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生态学杂志 ›› 2024, Vol. 43 ›› Issue (10): 3040-3046.doi: 10.13292/j.1000-4890.202410.003

• 研究论文 • 上一篇    下一篇

高寒区大豆苗期低温多雨对产量的影响

曲辉辉1,李秀芬1,朱海霞1,王晾晾1,曲秉阳2,王秋京1,吕佳佳1,纪仰慧1,姜丽霞1*

  

  1. 1黑龙江省气象科学研究所, 中国气象局东北地区生态气象创新开放实验室, 哈尔滨 150030; 2黑龙江省气象数据中心, 哈尔滨 150030)

  • 出版日期:2024-10-10 发布日期:2024-10-11

Effects of low temperature and excessive precipitation at seedling stage on soybean yield in high-latitude cold region.

QU Huihui1, LI Xiufen1, ZHU Haixia1, WANG Liangliang1, QU Bingyang2, WANG Qiujing1, LYU Jiajia1, JI Yanghui1, JIANG Lixia1*   

  1. (1Heilongjiang Province Institute of Meteorological Science, Innovation and Open Laboratory of Regional Eco-Meteorology in Northeast, China Meteorological Administration, Harbin 150030, China; 2Heilongjiang Meteorological Data Center, Harbin 150030, China).

  • Online:2024-10-10 Published:2024-10-11

摘要: 探究大豆苗期低温多雨对产量的影响,为大豆防灾减灾提供依据。基于黑龙江省大豆生长发育观测资料及已有研究成果,对WOFOST模型进行本地化与适应性检验;利用研究区内15个代表站点1971—2020年逐日气象资料、分区作物参数与土壤参数,模拟不同低温多雨情景下大豆产量,定量评价苗期低温多雨对大豆产量的影响。结果表明:WOFOST模型在黑龙江省本地化应用效果较好,可用于该地区大豆产量的模拟;在设定情景中,低温、多雨及二者叠加效应均会造成大豆减产,减产率存在极显著差异,叠加效应持续天数是导致产量降低的最主要因素;t-3.5情景持续6 d未对大豆产量造成显著影响,部分t-3.5处理持续12 d与大部分持续18 d情景则会造成大豆产量显著或极显著下降;在灾害持续时间和发生程度相同的前提下,低温与多雨叠加发生比二者单独发生对大豆产量影响更大。


关键词: 大豆, 低温多雨叠加效应, WOFOST模型, 产量, 苗期

Abstract: The effects of low temperature and rainy weather at seedling state on soybean yield were examined to provide basis for the prevention and reduction of soybean disaster. The localization and adaptability of WOFOST model were firstly tested based on the observation data of soybean growth in Heilongjiang Province and the results of previous research. Using daily meteorological data, regional crop parameters and soil parameters from 15 representative stations in the study area during 1971-2020, soybean yield under different low temperature and rainy scenarios was simulated, and the influence of low temperature and rainy weather at seedling stage on soybean yield was quantitatively evaluated. The results showed that the localization application of WOFOST model was effective in Heilongjiang Province and thus it could be used to simulate soybean yield in this region. Under the scenarios set here, low temperature, rainy weather and their combined effects would lead to significant reductions of soybean yield. The duration of combined effects was the main factor leading to soybean yield reduction. The t-3.5 scenario lasting for 6 days had no significant effect on soybean yield, while some cases of t-3.5 scenario lasting for 12 days and most cases of t-3.5 scenario lasting for 18 days significantly reduced soybean yield. Under the context of the same duration and degree of agro-disaster, the combined occurrence of low temperature and heavy rain had stronger effect on soybean yield than that of the two alone.


Key words: soybean, low temperature and rainy superposition effect, WOFOST model, yield, seedling stage