Application of principal component analysis and cluster analysis in regional flood frequency analysis : a case study in New South Wales, Australia

Ayesha S. Rahman, Ataur Rahman

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)

Abstract

This paper examines the applicability of principal component analysis (PCA) and cluster analysis in regional flood frequency analysis. A total of 88 sites in New South Wales, Australia are adopted. Quantile regression technique (QRT) is integrated with the PCA to estimate the flood quantiles. A total of eight catchment characteristics are selected as predictor variables. A leave-one-out validation is applied to determine the efficiency of the developed statistical models using an ensemble of evaluation diagnostics. It is found that the PCA with QRT model does not perform well, whereas cluster/group formed with smaller sized catchments performs better (with a median relative error values ranging from 22% to 37%) than other clusters/groups. No linkage is found between the degree of heterogeneity in the clusters/groups and precision of flood quantile prediction by the multiple linear regression technique.
Original languageEnglish
Article number781
Number of pages26
JournalWater
Volume12
Issue number781
DOIs
Publication statusPublished - 2020

Open Access - Access Right Statement

© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Keywords

  • New South Wales
  • flood forecasting
  • floods

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