| 引用本文: | 肖瑞欣,朱永华,吕海深,等.淮北平原作物生育期气象和农业干旱特征及其驱动因子[J].灌溉排水学报,2026,45(4):71-81. |
| XIAO Ruixin,ZHU Yonghua,LYU Haishen,et al.淮北平原作物生育期气象和农业干旱特征及其驱动因子[J].灌溉排水学报,2026,45(4):71-81. |
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| 摘要: |
| 【目的】分析淮北平原冬小麦和夏玉米各生长期气象干旱和农业干旱的空间分布及驱动机制，为针对性制定灌溉计划，减少因旱减产，保障作物稳产提供科学依据。【方法】基于1975—2024年ERA5-Land再分析数据，计算逐日标准化降水蒸散指数（SPEI）表征气象干旱和土壤水分亏缺指数（SWDI）表征农业干旱，结合作物生育期划分，统计冬小麦、夏玉米各生长阶段干旱时间并绘制空间分布图；采用皮尔逊与斯皮尔曼相关性分析，探究降水、潜在蒸散、温度等6类因子对不同作物生长期干旱的驱动作用。【结果】①冬小麦干旱高发于播种—出苗至出苗—返青期，农业干旱时间最高连续58 d，显著多于气象干旱最高连续46 d，空间上北部（宿州、淮北）气象干旱更频发，农业干旱呈“北多南少”特征；②夏玉米干旱以农业干旱为主导，灌浆—成熟期为高发期最高连续24 d，空间上南部（阜阳、蚌埠）多于北部；③气象干旱受水热因子驱动，小麦依赖“降水-温度-蒸散”协同，夏玉米以降水为主、露点温度为辅，农业干旱由土壤水分核心驱动，蒸散与温度通过“土壤供水-作物耗水”矛盾间接影响。【结论】淮北平原冬小麦前期播种—返青和夏玉米后期灌浆—成熟是干旱防控关键期，农业干旱影响更突出且存在区域分异；气象干旱与农业干旱的驱动机制差异为精准灌溉提供了依据—冬小麦需强化前期土壤保墒，夏玉米需重点保障后期根系层供水。 |
| 关键词: 淮北平原；冬小麦；夏玉米；气象干旱；农业干旱；驱动因素 |
| DOI：10.13522/j.cnki.ggps.2025245 |
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| Spatiotemporal patterns and driving factors of meteorological and agricultural droughts during winter wheat-summer maize growth period in the Huaibei Plain |
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XIAO Ruixin, ZHU Yonghua, LYU Haishen, LIANG Chenhui, PEI Ke, LI Yuxuan, LI Yixuan
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1. College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China; 2. College of Geography and Remote Sensing, Hohai University, Nanjing 211100, China; 3. National Key Laboratory of Water Disaster Prevention, Nanjing 210098, China
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| Abstract: |
| 【Objective】Drought is a major abiotic stress affecting agricultural production in the Huaibei Plain. Understanding its spatiotemporal patterns and driving factors is essential for developing effective mitigation strategies. This study analyzes the spatial variations and driving factors of meteorological and agricultural droughts during the growth periods of winter wheat and summer maize in the region.【Method】The analysis was based on ERA5-Land reanalysis data from 1975 to 2024, from which we estimated the daily Standardized Precipitation Evapotranspiration Index (SPEI) for meteorological drought and the Soil Water Deficit Index (SWDI) for agricultural drought. For each crop, the number of drought days during each growth stage was calculated, and spatial distribution maps of both drought types were generated. The effects of meteorological and soil factors on drought during different crop growth stages were evaluated using Pearson’s and Spearman’s correlation analyses.【Result】①For winter wheat, droughts were more frequent from the sowing-emergence to emergence-regreening stage than in other stages. Agricultural droughts could last consecutively up to 58 days, significantly longer than the maximum duration of meteorological droughts (46 days). Spatially, meteorological droughts occurred more frequently in the northern region, while agricultural droughts followed a ‘more in the north, less in the south’ pattern. ②For summer maize, droughts were mainly agricultural, particularly during the filling-maturity stage, where drought could last consecutively for 24 days. Spatially, droughts were more severe in the southern region than in the north. ③Meteorological droughts were driven by hydrothermal factors, with winter wheat drought influenced by precipitation, temperature and evapotranspiration, whereas summer maize drought was mainly affected by precipitation and dew-point temperature. In contrast, agricultural droughts were primarily driven by soil moisture, indirectly influenced by evapotranspiration and temperature through the imbalance between soil water supply and crop water demand.【Conclusion】The sowing-regreening stage of winter wheat and the filling-maturity stage of summer maize in the Huaibei Plain are particularly prone to drought stress. Agricultural droughts are dominant and exhibit distinct regional variations. Differences in the determinants of meteorological and agricultural droughts can guide precision irrigation strategies, such as improving soil water content during the early growth stage of winter wheat and maintaining root-zone moisture during the late growth stage of summer maize. |
| Key words: Huaibei Plain; winter wheat; summer maize; meteorological drought; agricultural drought; driving factors |
