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Uncertainty evaluation of copula analysis of hydrological droughts in the East River basin, China

机译:东部流域水文干旱关联分析的不确定性评估

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摘要

The joint probability behaviors of extreme hydro-meteorological events, such as droughts, have been receiving increasing attentions in recent years. Since extreme hydro-meteorological events are reflected by more than one variable, such as duration and intensity, copula functions have been widely applied. However, uncertainties of copula-based analysis of hydrological droughts as a result of selection of marginal distribution and copulas have not yet received significant concerns. The aim of this study is to evaluate such uncertainties based on Bayesian approach. The method is used to analyze hydrological drought in the East River basin (China), which is the principal supplier of water resources for megacities in the Pearl River Delta and also for Hong Kong. The results indicate that the credible intervals of most likely design drought events with a return period of 20 years in terms of drought severity and duration are considerably large at all stations in the East River basin, covering the drought event curves at return periods of 10 and 50 years. Also the influences of heavy-tailed marginal distribution on the uncertainty evaluation of joint distribution have been investigated. Results show that the stronger the heavy-tailed marginal distribution, the greater the uncertainty of the joint distribution, especially for the extreme event Results of this study provide a technical reference for uncertainty evaluation in copula-based analysis of drought events at regional and global scales. The large credible interval of drought severity and duration greatly challenges measures of mitigation of drought hazards and water resource management. (C) 2015 Elsevier B.V. All rights reserved.
机译:近年来,干旱等极端水文气象事件的联合概率行为受到越来越多的关注。由于极端的水文气象事件由持续时间和强度等多个变量反映,因此copula函数已被广泛应用。然而,由于选择边际分布和copulas,基于copula的水文干旱分析的不确定性尚未引起人们的广泛关注。这项研究的目的是基于贝叶斯方法评估这种不确定性。该方法用于分析东部流域(中国)的水文干旱,东部流域是珠三角和香港的大城市的主要水资源供应者。结果表明,就干旱严重程度和持续时间而言,最有可能发生的设计干旱事件的可信间隔(在干旱严重程度和持续时间方面为20年)在东河流域的所有站点上都相当大,涵盖了在10和15年的干旱时期的干旱事件曲线。 50年还研究了重尾边缘分布对联合分布不确定性评估的影响。结果表明,重尾边缘分布越强,联合分布的不确定性就越大,特别是对于极端事件而言,本研究结果为基于copula的区域和全球尺度的干旱事件分析中的不确定性评估提供了技术参考。干旱严重程度和持续时间的可信区间很大,极大地挑战了减轻干旱危害和水资源管理的措施。 (C)2015 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Global and planetary change》 |2015年第6期|1-9|共9页
  • 作者单位

    Sun Yat Sen Univ, Dept Water Resources & Environm, Guangzhou 510275, Guangdong, Peoples R China|Sun Yat Sen Univ, Guangdong High Educ Inst, Key Lab Water Cycle & Water Secur Southern China, Guangzhou 510275, Guangdong, Peoples R China|Suzhou Univ, Sch Earth Sci & Engn, Suzhou 234000, Anhui, Peoples R China;

    Sun Yat Sen Univ, Dept Water Resources & Environm, Guangzhou 510275, Guangdong, Peoples R China|Sun Yat Sen Univ, Guangdong High Educ Inst, Key Lab Water Cycle & Water Secur Southern China, Guangzhou 510275, Guangdong, Peoples R China;

    Texas A&M Univ, Dept Biol & Agr Engn, College Stn, TX 77843 USA|Texas A&M Univ, Zachry Dept Civil Engn, College Stn, TX 77843 USA;

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

    hydrological drought; copula; uncertainty; Bayesian model;

    机译:水文干旱copula不确定性贝叶斯模型;

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