4. THE ACRU MODEL
4.1 Background
4.3.1 Runoff representation
Different runoff mechanisms may be dominant in different environments and in catchments with different characteristics of soils, vegetation and topography (Beven, 2000). Instead of incorporating detailed process descriptions of runoff generation, the ACRU model uses
catchment characteristics as a basis for the derivation of parameter values that control the amount of runoff generated on a given day. Although the parameters used cannot in reality be measured, they are linked to physical characteristics of the catchment such as its landcover climate and soil characteristics (Schulze, 1995a).
Stormtlow - Quickt10w and delayed stormtlow
Stormflow in ACRU is generated when net rainfall (after interception - see Section 4.4.1) exceeds initial abstractions. Initial abstractions are calculated as the product of a coefficient of initial abstraction (COAIM) and the soil water deficit ofthe critical response depth (SMDDEP) of the soil (Schulze, 1995a). COAlM is dependent on vegetation, site and management characteristics and is increased to 0.3 or 0.4 for forest simulations due to factors such as the presence of a litter layer on the forest floor. SMDDEP is a conceptual depth designed to control how much water the catchment soil can absorb (i.e. infiltrate) before surface runoffis initiated. This depth parameter is set by the model user and is considered shallower in arid regions where high intensity storms would provide predominantly surface runoff, and is generally considered deeper in forested regions with dense canopy cover and deep organic layers, where more interflow and 'pushthrough' mechanisms dominate (Schulze, 1995a). What this means for forest simulationsisthat a larger amount of rainfall needs to infiltrate before the deficit is reduced and stormflow commences.
Once the initial abstractions are exceeded, stormflowisgenerated and added to the stormflow store. A fraction of this store, as prescribed by a quicktlow response coefficient (QFRESP), is released and runs off on the same day, whilst the remaining stormflow is retained until the following day when the same fraction of the remaining stormflow is released (see Figure 4.1).
The QFRESP coefficient is dependant on factors such as catchment size and slope, the density of the land cover and the interflow potential of the soil. The model is therefore able to reproduce the sustained "dry weather" flow or delayed flow following a rainfall event resulting from lateral sub-surface contributions.
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Baseflow
A second response coefficient, known as the baseflow release coefficient, governs baseflow release from a groundwater store. This coefficient depends on factors such as geology, catchment area and slope. A baseflow release coefficient of 0.005-0.05 (0.5-5%) per day is suggested in the user manual (Schulze, 1995a). However, since the publication of the user manual a value of 0.09 (9%) per day was found to be more reasonable for most model applications (Pike, 2000, personal communication). The release from the baseflow store, however, is not constant and the "decay" in release from the store is dependent on the magnitude of the previous day's groundwater store (Schulze, 1995a), as shown in Equation 4.1.
where
=
=
final baseflow release coefficient input baseflow release coefficient
magnitude of previous day's groundwater store (mm)
Equation 4.1
The stormflow and baseflow response coefficients only control the timing of releases, and therefore impact on the day to day variability of streamflow and not the total soil water budget.
The implication of prescribing a quickflow response coefficient is that lateral flow is implied by the controlled release of water from the stormflow store and therefore water accumulated in the stormflow store isnot available for uptake by trees. In reality however, lateral flow occurs through the downslope movement of water in the soil, therefore this water wouldbe available to trees and other vegetation. The same applies to water accumulated in the baseflow store.
Once water enters this store, tree roots no longer have access to the water contained in the store.
In the opinion of Gorgens .and Lee (1992) these soil water translation parameters have only indirect physical meaning. They believed that this ''black-box element" required a more physical basis. A further implication of using such conceptual parameters is that the model user would require a degree of experience and therefore it could be argued that the selection of
appropriate values, although based on soil climate and vegetation characteristics, introduces a certain degree of subjectivity to the modelling process (Scott, 1994).
A further criticism of the ACRU model highlighted by Gorgens and Lee (1992), was that runoff production inACRU is not sensitive to landscape forms and morphology that have been shown to control runoff production. They suggested the union of the ACRU model with elements of terrain sensitive models such as those discussed in Chapter 3. Topographic controls of runoff production were considered by Gorgens and Lee (1992) to have a particularly important function in modelling forestry impacts since:
• Afforestation often occurs in headwater areas where topo-morphological controls of runoff can occur.
• Modelling the response of saturation zones would be useful for decisions regarding exclusion zones in permit allocations.
• Modelling the effects of riparian management policies might require topo-morphological controls to be explicitly represented, because riparian zones are the most common partial source areas ofrunoff generation.
To address these issues and account for partially saturated areas in the riparian zones of the catchment, ACR U developers included an option to re-direct runoff releases from upstream catchments into a designated riparian subcatchment, as described in the following section.