Hydrologic information extraction for flood disaster risk assessment in Pearl River Basin and Luan River Basin, China

Author

Zhang, Jing ; Song, Linrui ; Feng, Fan ; Gong, Huili

Author_Institution

3D Inf. Acquisition & Applic. Key Lab. of Educ. Minist., Capital Normal Univ., Beijing, China

fYear

2011

fDate

24-26 June 2011

Firstpage

1

Lastpage

4

Abstract

Flood disaster is one of the major natural disasters, the frequency and destructive power of it ranks one of the top disasters in China. In the flood risk assessment, the distribution of drainage network is a very important assessment factor. This study extract the watershed features of Pearl River Basin and Luan River Basin based on the Digital Elevation Model (DEM) and GIS-supported geospatial data model (Arc Hydro). Developed by the Hydrological module in ArcGIS, Arc Hydro is a hydrologic data modeling tool for the application of water resource. This paper aims to provide reliable data for the analysis of risk assessment and level of flood disaster by extracting drainage network using Arc Hydro. The study results showed that, it is feasible and effective to extract the risk assessment factors-drainage network based on DEM and Arc Hydro.

Keywords

digital elevation models; disasters; feature extraction; floods; geographic information systems; geophysical image processing; hydrological techniques; risk management; rivers; water resources; Arc Hydro; ArcGIS; China; GIS-supported geospatial data model; Luan River Basin; Pearl River Basin; digital elevation model; drainage network; drainage network extraction; feature extraction; flood disaster risk assessment; hydrologic information extraction; natural disasters; water resource; watershed features; Data models; Feature extraction; Floods; Humans; Risk management; Rivers; Water resources; DEM; arc hydro; arcGIS; drainage network extraction; flood risk assessment;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoinformatics, 2011 19th International Conference on

Conference_Location

Shanghai

ISSN

2161-024X

Print_ISBN

978-1-61284-849-5

Type

conf

DOI

10.1109/GeoInformatics.2011.5981166

Filename

5981166