Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1016/j.scs.2026.107244
Licence creative commons licence
Title (Primary) UrbanWaterBlocks: A python tool for block-based urban water management
Author Dev Roy, S.; Despot, D. ORCID logo ; Lippera, M.C.; Khurelbaatar, G. ORCID logo ; Friesen, J. ORCID logo
Source Titel Sustainable Cities and Society
Year 2026
Department SUBT
Volume 140
Page From art. 107244
Language englisch
Topic T7 Bioeconomy
Data and Software links https://doi.org/10.5281/zenodo.17396242
Keywords Low-Impact Development; Blue-Green Infrastructure; Decentralized Urban Water Management; Urban Block; Decentralization Potential
Abstract 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.
Dev Roy, S., Despot, D., Lippera, M.C., Khurelbaatar, G., Friesen, J. (2026):
UrbanWaterBlocks: A python tool for block-based urban water management
Sust. Cities Soc. 140 , art. 107244 10.1016/j.scs.2026.107244