极端降水引起的大面积夏玉米减产方法研究——以2021年河南“7·20”强降水事件为例

Approach for Evaluating Summer Maize Yield Losses under Extreme Rainfall Events:A Case Study in“7·20”Heavy Rain Event in Henan Province

【目的】建立洪涝条件下夏玉米减产的快速评估方法,评估2021年河南省“7·20”强降水事件对夏玉米产量的影响。【方法】根据2021年6月18日—7月29日河南省逐日的归一化植被指数(NDVI)遥感影像数据和DEM数据,利用像元统计法确定“7·20”强降水事件中河南省夏玉米连续被淹区域,依据夏玉米受淹时长与减产关系以及追肥对受淹夏玉米产量的补偿关系评估“7·20”强降水事件对河南省夏玉米产量造成的影响。【结果】河南省“7·20”强降水事件造成的涝灾区域主要分布在安阳、新乡和郑州,该次强降水事件造成夏玉米受淹面积共计261万hm^(2);中等程度受淹面积(淹水3 d)为57万hm^(2),严重受淹面积(淹水5 d)为13万hm^(2),绝收面积(淹水≥7 d)为20万hm^(2)。【结论】河南省“7·20”强降水事件造成的夏玉米产量损失为393万~491万t,占全省夏玉米总产量的17%~22%(以2019年夏玉米产量为基准),与调研数据基本一致。因此,本研究提出的极端降水事件下夏玉米受淹面积快速获取方法和减产估算模式可为变化环境下的粮食估产和国家粮食安全研究提供技术支撑。

【Objective】Flooding and waterlogging is a common abiotic stress facing agricultural production.Understanding its impact on crop yield is essential to evaluating food supply and security.The objective of this paper is to present a rapid and accurate method for assessing the impact of extreme rainfall events on crops.The method was then applied to evaluate effect of the flooding on 20 July(20/7),2021 on yield of summer maize in Henan province.【Method】We used daily normalized vegetation index(NDVI)acquired from remote sensing imageries and DEM data from 18 June to 29 July to estimate the flooded summer maize areas across the province after the 20/7 flooding,using pixel statistic method.The yield loss was estimated based on the relationship between flooding duration and maize yield reduction,as well as the compensatory effect of the topdressing afterwards.【Result】The flooded areas were mainly located in the north,including Anyang,Xinxiang,and Zhengzhou,affecting 39.09 million‘mu’of summer maize,in which 8.51 million‘mu’was moderately flooded(continuously flooding 3 days),1.95 million‘mu’was severely flooded(continuously flooding 5 days),and 2.96 million‘mu’lost harvest(continuously flooding 7 days).This flooding resulted in a direct loss of 3.93~4.91 million tons of summer maize,accounting for 17%~22%of maize production in the province(based on maize production in 2019).This is consistent with field survey results.The proposed method is thus accurate and reliable,quickly determining flooded cropped areas and estimating their yield losses.【Conclusion】A method based on remote sensing imageries is developed to evaluate flooding severity,its associated areas and crop yield losses.Comparing with ground-truth data obtained in the 20/7 flooding shows that the method is accurate and reliable.