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      https://www.ias.ac.in/article/fulltext/jess/126/06/0080

    • Keywords

       

      Drought; copula; Frank; Clayton; Gumbel; Karkheh River basin; Iran.

    • Abstract

       

      Investigation on drought characteristics such as severity, duration, and frequency is crucial for water resources planning and management in a river basin. While the methodology for multivariate drought frequency analysis is well established by applying the copulas, the estimation on the associated parameters by various parameter estimation methods and the effects on the obtained results have not yet been investigated. This research aims at conducting a comparative analysis between the maximum likelihood parametric and non-parametric method of the Kendall $\tau$ estimation method for copulas parameter estimation. The methods were employed to study joint severity–duration probability and recurrence intervals in Karkheh River basin (southwest Iran) which is facing severe water-deficit problems. Daily streamflow data at three hydrological gauging stations (Tang Sazbon, Huleilan and Polchehr) near the Karkheh dam were used to draw flow duration curves (FDC) of these three stations. The Q75 index extracted from the FDC were set as threshold level to abstract drought characteristics such as drought duration and severity on the basis of the run theory. Drought duration and severity were separately modeled using the univariate probabilistic distributions and gamma–GEV, LN2–exponential, and LN2–gamma were selected as the best paired drought severity–duration inputs for copulas according to the Akaike Information Criteria (AIC), Kolmogorov–Smirnov and chi-square tests. Archimedean Clayton, Frank, and extreme value Gumbel copulas were employed to construct joint cumulative distribution functions (JCDF) of droughts for each station. Frank copula at Tang Sazbon and Gumbel at Huleilan and Polchehr stations were identified as the best copulas based on the performance evaluation criteria including AIC, BIC, log-likelihood and root mean square error (RMSE) values. Based on the RMSE values, nonparametric Kendall-$\tau$ is preferred to the parametric maximum likelihood estimation method. The results showed greater drought return periods by the parametric ML method in comparison to the nonparametric Kendall $\tau$ estimation method. The results also showed that stations located in tributaries (Huleilan and Polchehr) have close return periods, while the station along the main river (Tang Sazbon) has the smaller return periods for the drought events with identical drought duration and severity.

    • Author Affiliations

       

      Esmaeel Dodangeh1 Kaka Shahedi1 Jenq-Tzong Shiau2 Maryam MirAkbari3

      1. Department of Watershed Management, Sari Agricultural Sciences and Natural Resources University, Sari, Iran.
      2. Department of Hydraulic and Ocean Engineering, National Cheng Kung University, Tainan 701, Taiwan, Republic of China.
      3. Department of Rehabilitation of Arid and Mountainous Regions, University of Tehran, Tehran, Iran.
    • Dates

       
  • Journal of Earth System Science | News

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