박철동
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2000년도 학술발표회 발표논문집
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    • pp.378-383
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    • 2000
  • The daily streamflow in the Yalu watershed located in the north-estern part of China was simulated by the DAWAST model. The parameters of model were calibrated by optimization technique with the input data of daily rainfall and pan evaporation occurred from 1997 to 1998, and they were Umax of 404mm, Lmax of 39mm, FC of 104mm, CP of 0.018, and CE of 0.003, respectively. Model verification tests were carried out with a data of 1996, and the results were generally satisfactory. Root mean square error was 0.3mm and Percent error in volume was 9.7%, and Correlation coefficient was 0.941.

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BASINS SWAT을 이용한 소유역 및 HRU 구분에 따른 유출량 변화 분석(용담댐 유역을 대상으로) (Variation analysis of Streamflow through partitioning of appropriate subwatersheds and Hydrologic Response Unit(HRU) using BASINS SWAT(Yongdam Dam Watershed))

  • 장철희;김현준;김남원
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2003년도 학술발표논문집
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    • pp.467-470
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    • 2003
  • The size, scale, and number of subwatersheds can affect a watershed modeling process and subsequent results. The objective of this study was to determine the appropriate level of subwatershed division for simulating streamflow. The Soil and Water Assessment Tool(SWAT) model with a GIS interface(BASINS SWAT) was applied to Yongdam Dam watershed. Daily output was analyzed from simulation, which was executed for 10 years using climate data representing the 1987 to 1996 period. The optimal number of subwatersheds and HRUs to adequately predict streamflow was found to be around 15, 174. Increasing the number of subwatersheds and HRUs beyond this level does not significantly affect the computed streamflow. this number of subwatersheds and HRUs can be used to optimize SWAT input data preparation requirements and simplify the interpretation of results without compromising simulation accuracy.

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임계수준 방법을 이용한 하천수 가뭄지수의 적용 (Application of Streamflow Drought Index using Threshold Level Method)

  • 성장현;정은성
    • 한국수자원학회논문집
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    • 제47권5호
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    • pp.491-500
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    • 2014
  • 하천수 가뭄을 평가하기 위하여 임계수준 방법을 이용한 하천수 가뭄지수 (streamflow drought index)를 소개하고 섬진강댐의 유입량을 대상으로 적용하였다. 사용한 임계수준은 고정, 월별 및 일별로써 연도별 가뭄의 1~3순위 분석결과, 1984년, 1988년과 1995년이 수문학적 가뭄의 크기도 컸고 오랫동안 지속되었다. 총 물 부족량과 지속기간의 극한값을 연도별로 비교해 본 바, 1984년, 1988년, 1995년과 2001년에 발생하였던 사상이 심각한 수준이었다. 또한 고정 임계수준은 계절 변동성을 반영하지못하는 단점이 있어서 최소한계절 이하의 임계수준 사용이 요구되었지만 월별과 일별로 정해진 임계수준은 적정한 것으로 판단되었다. 본 연구에서 제안한 방법론은 갈수예보 및 저수지 용량결정에 활용될 수 있겠다.