Spatial patterns in urban water consumption: The role of local climate zones and temperature dynamics

Mohammad Maleki, Amirbahador Damroodi, Mahsa Mostaghim, Amir Reza Bakhshi Lomer, Samira Sadat Saleh, Junye Wang, Nabi Moradpour, Iain D. Stewart, Kanglin (Connie) Chen, Fatemeh Kazemi

Research output: Contribution to journalJournal Articlepeer-review

2 Citations (Scopus)

Abstract

Urban Water Consumption (UWC) is a major challenge in arid regions, intensified by urbanization, population growth, and resource scarcity, prompting debates on relocating Iran's capital to address resource scarcity and sustainability. This study analyzed the relationship between Local Climate Zones (LCZ), Land Surface Temperature (LST), and water usage in Tehran (2015–2019) to inform urban water management. UWC data was spatially matched to urban areas to calculate per capita consumption. An LCZ map for the base year 2017 was generated using the Random Forest (RF) algorithm, achieving an accuracy of 88.88 %. LST data for the five years was derived using the single-channel algorithm. LCZ2 of dense midrise buildings exhibited the largest area, while LCZG of water had the smallest area. Annual per capita UWC showed a consistent upward trend, with 2019 experiencing the most significant increase. The highest UWC was in LCZG and LCZ2, respectively, while LCZ7 of low dense single buildings recorded the lowest. Most of the city's area had neighbourhoods with an average LST ranging between 30 °C and 35 °C throughout the study period. The correlation between population density, LST, and UWC was 10 % to 17 %. Modelling accuracy, measured by Root Mean Square Error (RMSE), ranged from 1.4 to 9.9. This research highlights the need for climate-sensitive urban design and sustainable water management, providing a foundation for policies to address water scarcity in vulnerable urban areas. Additionally, analyzing annual population dynamics and improving UWC modeling will help better reflect future urban water consumption patterns.

Original languageEnglish
Article number106438
JournalSustainable Cities and Society
Volume127
DOIs
Publication statusPublished - 1 Jun. 2025

Keywords

  • Cities
  • Local climate zones
  • Machine learning
  • Temperature dynamics
  • Urban water consumption

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