Impacts of historical records on extreme flood variations over the conterminous United States

X. Mei, Z. Dai, Z. Tang, P. H.A.J.M. van Gelder

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Evaluation of flood variations over time, especially for floods with large return periods, is of great significance to flood risk assessment. ‘Historical’ data that have been recorded before the construction of a gauging station provide an effective way to analyse the temporal changes of extreme floods. Here, comparison of maximum likelihood method, L-moment method and Bayesian theory are made to calculate the Gumbel distribution parameters via Monte Carlo simulation experiment. The best option is applied to 37 unregulated rivers over the conterminous United States to analyse their 100-year flood variations. The Monte Carlo simulation results indicate that L-moment method is substantially better than the other two estimators for both systematic and unsystematic series. Over 70% of studied river catchments detect 100-year flood decrease when the historical data are considered. The impacts of historical records on 100-year flood variation estimations are closely related to censoring threshold and historical period length.

Original languageEnglish (US)
Pages (from-to)S359-S369
JournalJournal of Flood Risk Management
Volume11
DOIs
StatePublished - Jan 2018

Fingerprint

historical record
natural disaster
Method of moments
Rivers
river
simulation
Gaging
return period
Catchments
Risk assessment
risk assessment
Maximum likelihood
catchment
experiment
evaluation
method
Experiments

Keywords

  • 100-year flood
  • Gumbel distribution
  • L-moment method
  • systematic records
  • unsystematic records

ASJC Scopus subject areas

  • Environmental Engineering
  • Geography, Planning and Development
  • Safety, Risk, Reliability and Quality
  • Water Science and Technology

Cite this

Impacts of historical records on extreme flood variations over the conterminous United States. / Mei, X.; Dai, Z.; Tang, Z.; van Gelder, P. H.A.J.M.

In: Journal of Flood Risk Management, Vol. 11, 01.2018, p. S359-S369.

Research output: Contribution to journalArticle

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