In the digital economy, water big data has emerged as a strategic asset with significant potential to create economic value and enhance sustainable water resources management. However, in Iran, despite the existence of extensive monitoring and data-generation infrastructure, a coherent economic value chain for water data has not yet been established. The current system, which is largely dependent on public funding, lacks financial sustainability and operational efficiency. This study aims to analyze the economic structure of the water data value chain and to design a localized and sustainable revenue model.



Using a mixed qualitative–quantitative approach, the water data value chain was adapted based on Porter’s framework and key financial indicators were estimated. The results indicate strong economic feasibility, with an internal rate of return of 32%, a positive net present value, and an estimated payback period of approximately three years. However, sensitivity analysis shows that the project is highly vulnerable to relatively small declines in revenue, of about 7%.



Stage-based efficiency analysis reveals that data collection is the least efficient stage, while data dissemination and service provision generate the highest value. In addition, willingness-to-pay analysis indicates that around 68% of target users are willing to pay for high-quality water data. Based on an AHP evaluation, value-added services and organizational subscription models are identified as the most suitable revenue strategies, forming the basis for an integrated framework for sustainable water data governance and commercialization.