泉涛, 章成果, 冯颖, 李红军, 郭英, 沈彦俊. “23·7”特大暴雨对河北平原玉米产量的影响研究[J]. 中国生态农业学报 (中英文), 2024, 32(6): 1−10. DOI: 10.12357/cjea.20230703
引用本文: 泉涛, 章成果, 冯颖, 李红军, 郭英, 沈彦俊. “23·7”特大暴雨对河北平原玉米产量的影响研究[J]. 中国生态农业学报 (中英文), 2024, 32(6): 1−10. DOI: 10.12357/cjea.20230703
QUAN T, ZHANG C G, FENG Y, LI H J, , SHEN Y J. Impact of the “23·7” extreme heavy precipitation on maize yield in the Hebei Plain[J]. Chinese Journal of Eco-Agriculture, 2024, 32(6): 1−10. DOI: 10.12357/cjea.20230703
Citation: QUAN T, ZHANG C G, FENG Y, LI H J, , SHEN Y J. Impact of the “23·7” extreme heavy precipitation on maize yield in the Hebei Plain[J]. Chinese Journal of Eco-Agriculture, 2024, 32(6): 1−10. DOI: 10.12357/cjea.20230703

“23·7”特大暴雨对河北平原玉米产量的影响研究

Impact of the “23·7” extreme heavy precipitation on maize yield in the Hebei Plain

  • 摘要: 洪涝是一种破坏力巨大的自然灾害, 对粮食生产构成严重威胁。受台风“杜苏芮”和“卡奴”的影响, 2023年7月29日至8月1日京津冀地区出现百年一遇的特大暴雨洪水灾害, 给京津冀地区造成了重大损失, 导致部分农田几乎绝收。为评估极端暴雨事件对当地粮食产量的影响, 本研究使用MODIS MOD09GQ数据分析了暴雨前后的归一化植被指数(NDVI)变化, 据此划定了本次暴雨造成的受灾农田区域(主要在河北平原)及其受灾程度, 同时结合2016—2020年玉米种植空间分布、农业统计数据和NDVI数据, 估算了受灾农田区域未发生暴雨和发生暴雨后两种情景下的玉米产量, 进而评估了本次暴雨造成的玉米产量损失。主要得到以下结果: 1)暴雨发生后, 河北平原受灾农田区域的NDVI普遍减少0~0.35, 相比之下, 未受灾农田区域的NDVI均有所增加。2)本次强降雨导致河北平原约24万hm2农田受到影响, 绝产面积约13万hm2, 减产面积约11万hm2。3)蓄滞洪区周边的22个县(市、区)是本次暴雨的主要受灾区域, 据回归分析结果, 本次暴雨可能造成的玉米产量损失多达22万t, 且92%的产量损失是由作物绝产所致。本研究为遥感手段估算极端降雨导致的粮食减产提供了一个快速且可靠的计算框架, 同时强调了极端降雨对粮食安全的巨大威胁。

     

    Abstract: Flooding is a devastating natural disaster that poses serious threats to food production. Affected by Typhoons Doksuri and Khanun, between July 29 and August 1, 2023, the Beijing-Tianjin-Hebei region experienced unprecedented heavy precipitation and consequent enormous flooding, directly causing almost grain failure. To explore the impact of heavy precipitation on local grain yield, this study used the MODIS MOD09GQ product to compare the NDVI difference before and after heavy precipitation in the Hebei Plain (the main flood-submerged area), and the area of submerged farmland and the degree of grain failure were analyzed. The spatial distribution of maize (the main local summer crop), agricultural statistics, and NDVI data for 2016–2020 were also combined to estimate maize yields under the two scenarios, with and without heavy precipitation, by which we estimated the yield loss of maize due to heavy precipitation. The main conclusions were as follows: 1) After heavy precipitation, the NDVI of the affected farmland decreased in the range of 0-0.35, while the NDVI of the unaffected farmland showed varying degrees of increase on the Hebei Plain. 2) In the Hebei Plain, approximately 240 000 hm2 of crops was affected by heavy precipitation, with complete crop failure in 130 000 hm2 of farmland and moderate crop failure in 110 000 hm2 of farmland. 3) The estimated 22 counties (city, district) around the flood detention basins were mostly affected by heavy precipitation. According to the results of the regression analyses, this heavy precipitation event caused a 220 000 t of potential loss of maize, and 92% of this yield loss was due to crop extinction. This study provides a fast and reliable assessment framework for the use of a remotely sensed approach to estimate flood-induced grain reduction and further emphasizes the harmful effects of extreme climate events on food security.

     

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