A systematic review of approaches for modelling current and future impacts of extreme rainfall events using green infrastructure

• Published in: Journal of cleaner production Vol. 290; p. 125173
• Main Authors: Reu Junqueira, Juliana, Serrao-Neumann, Silvia, White, Iain
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 25.03.2021
• Subjects: Climate change; Flooding; Land-use planning; LID; Low-impact development; Stormwater management; Urban drainage; Climate change; LID; Stormwater management; Low-impact development; Urban drainage; Flooding; Land-use planning
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2020.125173

A range of modelling approaches has been developed to assess how green infrastructure could mitigate the effects of extreme rainfall events. This paper seeks to develop this agenda by reviewing how these modelling approaches incorporate, consider, and appraise information of value to land-use planning, policy, and practice to better understand why their implementation is infrequent and to help develop a research agenda. Our findings indicate that the information generated by current GI modelling approaches are not well integrated into the demands of land-use planning, and may more reflect the information availability than useability. We find that modelling outputs do not tend to generate the type of high resolution information covering the appropriate spatial and temporal scales that is needed to best support planning decisions. There are also gaps in the assessment of future climate risks, such as increased rainfall intensity, and how this links to future pressures, such as escalating urban growth and development demands, and the interaction between the two areas. The paper concludes that to increase the implementation of green infrastructure, modelling researchers should work more closely with decision-makers to better link data on the effects of GI to the politics involved in their implementation in planning decisions, particularly how trade-offs occur over different scales and times, and between sectors. •GI modelling rarely incorporates future climate change and development pressures.•Models link poorly to planning and reflect data availability more than user’s needs.•GI modelling needs systemic approaches to support land-use planning decisions.•Greater range of spatial and temporal scales should be considered in GI modelling.