Spatiotemporal distribution of agrometeorological disasters in China and its impact on grain yield under climate change

Abstract

Agrometeorological disasters (AMDs) in the context of climate change pose a great threat to agricultural production and food security in China. This study analyzed spatiotemporal characteristics of five types of AMDs (drought, flood, hail, low-temperature freezing and snow (LTFS), and typhoon) in China, assessed the impacts of AMDs on meteorological yield, and explored the influences of extreme climate on AMDs and meteorological yield. The results demonstrated that the total covered rate of AMDs generally showed a decreasing trend from 1978 to 2020 in China. The covered rates of drought, flood, and hail had significant downward trends, while the covered rates of the LTFS and typhoons had insignificant increasing trends. The AMDs’ structure in different regions obviously changed after 2010. In addition, Pearson correlation analysis revealed that the covered rates of drought, flood, and typhoon were affected by the extreme precipitation indicators, and hail and LTFS were affected by the extreme temperature indicators. The increases of extreme temperature led to the decrease of the meteorological yield, while the effect of extreme precipitation on meteorological yield varied from region to region. This study provides significant references for guiding disaster mitigation.