scholarly journals Flood frequency analysis: Evidence and implications of secular climate variability, New South Wales

2002 ◽  
Vol 38 (5) ◽  
pp. 20-1-20-7 ◽  
Author(s):  
Stewart W. Franks ◽  
George Kuczera
Keyword(s):  
Climate Variability ◽  
Frequency Analysis ◽  
New South ◽  
New South Wales ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
South Wales

Multi-decadal climate variability, New South Wales, Australia

2004 ◽  
Vol 49 (7) ◽  
pp. 133-140 ◽  
Author(s):  
S.W. Franks
Keyword(s):  
Climate Variability ◽  
General Circulation ◽  
Decadal Variability ◽  
Southern Oscillation ◽  
New South ◽  
New South Wales ◽  
General Circulation Models ◽  
Drought Risk ◽  
Decadal Climate Variability ◽  
South Wales

Traditional hydrological risk estimation has treated the observations of hydro-climatological extremes as being independent and identically distributed, implying a static climate risk. However, recent research has highlighted the persistence of multi-decadal epochs of distinct climate states across New South Wales (NSW), Australia. Climatological studies have also revealed multi-decadal variability in the magnitude and frequency of El Niño/Southern Oscillation (ENSO) impacts. In this paper, examples of multi-decadal variability are presented with regard to flood and drought risk. The causal mechanisms for the observed variability are then explored. Finally, it is argued that the insights into climate variability provide (a) useful lead time for forecasting seasonal hydrological risk, (b) a strong rationale for a new framework for hydrological design and (c) a strong example of natural climate variability for use in the testing of General Circulation Models of climate change.

scholarly journals Identification of a change in climate state using regional flood data

2002 ◽  
Vol 6 (1) ◽  
pp. 11-16 ◽  
Author(s):  
S. W. Franks
Keyword(s):  
Climate Variability ◽  
Decadal Variability ◽  
Frequency Estimation ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
South Wales ◽  
Circulation Patterns ◽  
Mean Sea Surface ◽  
Mean Circulation ◽  
Change In Mean

Abstract. Flood frequency analysis typically assumes that annual floods arise from a single distribution and are independent. However, there is significant evidence for the existence of persistent climate modes. Timescales associated with climate variability range from inter-annual through to longer, multi-decadal time scales. In the case of the Australian climate, previous studies of the Indian and Pacific Oceans have indicated marked multi-decadal variability in both mean Sea Surface Temperatures (SST) and typical circulation patterns. In this light, data from 40 stream gauges around New South Wales are examined to determine whether flood frequency data are indeed independent and distributed identically. Given likely correlation in flood records between gauges, an assessment of the regional significance of observed changes in flood frequency is required. To achieve this, flood observations are aggregated into a regional index. A simple non-parametric test is then employed to identify the timing and magnitude of any change in mean annual flood. Finally, it is shown that the identified change in flood frequency corresponds directly to an observed shift in SST and mean circulation. These results demonstrate the role of natural variability in climate parameters and the need for an improved conceptual framework for flood frequency estimation. Keywords: Floods, flood frequency, climate variability, IPO, PDO, climate change

scholarly journals Application of Principal Component Analysis and Cluster Analysis in Regional Flood Frequency Analysis: A Case Study in New South Wales, Australia

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 781 ◽  
Author(s):  
Ayesha S Rahman ◽  
Ataur Rahman
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
New South ◽  
Principal Component ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
South Wales ◽  
Regional Flood Frequency Analysis ◽  
And Cluster Analysis ◽  
Regional Flood Frequency

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.

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