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Frequency Analysis Incorporating a Decision Support System Over Mahanadi Catchment in India
Different statistical criteria used for selecting the best fit for distributions are usually “biased” against the tail (large extreme events) as they give more weightage to the central tendency of the distribution. The extreme events are generally designated as the improbable events or outliers having less frequency of occurrence, resulting in the erroneous estimation of their magnitude and frequency. The present study evaluates the usefulness of the decision support system (DSS) to find a suitable class of probability distribution functions depending upon the tail heaviness. DSS analyzes the tail behavior of the sample data based on various graphical methods, viz., mean excess function plot, hill plot, log–log plot, max-sum ratio plot, and concentration profile. Once the distribution class is identified, the best fit distribution from various distributions in the class can be explored. The utility of the DSS is demonstrated through an application to the extreme precipitation data over the Mahanadi River basin. We have considered the gridded precipitation data obtained from the Indian Meteorological Department (IMD)-Pune having a resolution of 0.25°. Results show that almost all the graphical techniques combined to form a decision support system allow us to discriminate the exponential tail with a heavy tail, and one should rely on more than one graphical method for rational conclusions.
Frequency Analysis Incorporating a Decision Support System Over Mahanadi Catchment in India
Different statistical criteria used for selecting the best fit for distributions are usually “biased” against the tail (large extreme events) as they give more weightage to the central tendency of the distribution. The extreme events are generally designated as the improbable events or outliers having less frequency of occurrence, resulting in the erroneous estimation of their magnitude and frequency. The present study evaluates the usefulness of the decision support system (DSS) to find a suitable class of probability distribution functions depending upon the tail heaviness. DSS analyzes the tail behavior of the sample data based on various graphical methods, viz., mean excess function plot, hill plot, log–log plot, max-sum ratio plot, and concentration profile. Once the distribution class is identified, the best fit distribution from various distributions in the class can be explored. The utility of the DSS is demonstrated through an application to the extreme precipitation data over the Mahanadi River basin. We have considered the gridded precipitation data obtained from the Indian Meteorological Department (IMD)-Pune having a resolution of 0.25°. Results show that almost all the graphical techniques combined to form a decision support system allow us to discriminate the exponential tail with a heavy tail, and one should rely on more than one graphical method for rational conclusions.
Frequency Analysis Incorporating a Decision Support System Over Mahanadi Catchment in India
Lecture Notes in Civil Engineering
Timbadiya, P. V. (Herausgeber:in) / Patel, Prem Lal (Herausgeber:in) / Singh, Vijay P. (Herausgeber:in) / Manekar, Vivek L. (Herausgeber:in) / Gupta, Neha (Autor:in) / Chavan, Sagar Rohidas (Autor:in)
International Conference on Hydraulics, Water Resources and Coastal Engineering ; 2021
01.09.2023
14 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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