Water resource asset value accounting faces core challenges such as unclear definition of property rights, inconsistent measurement standards, and insufficient data credibility, which seriously restricts the marketization of water resources allocation efficiency and sustainable utilization process. This paper takes the optimal allocation of economic uses of water resources as the core goal, integrates blockchain and machine learning technology, and constructs a three-layer digital value accounting system composed of “data layer, model layer and report layer”. Blockchain technology is used for water resource property registration, transaction tracing and multi-source data distributed storage. Its decentralization and non-tampering characteristics can ensure the authenticity of ownership information and monitoring data, and smart contracts can realize the automatic execution of accounting records. The machine learning model deeply mines the dynamic mapping relationship between multi-dimensional data such as nature, economy, policy and asset value, and constructs an intelligent measurement model based on ensemble learning algorithm to break through the limitations of traditional static measurement methods. The system design covers the value accounting indicators and accounting subjects under the dimensions of economic value, ecological value and social value, and outputs structured reports to provide support for decision-making, such as water rights trading pricing, ecological compensation standard formulation and water resource tax base assessment. The system significantly improves the transparency, dynamic and scientific nature of value accounting, effectively responds to the traditional accounting problems, promotes the cross innovation of water economics and accounting digitalization, and provides a feasible scheme for the coordinated development of water resources asset fine management and ecological protection.
