The Potential of Knowing More: A Review of Data-Driven Urban Water Management.

The promise of collecting and utilizing large amounts of data has never been greater in the history of urban water management (UWM). This paper reviews several data-driven approaches which play a key role in bringing forward a sea change. It critically investigates whether data-driven UWM offers a promising foundation for addressing current challenges and supporting fundamental changes in UWM. We discuss the examples of better rain-data management, urban pluvial flood-risk management and forecasting, drinking water and sewer network operation and management, integrated design and management, increasing water productivity, wastewater-based epidemiology and on-site water and wastewater treatment. The accumulated evidence from literature points toward a future UWM that offers significant potential benefits thanks to increased collection and utilization of data. The findings show that data-driven UWM allows us to develop and apply novel methods, to optimize the efficiency of the current network-based approach, and to extend functionality of today's systems. However, generic challenges related to data-driven approaches (e.g., data processing, data availability, data quality, data costs) and the specific challenges of data-driven UWM need to be addressed, namely data access and ownership, current engineering practices and the difficulty of assessing the cost benefits of data-driven UWM.

Simulating flexibility, variability and decentralisation with an integrated energy system model for Great Britain.

Energy system models allow the development and assessment of ambitious transition pathways towards a sustainable energy system. However, current models lack adequate spatial and temporal resolution to capture the implications of a shift to decentralised energy supply and storage across multiple local energy vectors to meet spatially variable energy demand. There is also a lack of representation of interactions with the transport sector as well as national and local energy system operation. Here, we bridge these gaps with a high-resolution system-of-systems modelling framework which is applied to Great Britain to simulate differences between the performance of decarbonised energy systems in 2050 through two distinct strategies, an electric strategy and a multi-vector strategy prioritising a mix of fuels, including hydrogen. Within these strategies, we simulated the impacts of decentralised operation of the energy system given the variability of wind and across flexibility options including demand side management, battery storage and vehicle to grid services. Decentralised operation was shown to improve operational flexibility and maximise utilisation of renewables, whose electricity supplies can be cost-effectively converted to hydrogen or stored in batteries to meet peak electricity demands, therefore reducing carbon-intensive generation and the requirement for investment in expanding the electricity transmission network capacity.

The potential of implementing superblocks for multifunctional street use in cities.

The Barcelona superblock has been proposed as a sustainable urban neighbourhood transformation strategy in cities. Superblock design reduces space assigned to cars to enable alternative uses for improving liveability and sustainability. Here, the potential for superblock transformation is systematically quantified and evaluated for cities with varying urban forms and densities. A superblock consists of nine (3×3) urban city blocks including interior and exterior streets. Miniblocks, consisting of four (2×2) blocks, are proposed as a less disruptive strategy to initiate urban transformation on which superblocks can build upon. A geospatial network-based approach is developed to find locations for introducing multifunctional streets. For possible site prioritization, the identified locations are evaluated concerning the potential disruption to traffic. The analysis reveals that the potential for super- and miniblocks, as well as their disruption effect, varies considerably across cities and is affected by the urban layout. For some cities, over 40% of the street network is potentially suitable for integrating super- or miniblock design, providing opportunities for city-scale transition towards more sustainable and liveable cities. A grid-like layout in cities is not a sufficient condition for high superblock potential and cities with irregular street layouts can show high transformation potential as well.

The cost of hybrid waste water systems: A systematic framework for specifying minimum cost-connection rates.

To determine the optimal connection rate (CR) for regional waste water treatment is a challenge that has recently gained the attention of academia and professional circles throughout the world. We contribute to this debate by proposing a framework for a total cost assessment of sanitation infrastructures in a given region for the whole range of possible CRs. The total costs comprise the treatment and transportation costs of centralised and on-site waste water management systems relative to specific CRs. We can then identify optimal CRs that either deliver waste water services at the lowest overall regional cost, or alternatively, CRs that result from households freely choosing whether they want to connect or not. We apply the framework to a Swiss region, derive a typology for regional cost curves and discuss whether and by how much the empirically observed CRs differ from the two optimal ones. Both optimal CRs may be reached by introducing specific regulatory incentive structures.

Economies of density for on-site waste water treatment.

Decentralised wastewater treatment is increasingly gaining interest as a means of responding to sustainability challenges. Cost comparisons are a crucial element of any sustainability assessment. While the cost characteristics of centralised waste water management systems (WMS) have been studied extensively, the economics of decentralised WMS are less understood. A key motivation for studying the costs of decentralised WMS is to compare the cost of centralised and decentralised WMS in order to decide on cost-efficient sanitation solutions. This paper outlines a model designed to assess those costs which depend on the spatial density of decentralised wastewater treatment plants in a region. Density-related costs are mostly linked to operation and maintenance activities which depend on transportation, like sludge removal or the visits of professionals to the plants for control, servicing or repairs. We first specify a modelled cost-density relationship for a region in a geometric two-dimensional space by means of heuristic routing algorithms that consider time and load-capacity restrictions. The generic model is then applied to a Swiss case study for which we specify a broad range of modelling parameters. As a result, we identify a 'hockey-stick'-shaped cost curve that is characterised by strong cost reductions at high density values which level out at around 1 to 1.5 plants per km(2). Variations in the cost curves are mostly due to differences in management approaches (scheduled or unscheduled emptying). In addition to the well-known diseconomies of scale in the case of centralised sanitation, we find a similar generic cost behaviour for decentralised sanitation due to economies of density. Low densities in sparsely populated regions thus result in higher costs for both centralised and decentralised system. Policy implications are that efforts to introduce decentralised options in a region should consider the low-density/high-cost problem when comparing centralised and decentralised options.

To connect or not to connect? Modelling the optimal degree of centralisation for wastewater infrastructures.

The strong reliance of most utility services on centralised network infrastructures is becoming increasingly challenged by new technological advances in decentralised alternatives. However, not enough effort has been made to develop planning tools designed to address the implications of these new opportunities and to determine the optimal degree of centralisation of these infrastructures. We introduce a planning tool for sustainable network infrastructure planning (SNIP), a two-step techno-economic heuristic modelling approach based on shortest path-finding and hierarchical-agglomerative clustering algorithms to determine the optimal degree of centralisation in the field of wastewater management. This SNIP model optimises the distribution of wastewater treatment plants and the sewer network outlay relative to several cost and sewer-design parameters. Moreover, it allows us to construct alternative optimal wastewater system designs taking into account topography, economies of scale as well as the full size range of wastewater treatment plants. We quantify and confirm that the optimal degree of centralisation decreases with increasing terrain complexity and settlement dispersion while showing that the effect of the latter exceeds that of topography. Case study results for a Swiss community indicate that the calculated optimal degree of centralisation is substantially lower than the current level.