Change Characteristics of Climate and Main Agricultural Meteorological Disasters in Shiyang River Basin

Based on 35 a meteorological data and main crops planting data in Shiyang River basin meteorological station,the agricultural climate change,agricultural production,hydrology change and the influences on the crops layout,planting in the basin were discussed.The results showed that the linear inclined rates of ≥0 ℃,10 ℃ accumulated temperature increase in the north-central part were bigger than in the south,and the heat resources increased evidently.The annual precipitation increased in the linear inclined rate which was 4.719 mm/10 a,and the annual runoff decreased in 0.274×109 m3/10 a velocity.The climate productivity increased in 134.62 kg/(hm2·10 a) velocity.In late spring and early summer,the regional drought increased evidently,and the frostless period prolonged.The sand storm decreased evidently.The gale in the south increased and decreased in the north-central part.The agricultural climate change made that the spring wheat planting zone advanced to the high-altitude area.The seeding date advanced,and the growth period shortened.It didn't favor for the yield formation.However,it was favorable to improve the yield and quality of thermophilous crops such as the corn,cotton and wine grape and so on.

Research Overview of Chinese Agricultural Meteorological Disaster Risk Assessment

This paper summarized the key concepts, evaluation principle and meth-ods of the agricultural meteorological disaster risk, then reviewed the research progress of main agricultural meteorological disaster risk assessment. The aim is to provide the reference of the system theory and method of agricultural meteorological disaster risk assessment.

Characteristics and risk assessment of agricultural meteorological disasters based on 30 years’disaster data from Heilongjiang Province of China

To determine the influence of agricultural meteorological disasters on agriculture in Heilongjiang Province,the disaster areas associated with different types of disasters and their variation characteristics were analyzed based on the statistical data of agricultural disasters from 1983 to 2013 in Heilongjiang Province,China.The moving average and the Mann-Kendall test were applied to identify the variation trends of drought,flooding,hailstorms and freezing(based on the disaster ratio and the disaster intensity index).Then,the Morlet wavelet analysis method was used to identify the periodicity of these four kinds of agricultural meteorological disasters.Finally,a fuzzy comprehensive evaluation method was adopted to analyze the degrees of agricultural loss induced by these disasters.The following results were obtained:1)The disaster ratio and disaster intensity index for drought exhibited increasing trends;the disaster ratio and disaster intensity index for flooding exhibited decreasing trends;for hailstorms,the disaster ratio exhibited no obvious trend of change,whereas the disaster intensity index exhibited an increasing trend;and for freezing,the disaster ratio also exhibited no obvious trend of change,whereas the disaster intensity index exhibited a decreasing trend.2)Mutation points were observed in the disaster ratio series for drought,flooding and hailstorms,whereas no mutation point was evident in the disaster ratio series for freezing.3)Multiple time-scale characteristics were observed in the disaster ratio series for all four types of agricultural meteorological disasters.Furthermore,the disaster ratio series for the different types of disasters had different main periodicities.4)From the perspective of the degree of agricultural loss induced by each type of disaster,drought was identified as the most severe type of agricultural meteorological disaster,followed by flooding,freezing,and hailstorms.The degree of agricultural loss caused by each type of disaster was different during different periods.Finally,based on the results,several strategies were identified for mitigating the effect of agricultural meteorological disasters in Heilongjiang Province.