<p>Disaster Risk Reduction (DRR) is increasingly determined by the quality of measurements, standards, institutional competence, and verification mechanisms that govern complex socio-technical systems. In infrastructure-intensive and hazard-prone economies, disaster risk is not merely an external contingency but a cumulative outcome of how physical, industrial, and digital systems are measured, regulated, and operated across their lifecycle. This article advances a measurement-based governance framework for DRR by extending the Aswal Model of National Quality Infrastructure and integrating metrology, standardization, accreditation, and conformity assessment into the disaster risk reduction cycle. The framework places continuous, traceable, and uncertainty-aware risk assessment—covering hazard, exposure, vulnerability, and capacity—at the core of governance, while interpreting preparedness, mitigation, response, and recovery as parameter-driven and auditable functions. A traceable measurement-to-governance chain is introduced to demonstrate how calibrated observations and validated models, supported by uncertainty characterisation and standards-based traceability, translate into decision thresholds, regulatory instruments, and operational actions, with audit and feedback enabling continuous improvement. The paper further shows how national disaster-risk policy, including the Prime Minister’s 10-Point Agenda on Disaster Risk Reduction, can be operationalised through existing quality-infrastructure mechanisms without institutional duplication. By embedding DRR within national quality infrastructure systems, the framework strengthens regulatory coherence, institutional reliability, auditability, and adaptive learning, highlighting the expanding role of measurement science as a foundational instrument of credible and resilient risk governance.</p>