Drought Vulnerability Assessment of Winter Wheat Using an Improved Entropy–Comprehensive Fuzzy Evaluation Method: A Case Study of Henan Province in China

Abstract

The percentage precipitation anomaly was used to index the effect of drought on winter wheat grown in Henan Province for the years 2011–2020. Of interest was the effect of drought on winter wheat yield and the accurate assessment of the damage done to winter wheat by drought events in order to improve the risk management of winter wheat in the context of drought hazards. The spatial and temporal variability of winter wheat drought risk in Henan Province was determined by analysis of climate data, winter wheat yield, cultivated area, and socio-economic data across three dimensions: exposure or susceptibility to drought, economic–environmental sensitivity to drought, and capacity to resist drought. A drought vulnerability assessment model, based on the entropy value method and a comprehensive fuzzy evaluation, was developed to assess the drought vulnerability of winter wheat in Henan Province compared with the percentage precipitation anomaly model. (1) There were significant spatial differences in the frequency of the five drought categories devised. (2) Areas in which there was a high frequency of mild drought events were mainly in northern and western Henan and southwestern Henan, with the frequency ranging from 17% to 29%. (3) Areas in which there was a high frequency of moderate drought events were mainly in northwestern, central, and southeastern Henan. (4) Areas in which there was a high frequency of severe and extreme drought were mainly in Anyang in northern Henan, Zhengzhou in central Henan, and Xinyang and surrounding areas in southern Henan, with the frequency ranging from 7% to 9.70%. (5) Winter wheat drought vulnerability shows an overall annually increasing trend. The susceptibility dimension had the greatest influence of the three dimensions, followed by economic–environmental sensitivity and then drought resistance, which had the least impact. The model created in this study shows the influence of drought on winter wheat production more intuitively than a conventional fuzzy synthesis, and the results can inform decision-making in winter wheat drought risk assessment and management.