Urban digital twins and water sensitive urban design: A systematic literature review
Year: 2026
Type: review
Study design: Systematic Review
Abstract: Urban water systems face increasing pressures from urbanization, climate change, and infrastructure complexity. Water Sensitive Urban Design (WSUD) provides an integrated framework for sustainable urban water management; however, its implementation requires tools capable of integrating monitoring, modeling, and decision-support processes across complex urban systems. Urban Digital Twins (UDTs) have recently emerged as promising platforms that can support such integration by linking physical infrastructure with digital models through real-time data integration and simulation. This study presents a systematic literature review examining how digital twin technologies support WSUD in urban water management. Following the PRISMA methodology, 170 publications from the Scopus and ScienceDirect databases (2014–2024) were screened, resulting in 48 studies for detailed analysis. The results show that digital twins are primarily applied in hydraulic modeling, infrastructure monitoring, leak detection, and flood forecasting. However, most studies remain at conceptual or prototype stages, with relatively few pilot or operational implementations. Major challenges include data interoperability, integration of heterogeneous datasets, and governance issues related to stakeholder participation. By synthesizing existing applications and technological capabilities, this review identifies key socio-technical requirements for integrating digital twins into water-sensitive urban planning and proposes a conceptual DT–WSUD integration framework. The study also highlights critical research gaps related to operational deployment, participatory governance, and performance evaluation of digital twin–supported WSUD systems.
Source: Sustainable Cities and Society
Authors: Gamze Altındaş, Gamze Dane, Alper Baba
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,870
OpenAlex ID: W7160036022
