Abstract
Abstract This article combines geographic information system (GIS) technology and database technology to analyse agricultural, natural disasters. The article uses a fractional linear regression equation to define the comprehensive intensity grading standard of the disaster-causing factors of torrential rain. At the same time, we use GIS to superimpose the agricultural vulnerability index into the storm disaster risk zoning to obtain the degree of agricultural impact under different levels of risk. At the end of the thesis, the model is applied to actual case analysis to verify the effectiveness of the algorithm model.
Highlights
Global warming has led to an increase in the frequency of burdensome precipitation events in most regions
Some scholars obtained the evaluation model of Weifang City’s agricultural economic loss rate based on the disaster loss rate index and the comprehensive disaster evaluation index combined with geographic information system (GIS) technology
This study comprehensively considered the type of rainfall area, the intensity, and duration of the rainfall and determined the disaster-causing index of the rainstorm disaster
Summary
Global warming has led to an increase in the frequency of burdensome precipitation events in most regions. Foreign scholars have done a lot of research on the methods of storm disaster risk assessment They believe that the formation of disasters results from the comprehensive effects of the carrier’s vulnerability, hazards and exposure [1]. Domestic research on torrential rain disasters mainly focuses on disaster-causing indicators, risk assessment models and zoning methods. Many studies use the frequency of heavy rain disasters as disaster indicators for risk assessment This method can only describe the number of disasters singly and cannot efficiently assess the degree of risk of disasters. The disaster indicators of torrential rains must consider the type of area, intensity, and duration of occurrence to have pertinence and practical guiding significance. Some others comprehensively consider disaster-causing factors, disaster-bearing bodies and disaster prevention capabilities to build a model to assess the risk of heavy rain disasters in Fujian Province. This article provides a timely and efficient scientific basis for disaster relief decision-making and post-disaster reconstruction
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