QUAN T, ZHANG C G, FENG Y, LI H J, SHEN Y J. Impact of the “July 23” extreme heavy precipitation on maize yield in the Hebei Plain[J]. Chinese Journal of Eco-Agriculture, 2024, 32(0): 1−10. DOI: 10.12357/cjea.20230703
Citation: QUAN T, ZHANG C G, FENG Y, LI H J, SHEN Y J. Impact of the “July 23” extreme heavy precipitation on maize yield in the Hebei Plain[J]. Chinese Journal of Eco-Agriculture, 2024, 32(0): 1−10. DOI: 10.12357/cjea.20230703

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

  • Flooding is a devastating natural disaster, which poses a serious threat to food production. Affected by Typhoons Doksuri and Khanun, between 29 July and 1 August 2023, the Beijing-Tianjin-Hebei region experienced an unprecedently heavy precipitation and consequent enormous flooding, directly causing almost grain failure. In order to explore the impact of this heavy precipitation on local grain yield, this study used MODIS MOD09GQ product to compare the NDVI difference before and after the heavy precipitation in the Hebei Plain (main flood-submerged area), and accordingly, the area of submerged farmland and degree of grain failure were analyzed. The spatial distribution of maize (main summer crop locally), agricultural statistics and NDVI data in 2016-2020 were also combined to estimate maize yields under the two scenarios, i.e., with and without heavy precipitation, by which we estimated the yield loss of maize due to the heavy precipitation. The main conclusions were as follows: 1) After the 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 increases in the Hebei Plain. 2) In the Hebei Plain, there were approximately 240,000 hm2 of crops affected by the heavy precipitation, with complete crop failure in 130,000 hm2 of farmland and moderate crop failure in 110,000 hm2 of farmland. 3) An estimated 22 counties around the flood detention basins were mostly affected by the 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 the yield loss was due to crop extinction. This study provides a fast and reliable assessment framework on how to use remotely-sensed approach to estimate flood-induced grain reduction, and further emphasized the huge harmfulness of extreme climate event on food security.
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