Climatic and physical factors that influence the homogeneity of regional floods in southeastern Australia

Abstract

The identification of hydrologically “homogeneous” regions is a primary step in many regional flood frequency techniques. Although statistical procedures for identifying homogeneous regions abound in the literature, there has been relatively little effort directed toward the identification of the physical and climatic basin characteristics that cause similarity in standardized flood peak distributions. We use regional flood peak and basin characteristics data for 104 basins in southeastern Australia to investigate the physical and climatic factors associated with the statistical distributions of flood peaks; the degree of geographical coherence of homogeneous regions; and the extent to which information on flood peak statistics is encapsulated by the physical and climatic characteristics of basins that are commonly used in regionalization studies. Our results show that (1) membership of a particular homogeneous region is determined largely by a combination of climatic characteristics that is related to runoff generation; (2) supergroups consisting of sites within aggregated homogeneous regions that have reasonably similar flood responses show some degree of spatial coherence; and (3) the basin characteristics that influence regional homogeneity can be identified despite the use of indices that smooth spatial and temporal variability.

Regional flood frequency analysis in arid regions: A case study for Australia

“…Many RFFA methods have been developed and tested for different countries in the world (e.g. Cunnane, 1988;Hosking and Wallis, 1993;Zrinji and Burn, 1994;Bates et al, 1998;Pandey and Nguyen, 1999;Ouarda et al, 2001;Merz and Blöschl, 2005;Micevski and Kuczera, 2009;Gaume et al, 2010). Some of the most commonly adopted RFFA methods in practice include the index flood method (Dalrymple, 1960;Hosking and Wallis, 1993), rational method (Mulvany, 1851;I.…”

Selection of the best fit flood frequency distribution and parameter estimation procedure: a case study for Tasmania in Australia

“…They found that the Generalised Extreme Value (GEV) and Wakeby distributions provide the best approximation to flood flow data in the regions of Australia that are dominated by rainfall during the winter months. Bates et al (1998) adopted the method of L moments in identifying homogeneous regions in the context of regional flood frequency analysis for south-east Australia. Haddad and Rahman (2008) compared a number of distributions and parameter estimation procedures for 18 catchments in south-east Australia and found that the GEV distribution provided the best fit to the selected data set.…”

Regional Dry Spells Frequency Analysis by L-Moment and Multivariate Analysis

“…In hydrological applications the site characteristics would typically include geographical location of the site or other physical properties such as watershed area and slope, associated with the site (e.g. Bates et al 1998;Chiang et al 2002). For AMDSL time series, the latitude and longitude of the stations are considered as the site characteristics.…”

“…These techniques include multivariate statistics such as regression, hierarchical cluster and principal component analyses (e.g. Bates et al 1998;Chiang et al 2002;Modarres 2006), region of influence (Burn 1990) and canonical correlation analysis (Cavadias et al 2001).…”