2.6.2.3.3.1 Analytic element model
Analytic element models are grid-independent (Bakker, 2013). Their resolution is determined by the discretisation of the internal boundary elements, the points, lines and polygons representing head or flux boundaries. In the temporal domain it is necessary to define stress periods (i.e. periods in which the stresses and boundary conditions are constant), but it is not necessary to temporally discretise into time steps. This means the solution to groundwater flow equations can be evaluated at arbitrary points and times. Yearly stress-periods are chosen as this corresponds to the temporal resolution of the available mine pumping rates. As the analytic element model is only simulating the change due to coal resource development, the simulation period starts in 1995, the earliest date mine pumping rates are available, and ends in 2102, as specified in companion submethodology M07 (as listed in Table 1) for groundwater modelling (Crosbie et al., 2016).
In view of the uncertainty analysis, certain aspects of the model are simulated as a stochastic process. Throughout the product, the model design or the model results will be illustrated using data of a single realisation. These single realisations are typical examples of the stochastic process, but should by no means be regarded as an ‘optimal’ realisation or representing the mean or median of the range.
2.6.2.3.3.2 Alluvial MODFLOW models
The extent of the alluvial models is based on the mapped alluvium in the geological map 1:100,000 (McVicar et al., 2014, Figure 22). The model domain is discretised in 90 m grid cells with all grid cells outside the alluvium extent marked inactive (Figure 10).
The simulation period starts in 1983, ends in 2102 and has 1440 monthly stress periods (period of time in which all model stresses, such as pumping and recharge, remain constant) with one time step per stress period, in line with companion submethodology M07 (as listed in Table 1) for groundwater modelling (Crosbie et al., 2016).
The indicated zones correspond to surface water receptor catchments (see Section 2.6.1.3.2).
Data: Bioregional Assessment Programme (Dataset 1, Dataset 2)
