Rapid expert tool for different professions based on estimated ecosystem variables for retrofitting of drainage systems

• Traditional ‘community and environment’ variables do favour infiltration trenches, soakaways and belowground storage.
• Generic ecosystem service categories and variables suitable for sustainable drainage systems were defined and quantified.
• For the urban example case study, the overall ecosystem service scores were relatively low regardless of professional bias.
• The novel ecosystem service variables promote permeable pavement systems regardless of the professional perspective.
• Variable estimation errors are relatively low even for a virtually untrained example cohort of engineering students.

There is a need for a geospatial decision support tool for different professions such as drainage engineers and urban planners, which is useful for a quick assessment of the potential of ecosystem services when retrofitting sustainable drainage systems (SuDS) in urban areas. Therefore, the aim of this paper is to develop an innovative rapid decision support tool based on ecosystem service variables for retrofitting of key SuDS techniques by different professionals such as drainage engineers, developers, ecologists, planners and social scientists. This unique and transparent spreadsheet-based tool proposes the retrofitting of a SuDS technique that obtained the highest ecosystem service score for an urban site. This approach is based on a novel ecosystem service philosophy adapted to SuDS rather than on traditional engineering judgement associated with variables based on quick community and environment assessments. For the Greater Manchester example case study area, a comparison with the traditional approach of determining community and environment variables indicates that infiltration trenches, soakaways and belowground storage systems are usually less preferred than permeable pavement systems regardless of the professional perspective. However, ponds also received relatively high scores, because of their great potential impact in terms of water quality improvement and flood control. The estimation of variables was undertaken with high confidence and manageable error.

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