Title
Investigation into Feasibility of Data Assimilation Approach for Flood Level Estimation Using Temporal-Spatial State Space Model.
Abstract
This study presents flood level estimation using state space model. Traditional water-level sensors for large-scale river can detect water-level rising, though they have limitations in detecting urban flooding depth. Therefore, we propose a flood estimation method, which integrate observed data and flood analysis simulation with minimizing the number of water-level sensors. The estimation method of this research consists of three procedures: flood simulation using a continuity equation and motion equations, compensation using geographic characteristics and data assimilation using temporal-spatial state space model. We apply state space model to actual flooding data of Typhoon in 2017. The analysis result shows that estimated values agree with the observed values. This study is an approach to know the flood level in the urban area with the limited observation data for detecting the real-time flooding of small rivers and waterways, and the flooding process of living areas like the street.
Year
DOI
Venue
2019
10.1109/BIGCOMP.2019.8679235
BigComp
Keywords
Field
DocType
Mathematical model,Estimation,Data models,Rivers,Analytical models,Simulation,Floods
Meteorology,Data modeling,Continuity equation,Typhoon,State-space representation,Environmental science,Data assimilation,Flooding (psychology),Urban area,Flood myth
Conference
ISSN
ISBN
Citations 
2375-933X
978-1-5386-7789-6
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Kei Hiroi11912.00
Daisuke Murakami200.34
Kazumi Kurata301.01
Takashi Tashiro400.34