Managing multiple non-point pressures on water quality and ecological habitat: Spatially targeting effective mitigation actions at the landscape scale.

Abstract:

Catchment systems deliver many benefits to society and ecology but also produce a range of undesirable externalities including flooding, diffuse pollution from agriculture, forestry and urban areas and the export of FIOs. These diffuse pressures are coupled with increasing stream temperature pressures on river from projected climate change. These pressures can be reduced through actions at the landscape scale but are often tackled individually. Any intervention may have benefits for other pressures and hence the challenge is to consider all of the different pressures simultaneously to find solutions with high levels of cross-pressure benefits.

The general approach taken within this research has been to use simple but spatially distributed models to predict the pattern of each of the pressures at the landscape scale. These models follow a minimum information requirement approach along the lines of the SCIMAP modelling approach (www.scimap.org.uk). This approach aims to capture the key features of the processes in relative rather than an absolute sense and hence is good at determining key locations to act within a landscape for maximum benefit. The core of the approach is to define the critical sources areas for each pressure based on the analysis of the pattern of the pressure in the landscape and the connectivity from the sources areas to the rivers and lakes.

To identify the optimal locations with the landscape for mitigation actions, the benefit of a mitigation action at each location in the landscape needs to be considered. However, as one action has been made, it may change the suitability of other locations in the landscape. For example, as tree cover reduces the temperature in one river reach, the impacts of this cooling are transported downstream with the flow. Therefore, actions need to be considered in sets across multiple sites and objectives to identify the optimal actions set.

These modelling results are integrated into a decision support tool which allows the user to explore the implications of considering an individual pressure as opposed to the set of pressures. This is achieved by allowing the user to change the importance of different pressures to identify the optimal locations for a custom combination of pressures. For example, reductions in flood risk can be prioritized over reductions in fine sediment.