Journal article
Metastatistical Extreme Value Distribution applied to floods across the continental United States
Advances in water resources, Vol.136, p.103498
02/2020
DOI: 10.1016/j.advwatres.2019.103498
Abstract
•We develop a Metastatistical Extreme Value Distribution (MEVD) tailored for floods.•We compare the MEVD with the GEV and LP3 distributions.•MEVD outperforms the GEV and LP3 in the analyzed USGS stations (76 and 86% of the cases).•We propose a mixed MEVD approach to account for El Niño Southern Oscillation.
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.
Details
- Title: Subtitle
- Metastatistical Extreme Value Distribution applied to floods across the continental United States
- Creators
- Arianna Miniussi - Department of Civil, Architectural, and Environmental Engineering, University of Padua, Padua, ItalyMarco Marani - Department of Civil, Architectural, and Environmental Engineering, University of Padua, Padua, ItalyGabriele Villarini - IIHR-Hydroscience & Engineering, University of Iowa, Iowa City, Iowa, United States
- Resource Type
- Journal article
- Publication Details
- Advances in water resources, Vol.136, p.103498
- Publisher
- Elsevier Ltd
- DOI
- 10.1016/j.advwatres.2019.103498
- ISSN
- 0309-1708
- eISSN
- 1872-9657
- Language
- English
- Date published
- 02/2020
- Academic Unit
- Civil and Environmental Engineering; IIHR--Hydroscience and Engineering
- Record Identifier
- 9984066115702771
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