UrbanWaterBlocks: A Python Tool for Block-Based Urban Water Management

• Introduces UrbanWaterBlocks, an open-source Python tool for urban water planning. • Generates topologically corrected urban blocks by cleaning street network data. • Integrates global datasets to derive key block-level attributes. • Evaluates LID decentralization potential using a data-reduced approach. • Test in Leipzig with an automated, modular, reproducible, and scalable workflow. Urban areas face increasing risks from climate change, rapid urbanization, and aging urban water infrastructure, necessitating innovative approaches for sustainable urban water management. Decentralized urban water management using Low-Impact Development (LID) offers a promising approach, but effective planning for the urban environment at a comprehensive level is often challenging due to manual workflows, a lack of scalable and reproducible tools, and scattered, inconsistent data sources. To address these challenges, this paper introduces UrbanWaterBlocks, an open-source Python-based approach designed to divide the urban area into scalable units, by automatically generating and analysing urban blocks for decentralized urban water management. The approach integrates three core functionalities: (i) generation of urban blocks for any city from street networks, (ii) calculation of key spatial and demographic attributes for each block, and (iii) assessment of the decentralization potential for implementing LID technologies in those blocks. Applied to two districts of Leipzig, Germany, the approach demonstrates its effectiveness in supporting pre-feasibility assessments, facilitating comparison of LID technology options, and identifying priority areas for intervention. This positions the approach as a practical resource for urban planners, researchers, and decision-makers by supporting block-scale analysis of urban water management potential and facilitating the design of more resilient urban environments. The UrbanWaterBlocks approach is archived and publicly accessible on Zenodo: TEMPORARY ANONYMOUS LINK FOR REVIEW – PERMANENT DOI WILL BE ADDED LATER ONCE ACCEPTED: https: //zenodo. org/records/17396242? preview=1&token=eyJhbGciOiJIUzUxMiJ9. eyJpZCI6ImZiNzg4NzY1LWUzMWYtNDkwOC1hZWRlLWNiZWIwMzdmZjAzYyIsImRhdGEiOnt9LCJyYW5kb20iOiJjNzcyMDFjNTJmYzQ0OWMzOTYwYmEzYjNlNTUxM2QwNSJ9. E6lIsH2Ce3LcCHZFS714IHgz0vUlfmiKPFVArlkYji-dMY1E7bQJBXMI4VkdwnmHyGpVea8v2z4KsFkjKvsVQ.