Metastatistical Extreme Value Distribution applied to floods across the continental United States

Arianna Miniussi, Marco Marani, Gabriele Villarini

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

This study analyzes daily mean streamflow records from 5,311 U.S. Geological Survey stream gages in the continental United States and develops a Metastatistical Extreme Value Distribution (MEVD) tailored for flood frequency analysis. We compare the new tool with the Generalized Extreme Value (GEV) and Log-Pearson Type III (LP3) distributions and investigate the role of El Niño Southern Oscillation (ENSO) in the generation of floods. Hence, we formulate the MEVD in terms of mixture of distributions to describe the occurrence of flood peaks generated under different ENSO phases. We find that the MEVD outperforms GEV and LP3 distributions respectively in about 76% and 86% of the stations, with a significant improvement in the accuracy of quantiles corresponding to return periods much larger than the calibration sample size. The ENSO signature detected in the distributions of the daily peak flows does not necessarily improve the estimation of high return period flow values.

Original languageEnglish (US)
Article number103498
JournalAdvances in Water Resources
Volume136
DOIs
StatePublished - Feb 2020
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Water Science and Technology

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