Integrated Urban Planning Decision-Making Process Towards Water Neutral Solutions

Urban water security levels will be threatened during the next few years due to new development pressures combined with the climate emergency and increasing population growth in cities. In the UK, London’s planning authorities have a target of more than half a million households for the next 10 years. This new housing will increase the current impacts on urban consumer demand, flood risk, and river water quality indicators. In our previous work, we developed a new concept for urban Water Neutrality (WN) inside an integrated urban planning sustainability framework called CityPlan to deal with water stress and urban complexity issues. This framework integrates the UK’s planning application process with systemic design solutions and evaluation, all being spatially represented in a GIS platform. With the new digital era, there is a constantly increasing number of spatial datasets that are openly available from different sources, but most of them are disaggregated and difficult to understand by key urban stakeholders such as Local Planning Authorities, housing developers, and water companies. Moreover, there are several Multi-Criteria Decision Support Tools (MCDST) that address water management challenges in the literature; but there is still little evidence of one that evaluates the impacts and opportunities to allocate water neutral urban developments.

In this work, we expand the CityPlan framework and present an innovative fully data-driven approach to test WN indicators at different urban scales. WaNetDST integrates GIS spatial data with a series of rules for development impact and offset opportunity based on the current properties of the urban land. This integration is linked to a new scoring system from expert advice that maps strategic areas for water neutral interventions and links the most impactful zones with others more prone to be intervened. The tool connects different urban scales with a series of case study areas: from city (i.e., London), to borough (i.e., Enfield), and to urban development scale (i.e., Meridian Water Development). In the end, WaNetDST visually compares the need for housing vs. green spaces and the trade-offs between new housing vs. retrofitting existing infrastructure, providing a series of maps that guide the planning decision-making process in an integrated way. The results from CityPlan might potentially change the decision-making process for LPAs and housing developers and open a new dialogue between boroughs inside the same city, providing a novel and automated system for WN trade-offs and linking data-driven design with future planning decisions