Abstract
Groundwater discharge is believed to dominate dry season flows in perennial river systems and to sustain aquatic biodiversity. River flow statistics, extracted from the SPATSIM modelling system, were used to estimate the contribution of groundwater to river flow regimes. The flow statistics were compared for the principal aquifer types (based on major geological formations) in South Africa. This analysis focused on seasonal variation in flows rather than the annual totals or Baseflow Index. Groundwater discharge is expected to reduce flow variability and sustain flows, making flow concentrations lower than rainfall concentrations. Catchments dominated by carbonates have the greatest proportion of baseflow (37%), followed by basement complex (31%) and extrusive aquifer types (31%). The weak relationships between river flow indexes (particularly the Baseflow Index, Coefficient of Variation and Hydrological Index) and the seasonality or concentration statistics imply that catchment storage characteristics and other non-climatic factors play an important role in flow regulation. The geographic distribution of total flow concentrations differs markedly from rainfall concentrations, further evidence that non-climatic factors are important determinants of flow regimes. Karoo dykes and sills, extrusives and unconsolidated deposits are under-represented and the TMG sub-type, carbonates and basement complex and younger granites are over-represented among catchments with evenly distributed baseflows. The Baseflow Index and groundwater-fed baseflow are ecologically meaningful variables but lack clear thresholds that correspond with ecologically important changes in river flow regimes, for example perennial versus seasonal flow. Flow concentrations and percentage zero flows are useful and potentially ecologically important variables and should be tested as predictors of the aquatic and riparian biodiversity of river systems at a range of scales.
Highlights
Rivers are complex, hierarchical systems with three main interlinked components: the geological and geomorphological component which forms the basic physical template; the climatic and hydrological components which are key abiotic drivers of the system through water flow regimes, water quality and water temperature; and the biological component with a suite of species and communities which have adapted to the conditions created by their interactions with the abiotic components (Poff et al, 1997; Ward, 1998; Ward and Tockner, 2001; Wiens, 2002)
South African river systems have been prioritised for conservation based on their river heterogeneity signatures which are derived, at a coarse national scale, from a combination of the geomorphological province (Partridge, 1997), ecoregion (Kleynhans et al, 2004) and an index of river flow variability, the Hydrological Index (HI, Hughes and Hannart, 2003)
South Africa has an ancient land-surface made up of a range of geological formations which differ in their geological ages, history and lithology (King, 1942; Partridge and Maud, 1987; Partridge, 1997)
Summary
Hierarchical systems with three main interlinked components: the geological and geomorphological component which forms the basic physical template; the climatic and hydrological components which are key abiotic drivers of the system through water flow regimes, water quality and water temperature; and the biological component with a suite of species and communities which have adapted to the conditions created by their interactions with the abiotic components (Poff et al, 1997; Ward, 1998; Ward and Tockner, 2001; Wiens, 2002). South African river systems have been prioritised for conservation based on their river heterogeneity signatures which are derived, at a coarse national scale, from a combination of the geomorphological province (Partridge, 1997), ecoregion (Kleynhans et al, 2004) and an index of river flow variability, the Hydrological Index (HI, Hughes and Hannart, 2003) This approach was originally applied to the Greater Addo National Park (Roux et al, 2002) and extended to the national scale. The best substitute currently available was the WR90 synthesised flow records (Midgley et al, 1994) accessed using the SPATSIM (SPAtial and Time Series Information Modelling) flow modelling system (Hughes and Palmer, 2005) This means that there are interpolations and extrapolation of the data between gauged and un-gauged catchments, but it is unlikely that this will completely mask the broad patterns being investigated in this analysis. Sub-surface groundwater flow and non-flowing perennial pools are ecologically important but the linkages with surface water flow have not been quantified at a scale that is appropriate for this analysis
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