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<p>In recent years, copula-based multivariate drought analysis has garnered significant attention. However, the uncertainties associated with input data and copula parameter estimation remain insufficiently addressed This study aims to evaluate these uncertainties using a bootstrap approach, focusing on Severity-Duration-Frequency (SDF) curves for hydrometeorological droughts through Maximum Entropy Copula (ME-copula), Empirical Copula (EM-copula), and Theoretical Copula (TH-copula) methods at various conditional probabilities (CP). The results indicate that drought severity decreases when CP is reduced or the conditional return period (Tr) increases, while at a constant CP, severity intensifies with longer drought durations. The three methods show minor differences in estimated CPs, with ME-copula aligning closely with EM-copula. Notably, uncertainty from input data is significantly higher than copula parameters, with the order of uncertainty being TH-copula &gt; ME-copula &gt; EM-copula. The study demonstrates that ME-copula provides a robust framework for modeling the joint distribution of drought severity and duration, aiding in uncertainty reduction and enhancing drought preparedness strategies.</p>

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Uncertainty quantification in drought severity-duration-frequency analysis: a maximum entropy copula framework for arid region

  • 期刊论文

  • 发表日期：

    2025年8月7日

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  • Fatemeh Pourhagverdi,
  • Zohreh Pakdaman,
  • Ommolbanin Bazrafshan,
  • Marzieh Shekari,
  • Hossein Zamani

摘要

In recent years, copula-based multivariate drought analysis has garnered significant attention. However, the uncertainties associated with input data and copula parameter estimation remain insufficiently addressed This study aims to evaluate these uncertainties using a bootstrap approach, focusing on Severity-Duration-Frequency (SDF) curves for hydrometeorological droughts through Maximum Entropy Copula (ME-copula), Empirical Copula (EM-copula), and Theoretical Copula (TH-copula) methods at various conditional probabilities (CP). The results indicate that drought severity decreases when CP is reduced or the conditional return period (Tr) increases, while at a constant CP, severity intensifies with longer drought durations. The three methods show minor differences in estimated CPs, with ME-copula aligning closely with EM-copula. Notably, uncertainty from input data is significantly higher than copula parameters, with the order of uncertainty being TH-copula > ME-copula > EM-copula. The study demonstrates that ME-copula provides a robust framework for modeling the joint distribution of drought severity and duration, aiding in uncertainty reduction and enhancing drought preparedness strategies.