Real-time flood simulations using CA model driven by dynamic observation data

被引：26

作者：

Li, Yi ^{[1
,2
]}

Gong, Jianhua ^{[1
,2
]}

Liu, Heng ^{[3
]}

Zhu, Jun ^{[4
]}

Song, Yiquan ^{[5
]}

Liang, Jianming ^{[1
,2
]}

机构：

[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing, Peoples R China

[2] Zhejiang CAS Applicat Ctr Geoinformat, Jiaxing, Zhejiang, Peoples R China

[3] Res Inst Water Resources & Hydropower, Shenyang, Liaoning, Peoples R China

[4] Southwest Jiaotong Univ, Chengdu, Sichuan, Peoples R China

[5] Tianjin Normal Univ, Coll Urban & Environm Sci, Tianjin, Peoples R China

来源：

INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE | 2015年 / 29卷 / 04期

基金：

中国国家自然科学基金;

关键词：

virtual geographic experiment; cellular automata; dynamic data-driven; flood simulation; INUNDATION MODELS; CALIBRATION; GEOGRAPHY; GLUE;

D O I：

10.1080/13658816.2014.977292

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

It is difficult to obtain accurate simulation results without observation data. So using real-time dynamic observation data in the simulation process has become an academic frontier of international research. This paper is a probing research on the data-driven adaptive modeling and automatic refactoring methods of flood routing simulation. A cellular automata (CA) data-driven flooding model was developed using the Hunhe River in Shenyang City as a case study. The proposed model can increase the accuracy of simulations by calculating differences in the water stages using high temporal resolution observational data. Meanwhile, corresponding parameter analysis was carried out based on the proposed CA model and the best lagging time between simulation and observation was discussed.

引用

页码：523 / 535

页数：13

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