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Modeling of maximum precipitation using maximal generalized extreme value distribution

Author

Listed:
  • Farnoosh Ashoori
  • Malihe Ebrahimpour
  • Abolghasem Bozorgnia

Abstract

Distribution of maximum or minimum values (extreme values) of a dataset is especially used in natural phenomena including sea waves, flow discharge, wind speeds, and precipitation and it is also used in many other applied sciences such as reliability studies and analysis of environmental extreme events. So if we can explain the extremal behavior via statistical formulas, we can estimate how their behavior would be in the future. In this paper, we study extreme values of maximum precipitation in Zahedan using maximal generalized extreme value distribution, which all maxima of a data set are modeled using it. Also, we apply four methods to estimate distribution parameters including maximum likelihood estimation, probability weighted moments, elemental percentile and quantile least squares then compare estimates by average scaled absolute error criterion and obtain quantiles estimates and confidence intervals. In addition, goodness-of-fit tests are described. As a part of result, the return period of maximum precipitation is computed.

Suggested Citation

  • Farnoosh Ashoori & Malihe Ebrahimpour & Abolghasem Bozorgnia, 2017. "Modeling of maximum precipitation using maximal generalized extreme value distribution," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(6), pages 3025-3033, March.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:6:p:3025-3033
    DOI: 10.1080/03610926.2015.1034325
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