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Smart Agriculture ›› 2021, Vol. 3 ›› Issue (2): 126-137.doi: 10.12133/j.smartag.2021.3.2.202106-SA004

• 信息处理与决策 • 上一篇    

东北三省地区生长季旱涝对春玉米产量的影响

王蔚丹1,2(), 孙丽1,2(), 裴志远1,2, 马尚杰1,2, 陈媛媛1,2, 孙娟英1,2, 董沫1,2   

  1. 1.农业农村部耕地利用遥感重点实验室,北京 100121
    2.农业农村部规划设计研究院,北京 100121
  • 收稿日期:2021-06-01 修回日期:2021-06-28 出版日期:2021-06-30
  • 基金资助:
    国家重点研发计划(2016YFB0501505)
  • 作者简介:王蔚丹(1985-),女,博士,研究方向为农业干旱监测及自然灾害风险分析。Email:wangwd52@mail.bnu.edu.cn
  • 通信作者: 孙 丽(1978-),女,高级工程师,研究方向为农业遥感监测。电话:010-59197153。Email:sunli0618@163.com

Effect of Growing Season Drought and Flood on Yield of Spring Maize in Three Northeast Provinces of China

WANG Weidan1,2(), SUN Li1,2(), PEI Zhiyuan1,2, MA Shangjie1,2, CHEN Yuanyuan1,2, SUN Juanying1,2, DONG Mo1,2   

  1. 1.Key Laboratory of Cultivated Land Use, Ministry of Agriculture and Rural Affairs, Beijing 100121, China
    2.Academy of Agricultural Planning & Engineering, Ministry of Agriculture and Rural Affairs, Beijing 100121, China
  • Received:2021-06-01 Revised:2021-06-28 Online:2021-06-30
  • corresponding author: SUN Li, Email:sunli0618@163.com
  • About author:WANG Weidan, Email:wangwd52@mail.bnu.edu.cn
  • Supported by:
    National Key Research and Development Program of China (2016YFB0501505)

摘要:

评估生长季旱涝对作物产量的影响有助于农民采取措施增产保收。本研究基于1988—2017年气象站点数据和灾情、产量等统计数据,以中国东北三省为研究区,通过对比多时间尺度指标——标准化降水指数(SPI)和标准化降水蒸散指数(SPEI)与旱涝受灾率的关系,选择优势指数表征东北春玉米生长季干湿状况,基于HP滤波构建相对气象产量,利用距离相关分析方法选取合理时间尺度和关键月份的指数,分析这些指数与春玉米相对气象产量的关系以及不同生育阶段水分条件与产量之间的关系。结果表明:(1)SPI、SPEI均能表征东北地区农作物受旱和受涝状况,整体上SPEI在表征东北地区旱涝时更具优越性,尤其在辽宁省,因旱受灾率与SPI和SPEI相关系数差距明显,因涝受灾率与SPEI相关系数最大值为0.54,与SPI相关性不显著。(2)辽宁省SPEI3-8与相对气象产量的距离相关系数最大,吉林省和黑龙江省SPEI6-8与相对气象产量的距离相关系数最大;各省对应的SPEI与相对气象产量呈向下的抛物线趋势,其中辽宁省春玉米产量受干旱和雨涝的共同影响,吉林、黑龙江两省主要受干旱灾害的影响。(3)辽宁省春玉米在拔节—抽穗期主要受干旱影响,生长季后期受洪涝灾害影响较前期加重;当SPEI为1.0左右时,吉林省春玉米在出苗—拔节、拔节—抽穗期可达到最高产,抽穗—乳熟期受干旱影响严重;黑龙江关键生育期主要受旱灾影响,在出苗—拔节、拔节—抽穗期正常偏湿年份可达到最高产量,但中度及以上雨涝仍会导致玉米减产,抽穗—乳熟期在轻度湿润时可高产,重度湿润时会因涝减产。本研究对东北三省地区预估旱涝灾害对春玉米产量影响和及时采取灾害防御措施具有一定的参考价值。

关键词: 干旱, 洪涝, 标准化降水指数SPI, 标准化降水蒸散指数SPEI, 产量, 春玉米, 东北三省

Abstract:

With the change of global climate, extreme weather events such as drought and flood disasters occur frequently. These have a great impact on crop yields. As an important main grain producing area, the impact of drought and flood on the agricultural production of the three provinces in three northeast provinces of China cannot be ignored. Based on historic meteorological data such as daily precipitation, maximum temperature, minimum temperature, 2 m average wind speed, sunshine hours and relative humidity, etc., the standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) during 1988-2017 in three northeast provinces of China were calculated with different time scales. Through comparing with characterization of drought and flood disasters in history, SPEI was chosen to judge drought and flood in the growth season of spring maize. With the purpose of evaluating the effects of drought and flood on spring maize yield, based on the distance correlation analysis method, the index of reasonable time scale and key month were selected to analyze the relationship between the index and the relative meteorological yield of spring maize. The relationship between water conditions at different growth stages and the yield was also analyzed. The results showed that: (1) both SPI and SPEI could represent the drought and flood conditions in three northeast provinces of China. Compared with SPI, SPEI had higher correlation with the drought and flood disaster rate, and SPEI was more advantageous in characterizing the drought and flood conditions in the study area; (2) relative meteorological yield was significantly correlated with drought disaster rate in all three provinces (P<0.01), and reached 0.05 significant level with flood disaster rate in Liaoning province, but not significant in Jilin and Heilongjiang province; (3) the distance correlation coefficient between SPEI3-8 and relative meteorological in Liaoning province was the largest, and that between SPEI6-8 and relative meteorological yield in Jilin and Heilongjiang province was the largest. SPEI and relative meteorological yield showed a downward parabolic trend. Overall, the impact of waterlogging on the yield in Liaoning was slightly less than that of drought, mild drought or moderate wet could lead to a decrease in yield. The impact of drought disaster in Jilin and Heilongjiang was much greater than that of flood, but severe humidity could lead to a decrease in yield. Compared with other provinces, the maize yield in Liaoning province fluctuated more sharply with the change of dry and wet; (4) in Liaoning province, maize may reach the highest yield when the jointing-heading period was close to severe wet, which was mainly affected by drought. In the late growing season, the impact of flood disasters was more severe than that of the early growing season, and both drought and flood disasters had effects on the yield. In Jilin province, the highest yield of spring maize was reached when SPEI was about 1.0 during the period of emergence-jointing and jointing-heading, and the effect of drought was more serious during the period heading-milking. The key growth periods in Heilongjiang province were mainly affected by drought, and the maximum yield was reached in the normal-wet years of emergence-jointing and jointing-heading stages, but medium-scale size or more severe floods still led to the decrease of maize yield. The high yield could be achieved in the slightly wet years in period of heading-milking stage, while the decrease could be caused by flood when it was severely wet. This research can provide a reference for estimating the impact of drought and flood disasters on spring maize and taking disaster prevention measures in three northeast provinces of China.

Key words: drought, flood, standardized precipitation evapotranspiration index, yield, spring maize, three northeast provinces of China

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