Digital twins are transforming the paradigm of water management and water hazard mitigation globally, facilitating more effective governance. However, comprehensive digitalisation at the basin scale still faces major challenges in data, modelling, policy incentives, and, most critically, widespread inequity. This article outlines a framework for building widely applicable digital-twin basins and addressing the main obstacles. Ensuring high-quality water data requires more comprehensive and well-controlled data aggregation and provision protocols. Significant improvements to the existing data infrastructure are necessary to support this effort. Most existing water models are not effectively integrated and do not include multi-physics to reflect all essential correlated physical processes at the basin scale. The current advancement in physics-informed data-driven approaches may provide a solution. Furthermore, global initiatives are critical to reducing major inequity in less developed regions, particularly the Global South, during digitalisation. It is imperative that researchers, practitioners and policymakers take decisive actions to prioritise research and allocate resources to foster transboundary collaborations towards integrated and extensive digital-twin basin systems, promoting the sustainability and resilience of global water resources.
Global water management efforts are increasingly strained by a mounting array of challenges such as flooding, infrastructure failures, water quality degradation, and imbalanced water distribution1. Since the 2020 s, we have witnessed a major escalation of water hazards, marked by key events such as the historical deluge in Germany/Belgium and the deadly inundation of Zhengzhou, China, both in 2021, the Pakistan flash flood in August 2022, a series of record-breaking floods in New Zealand’s North Island in early 2023 and, most recently, the widespread flooding in northeastern China in August 20232,3,4,5. Owing to the changing climate, threats are equally felt by both developed and less-developed nations, and our conventional global strategy for water-hazard mitigation and recovery, especially at the basin level, is being proven inadequate.
Coping with the unprecedented challenge entails a fundamental paradigm shift. As the agenda of the UN’s Sustainable Development Goals (SDGs) becomes imminent, there is a growing consensus that comprehensive digitalisation may be a key solution6. Rapid advancements in data processing and computing power are facilitating the digitalisation of our communities, environment, and indeed, the Earth itself7,8. Among many feasible pathways, digital twinning has been extensively discussed and piloted. The concept of digital twinning, which originated from and has developed primarily in manufacturing sectors, aims to represent a process or a system digitally and incorporate continuous updates using observations of reality9. Digital twins support decision-making by simulating the behaviours of the modelled process or system under various conditions. Users can apply different scenarios to the twin to examine the resulting outcomes. These scenarios can include factors such as system interactions with other systems or human interventions10. In other words, a digital twin, often a cloud software platform with data visualisation, acts as a virtual surrogate of and enables flexible coupling-decoupling with its real-world counterpart8. More importantly, leveraging its embedded physical models and data assimilation algorithms, a digital twin can cope with high-dimensional optimisation problems that are challenging via conventional modelling approaches.
In 2022, China launched the Digital-Twin River Basin campaign, aiming at fully digitalising its basins nationwide by 2030, and 7 major ones, including the Yangtze and Yellow River Basins, will be completed by 2025. The European Union’s Destination Earth project, with the intention to digitalise the entire Earth’s climate, also emphasises its application in managing global floods, droughts and water resources11. Undoubtedly, digital twins are transforming the essential approach by which people manage water at a faster pace than ever.
Efforts required for data unification and basin-level digitalisation are unprecedented. Although countries have been piloting digital twins in water sectors, such as the US FLASH flood forecasting system, Valencia’s city-wide water network, and Singapore’s rainfall monitoring-recasting system12,13, the applications are constrained either in spatiotemporal scales or in specific water subdivisions. People have yet to agree on the overarching architecture, essential functions, and projected industrial standards for digital basins, let alone the requisite upgrades for water infrastructure and technologies. Building consensus is on top of the agenda.
In this article, we detail the architecture and core capabilities of a fully functional digital-twin river basin and identify significant challenges confronting water researchers, practitioners and policymakers on the brink of the digital age – primarily those related to water data, water models, and international collaborative efforts. We also discussed widespread inequity that may arise at the early stage of digitalisation due to the lack of infrastructure and technologies and political causes in less-developed countries, which may exacerbate water mismanagement.
