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Gumbel–Hougaard copula-based tetravariate flood frequency analysis for the Hirakud reservoir catchment
The floods are averted depending upon the effective operations of gate keeping downstream conditions in mind. In this regard inflow hydrographs have a major role to play. The tetravariate flood frequency analysis has been done in this study by taking four variables of a hydrograph i.e. peak (Qp), volume (V), duration (D) and time to peak (Tp). The variable time to peak has given more emphasis in this study, as it characterizes the inflow more effectively and its severity gives less time for operation of dam. In this study, the dependence parameters () of the proposed copula model are determined, finally the values of best fit marginal for all the four variables and dependence parameters () are applied in four-dimensional asymmetric Gumbel–Hougaard copula. The main advantage of using this model is that, it relaxes the restriction of using a similar type of marginal distributions for all the four basic variables. The three hourly inflow data of Hirakud reservoir has been taken to fit the proposed model. Finally, this model is validated using the observed tetravariate probability plotting position model. The result of the copula model is in better agreement with the observed tetravariate probability, ultimately using this copula model, conditional probability is determined.
Gumbel–Hougaard copula-based tetravariate flood frequency analysis for the Hirakud reservoir catchment
The floods are averted depending upon the effective operations of gate keeping downstream conditions in mind. In this regard inflow hydrographs have a major role to play. The tetravariate flood frequency analysis has been done in this study by taking four variables of a hydrograph i.e. peak (Qp), volume (V), duration (D) and time to peak (Tp). The variable time to peak has given more emphasis in this study, as it characterizes the inflow more effectively and its severity gives less time for operation of dam. In this study, the dependence parameters () of the proposed copula model are determined, finally the values of best fit marginal for all the four variables and dependence parameters () are applied in four-dimensional asymmetric Gumbel–Hougaard copula. The main advantage of using this model is that, it relaxes the restriction of using a similar type of marginal distributions for all the four basic variables. The three hourly inflow data of Hirakud reservoir has been taken to fit the proposed model. Finally, this model is validated using the observed tetravariate probability plotting position model. The result of the copula model is in better agreement with the observed tetravariate probability, ultimately using this copula model, conditional probability is determined.
Gumbel–Hougaard copula-based tetravariate flood frequency analysis for the Hirakud reservoir catchment
Padhee, Raj Beer (author) / Kar, Anil Kumar (author) / Das, Pradip Kumar (author)
ISH Journal of Hydraulic Engineering ; 28 ; 430-437
2022-10-02
8 pages
Article (Journal)
Electronic Resource
Unknown
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