Extreme Climatic Characteristics and Their Effects on Maize Yield in Hei-longjiang Province from 1961 to 2020

This paper analyzed the extreme climatic characteristics of maize in Heilongjiang Province during different growth periods using the climate data and maize yield data from 1961 to 2020,and applied the principal component analysis to analyze the extent of different extreme climatic events affecting maize yield.The results showed that the extreme cold events showed a decreasing trend,and the extreme warm events showed an increasing trend,and the trend of extreme precipitation change was not obvious.Maize yield was negatively correlated with TN10p(cold nights),TX10p(warm days)and T8(days below the lower temperature limit),and positively correlated with TN90p(warm nights).T34(days above the upper temperature limit)and TX90p(warm days)during the tasseling-milking period were negatively correlated with the maize yield,and this part was concentrated in the southern part of Heilongjiang Province.The maize yield was positively correlated with the extreme precipitation during the seedling period and negatively correlated with the extreme precipitation during the filling-maturity period of maize,but the correlations were not significant.The effects of extreme weather events on maize yield were higher during the seedling and the filling-maturity periods than those during the jointing-tasseling and the tasseling-milking periods.The effects of extreme precipitation on the maize yield were less than those of the extreme temperature during different growth periods in all regions,but the effects of the extreme precipitation on maize yield were significantly higher in the Songnen Plain than those in other regions.There were regional differences in the impact of climate extremes on maize during different growth periods.The area with the greater impact of climate extremes during the seedling period was the Songnen Plain,the areas with the greater impact of climate extremes during the jointing-tasseling period were the northern part of the Sanjiang Plain,and the areas with the greater impact of climate extremes during the filling-maturity period were the Lesser Khingan Mountains and the semi-mountainous areas of Mudanjiang.

Assessing Maize Drought Hazard for Agricultural Areas Based on the Fuzzy Gamma Model

Drought is one of the severe meteorological disasters and causes of serious losses for agricultural productions, and early assessment of drought hazard degree is critical in management of maize farming. This study proposes a novel method for assessment of maize drought hazard in different growth stages. First, the study divided the maize growth period into four critical growth stages, including seeding, elongation, tasseling, and filling. Second, maize drought causal factors were selected and the fuzzy membership function was established. Finally, the study built a fuzzy gamma model to assess maize drought hazards, and the gamma 0.93 was finally established using Monte Carlo Analysis. Performing fuzzy gamma operation with 0.93 for gamma and classifying the area yielded a map of maize drought hazards with four zones of light, moderate, severe, and extreme droughts. Using actual field collected data, seven selected samples for drought hazard degree were examined, the model output proved to be a valid tool in the assessment maize drought hazard. This model will be very useful in analyzing the spatial change of maize drought hazard and influence on yield, which is significant for drought management in major agricultural areas.