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<p>This study evaluated the meteorological drought based on the Standardized Precipitation Evapotranspiration Index (SPEI) and copula theory in the north-western state of Rajasthan, India. The SPEI was calculated at 1-, 3-, 6-, 9-, and 12-month time scales. Drought characteristics (Duration, Severity, Peak, and Intensity) were identified using the run theory, and several marginal distributions were fitted to them. The Log-Normal distribution was recognized as the best-fitted marginal distribution for most of the stations. The best-fitted marginal distributions were used to construct the bivariate probability distributions of drought characteristics based on copula functions. The best-fitted copula was identified based on the AIC, BIC, and RMSE values. The Bivariate Clayton Copula was recognized as the most suitable function for determining the joint behaviour of drought characteristics. The drought characteristics were evaluated at 5-, 10-, 25-, and 50-year return periods. The results reveal that the importance of using bivariate analysis, as the “AND” case showed significantly higher return periods (7.2–66.8&#xa0;years) than the “OR” case (3.1–35.5&#xa0;years), emphasizing a stronger risk under concurrent drought conditions, crucial for planning and resilience strategies. The results obtained from this analysis hold promise in enhancing the risk monitoring method proposed in this study, ultimately offering valuable insights that can be leveraged in the decision-making process aimed at minimizing the impacts of drought and curbing the progression of desertification in the study area characterized by rain-fed agriculture.</p>

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Copula-based meteorological drought risk assessment in Northwest India

  • 期刊论文

  • 发表日期：

    2025年10月10日

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  • Yogesh Kumar,
  • Shekhar Singh,
  • Anil Kumar

摘要

This study evaluated the meteorological drought based on the Standardized Precipitation Evapotranspiration Index (SPEI) and copula theory in the north-western state of Rajasthan, India. The SPEI was calculated at 1-, 3-, 6-, 9-, and 12-month time scales. Drought characteristics (Duration, Severity, Peak, and Intensity) were identified using the run theory, and several marginal distributions were fitted to them. The Log-Normal distribution was recognized as the best-fitted marginal distribution for most of the stations. The best-fitted marginal distributions were used to construct the bivariate probability distributions of drought characteristics based on copula functions. The best-fitted copula was identified based on the AIC, BIC, and RMSE values. The Bivariate Clayton Copula was recognized as the most suitable function for determining the joint behaviour of drought characteristics. The drought characteristics were evaluated at 5-, 10-, 25-, and 50-year return periods. The results reveal that the importance of using bivariate analysis, as the “AND” case showed significantly higher return periods (7.2–66.8 years) than the “OR” case (3.1–35.5 years), emphasizing a stronger risk under concurrent drought conditions, crucial for planning and resilience strategies. The results obtained from this analysis hold promise in enhancing the risk monitoring method proposed in this study, ultimately offering valuable insights that can be leveraged in the decision-making process aimed at minimizing the impacts of drought and curbing the progression of desertification in the study area characterized by rain-fed agriculture.