A Spatiotemporal Dataset of Urban Water Distribution Schedules

Yanira Rivera 

Urban water supply in several rapidly growing cities in Latin America is managed through intermittent distribution schedules rather than continuous service, often in response to drought or water scarcity conditions. However, these practices are unevenly documented, and publicly available information is largely limited to cities where water authorities disclose distribution schedules. As a result, structured datasets suitable for systematic analysis remain scarce.

This study presents a reconstructed spatiotemporal dataset of municipal water distribution calendars for Tegucigalpa, Honduras. Historical schedules published by the municipal water authority (UMAPS) were systematically collected and transformed into a standardized dataset, capturing scheduled water availability across neighborhoods from 2016 to 2025. The reconstruction process involved extracting schedule information from heterogeneous source formats, harmonizing neighborhood identifiers, and linking distribution units to a consistent spatial neighborhood framework.

The resulting dataset provides quantitative indicators of scheduled water availability, including hours and days of supply per neighborhood and month. The full processing workflow, along with the open-source code used for data extraction, standardization, and aggregation, is publicly released to ensure transparency and reproducibility.