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/m³ (for a payback period of 30 years).

水资源短缺和干旱是世界许多地区日益严重的问题。在城市供水系统的背景下，向循环过渡可能意味着废水处理和再利用。水回用项目的规划和评估需要决策者评估替代方案的成本和收益。手动或半自动方法仍然是规划饮用水和再生水分配网络的常见做法。这项工作展示了一种决策支持工具，该工具基于开放数据源和图论与贪婪优化算法相结合，能够自动计算给定场景的最佳再生水网络。该工具不仅提供每单位投资成本的最大服务再生水量，还提供所需管道的长度和直径，储罐的位置和大小、服务的人口以及建设成本，即同一架构下的所有内容。该工具的实用性在两个不同但互补的城市中得到了体现，这两个城市在规模、密度和地形方面具有互补性。一个约有 100,000 名居民的城市的最佳水回收网络的建设成本估计在 0.17–0.22 欧元/立方米之间³（投资回收期为 30 年）。