Risk assessment model of agricultural drought disaster based on grey matter-element analysis theory

Abstract

Carrying out risk assessments of agricultural drought disasters is helpful to understanding agricultural drought quantitatively and scientifically guiding drought prevention and drought relief work. In this paper, the risk assessment system and evaluation index of drought disasters are constructed, and they are composed of a drought risk subsystem, drought exposure subsystem, disaster damage sensitivity subsystem and drought resistance subsystem. Based on the grey matter-element analysis method, the agricultural drought risk evaluation model was established. Grey matter-element analysis method was used to evaluate the risk of agricultural drought in 18 regions of Henan Province, China in 2019. The results validation showed that high drought disaster risk area in Henan province is located in the western, north and the central area. This study provides a new method for the risk assessment of agricultural drought disasters. Understanding the risk in the study area can improve agricultural system resilience. This model could be used to provide support for increasing agricultural drought disaster resilience and risk management efficiency.

Application progress of grey model technology in agricultural science

“…Through principal component analysis, grey clustering analysis, support vector machine and other methods, Qiao et al (2014) can accurately monitor the condition of wheat take-all disease through near-earth imaging spectral images, which has guiding significance for the control of wheat take-all disease. In order to quantitatively evaluate the vulnerability of regional agricultural drought and identify the main indicators that affect its intensity change, scholars have established regional agricultural drought vulnerability evaluation model and agricultural drought risk evaluation model based on grey correlation evaluation and grey cluster evaluation, which provides a new method for agricultural disaster risk assessment (Jin et al , 2019; Xu et al , 2021a). Lou et al have successively built the grey cloud clustering model (Luo et al , 2020) and the particle swarm optimization grey clustering coefficient vector model (Luo et al , 2021) based on panel data, and evaluated the agricultural drought disaster risk in Henan Province.…”