Chinese Journal of Agrometeorology ›› 2018, Vol. 39 ›› Issue (04): 280-291.doi: 10.3969/j.issn.1000-6362.2018.04.007

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Grain Yield Loss Evaluation Based on Agro-meteorological Disaster Exposure in the Middle-Lower Yangtze Plain

ZHANG Yi,LIU Bu-chun,YANG Xiao-juan,LIU Yuan,BAI Wei,DONG Bo-chao   

  1. 1.Institute of Environment and Sustainable Development in Agriculture, CAAS/National Engineering Laboratory of Efficient Crop Water Use and Disaster Reduction/Key Laboratory of Agricultural Environment, MOA, Beijing 100081, China; 2.College of Agronomy, Shenyang Agricultural University, Shenyang 110866
  • Received:2017-07-21 Online:2018-04-20 Published:2018-04-17

Abstract: Multiple linear regression analysis was used to identify the relationship between grain climate yield loss and the covered, affected and destroyed areas of crop, based on statistical data of crop disasters and grain yield (1949-2014) in the Middle Lower Yangtze Plain. Principal component analysis (PCA) was used to evaluate the impacts of main agro-meteorological disasters on grain climate loss. The results showed that the grain climate yield loss was significantly correlated with the whole disaster exposure at the province level (P<0.05), and the correlation also reached extremely significant (P<0.01), except for Hunan province. Specifically, the affected area was more closely related to grain climate yield loss. The coefficients of determination (R2) of the whole disaster exposure of yield regression models were over 0.9 except for shanghai city. According to the correlation between grain climate yield and drought, flood, windstorm, chilling, and typhoon to establish the main disaster exposure yield model, R2 of model was higher than the whole disaster exposure yield model, except for Hunan province. However, there was no significant difference between the two models based on single factor variance analysis. Two types of model error were mainly due to the fluctuation of grain crop planting structure. The model of disaster damage and yield assessment established in this study simulated the relationship between disaster exposure and grain yield. The predication results indicated that the disaster exposure model would be used as the short-term prediction for grain yield in the Middle Lower Yangtze Plain by using the data of disaster area in 2015.

Key words: The loss caused by disasters, Meteorological disaster, Yield simulation model, Losing rate, Disaster loss evaluation