Abstract:

Over the years, floods have caused serious damage to crops in Hubei Province, restricting agricultural economy and threatening social development. It is necessary to carry out flood risk assessment in Hubei. This paper proposed a method of modeling quantitative risk assessment in Hubei Province. Fifteen indicators were extracted from multi-source data (meteorological, socio-economic, geographical characteristics and other data), and the principal component analysis method was adopted to determine the weight of each indicator on flood disaster to establish a risk assessment model, and the geographic information system (GIS) analysis technology was used to get the flood disaster risk zoning map. On the basis of the existing evaluation index system, through the way of web crawler, we obtained better disaster emergency indicators to reflect the ability of prevention and reduction, and used the principal component analysis method to reduce the subjective factors in model building. The results show that: (1) rainfall and topography are the most important factors of flood occurrence in Hubei; (2) most of the central and eastern parts of Hubei are high-risk areas, among which, Wuhan, Huangshi and other parts along the Yangtze River basin in the east are in a heavy risk area; the southwest of the province is mostly in a medium risk area, and the northwest is in a low risk area. In conclusion, this model could provide scientific support and a decision-making basis for carrying out comprehensive disaster reduction, adjusting regional sustainable development structure and monitoring agricultural production in Hubei Province, which has great scientific and practical significance.

Key words: agricultural risk assessment, flood disaster, web crawler, principal component analysis, GIS analysis