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Monitoring drought dynamics in China using Optimized Meteorological Drought Index (OMDI) based on remote sensing data sets

机译:基于遥感数据集的优化气象干旱指数(OMDI)监测中国的干旱动态

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摘要

Timely and accurate monitoring of the spatiotemporal changes in drought is very important for the reduction in the social losses caused by drought. The Optimized Meteorological Drought Index (OMDI), originally established in southwestern China, showed great potential for drought monitoring over large regions on a large scale. However, the applicability of the index requires further evaluation, especially when used throughout China, which has a different agricultural divisions, variable climatic conditions, complex terrain and diverse land cover. In addition, the OMDI model relies on training data to construct local parameters for the model. On a large scale, it is of great significance to use multisource remote sensing data sets to construct OMDI model parameters. In this paper, the constrained optimization method was used to establish weights for the MODIS-derived Vegetation Conditional Index (VCI), TRMM-derived Precipitation Condition Index (PCI), and GLDAS-derived Soil Moisture Condition Index (SMCI) and calculate the OMDI based on the Standard Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and weather stations. The accuracy of the OMDI model was evaluated by using the correlation coefficient. Moreover, the spatiotemporal changes in drought were also analyzed through trend analysis, Mann-Kendall (MK) statistics and the Hurst index on the monthly and annual scales. The results showed that (1) the highest positive correlation between the OMDI and the SPI was SPI-1, which was higher than that for any other month interval, such as 3 months, 6 months, 9 months and 12 months of the SPI. The results indicated that the OMDI was suitable to monitor meteorological drought. (2) In the nine agricultural subareas in China, the degree of drought in the Yangtze River (DYR) area had the most severe evolution and change frequency. This region was very sensitive to drought in the past two decades. (3) The area with OMDI variation coefficient less than 0.1 accounted for 94%, indicating that the degree of drought fluctuates little; The linear tendency rate is 0.0004, and the area greater than 0 reaches 66.44%, indicating that the drought is developing in a lightning trend. (4) The Hurst index value is mostly higher than 0.5 (the area ratio is 56.31%), and the area of "Positive-Consistent" and "Negative- Opposite" accounted for 54.02%, indicating that more than half of China's area drought changes will show a trend of mitigation in the future.
机译:及时,准确地监测干旱的时空变化对于减少干旱造成的社会损失的减少非常重要。最初在中国西南部建立的优化气象干旱指数(OMDI)表现出大规模大地区干旱监测的巨大潜力。然而,指数的适用性需要进一步的评估,特别是当在整个中国使用时,该农业部门具有不同,可变气候条件,复杂的地形和不同的陆地覆盖。此外,OMDI模型依赖于训练数据来构建模型的本地参数。在大规模中,使用MultiSource遥感数据集构建OMDI模型参数具有重要意义。在本文中,使用约束优化方法为Modis衍生的植被条件指数(VCI),TRMM衍生的沉淀条件指数(PCI)和GLDAs衍生的土壤水分状况指数(SMCI)建立重量并计算OMDI基于标准沉淀指数(SPI),标准化沉淀蒸散散热物指数(SPEI)和气象站。通过使用相关系数来评估OMDI模型的准确性。此外,还通过趋势分析,Mann-Kendall(MK)统计数据和月度和年度尺度的赫斯特指数分析了干旱的时空变化。结果表明,(1)OMDI和SPI之间的最高阳性相关性是SPI-1,其均高于任何其他月间隔,例如3个月,6个月,9个月和12个月的SPI。结果表明,OMDI适合监测气象干旱。 (2)在中国的九个农业蛛网中,长江(DYR)地区的干旱程度具有最严重的演变和变化频率。在过去二十年中,该地区对干旱非常敏感。 (3)OMDI变异系数小于0.1的区域占94%,表明干旱程度略微波动;线性趋势率为0.0004,大于0的面积达到66.44%,表明干旱正在发生雷电趋势。 (4)赫斯特指数值大多高于0.5(面积比为56.31%),以及“积极一致”和“负面相反”的面积占54.02%,表明中国的一半以上的地区干旱变化将在未来显示减缓趋势。

著录项

  • 来源
    《Journal of Environmental Management》 |2021年第15期|112733.1-112733.14|共14页
  • 作者单位

    College of Geography and Environmental Science Northwest Normal University Lanzhou 730070 Gansu China;

    College of Geography and Environmental Science Northwest Normal University Lanzhou 730070 Gansu China;

    College of Geography and Environmental Science Northwest Normal University Lanzhou 730070 Gansu China;

    Faculty of Geomatics Lanzhou Jiaotong University Lanzhou 730070 China Institute of Geographic Sciences and Natural Resources Research CAS Beijing 100101 China;

    School of Urban Economics and Tourism Culture Lanzhou City University Lanzhou 730070 Gansu China;

    College of Geography and Environmental Science Northwest Normal University Lanzhou 730070 Gansu China;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Optimized meteorological drought index; Evolution dynamics; Remote sensing data sets; Constrained optimization method; China;

    机译:优化的气象干旱指数;进化动态;遥感数据集;约束优化方法;中国;

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