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基于当量积温对寒地水稻生长季低温冷害年的判定
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  • 英文篇名:Identification on Cold Damage Year Based on Accumulated Equivalent Temperature during Rice Growth Season in Cold Region
  • 作者:朱海霞 ; 吕佳佳 ; 闫平 ; 曲辉辉 ; 王萍 ; 于瑛楠 ; 王秋京 ; 李秀芬 ; 李百超
  • 英文作者:ZHU Hai-xia;LV Jia-jia;YAN Ping;QU Hui-hui;WANG Ping;YU Ying-nan;WANG Qiu-jing;LI Xiu-fen;LI Bai-chao;Innovation and Opening Laboratory of Regional Eco-Meteorology in Northeast China/Meteorological Academician Workstation of Heilongjiang Province/Heilongjiang Province Institute of Meteorological Sciences;Heilongjiang Meteorological Bureau;
  • 关键词:延迟型冷害 ; 当量积温 ; 距平百分率 ; 冷害年 ; 冷害程度
  • 英文关键词:Delayed-growth type cold damage;;Accumulated equivalent temperature;;Departure percent;;Cold damage year;;Cold damage degree
  • 中文刊名:ZGNY
  • 英文刊名:Chinese Journal of Agrometeorology
  • 机构:中国气象局东北地区生态气象创新开放实验室/黑龙江省气象院士工作站/黑龙江省气象科学研究所;黑龙江省气象局;
  • 出版日期:2019-06-13
  • 出版单位:中国农业气象
  • 年:2019
  • 期:v.40
  • 基金:中国气象局沈阳大气环境研究所中央级公益性科研院所基本科研业务费专项(2016SYIAEZD1);中国气象局东北地区生态气象创新开放实验室开放研究基金(stqx201804);; 国家自然科学基金(31671575)
  • 语种:中文;
  • 页:ZGNY201906005
  • 页数:11
  • CN:06
  • ISSN:11-1999/S
  • 分类号:44-54
摘要
基于水稻生物学性质,根据气温昼夜节律和水稻温强系数研究成果,从热量影响水稻发育的多种角度出发,设计当量积温、负当量积温、热量匹配累积指数三种水稻生长季热量表征指标,研究寒地水稻低温冷害的判识方法。采用21a滑动平均法,获得黑龙江省1971-2016年水稻生长季各热量指标的距平百分率,分析其对低温冷害的判识能力。结果表明:各热量指标距平百分率取值越低,对冷害的指示能力越高;利用加权隶属度模型构建三者综合距平百分率冷害判定模型,距平百分率>-5%为无冷害,-10%<距平百分率≤-5%为轻度冷害,-15%<距平百分率≤-10%为中度冷害,距平百分率≤-15%为重度冷害;综合距平百分率能够判识水稻生长季的低温冷害,且能反映冷害程度,对典型冷害年的判识准确率达100%;黑龙江省冷害群发性特征非常明显,如1971、1972、1976、1981、1983、1992、2002和2009年典型冷害年,不仅冷害发生区域广,且冷害程度较重;1986、1987、1989、1993、1995和2003年为轻度或局地冷害年。
        Based on rice biological characteristics, circadian temperature rhythm and temperature coefficient, taking accumulated equivalent temperature, negative accumulated equivalent temperature and heat matching index as index,the identification method for cold damage year was studied. By using moving average method on 21 years, departure percent was obtained for three factors in Heilongjiang province from 1971 to 2016, and the identifiable ability was analyzed. The results showed that identification ability was stronger, when the departure percent of every factor decreased more. This identification model for cold damage based on integrative departure percent was established by using weighted membership model. When departure percent was above-5%, named as zero cold damage year, when departure percent was above-10% and below-5%, named as slight cold damage year, when departure percent was above-15% and below-10%, named as moderate cold damage year, and when departure percent was below-15%,named as severe cold damage year. Integrative departure percent could indicate cold damage during rice growing season, and could reflect different degrees of cold damage, and totally indicated typical cold damage years. Cold damage performed a feature of outbreak in Heilongjiang province, for example in 1971, 1972, 1976, 1981, 1983,1992 and 2009. In these years, cold damage extended over extensive regions, and the damage degree was more severe, the other damage year was slight degree or regional damage, including 1986, 1987, 1989, 1993, 1995 and2003.
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