E. Koumaki, K. Kandris, G. Milis, et al. « Dynamic Risk Management for Smart Water Systems ». Art. de conf. presented sur 4th International Joint Conference on Water Distribution Systems Analysis and Computing and Control in the Water Industry. 2026.
Water systems are increasingly exposed to complex and interlinked risks driven by climate variability, infrastructure aging, operational disruptions and emerging threats such as cyber and contamination events. Although risk-based management is widely endorsed, practice often remains static, reactive and fragmented across the phases of risk anticipation, preparedness, and adaptive response. This is particularly acute in regions with compounded pressures (e.g., droughts, floods, heat extremes) and institutional complexity [1], [2]. In the future, as climate change accelerates, effectively addressing risks arising from increasingly compound phenomena and cross-sectoral interdependencies will become even more critical [3]. Therefore, handling water-related disruptions and emergencies requires a paradigm shift toward dynamic, data-driven risk management that anticipates and mitigates cascading effects before escalation.
As highlighted in the recent EC Recommendation and EU Directive [4], [5], more accurate and comprehensive risk assessments, accounting for interdependencies among multiple hazards, are urgently needed to improve planning, mitigation and response to high-impact incidents. Although several international policies and frameworks, including Agenda 21, the UN Sendai Framework for Disaster Risk Reduction, the Sustainable Development Goals and the Paris Agreement, promote a multi-risk perspective, standardised methodologies for operationalising this approach remain limited [6].
Operationalisation requires coherent policies, protocols, procedures and technologies to support all phases of risk-informed resilience management, encompassing preparedness, early warning, response and recovery.
The concept of risk-based management, often aligned with the ISO 31000 pecifications, has been progressively embedded in multiple EU directives and regulations that are directly or indirectly linked to water systems. These include,among others, the Drinking Water Directive (EU) 2020/2184, the Water Reuse Regulation (EU) 2020/741, the Urban Wastewater Treatment Directive (recast) 2024/3019, the Water Framework Directive 2000/60/EC and the Bathing Water Directive 2006/7/EC. Although each directive targets distinct water matrices, uses and stakeholders, they all promote a comprehensive, preventive and risk-based framework for safeguarding water quality and public health. This framework emphasizes the need for continuous monitoring, discrete sampling and preventive actions to detect and respond to events that may compromise safety
or compliance. At the same time, water governance operates within a complex regulatory landscape, where environmental, digital and resilience policies intersect. The NIS2 Directive (EU) 2022/2555 on cybersecurity, the Critical Entities Resilience (CER) Directive (EU) 2022/2557, the AI Act (EU) 2024/1689 and the Data Act (EU) 2023/2854 further reinforce the need for risk analysis, data sharing and cross-sectoral resilience. The recent European Water Resilience Strategy (COM(2025) 280 final) also calls for actions geared towards risk management.
Implementation challenges persist at both organizational and systemic levels. Translating legislative requirements into operational practice remains limited, particularly regarding coordination across stakeholders, infrastructures and risk domains.
Building on this regulatory review, a technical gap analysis was conducted to identify persistent barriers that hinder the effective implementation of risk-based management in smart and resilient water systems. The analysis drew upon active EU legislation, recent scientific literature and outcomes from Horizon 2020 and Horizon Europe projects. The findings reveal that current practices, especially in the operations and planning side, remain largely static, fragmented and technologically constrained [7]. Monitoring frameworks rely on infrequent sampling and non-real-time observations, limiting the ability to detect and respond to dynamic events [8]. The insufficient integration of smart technologies, such as low-cost sensors, digital twins and intelligent decision-support systems, further restricts proactive control and situational awareness [9], [10], [11].
Ensuring good data quality is also a recurring challenge, as sensors often operate in harsh environmental conditions and face calibration or maintenance issues, particularly when tasked with detecting emerging threats such as new pollutants or cyber-physical risks [12]. Moreover, interconnected systems (including other water and critical systems), remain poorly coordinated due to limited and fragmented data sharing among relevant actors. The absence of interoperable and standardized mechanisms for exchanging risk-related information, especially during emergencies, hinders early detection, rapid communication and coordinated response [13].
Addressing these gaps calls for a coordinated shift toward standardised, dynamic, data-centric and holistic approaches that can transform policy ambition into tangible resilience outcomes, strengthening the capacity to prevent, rather than merely respond to, emergencies. To this end, this policy brief paper, prepared by the “Intelligent and Smart Systems” Action Group of the ICT4Water Cluster, proposes two key policy directions:
The first policy direction focuses on the development and deployment of digital twins (or replicas) to support risk-based decision-making across natural and engineered water systems. These digital systems are computational tools that integrate real-time monitoring technologies, predictive analytics and early warning systems to enable adaptive risk management plans aligned with EU directives. Achieving this transition depends on the availability of high-quality,
representative and interoperable data, shifting the emphasis from big data to good data. Research and innovation should prioritise the development of smart, resilient sensors capable of maintaining performance in harsh environments and detecting emerging contaminants or system faults. Combining physics-based and data-driven models within these digital replicas will improve predictive capacity and enhance sustainable, evidence-based decision-making.
The second policy direction calls for the creation of integrated digital architectures for water systems data management, anchored in a federated Water Data Space. This data-centric architecture orchestrates interoperability between digital twins, monitoring infrastructures and operational databases, promoting real-time data exchange and seamless integration across heterogeneous platforms. Such an architecture operationalises a system-of-systems approach, strengthening crosssectoral coordination, optimising resource use and fostering public and stakeholder engagement.
In this policy brief paper, we go in depth on these policy directions following an evidence-driven approach based on the research and innovation results of projects within the ICT4Water Cluster. We also provide a roadmap for implementing these directions, and recommendations on the possible outcomes and impacts.
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