Chapter 6 – Flood modelling and POLYSCAPE
6.3 POLYSCAPE
POLYSCAPE is a semi-distributed, physically based land management toolbox that was developed to assist users to improve ecosystem services such as carbon sequestration, water quality, habitat connectivity, farm productivity, flood alleviation, and erosion reduction through targeted land management. The impact of land use changes on ecosystem services depends on their position within the landscape. As a rule, land use features should be sited in locations where they have the greatest benefit or highest value. However, changing the landscape to achieve a particular outcome, for example increasing agricultural productivity through conversion of forest to high yielding grassland, can have implications for other ecosystem services such as increased erosion and biodiversity loss. For this reason POLYSCAPE was developed to examine spatially explicit synergies
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and tradeoffs between ecosystem services and help users to decide whether they add, remove, or protect an existing feature in the landscape. Furthermore, local stakeholders often have detailed knowledge and landscape requirements which should be integrated into planning decisions. With this in mind, POLYSCAPE was designed as a negotiation tool, rather than a prescriptive tool, so local stakeholders can trial their own plans and build in their knowledge and landscape restrictions. POLYSCAPE can be applied at a range of scales from the farm scale up to catchments 10,000km in size.
6.3.1 Tool descriptions
POLYSCAPE is a toolbox that operates within ESRI’s ArcGIS versions 9.2 and above. Currently, POLYSCAPE (version 1.1) has 5 tools (algorithms) for investigating the effects of land use change on 1) flood risk; 2) erosion/sediment delivery; 3) habitat connectivity; 4) carbon sequestration; and 5) agricultural productivity. Further tools in development include water quality, amenity, and cultural valuation. In addition there is 6) a synergies and trade-off tool between the five ecosystem services, 7) a pre-processing tool, and 8) an editing tool for stakeholders to make their own adjustments to both input and output. All algorithm calculations and valuations are produced at the resolution of a raster based Digital Elevation Model (DEM). This research utilises the flood mitigation and pre- processing tools only and compares model output between six DEMs of varying resolution (1, 5, 10, 25m). The flood mitigation algorithm is based on recent research results from Carroll et al. (2004), Jackson et al. (2008), Marshall et al. (2009), and Wheater (2005).
POLYSCAPE can identify areas which have high potential for change. For example, when considering flood mitigation one might consider installing a pond or tree buffer strip in areas where large amounts of flow accumulate to reduce runoff. Furthermore, POLYSCAPE identifies areas of high existing value such as highly productive pasture, or wetlands with high biodiversity and flood alleviation benefits, and colours them as worthy for protection. This is achieved through the production of colour-coded “traffic-light” impact maps. The default colour system uses green to show areas where change is considered desirable, amber zones are marginal areas, and red highlights areas of existing high value where there is a high risk associated with any change. Bright red/green suggests high existing value, or opportunity for change respectively, whereas duller red/green indicates still significant, but less pronounced value or opportunity (Jackson et al. 2011). The flood mitigation algorithm works as follows. Features within the landscape that have high storage and/or permeability are assumed to mitigate flooding by acting as “sinks” for overland flow and slower near-surface flow; either storing the water, or slowing it down by routing through sub- surface pathways. How effective these features are for controlling runoff depends on their position
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within the landscape with areas with negligible upland contributing area far less effective than locations with large amounts of low permeability upland contributing area. The flood mitigation layer accordingly characterises features within the landscape by their permeability and storage capacity as defined by soil and land use data (Jackson et al. 2011). Then “using a novel algorithm based on modifying flow accumulation according to permeability/storage, it then discretises units within the landscape according to similarity of their hydraulic properties and spatially explicit topographical routing” (Jackson et al. 2011).
The flood mitigation algorithm can be used in two ways. The simplest ignores temporal effects by removing flow that enters “sink” areas from the flow accumulation data. Jackson et al. (2011) writes that “all land use or soil types that provide this mitigation are treated as of high existing value. Areas where a large amount of unmitigated flow routes directly to waterways are treated as priority areas for change”. The default parameters for defining high accumulation flow thresholds can also be changed to represent the characteristics of a particular catchment. The results from this modeling are contained in section 6.4.
The second way to apply the algorithm is more complex in that it can value land under different rainfall events (e.g. design flood rainfall input, known return period rainfall events) and antecedant soil conditions. It does this by routing water through hydrological response units within the landscape (i.e. cells with defined storage and hydraulic conductivity values) through a cascading ‘fill and spill’ approach. This requires more data (or assumptions) on soil water holding capacity and hydraulic conductivity (Jackson et al. 2011). This research utilises both the ground truthed national soil data and results from field studies. Results can be found in section 6.5.