Abstract

Studying the causes of drought is important because the formation of large regional droughts is linked to global atmospheric system abnormalities in China. Information about the effects of drought on crop production is needed in order to improve understanding of a region’s drought vulnerability and to improve food production safety in the North China Plain. This paper uses agricultural statistics and monthly Southern Oscillation Index data between 1961 and 2007 to quantitatively evaluate regional agricultural meteorological disasters and to assess the regressive models used to predict the grain yield and climatic yield losses caused by drought disasters. The data showed that the drought-covered area ratios declined, but the drought-affected area ratios rose. During the La Nina stage, the probability of a drought disaster was higher than during the El Nino stage, especially in Hebei. In the El Nino years, there were negative trends for the drought-covered, -affected and -destroyed area ratios in winter and positive trends in the other three seasons. In the La Nina years, the drought disaster area ratios were positive for all seasons. In Neutral years, there was more likely to be a drought event in autumn. The regression analyses for the three provinces showed that the grain climatic yield loss was significantly associated with the grain yield loss caused by drought disasters. This showed that regional grain yield simulations and evaluations of agro-meteorological disasters reliably predicted the field measured statistical data for drought disasters. Therefore, our results showed that there is a mixed seasonal trend in the drought disaster areas in the El Nino years, but a consistent upward trend for all seasons in the La Nina years. We also showed that the damage caused by drought disasters can be quantified by estimating the yield loss.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.