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Bivariate drought frequency curves and confidence intervals: a case study using monthly rainfall generation

机译:双变量干旱频率曲线和置信区间:使用每月降雨产生的案例研究

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Although water resources management practices recently use bivariate distribution functions to assess drought severity and its frequency, the lack of systematic measurements is the major hindrance in achieving quantitative results. This study aims to suggest a statistical scheme for the bivariate drought frequency analysis to provide comprehensive and consistent drought severities using observed rainfalls and their uncertainty using synthesized rainfalls. First, this study developed a multi-variate regression model to generate synthetic monthly rainfalls using climate variables as causative variables. The causative variables were generated to preserve their correlations using copula functions. This study then focused on constructing bivariate drought frequency curves using bivariate kernel functions and estimating their confidence intervals from 1,000 likely replica sets of drought frequency curves. The confidence intervals achieved in this study may be useful for making a comprehensive drought management plan through providing feasible ranges of drought severity.
机译:尽管水资源管理实践最近使用双变量分布函数来评估干旱的严重程度及其频率,但缺乏系统的测量方法是实现定量结果的主要障碍。这项研究旨在为双变量干旱频率分析提出一种统计方案,以利用观测到的降雨提供全面一致的干旱强度,并利用合成降雨提供不确定性。首先,这项研究建立了一个多变量回归模型,以气候变量为因变量来产生合成的每月降雨。使用copula函数生成致病变量以保留其相关性。然后,本研究着重于使用双变量核函数构建双变量干旱频率曲线,并从1000个可能的干旱频率曲线副本集中估计其置信区间。通过提供可行的干旱严重程度范围,本研究中获得的置信区间可能有助于制定全面的干旱管理计划。

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