Open AccessDevelopment of a Practical River Water Level Prediction Method Using Data Assimilation Technique
Author(s) -
Shuichi Tsuchiya,
Masaki Kawasaki
Publication year - 2019
Publication title -
journal of disaster research
Language(s) - English
Resource type - Journals
eISSN - 1883-8030
pISSN - 1881-2473
DOI - 10.20965/jdr.2019.p0260
Subject(s) - data assimilation , assimilation (phonology) , environmental science , surface runoff , flood myth , cascade , hydrology (agriculture) , drainage basin , meteorology , geology , geotechnical engineering , ecology , geography , engineering , linguistics , cartography , chemical engineering , biology , archaeology , philosophy
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.