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- Assigning receptors to water-dependent assets
- 3 Assigning receptors
- 3.3 Process for assigning receptors across the landscape
- 3.3.2 Spatial distribution of receptors across the landscape
The actual steps for spatially distributing receptors will inevitably vary among subregions or bioregions and depend to some extent on the types of asset in the water-dependent asset register and the subsequent landscape classes. However, it is important to ensure that the receptors are spatially distributed within a subregion or bioregion in a systematic and representative manner. Many approaches for assigning receptors to landscape classes are currently available to Assessment teams including:
- A generalised random tessellation stratified (GRTS) design proposed by Stevens and Olsen (2004). This approach uses an algorithm that maps two-dimensional space into one-dimensional space thereby defining an ordered spatial address. Stevens and Olsen (2004) argue that sampling designs with some degree of spatial regularity (such as gridded sampling or spatially stratified designs) tend to be more efficient than designs with no spatial structure. This approach is supported by existing standardised scripts but requires high-level spatial analysis skills.
- A second approach uses a network of the Bureau of Meteorology’s ‘Geofabric’ outlet nodes as anchors. Receptors are then placed within every landscape class element within the catchment at the point closest (in terms of a straight-line distance) to the defined catchment outlet nodes. This approach provides complete coverage of all assets and landscape classes within a PAE but may reduce the sampling efficiency. Scripts have been developed as part of BA to implement this tool. The advantage of this approach is that it ensures that all assets receive at least one receptor (in most cases many); it also recognises that for many receptors there will be no discernible impacts, and that communication of this is in itself an important output.
- A third approach places receptors in a systematic grid across the PAE with the grid spacing determined by the requirements of the analysis and the rate of change of the available information, including the results of the available models.
These, and other suitable approaches, will enable the development of a preliminary receptor register that contains many thousands of receptors and completely covers the PAE. Care must be taken to ensure that all assets are assigned to or have appropriate receptors. In the event that all assets are assigned to a landscape class this step is relatively straightforward. It is the Assessment team’s responsibility to ensure that the final distribution of receptors facilitates the estimation of impacts on assets. This means that receptors within an asset need to be at a sufficient density to provide statistical estimates of impact (see companion submethodology M10 (as listed in Table 1) for identifying and analysing risk). Furthermore, note that these approaches produce a distribution of receptors beyond the capacity of what can be realistically delivered within the constraints of the uncertainty analysis. The Assessment team will need to work together to decide on the number and location of the subset of receptors that will be nominated as model nodes, with the understanding that impacts at this subset of model nodes will need to be interpolated to receptors at assets.
For surface water assessments, model nodes could be located at the outlet of the river basins (water catchments); here use of the Bureau of Meteorology’s ‘Geofabric’ may be particularly useful in selecting these receptors. The Geofabric is a nationally consistent series of interrelated spatial datasets defining hierarchically-nested river basins, stream segments, hydrological networks and associated cartography (Bureau of Meteorology, 2012). For example, existing Geofabric nodes at the lowest point in each selected river basin can be located, using a digital elevation model (DEM) to generate a network of surface water receptors, densities of which will vary depending on the level of the river basin in the hierarchy. The receptors will cover all flowing and standing water features defined in the landscape class and asset spatial layers (see the worked example in Section 3.3.4). The appropriate river basin level is assessed by ensuring complete and representative coverage of surface water assets. The uncertainty around the nominated flow metrics will be determined by statistical emulators located at these receptors. The Assessment team must then develop appropriate rules to interpolate the hydrological response variables and associated uncertainty to each of the receptors associated with individual assets within the river basins. A key consideration in this decision should be how representative are the outlet nodes of flow regimes within the contributing catchment.
In groundwater assessments receptors for groundwater-dependent landscape classes need to be built into the groundwater model before the model is run. In this situation, receptors could be placed in a systematic grid across the PAE (e.g. at the x,y centroid of the model pixel), at bores within a groundwater management zone or at x,y centroids of GDE polygons, or some combination of the three. Regardless of the approach used to assign groundwater receptors, model emulators will only be built at a subset of these receptors. Again, the Assessment team must develop appropriate rules to interpolate the hydrological response variables and associated uncertainty to each of the receptors associated with individual assets within the groundwater system.
All these approaches will provide an extensive preliminary distribution of receptors (step one for assigning receptors). Subsequently, the preliminary distribution must be tested for gaps, bias and efficiency (see Section 3.3.3) and, if required, refined (step six for assigning receptors). For example, an intersection is required to ensure that all assets are represented. If they are not adequately represented, additional receptors should be added. Decisions around the final density of receptors need to be addressed by the Assessment team. Based on the preliminary results of the modelling (step four for assigning receptors) the numbers and location of receptors may be refined. For example, extra receptors may be required directly downstream and upstream of proposed developments. The point-of-truth distribution of receptors is stored as a spatial (point) dataset in the Bioregional Assessment Repository and documented in the receptor register, which is initially published as an Excel spreadsheet (see Chapter 4); the receptor register can be updated at any time during the Assessment and will be published on the Bioregional Assessment Information Platform. However, the associated product 1.4 (description of the receptor register) will not be updated.
METHODOLOGY FINALISATION DATE
- 1 Background and context
- 2 Defining receptors
- 3 Assigning receptors
- 3.1 Overview of process for assigning receptors
- 3.2 Landscape classification
- 3.3 Process for assigning receptors across the landscape
- 4 Developing a receptor register
- References
- Datasets
- Glossary
- Citation
- Acknowledgements
- Contributors to the Technical Programme
- About this submethodology