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JDR Vol.14 No.2 pp. 260-268
(2019)
doi: 10.20965/jdr.2019.p0260

Paper:

Development of a Practical River Water Level Prediction Method Using Data Assimilation Technique

Shuichi Tsuchiya and Masaki Kawasaki

River Department, National Institute for Land and Infrastructure Management (NILIM)
1 Asahi, Tsukuba, Ibaraki 305-0804, Japan

Corresponding author

Received:
October 9, 2018
Accepted:
January 18, 2018
Published:
March 1, 2019
Keywords:
flood forecast, data assimilation, particle filter, flood risk line
Abstract

With the aim of accurately predicting river water levels a few hours ahead in the event of a flood, we created a river water level prediction model consisting of a runoff model, a channel model, and data assimilation technique. We also developed a cascade assimilation method that allows us to calculate assimilations of water levels observed at multiple points using particle filters in real-time. As a result of applying the river water level prediction model to Arakawa Basin using the assimilation technique, it was confirmed that reproductive simulations that produce results very similar to the observed results could be achieved, and that we would be able to predict river water levels less affected by the predicted amount of rainfall.

Cite this article as:
S. Tsuchiya and M. Kawasaki, “Development of a Practical River Water Level Prediction Method Using Data Assimilation Technique,” J. Disaster Res., Vol.14, No.2, pp. 260-268, 2019.
Data files:
References
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Last updated on May. 22, 2019