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STUDY AND APPLICATION OF FLOOD CONTROL RISK TREND ANALYSIS MODEL

Authors :
S. Song
M. Zhang
S. Yang
F. Dong
Y. Liu
L. Chen
N. Tang
S. Wang
Z. Xiao
Source :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLVIII-5-W1-2023, Pp 37-44 (2023)
Publication Year :
2023
Publisher :
Copernicus Publications, 2023.

Abstract

In order to analyze the comprehensive risks of natural disasters quantitatively and improve the accuracy of natural disaster management and control, this paper expands the F indicator, Forecast, which is about real-time monitoring and early warning data of natural disasters, and forms the flood control risk trend analysis model framework based on PSR. The framework is named FPSR, i.e. Forecast-Pressure-State-Response, composed of static data and dynamic data. By establishing the four-level index system of flood control risk trend analysis in Fangshan District of Beijing, screening factors, and using analytic hierarchy process, AHP, and experts scoring to determine the weights of each factor, it constructs the flood control risk trend analysis model, FCRTAM. At last, using the real-time monitoring and early warning data of natural disasters in Beijing and the information such as disaster-causing factors, historical natural disasters, major hidden dangers, disaster-bearing bodies, disaster reduction resources (capacities), etc., from National Natural Disaster Comprehensive Risk Census in Fangshan, it analyzes the flood control situation of each town in Fangshan. The results show that the results flood control risk index calculated according to FCRTAM is basically consistent with the actual flood control situation of the towns in Fangshan, and can provide theoretical basis for flood control comprehensive risk trend analysis and the decision-making of disaster prevention and reduction in Fangshan District, which has high use value.

Details

Language :
English
ISSN :
16821750 and 21949034
Volume :
XLVIII-5-W1-2023
Database :
Directory of Open Access Journals
Journal :
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.4fe1023737094fb4baf792e9e64a614b
Document Type :
article
Full Text :
https://doi.org/10.5194/isprs-archives-XLVIII-5-W1-2023-37-2023