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April 19, 2026Blue-Green Systems0 citationsOpen Access

Editorial: Special issue ‘Digital Water’

MSMilan StojkovicRSRobert SitzenfreiDLDonghoon Lee

Key Points

  • The aim is to explore how digital transformation can address various challenges in the water industry, including climate change and resource scarcity.
  • Overview of digital technologies used in water management, such as IoT and AI/ML algorithms.
  • Discussion on remotely sensed data and its role in monitoring hydrometeorological conditions.
  • Analysis of decision-making processes using automated agents and digital twins.
  • Digital technologies enhance operational efficiency and data-driven decisions within water systems.
  • AI/ML algorithms can predict system states and assess flood risks in diverse environments.
  • Robust digital tools remain essential, but human involvement is crucial to mitigate risks associated with automation.

Abstract

Strategic digital transformation in the water industry offers a comprehensive framework for addressing the mounting pressures of climate change, aging infrastructure, urbanisation, resource scarcity, and public-health risks through systematic digitalisation (Grievson et al. 2022).In this context, digital transformation refers to the fundamental rethinking of processes by integrating digital technologies, both hardware and software, to enhance operational efficiency, data-driven decision-making and service delivery (Giustolisi 2023).Key enablers of this transformation include the Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), advanced sensor technologies, and remotely sensed data, all of which have demonstrated the capacity for effective water resources management (Ansari Vinokicet al. 2025).Furthermore, remotely sensed data acquired through satellites permits the systematic collection of spatially distributed information at large scales, such as river basins, enabling continuous monitoring of dynamic changes in hydrometeorological conditions and land use patterns that directly influence water quantity and quality (Abegeja 2024).In terms of water system operation, AI and automated agents (e.g., digital twins) provide advanced computational support for complex, multi-objective decision-making processes by analyzing high-dimensional datasets and enabling automated operational responses designed to satisfy multiple system functions simultaneously, including flood risk mitigation, river forecasting, water quality management, reservoir operation, hydropower generation, and ecosystem and biodiversity conservation (Kadiyala et al. 2025).These environmental and water-related objectives are intrinsically linked to human well-being and societal resilience (Prodanovic et al. 2024).While digital technologies offer substantial benefits for the operation of water systems, their implementation must be approached with caution.Cross-industry experience highlights the critical importance of maintaining humans in the loop within increasingly automated decision-making processes, ensuring that operators remain actively engaged, well trained, and fully aware of both system capabilities and limitations (Savicet al. 2021).Equally important is the provision of robust and reliable manual override mechanisms that allow effective intervention when digital tools malfunction.As water systems become more interconnected and reliant on cyberphysical infrastructures, addressing cybersecurity threats inherent to digital waters becomes a requirement, particularly given the potential consequences of cyberattacks on essential public services (Tuptuk et al.

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Cite This Study

Stojkovic et al. (2026) studied this question.

synapsesocial.com/papers/69e470a4010ef96374d8d910https://doi.org/10.2166/bgs.2026.015
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