Smart dams and digital twins: managing risk and modernisation in hydropower

The hydropower industry is entering a new phase of digitisation. As assets age and operational pressures increase, owners and operators are moving toward “smart dams” systems that merge conventional civil engineering with advanced data and control technologies. The Dentons paper sets out how these systems are reshaping risk allocation, project delivery, and governance across the sector.

Digital integration in practice

Smart dams go well beyond remote monitoring. They combine real-time sensing, automation, and AI-driven analytics to optimise reservoir management, turbine operation, and structural performance. Digital twins extend this further by enabling predictive maintenance, simulation of extreme events, and early testing of design modifications.

For operators, the value lies in operational efficiency, early fault detection, and better forecasting of hydrological variability. For developers and lenders, the focus is increasingly on data integrity, system reliability, and how these digital tools alter contractual and regulatory exposure.

Lessons from recent projects

Several case studies in the Dentons analysis show how these technologies are being adopted:

• Dinorwig Power Station, Wales: Integration of digital monitoring into a legacy pumped-storage facility improved turbine performance and grid responsiveness, but also exposed challenges around interoperability, data ownership, and liability when predictive models diverge from real-world results.
• Warragamba Dam, Australia: AI-driven flood models and sensor arrays cut inspection requirements but revealed gaps in privacy and data retention laws.
• Punt dal Gall Dam, Switzerland–Italy: A cross-border digital twin project strengthened seismic resilience but underscored the need for aligned data governance between jurisdictions.
• Changjiang Basin, China: Centralised control of 31 dams demonstrated basin-wide optimisation benefits, but also highlighted systemic cyber-risk if defences fail.

Together, these projects underline that digital optimisation introduces as many governance and legal questions as it solves engineering problems.

Contractual and regulatory implications

Dentons’ analysis emphasises that digital risk must be treated as a core contractual component, not an afterthought. Critical points include:

• Data rights and accountability: Contracts should define ownership, access, and quality standards for operational data, including who may rely on it for regulatory or financial reporting.
• Software lifecycle management: Licensing, update obligations, and escrow provisions must cover cybersecurity maintenance and vendor insolvency.
• Cybersecurity allocation: Each party’s responsibilities for protection, monitoring, and breach response need to be clear, with insurance and liability aligned to those duties.
• Change control: Digital systems evolve quickly—agreements must provide structured procedures for upgrades without causing cost or schedule disputes.
• Competence and transfer: Modernised assets demand new digital skills; training, documentation, and secure data handover should be contractual deliverables.

The legal treatment of automated decision-making is also emerging as a frontier issue. In jurisdictions such as the UK, existing reservoir safety legislation predates automation, raising questions about whether digital evidence or AI-generated alerts satisfy statutory inspection duties.

Cyber and financial risk

Centralised, sensor-rich systems increase exposure to cyber incidents that could interrupt power generation or compromise public safety. Yet most national frameworks still lack minimum cybersecurity standards for water or energy infrastructure. Contractual remedies—segregated system architectures, role-based access control, red-team testing, and defined remediation procedures – remain the current best practice.

Digitisation also raises financial considerations. Smart upgrades and digital-twin implementation require significant capital investment, often beyond traditional O&M budgets. Dentons notes that new funding models – public-private partnerships, blended finance, and climate-linked instruments – are emerging to close this gap and prevent a widening digital divide between well-funded utilities and smaller regional operators.

The path forward

The outlook for the sector is clear: international standards on data exchange, interoperability, and digital-twin use will soon shape cross-border hydropower collaboration. AI-driven predictive management is expected to become the norm, accompanied by “zero-trust” cybersecurity architectures and greater transparency requirements from regulators.

For project sponsors, lenders, and operators, the message from Dentons’ research is pragmatic rather than theoretical: smart dams represent an operational advance, but also a legal and contractual transformation. Managing data, cyber, and automation risk is now central to long-term asset performance and regulatory compliance.

As the hydropower sector accelerates toward digitally enabled operations, success will depend not only on engineering and software, but on governance frameworks that evolve at the same pace.