Agricultural drought vulnerability assessment and diagnosis based on entropy fuzzy pattern recognition and subtraction set pair potential

Rongxing Zhou; Juliang Jin; Yi Cui; Shaowei Ning; Xia Bai; Libing Zhang; Yuliang Zhou; Chengguo Wu; Fang Tong

Alexandria Engineering Journal (Jan 2022)

Agricultural drought vulnerability assessment and diagnosis based on entropy fuzzy pattern recognition and subtraction set pair potential

Rongxing Zhou,
Juliang Jin,
Yi Cui,
Shaowei Ning,
Xia Bai,
Libing Zhang,
Yuliang Zhou,
Chengguo Wu,
Fang Tong

Affiliations

Rongxing Zhou: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Juliang Jin: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Yi Cui: Corresponding author.; School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Shaowei Ning: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Xia Bai: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Libing Zhang: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Yuliang Zhou: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Chengguo Wu: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China
Fang Tong: School of Civil Engineering, Hefei University of Technology, Hefei 230009, China; Institute of Water Resources and Environmental Systems Engineering, Hefei University of Technology, Hefei 230009, China

Journal volume & issue: Vol. 61, no. 1
pp. 51 – 63

Abstract

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The assessment and diagnosis of agricultural drought vulnerability is the basis for the scientific control and prevention of agricultural drought risk. In order to quantitatively evaluate the regional agricultural drought vulnerability and effectively deal with the fuzziness and randomness between evaluation sample and evaluation grade, the entropy fuzzy pattern recognition model, which was coupled with maximum information entropy principle and fuzzy pattern recognition method, was applied to the evaluation of agricultural drought vulnerability. Furthermore, in order to find methods to reduce drought vulnerability, the subtraction set pair potential method was used to further identify the main influence factors of agricultural drought vulnerability. In addition, a case study was carried out in Bengbu City, China. The results showed that during the period from 2001 to 2010, the evaluation value of agricultural drought vulnerability in Bengbu dropped from grade IV to III, which meant that the tolerance of agricultural system to drought had been improved. Moreover, the main factors that affected the vulnerability in Bengbu were precipitation, water use efficiency and irrigation protection area rate. And the latter two were the main objects of regulation and control. Compared with the other three methods, the physical concept of drought vulnerability assessment model based on entropy fuzzy pattern recognition is more obvious, and the evaluation results are reasonable and credible. The drought vulnerability diagnosis method based on subtraction set pair potential can accurately identify key influence factor and provide measures to reduce drought vulnerability and improve drought risk management.

Published in Alexandria Engineering Journal

ISSN: 1110-0168 (Print); 2090-2670 (Online)
Publisher: Elsevier
Country of publisher: Egypt
LCC subjects: Technology: Engineering (General). Civil engineering (General)
Website: http://www.journals.elsevier.com/alexandria-engineering-journal/

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