• Title/Summary/Keyword: stochastic continuous storage function

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Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (I) : Model Development (앙상블 칼만필터를 연계한 추계학적 연속형 저류함수모형 (I) : - 모형 개발 -)

  • Bae, Deg-Hyo;Lee, Byong-Ju;Georgakakos, Konstantine P.
    • Journal of Korea Water Resources Association
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    • v.42 no.11
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    • pp.953-961
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    • 2009
  • The objective of this study is to develop a stochastic continuous storage function model for enhancement of an event-oriented watershed and channel storage function models which have been used as an official flood forecast model in Korea. For this study, soil moisture accounting component is added to the original storage function model and each hydrologic component, such as surface flow, subsurface flow, groundwater flow and actual evaportranspiration, is simulated as a function of soil water content. And also, ensemble Kalman filtering technique is used for real-time assimilation of measured streamflow from various stream locations in the watershed. Therefore the enhanced model will be able to simulate hydrologic components for long-term period without additional estimation of model parameters and to give more accurate and reliable results than those from the existing deterministic model due to the assimilation of measured streamflow data.

Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (II) : Application and Verification (앙상블 칼만필터를 연계한 추계학적 연속형 저류함수모형 (II) : - 적용 및 검증 -)

  • Lee, Byong-Ju;Bae, Deg-Hyo;Shamir, Eylon
    • Journal of Korea Water Resources Association
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    • v.42 no.11
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    • pp.963-972
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    • 2009
  • The objective of this study is to evaluate an application of stochastic continuous storage function model with ensemble Kalman filter technique. The case study is performed at the upstream basin of Jibo streamflow gauge including Andong and Imha dam. Test period is for the rainy season during 2006 and 2007. Long term runoff analysis is feasible in the case of using deterministic model. Ensemble members for input data and parameters are generated using Monte Carlo simulation for the purpose of applying ensemble Kalman filter technique. The cumulative absolute errors of stochastic model to the deterministic one are improved for the amount of 17.5 %, 18.3 % and more than 40.0 % for Andong dam, Imha dam and Jibo station, respectively. The results indicate that the stochastic model improves the accuracy of the simulated discharge considerably.

A Study on the Development of the Stochastic Continuous Storage Function Model (추계학적 연속형 저류함수 모형 개발에 관한 연구)

  • Lee, Byong-Ju;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2009.05a
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    • pp.231-235
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    • 2009
  • 본 연구에서는 홍수예보를 위한 사상형 모형인 저류함수모형 적용시 문제점을 개선하기 위해 기존의 저류함수 모형에 자유수와 장력수의 2개 영역으로 구성된 토양수분모의 컴포넌트를 결합하여 지표유출, 중간유출, 기저유출의 유출수문성분에 대한 연속적인 모의가 가능하도록 하였으며 실시간 홍수예측을 위해 다수의 유량 관측지점과의 실시간 오차 보정이 가능하도록 앙상블 칼만 필터링 기법을 도입하였다. 개발된 모형의 적용성을 평가하기 위해 낙동강 권역을 대상유역으로 선정하였으며 시단위 강우자료, 기상자료, 유량자료를 비롯하여 GIS를 기반의 지형자료를 구축하였다. 연속형 저류함수형의 매개변수 추정결과 주요지점의 관측유량에 대해 높은 적합도를 보였으며 1시간 선행시간의 홍수량 예측결과에서도 높은 정확도를 보이는 것으로 나타났다.

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