Bakhatiari, Vahid, Kerchi, Hamed Darabi, Piadeh, Farzad, Behzadian Moghadam, Kourosh ORCID: https://orcid.org/0000-0002-1459-8408 and Nasirzadeh, Farnad (2025) Role of the internet of things in flood risk management: a critical review on current practices and future directions. Natural Hazards. ISSN 0921-030X

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Abstract

The Internet of Things (IoT) has become increasingly important in flood risk management (FRM). This trend emerged as climate change intensified flooding events, driving the urgent need for localised early warning systems. Previous studies demonstrated the effectiveness of IoT sensors in forecasting potential floods and supporting flood modelling. However, comprehensive research addressing all FRM stages - prevention, mitigation, preparedness, response, and recovery - has remained limited. To address this research gap, this study identified five key IoT sensor categories: water quantity, water quality, rainfall intensity, weather conditions, and catchment characteristics. The roles, objectives, and applications of these sensors across FRM stages were then investigated. Results showed that water quantity sensors were the most common, accounting for 48% of documented IoT applications. Weather condition sensors (27%) and rainfall intensity sensors (21%) were also widely used, especially after 2021. Additionally, IoT-based FRM had three primary Objectives flood modelling (61%), alerting (25%), and visualisation (14%). Most cases (42%) focused on the preparedness stage, while prevention (8%) and recovery (5%) were underrepresented, highlighting clear gaps in existing research. The review also revealed several overlooked sensor types, including groundwater level, biochemical oxygen demand, and nitrite sensors. Despite their potential to enhance quality-based flood modelling, these sensors were rarely utilised. Consequently, the study emphasised the need for broader integration of IoT sensors throughout all FRM stages. Such integration could support more resilient, data-driven flood management strategies, particularly in regions where IoT deployment has remained limited.

Item Type:	Article
Identifier:	10.1007/s11069-025-07589-2
Additional Information:	This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11069-025-07589-2
Date Deposited:	08 Oct 2025
URI:	https://repository.uwl.ac.uk/id/eprint/14160

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