Abstract
This paper examines the applicability of independent component analysis (ICA) in regional flood frequency analysis (RFFA). Data from 88 catchments in New South Wales, Australia are adopted in this study. The ICA is integrated with both quantile regression technique (QRT) and parameter regression technique (PRT). A total of eight climatic and catchment characteristics is used as potential predictor variables in the study. For ICA, independent components (IC) are used as the predictor variables and a ‘cumulative percent relevance’ criterion is adopted to select the best predictors. A leave-one-out validation is adopted to assess the performances of the competing models using a suit of statistical evaluation measures. It is found that the QRT model with four catchment characteristics, and the PR model with all the ICs as predictors outperform the other candidate models. These models provide a absolute median relative error in the range of 33% to 44% for the QRT model (with catchment characteristics as predictors), and 48% to 59% for the PRT model (with the ICs as predictors) for design flood estimation. This is comparable to the relative error values (57% to 64%) reported for the RFFA technique recommended in the Australian Rainfall and Runoff.
Original language | English |
---|---|
Article number | 124372 |
Number of pages | 16 |
Journal | Journal of Hydrology |
Volume | 581 |
DOIs | |
Publication status | Published - 2020 |
Keywords
- New South Wales
- flood forecasting
- mathematical models