A wide array of hydrological metrics have traditionally been used to quantify key aspects of streamflow behaviour. However, there is growing recognition that a select number of metrics can define flow regimes more effectively, reducing redundancy while still capturing unique patterns of streamflow variability. This study used nine hydrological metrics to define flow regimes across the state of South Australia. Daily flow data from 232 surface water gauging sites were used to define existing flow regimes throughout the landscape through varying degrees of naturalness and alteration. Hierarchical clustering and classification tree analyses were used to classify streamflow data into flow regimes. The result was thirteen flow regime types, nine being defined by an amalgamation of hydrological aspects and four exemplifying ‘extreme’ flow regimes.
Building on this classification, we investigated the drivers of eleven of these flow regime types within the Mount Lofty Ranges, South Australia. Thirty-three variables derived from spatial, climate, and derived design data were used to understand the impacts of catchment land cover, geomorphology, climate, and hydrological processes on streamflow.
The simplification of metrics used in the analysis allowed for easier interpretation and understanding of the factors that differentiated flow regime types. These results provide a baseline for understanding streamflow characteristics, including criteria that may be used as trigger values for environmental management. By understanding the predominant drivers of flow regimes, these characteristics may be predicted in ungauged areas. This information can also be used to evaluate how changes in catchment characteristics may influence flow regimes.