Risk Assessment of Agricultural Drought Disaster on the Huaibei Plain of China Based on the Improved Connection Number and Entropy Information Diffusion Method

Abstract

In recent years, drought disaster has occurred frequently in China, causing significant agricultural losses. It is increasingly important to assess the risk of agricultural drought disaster (ADD) and to develop a targeted risk management approach. In this study, an ADD risk assessment model was established. First, an improved fuzzy analytic hierarchy process based on an accelerated genetic algorithm (AGA-FAHP) was used to build an evaluation indicator system. Then, based on the indicators, the ADD assessment connection numbers were established using the improved connection number method. Finally, the entropy information diffusion method was used to form an ADD risk assessment model. The model was applied to the Huaibei Plain in Anhui Province (China), with the assessment showing that, in the period from 2008 to 2017, the plain was threatened continuously by ADD, especially during 2011–2013. The risk assessment showed that southern cities of the study area were nearly twice as likely to be struck by ADD as northern cities. Meanwhile, the eastern region had a higher frequency of severe and above-grade ADD events (once every 21 years) than the western region (once every 25.3 years). Therefore, Huainan was identified as a high-risk city and Huaibei as a low-risk city, with Suzhou and Bengbu more vulnerable to ADD than Fuyang and Bozhou. Understanding the spatial dynamics of risk in the study area can improve agricultural system resilience by optimizing planting structures and by enhancing irrigation water efficiency. This model could be used to provide support for increasing agricultural drought disaster resilience and risk management efficiency.

Quantitative Evaluation and Obstacle Factor Diagnosis of Agricultural Drought Disaster Risk Using Connection Number and Information Entropy

“…By the normalization of Formula (6), the components of ternary connection number for evaluation index of agricultural drought disaster risk can be finally obtained [ 33 ]: …”

“…According to the weight of index j in subsystem k obtained by Formula (1), i.e., w kj , calculate the ternary connection number of subsystem k for sample i , i.e., u ik [ 33 ]: …”

“…Set pair analysis is a new quantitative analysis method of uncertainty [ 32 ]. The identical–different–inverse relation structure of the connection number for the set pair composed of two sets, i.e., evaluation sample and evaluation criteria, can be used to fully reflect the certainty and uncertainty between these two sets, which has been widely applied to natural disasters risk evaluation [ 33 ]. Wang et al [ 34 ] proposed a set pair analysis method for the evaluation of flood damage risk.…”

“…Wang et al [ 44 ] assessed the agricultural drought disaster risk based on the set pair analysis theory. Chen et al [ 33 ] conducted the risk assessment of agricultural drought disasters using the improved connection number and entropy information diffusion. Jin et al [ 30 ] adopted semipartial subtraction set pair potential of ternary connection number to evaluate the drought disaster risk and identify its influencing factors.…”

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

“…Some use statistical methods to analyse precipitation index (SPI) and crop yield to further evaluate the risk of agricultural drought on crops (Todisco et al 2013). Other people use probabilistic risk estimation model or introducing fuzzy mathematics into risk estimation to propose the definition of probability risk (Cui et al 2018;Wilhelmi and Wilhite 2002;Chen et al 2020;Shuqi et al 2019). Factor analysis evaluation model is also useful.…”