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Regional Frequency Analysis of Droughts in China: A Multivariate Perspective

机译:基于多变量视角的中国干旱区域频率分析

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摘要

Joint probability behavior of droughts is important for China due to the fact that China is the agricultural country with the largest population in the world and it is particularly the case in the backdrop of intensifying weather extremes in a warming climate. In this case, regionalization of droughts is done using Fuzzy C- Means (FCM) clustering technique and also multivariate L-moment method. Besides, copula is used to estimate regional joint probability in terms of drought duration and severity. Evaluation of uncertainty in the joint probability curves is done using the Bootstrap resampling technique. The results indicate that: (1) five homogenous regions of droughts are subdivided. Regionalization in this study clarified the changing properties or nature of droughts, i.e., the blurred or ambiguous boundaries of the drought-impacted regions; (2) droughts in the northwest China are characterized by longer drought duration and larger drought severity, and the occurrence of the droughts in the northwest China is subject to be higher due to longer waiting time between drought events. Adverse is found for changes of droughts in the southeast China. The droughts in the north China are moderate in terms of drought duration and severity and also waiting time between drought events when compared to those in the northwest and southeast China; (3) the regional joint frequency curves are obtained with respect to drought duration and severity using the bivariate copula functions. Then the joint probabilities of droughts can be calculated using the regional probability curves and also results of mean drought duration, drought severity and waiting time between drought events. Furthermore, droughts in the regions without meteorological data can also be estimated in terms of joint probability using index-drought method proposed in this study. This study will provides theoretical and practical grounds for development and enhancement of human mitigation to drought hazards in China, and is of great importance in terms of planning and management of water resources and agricultural activities in the backdrop of intensifying weather extremes under the influences of warming climate.
机译:由于中国是世界上人口最多的农业国,因此干旱的联合概率行为对中国很重要,在气候变暖的极端天气加剧的背景下尤其如此。在这种情况下,干旱的分区是使用模糊C均值(FCM)聚类技术以及多变量L矩方法完成的。此外,copula用于根据干旱持续时间和严重程度估计区域联合概率。联合概率曲线中的不确定性评估是使用Bootstrap重采样技术完成的。结果表明:(1)将干旱划分为五个均匀区域。本研究中的区域化明确了干旱的性质或性质的变化,即受干旱影响的地区的边界模糊或模棱两可; (2)中国西北地区的干旱具有持续时间较长和干旱严重程度较高的特点,由于干旱事件之间的等待时间较长,因此西北地区的干旱发生率较高。人们发现中国东南部的干旱变化不利。与中国西北地区和东南部地区相比,中国北方地区的干旱持续时间和严重程度以及干旱事件之间的等待时间中等。 (3)使用双变量copula函数获得关于干旱持续时间和严重程度的区域联合频率曲线。然后,可以使用区域概率曲线以及平均干旱持续时间,干旱严重性和干旱事件之间的等待时间的结果来计算干旱的联合概率。此外,也可以使用本研究提出的指数干旱法,以联合概率的方式估计没有气象数据的地区的干旱。这项研究将为中国发展和增强人类减灾措施提供理论和实践依据,在变暖影响下极端天气加剧的背景下,对水资源和农业活动的规划和管理具有重要意义。气候。

著录项

  • 来源
    《Water Resources Management》 |2015年第6期|1767-1787|共21页
  • 作者单位

    Department of Water Resources and Environment Sun Yat-sen University">(1);

    Key Laboratory of Water Cycle and Water Security in South China of Guangdong High Education Institute Sun Yat-sen University">(2);

    Guangdong Key Laboratory for Urbanization and Geo-simulation Sun Yat-sen University">(3);

    Department of Water Resources and Environment Sun Yat-sen University">(1);

    Key Laboratory of Water Cycle and Water Security in South China of Guangdong High Education Institute Sun Yat-sen University">(2);

    Department of Biological Agricultural Engineering and Zachry Department of Civil Engineering Texas A M University">(4);

    Department of Geography and Resource Management and Institute of Environment Energy and Sustainability The Chinese University of Hong Kong">(5);

    Department of Water Resources and Environment Sun Yat-sen University">(1);

    Key Laboratory of Water Cycle and Water Security in South China of Guangdong High Education Institute Sun Yat-sen University">(2);

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Meteorological droughts; Regional frequency analysis; Multivariate L-moment; Copula functions; FCM algorithm; China;

    机译:气象干旱;区域频率分析;多元L矩Copula功能;FCM算法;中国;

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