王晓东, 陈金华, 陈曦, 岳伟, 魏忠光. 淮河流域农田旱涝逐日监测指标优化及适用性分析[J]. 农业工程学报, 2021, 37(23): 117-126. DOI: 10.11975/j.issn.1002-6819.2021.23.014
    引用本文: 王晓东, 陈金华, 陈曦, 岳伟, 魏忠光. 淮河流域农田旱涝逐日监测指标优化及适用性分析[J]. 农业工程学报, 2021, 37(23): 117-126. DOI: 10.11975/j.issn.1002-6819.2021.23.014
    Wang Xiaodong, Chen Jinhua, Chen Xi, Yue Wei, Wei Zhongguang. Optimization and applicability analysis of daily farmland drought and flood monitoring index in Huaihe River Basin[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(23): 117-126. DOI: 10.11975/j.issn.1002-6819.2021.23.014
    Citation: Wang Xiaodong, Chen Jinhua, Chen Xi, Yue Wei, Wei Zhongguang. Optimization and applicability analysis of daily farmland drought and flood monitoring index in Huaihe River Basin[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(23): 117-126. DOI: 10.11975/j.issn.1002-6819.2021.23.014

    淮河流域农田旱涝逐日监测指标优化及适用性分析

    Optimization and applicability analysis of daily farmland drought and flood monitoring index in Huaihe River Basin

    • 摘要: 淮河流域是中国农业旱涝灾害发生最为频繁的地区之一。研究该区农田旱涝时空格局特征,建立主要粮食作物农田旱涝动态监测方法,并提升其时效性与精细化水平,能为区域农田水资源合理调配提供参考。该研究选取1971-2020年淮河流域173个气象站点逐日气象观测数据和土壤水分数据,针对区域土壤及主要种植作物相关特性,优化了农田水分收支项,并计算了站点日尺度标准化前期降水蒸散指数(Standardized Antecedent Precipitation Evapotranspiration Index,SAPEI)。对SAPEI在淮河流域农田旱涝监测中的适用性进行评价,同时基于SAPEI分析了淮河流域50 a农田旱涝时空特征。结果表明:基于三参数log-Logistic概率分布拟合方法适用于淮河流域SAPEI的计算。SAPEI能较真实地反映面上逐日农田旱涝变化,有93%样本计算的Kappa系数超过0.6,与实际田间土壤墒情旱涝等级一致性程度达到高度一致或者几乎完全一致。基于SAPEI的旱涝时空分布特征显示年平均SAPEI呈上升趋势,总体表现出干旱趋于缓和;冬小麦生育期呈下降趋势,在1992年发生突变,由正常逐渐转变为偏旱;一季稻生育期正负波动明显;夏玉米生育期呈上升趋势,其中2001-2010年指数持续大于0,处于明显偏湿时段。从空间分布来看,流域大部分站点干旱呈现缓和趋势。SAPEI在淮河流域农田旱涝监测中具有较好的适用性,基于该指数开展旱涝监测和评估,能有效预防并减轻农田旱涝对作物影响,并为防灾减灾措施的制定提供决策依据。

       

      Abstract: Agricultural drought and flood disasters occur most frequently in the Huaihe River Basin of China, accounting for 80% of the total loss of grain production. Taking the Huaihe River Basin as the study area, this study aims to dynamically monitor the spatial and temporal pattern of farmland drought and flood for the main food crops, thereby improving the rational allocation for the regional water resources at the timeliness and precision level. The daily meteorological observation and soil moisture data were collected at the 173 meteorological stations from 1971 to 2020. The budget of farmland water was optimized to calculate the Standardized Antecedent Precipitation Evapotranspiration Index (SAPEI), according to the relevant characteristics of regional soil and main planting crops. The timeliness and refinement level of SAPEI was satisfied with the commercial requirements for the surface dry and wet changes in most areas, considering the farmland water balance and rational assessment of the drought and flood at multiple time/space scales. The applicability of SAPEI was finally evaluated on the temporal and spatial characteristics of farmland drought and flood over the past 50 years. The results showed that the probability distribution fitting of three parameter log-logistic was applicable to the SAPEI in the study area. The annual SAPEI showed an upward trend as a whole, indicating that the drought slowed down. There was a downward trend with an abrupt change in 1992 from the normal to the drought during the growth period of winter wheat. There were also some outstanding positive and negative fluctuations during the growth period of single cropping rice. For example, the SAPEI had achieved a minimum of -0.921 in 1978, where the continuous drought appeared from spring to autumn in the planting area of single cropping rice in the southern study area. More importantly, the precipitation was generally only half of water demand, where the yield of rice decreased significantly, indicating a very serious drought. There was an upward trend during the growth period of summer maize, where the index was continuously greater than 0 from 2001 to 2010, indicating an outstanding wet period. In addition, there was a moderate trend of drought at most stations in the spatial distribution. A case study showed that the SAPEI truly represented the daily changes of surface farmland drought and flood, 93% of the samples with the Kappa coefficient over 0.6, indicating better consistency. Consequently, the SAPEI can be applied to daily dynamically monitor the service of farmland drought and flood, thereby timely preventing and reducing the impacts of the farmland drought and flood on the crops in the Huaihe River Basin. This finding can also provide a strong reference for the decision-making on disaster prevention and reduction measures.

       

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