Ensemble Kalman Filtering and Particle Filtering in a Lag-Time Window for Short-Term Streamflow Forecasting with a Distributed Hydrologic Model-Reference-Cited by-同舟云学术

Ensemble Kalman Filtering and Particle Filtering in a Lag-Time Window for Short-Term Streamflow Forecasting with a Distributed Hydrologic Model

Published:2013-12 Issue:12 Volume:18 Page:1684-1696
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Noh Seong Jin¹,Tachikawa Yasuto²,Shiiba Michiharu³,Kim Sunmin⁴

Affiliation:

1. Research Specialist, Water Resources Research Division, Water Resources and Environment Research Dept., Korea Institute of Construction Technology, 2311 Daewha-Dong, Ilsan-Gu, Goyang-Si, Gyeonggi-Do 411-712, Korea (corresponding author).

2. Associate Professor, Dept. of Civil and Earth Resources Engineering, Kyoto Univ., Kyoto 615-8540, Japan.

3. Professor, Dept. of Civil and Earth Resources Engineering, Kyoto Univ., Kyoto 615-8540, Japan.

4. Lecturer, Dept. of Civil and Earth Resources Engineering, Kyoto Univ., Kyoto 615-8540, Japan.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0000751

Reference52 articles.

1. A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking

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3. Case Study: Improving Real-Time Stage Forecasting Muskingum Model by Incorporating the Rating Curve Model

4. Assimilation of Observed Soil Moisture Data in Storm Rainfall-Runoff Modeling

5. Analysis Scheme in the Ensemble Kalman Filter

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