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Optimal design of water reuse networks in cities through decision support tool development and testing.

Eusebi CalleDavid MartínezGianluigi ButtiglieriLluís CorominasMiquel FarrerasJoan Saló-GrauPere VilàJosep Pueyo-RosJoaquim Comas
Published in: NPJ clean water (2023)
Water scarcity and droughts are an increasing issue in many parts of the world. In the context of urban water systems, the transition to circularity may imply wastewater treatment and reuse. Planning and assessment of water reuse projects require decision-makers evaluating the cost and benefits of alternative scenarios. Manual or semi-automatic approaches are still common practice for planning both drinking and reclaimed water distribution networks. This work illustrates a decision support tool that, based on open data sources and graph theory coupled to greedy optimization algorithms, is able to automatically compute the optimal reclaimed water network for a given scenario. The tool provides not only the maximum amount of served reclaimed water per unit of invested cost, but also the length and diameters of the pipes required, the location and size of storage tanks, the population served, and the construction costs, i.e., everything under the same architecture. The usefulness of the tool is illustrated in two different but complementary cities in terms of size, density, and topography. The construction cost of the optimal water reclaimed network for a city of approximately 100,000 inhabitants is estimated to be in the range of €0.17-0.22/m 3 (for a payback period of 30 years).
Keyphrases
  • wastewater treatment
  • primary care
  • deep learning
  • minimally invasive
  • climate change
  • electronic health record
  • big data
  • convolutional neural network
  • neural network