3.2.4 Assessing potential impacts for landscape classes and assets


The approach for assessing potential impacts for landscape classes and water-dependent assets is discussed in companion submethodology M10 (as listed in Table 1) for analysing impacts and risks (Henderson et al., 2018). The zone of potential hydrological change focuses the attention of the analysis on areas where there may be changes in surface water and/or groundwater that are attributable to additional coal resource development.

The principal focus of BAs is water-dependent assets that are nominated by the community. These assets may have a variety of values, including ecological, sociocultural and economic values. The water-dependent asset register (companion product 1.3 for the Gloucester subregion (McVicar et al., 2015); Bioregional Assessment Programme, 2017; Bioregional Assessment Programme, Dataset 2) provides a simple and authoritative listing of the assets within the assessment extent. The register is a compilation of assets identified in local land services (formerly catchment management authorities) databases and Commonwealth and state databases, and through the Gloucester assets workshop. To be included in the register, assets must have spatial information, intersect the assessment extent for the subregion and have a water-dependency. These assets are considered in the impact and risk analysis reported in this product.

Landscape classification discretised the heterogeneous landscape into a manageable number of landscape classes for impact and risk analysis. Landscape classes represent key surface ecosystems that have broadly similar physical, biological and hydrological characteristics. They were used to reduce the complexity inherent in assessing impacts on a large number of water-dependent assets by focusing on the hydrological drivers and interactions relevant to a regional-scale assessment. The landscape classes provide a meaningful scale for understanding potential ecosystem impacts and communicating them through their more aggregated system-level view. The landscape classification for the Gloucester subregion is described in companion product 2.3 (Dawes et al., 2018) and the methodology that underpins it is described in companion submethodology M05 (as listed in Table 1) for developing a conceptual model of causal pathways (Henderson et al., 2016).

Potential hydrological changes were assessed by overlaying the extent of a landscape class or asset on the zone of potential hydrological change due to additional coal resource development. For the landscape classes or assets that lie outside the zone, hydrological changes (and hence potential impacts due to coal resource development) are very unlikely, and are thus ruled out in terms of further assessment. Section 3.4.2 identifies landscape classes in the Gloucester subregion that can be ruled out on this basis.

Where an asset or landscape class wholly or partially intersects the zone of potential hydrological change, there is the potential for impact. This does not mean there will be an impact, but rather, based on the magnitude of the hydrological change, the possibility of an impact cannot be ruled out and further investigation is required. The nature of the water dependency of the landscape class can be important for informing the assessment. For example, if the water dependence of a landscape class relies on overbank flows to support seedling establishment, but the significant hydrological changes in the nearby stream relate only to low-flow variables (i.e. flows that are contained within the streambanks), then it is possible to rule the landscape class out of further consideration because it is unlikely to be impacted.

Four receptor impact models were built, representing two landscape classes in the Gloucester subregion (Table 4), and were used to quantitatively predict the impact of the predicted hydrological changes on one or more receptor impact variables within the receptor impact model (companion product 2.7 for the Gloucester subregion (Hosack et al., 2018b)). Ecological meaningful hydrological response variables and receptor impact variables (Table 4) were elicited from experts (listed in Table 3 in companion product 2.7 for the Gloucester subregion (Hosack et al., 2018b)) during qualitative and receptor impact model building workshops and subsequent follow-up by email. A full description of receptor impact modelling is described in companion submethodology M08 (as listed in Table 1) (Hosack et al., 2018a).

Table 4 Landscape classes, receptor impact models and their model variables


Landscape class

Receptor impact variable (with associated sample units)

Hydrological response variables

Perennial – gravel/cobble streams

Annual mean percent canopy cover of woody riparian vegetation (predominately Casuarina cunninghamiana, Melia azedarach, Eucalyptus amplifolia and Angophora subvelutina) in a transect 20 m wide and 100 m long covering the bottom of the stream bench to the high bank

dmaxRef

tmaxRef

EventsR0.3

EventsR3.0

Perennial – gravel/cobble streams

Mean number of larvae of the family Hydropsychidae (net-spinning caddisflies) in a 1 m2 sample of riffle habitat

ZQD

Perennial – gravel/cobble streams

Mean abundance of the eel-tailed catfish (Tandanus tandanus) in a 600 m2 transect whose long axis lies along the mid-point of the stream

ZQD

QBFI

Intermittent – gravel/cobble streams

Mean richness of hyporheic invertebrate taxa in 6 L of water pumped from a depth of 40 cm below the streambed (riffle and gravel bars)

ZQD

dmaxRef = maximum drawdown, tmaxRef = year of maximum drawdown, EventsR3.0 = overbank events, EventsR0.3 = overbench events, ZQD = zero-flow days (averaged over 30 years), QBFI = baseflow index

Potential impacts are reported in Section 3.4 for landscape classes and in Section 3.5 for assets.

In addition, impact profiles for landscape classes and assets are available at www.bioregionalassessments.gov.au. Each profile summarises the hydrological changes and potential impacts that pertain to that landscape class or asset (e.g. increase in the number of low-flow days for the streams in the ‘Perennial – gravel/cobble streams’ landscape class in the zone of potential hydrological change). Users can aggregate and consider potential impacts for their own scale of interest.

Users can also explore the results for landscape classes and assets using a map-based interface at www.bioregionalassessments.gov.au/explorer/GLO/landscapes and www.bioregionalassessments.gov.au/explorer/GLO/assets.

3.2.4.1 Information management and processing

A very large number of multi-dimensional and multi-scaled datasets were used in the impact and risk analysis for each BA, including hydrological model outputs, and ecological, economic and sociocultural asset data from a wide range of sources. Part of the approach used to manage these datasets and produce meaningful results was to adopt a clear spatial framework as an organising principle. While the inherently spatial character of every BA is important and must be addressed, it is also essential that the temporal and other dimensions of the analysis do not lose resolution during data processing. For example, knowing where a potential impact may take place is obviously important, but so is knowing when, which hydrological response variables may change, which assets may be affected, and what level of impact may result.

The datasets for this BA were organised into an impact and risk analysis database (Bioregional Assessment Programme, Dataset 3) to enable efficient management. The purpose of the database is to produce result datasets that integrate the available modelling and other evidence across the assessment extent of the BA. These databases are required to support three types of BA analyses: analysis of hydrological changes, impact profiles for landscape classes, and impact profiles for assets. The results of these analyses are summarised in this product, with more detailed information available on www.bioregionalassessments.gov.au. The impact and risk analysis database is also available on data.gov.au (Bioregional Assessment Programme, Dataset 3).

The datasets used in the impact and risk analysis database (Bioregional Assessment Programme, Dataset 3) include the assets, landscape classes, modelling results (groundwater, surface water and receptor impact modelling), coal resource development 'footprints' and other relevant geographic datasets, such as the boundaries of the subregion, assessment extent and zone of potential hydrological change. All data in the impact and risk analysis database (and the results derived from it) meet the requirements for transparency.

The impact and risk assessment requires the geoprocessing of complex queries on very large spatial datasets. To overcome the computational overload associated with this task a relational, rather than geospatial approach was utilised. All dataset geometries are split against a universal grid of assessment units that exhaustively cover the assessment extent (Figure 11). An assessment unit is a geographic area represented by a square polygon with a unique identifier. The spatial resolution of the assessment units is closely related to that of the BA groundwater modelling and is typically 1 km x 1 km, though due to the small size of the Gloucester subregion and the resolution of the groundwater modelling it is 0.5 km x 0.5 km. Assessment units were used to partition asset and landscape class spatial data for impact analysis. The gridded data can be combined and recombined into any aggregation supported by the conceptual modelling, causal pathways and model data.

The gridded data were normalised and loaded into the impact and risk analysis database (Bioregional Assessment Programme, Dataset 3). Impact area, length and counts are calculated for individual features (e.g. stream reaches, individual assets, groups of assets or landscape classes) at the assessment unit level. An individual analysis result is executed by selecting the assessment units of interest and summing the pre-calculated values of area, length or count for the required dataset. This approach of front-loading the geospatial analysis through grid base attribution is fundamental to enabling the volume of calculations required to complete the assessment. The approach uses the source geometries in calculation and hence does not impact on the analysis calculations. In a few cases, source geometries were found to create geospatial errors and were removed from the analysis. The removing of invalid geometries did not in any case, affect the analysis results more than a combined total area of one assessment unit per geospatial item.

The interpolated modelled groundwater drawdowns (see Section 3.2.3.1) are at the same resolution as the assessment unit and contain a single value per assessment unit. However, the surface water modelling generated results at points that are extrapolated to links (see Section 3.2.3.2), which were then mapped to assessment units. An example of this can be seen in Figure 11, where the assessment units containing nodes 14 and 15 are assigned the value associated with that node.

However, where the assessment unit contains multiple stream reaches (e.g. at the confluence of the two streams shown in Figure 11), it was necessary to prioritise which stream reach was used to inform the value of the assessment unit for representing the surface water modelling results. The general rules for prioritising a stream reach take into account:

  • whether the modelled reaches show a hydrological change (i.e. a reach with a potential hydrological change takes priority over a reach predicted to have no significant change)
  • whether the stream reach is represented in the model (i.e. modelled reaches take priority)
  • the stream order of each reach (i.e. a higher order stream (e.g. main channel) takes priority over a lower order stream (e.g. tributary))
  • reach length (i.e. where two streams in an assessment unit are of equally high stream order, priority is given to the longer of the two).

Figure 11

Figure 11 Assessment units and interpolation of surface water nodes across the assessment extent

Data: Bioregional Assessment Programme (Dataset 7, Dataset 8)

Last updated:
18 December 2018
Thumbnail of the Gloucester subregion

Product Finalisation date

2018