TY - JOUR
T1 - Spatial patterns in urban water consumption
T2 - The role of local climate zones and temperature dynamics
AU - Maleki, Mohammad
AU - Damroodi, Amirbahador
AU - Mostaghim, Mahsa
AU - Bakhshi Lomer, Amir Reza
AU - Sadat Saleh, Samira
AU - Wang, Junye
AU - Moradpour, Nabi
AU - Stewart, Iain D.
AU - Chen, Kanglin (Connie)
AU - Kazemi, Fatemeh
N1 - Publisher Copyright:
© 2025
PY - 2025/6/1
Y1 - 2025/6/1
N2 - 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.
AB - 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.
KW - Cities
KW - Local climate zones
KW - Machine learning
KW - Temperature dynamics
KW - Urban water consumption
UR - https://www.scopus.com/pages/publications/105005267012
U2 - 10.1016/j.scs.2025.106438
DO - 10.1016/j.scs.2025.106438
M3 - Journal Article
AN - SCOPUS:105005267012
SN - 2210-6707
VL - 127
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 106438
ER -