Spatiotemporal Characteristics and Change Trend of Continuous Rainfall during Cotton's Growing Stages in Hebei Province
Based on meteorological data and observed cotton growing data of cotton growing area in Hebei Province from 1971 to 2020,the spatiotemporal characteristics and change trend of continuous rainfall(CR)were analyzed by linear regression analysis,Mann-Kendall trend test,re-scaled range(R/S)analysis and non-periodic cycle analysis,etc.The results showed that the CR with high intensity and heavy impacts occurred mainly from late June to early September,and the most prominent period was from early July to mid-August.The probability and intensity of CR from high to low were flower-boll stage＞squaring stage＞boll opening stage＞seeding stage.The CR in south of Baoding,west of Hengshui,Shijiazhuang,Xingtai and Handan mainly occurred during flower-boll stage and boll opening stage,while the CR in other cotton planted areas mainly occurred during flower-boll stage and squaring stage.Handan,Xingtai,south of Hengshui,west of Shijiazhuang,mid-west of Baoding,north of Tangshan and Qinhuangdao were worse-hit areas of CR,while the other cotton planted areas were the light-hit areas of CR.As obvious mutation of rainy days and sunshine duration during continuous rainfall process occurred in 1989,the rainy days entered high value period,sunshine duration entered low value period and occurrence station times of CR entered obvious rising period.The rainy days and sunshine duration during continuous rainfall process showed significant upward and downward trends respectively in past 50 years.The future trends are consistent with the past trends,and the average cycle durations are 9～11 years.The variation of rainy days and sunshine duration resulted in the continuous increasing trend of the occurrence station times of CR in the past 50 years and the next 10 years.Overall,the risk of CR will increase in the future and the defensive measure should be strengthened.
CottonContinuous rainfall disasterEvolution characteristicsChange trendHebei Province
国家科技期刊平台
NSTL
万方数据
