Climate emergency and exponential population growth threaten urban water security in cities worldwide. In the UK, London aims to build more than half a million households over the next 10 years to cope with a growing demand for housing. These new urban developments will significantly increase the consumer water demand, urban flood risk, and river water pollution levels; therefore, a sustainable approach to development is urgently required. Urban Water Neutrality (WN) has emerged as a concept to frame these concerns about rising water stresses in cities. We adapt the definition of WN as a design process aimed to first minimise the impact of every new development and then offset any remaining stresses with interventions external to the development, so the current overall impact levels are not increased after the project completion. Despite several studies related to WN, little evidence is available on how urban water neutrality might be achieved to tackle predicted pressures at city scale. In this work, we present a novel urban design and evaluation module called CityPlan. It integrates spatial data with an integrated urban water management model, enabling urban design at systems level and delivering a new index that assesses possible future scenarios. Urban form properties and urban water security indicators are improved with design options that deliver different scores of the Water Neutrality Index (WNI). The results from the WNI indicate the potential of a particular urban design scenario to achieve water neutrality and how multiple interventions should be combined at city scale. In London, CityPlan’s results suggest that it will be necessary to retrofit almost the same number of existing homes with WN design options outside the planned development areas to completely offset the forthcoming water stresses. CityPlan provides a clear vision of how water neutrality can be achieved for urban water systems and is a powerful tool for urban planners and other stakeholders to effectively promote new policies and drive sustainable development. Moreover, it provides a framework to contextualise water neutrality and its key role in urban water security.

Urban-rural nature-based solutions (NBS) have co-benefits for water availability, water quality, and flood management. Searching for optimal integrated urban-rural NBS planning to maximise these co-benefits is important for catchment scale water management. This study develops an integrated urban-rural NBS planning optimisation framework. In this framework, the CatchWat-SD model is developed to simulate a multi-catchment integrated water cycle in the Norfolk region, UK. Three rural (runoff attenuation features, regenerative farming, floodplain) and two urban (urban green space, constructed wastewater wetlands) NBS interventions are integrated into the model at a range of implementation scales. A many-objective optimization problem with seven water management objectives to account for flow, quality and cost indicators is formulated, and the NSGAII algorithm is adopted to search for optimal NBS portfolios. Results show that rural NBS have more significant impacts across the catchment, which increase with the scale of implementation. Integrated urban-rural NBS planning can improve water availability, water quality, and flood management simultaneously, though trade-offs exist between different objectives. Runoff attenuation features and floodplains provide the greatest benefits for water availability. While regenerative farming is most effective for water quality and flood management, though it decreases water availability by up to 15% because it retains more water in the soil. Phosphorus levls are best reduced by expansion of urban green space to decrease loading on combined sewer systems, though this trades off against water availability, flood, nitrogen and suspended solids. The proposed framework enables spatial prioritisation of NBS, which may ultimately guide multi-stakeholder decision-making.

Existing tools for sewer network modelling are accurate but too slow for a range of modern applications such as optimisation or uncertainty analysis. Reduced complexity sewer network models have been developed as a response to this, however, current applications are slow to set up and still require high-fidelity models to be run for calibration. In this study, we compare and develop graph partitioning techniques to automatically group sections of sewer network into semi-distributed compartments. These compartments can then be simulated without calibration in the integrated modelling framework, CityWat-SemiDistributed (CWSD), which has been developed for application to sewer network modelling as part of this study. We find that combining graph partitioning with CWSD can produce accurate simulations 100-1,000x more quickly than existing high-fidelity modelling. We compare a range of graph partitioning techniques to enable users to specify the level of spatial aggregation of the partitioned network, also enabling them to preserve key locations for simulation. We test the impact of temporal resolution, finding that accurate simulations can be produced with timesteps up to one hour. Our experiments show a log-log relationship between temporal/spatial resolution and simulation time, which would enable a user to pre-specify the speed and accuracy needed for their application. We expect that the speed and flexibility of the approach presented in this work may facilitate a variety of novel applications of sewer network models ranging from continuous simulations for long-term planning to spatial optimisation of network design.