Developing technical strategies to make water resources management smarter in Hamedan city

Hadi RezaeiRad ¹ ( Department of Urbanism, Faculty of Art and Architecture, Bu-Ali Sina University, Hamedan, Iran )
Majid Gharib Zahedi ² ( Urban Design student, Department of Urbanism, Faculty of Art and Architecture, Bu-Ali Sina University, Hamedan, Iran )

Submited date : 2025-06-16 Accepted date : 2025-09-14

Keywords: Water Resource Management, Smart City, Climate Change, Smartization strategies,

Abstract :

The growing water crisis caused by climate change, reduced precipitation, groundwater depletion, and unbalanced urban development has exposed the city of Hamedan to serious environmental, social, and economic challenges. In this context, “smartification” has emerged as an innovative strategy in urban water resource management, offering the potential to transform decision-making structures and resource allocation mechanisms.This study aims to develop an integrated conceptual model for implementing smart water resource management within the smart city framework of Hamedan. A mixed-methods approach (qualitative–quantitative) was adopted. In the first stage, key indicators related to smart cities and water resource management were extracted through a systematic review of the literature. These indicators were then refined and validated using the Delphi method, involving domain experts in the water sector. In the next phase, the data were analyzed and categorized using Jenks natural breaks clustering technique.

The final outcome is a conceptual model structured around the interaction between technology, governance, and civic participation. The model incorporates eight integrated indicators: (1) digital water governance, (2) technology-enabled citizen engagement and water literacy, (3) smart monitoring of water quality, (4) real-time quantitative monitoring, (5) integrated data-driven water management, (6) climatic and ecological resilience, (7) spatial adaptation of resources and demands, and (8) water equity and spatial deprivation.

The findings suggest that the proposed model not only enables the identification of critical hotspots, optimization of allocation, and reduction of water losses, but also promotes participatory governance, institutional transparency, and urban resilience in the face of future climate-related crises.

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