Hydrological characteristics of Australia: national catchment classification and regional relationships

Jaffrés, Jasmine B.D., Cuff, Ben, Cuff, Chris, Knott, Matthew, and Rasmussen, Cecily (2022) Hydrological characteristics of Australia: national catchment classification and regional relationships. Journal of Hydrology, 612 (Part A). 127969.

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A continent-wide classification study of Australian catchments was undertaken to group drainage basins with comparable flow characteristics based on forty metrics from the themes of climate, topography, surface condition and hydrogeology. A principal component analysis reduced the multi-collinear indices to nine principal components (PCs). A fuzzy c-means cluster analysis on the PCs resulted in the delineation of eight subcatchment clusters with similar physiography, and 82.5% of subcatchments displaying a membership coefficient greater than 0.7. Subcatchments with poor cluster membership levels may be significant in highlighting complexity in the interaction between climatic controls and local geomorphological and land use variability. The clusters are distinguished by different attributes in several key subcatchment variables and each group is described in terms of its flow and flood profile. These interpretations are supported by separately derived streamflow signatures from gauged catchments. Cluster and PC distribution mapping revealed distinct spatial and drainage relationships between the subcatchments relevant to the assessment of flood behaviour. The spatial pattern of the river basin regionalisation via physical catchment similarity closely resembles the modified Köppen climate classification, with differences highlighting the importance of non-climate characteristics on streamflow behaviour in Australia. The catchment classification is an Australia-wide regionalisation scheme, incorporating datasets with disparate spatial distribution and ungauged subcatchments. This study therefore provides the framework for more detailed streamflow analysis by applying consistent methods across all catchments in Australia, and has implications for flood risk prediction, mitigation and planning.

Item ID: 80676
Item Type: Article (Research - C1)
ISSN: 1879-2707
Keywords: Catchment classification; Climate variability; Fuzzy c-means clustering; Streamflow patterns; Topography; Water infiltration capacity
Copyright Information: © 2022 Elsevier B.V. All rights reserved.
Date Deposited: 10 Oct 2023 23:08
FoR Codes: 37 EARTH SCIENCES > 3707 Hydrology > 370704 Surface water hydrology @ 40%
37 EARTH SCIENCES > 3702 Climate change science > 370202 Climatology @ 40%
41 ENVIRONMENTAL SCIENCES > 4199 Other environmental sciences > 419999 Other environmental sciences not elsewhere classified @ 20%
SEO Codes: 19 ENVIRONMENTAL POLICY, CLIMATE CHANGE AND NATURAL HAZARDS > 1904 Natural hazards > 190404 Hydrological hazards (e.g. avalanches and floods) @ 40%
18 ENVIRONMENTAL MANAGEMENT > 1803 Fresh, ground and surface water systems and management > 180399 Fresh, ground and surface water systems and management not elsewhere classified @ 50%
18 ENVIRONMENTAL MANAGEMENT > 1801 Air quality, atmosphere and weather > 180103 Atmospheric processes and dynamics @ 10%
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