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Water demand of urban Portuguese households by population trajectory and region

Bibliographic Data

ID21601662
AuthorsAna Paula Barreira (0000-0001-5816-3361, University of Algarve, corresponding author), Jorge Andraz (0000-0001-9209-3344, University of Algarve)
Year2026
Volume34
Issue1
Pages63-83
Publication date2026-01-02
Open AccessYes
TypeARTICLE
VenueEuropean Planning Studies (JOURNAL)
Journal identifiersISSN: 0965-4313 • E-ISSN: 1469-5944
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/09654313.2025.2574908
OpenAlexW4415438712
LanguageEN
References cited50

Portugal is one of the European countries most vulnerable to water shortages driven by climate change. This study explores the factors influencing household water demand across Portuguese municipalities with urban centres, emphasizing two often-overlooked elements: population trends (growth or decline) and regional location. Another innovation of the study is the inclusion of tourists in the estimation of household water demand. Using panel data for 2011 and 2021, models were developed for four population trajectories and three geographic regions. Results reveal that water consumption drivers vary depending on demographic and regional context. The lowest tariff block (5 m3) has little effect on consumption, while the highest block (15 m3) tends to reduce usage in most models. Municipalities with growing populations in the North tend to consume less water, while growing municipalities in the South – in a touristic region – exhibit higher levels of water consumption. These findings underscore the importance of tailoring water management policies to local demographic and regional characteristics, offering valuable insights for other areas facing similar pressures from climate and population change. Effective policies should combine pricing strategies with initiatives promoting efficient appliances and public education

City region · Population · Portuguese · Trajectory · Urbanization · Water resources management and optimization · Water Systems and Optimization · Water-Energy-Food Nexus Studies

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