Research on a cloud model intelligent computing platform for water resource management

As the demand for water management information systems continues to increase, addressing issues such as poor generalizability, low reusability, and difficulties in updating and maintaining water resource planning cloud model service platforms becomes crucial. To achieve goals like business-oriented functionality, high availability, and reliability, this study proposes constructing a cloud model service platform for basin water resource planning based on cloud computing technology and business workflows. This study couples water cycle models with multi-objective optimization models for water resource allocation, using digital topological water networks to achieve dynamic regional water resource allocation. The cloud service platform adopts a business-oriented modeling method based on B/S development architecture. This paper takes the Weihe River Basin as an example to simulate and analyze the evolution of the water cycle pattern and optimize the annual water resources allocation plan. Results show that: (1) the water cycle model of the cloud model service platform can better describe the runoff change process in the verification period; (2) through the cloud platform service model, the water shortage rate of the Weihe River Basin in 2025 is 7.95%. The research findings provide technical references and insights for intelligent water management and refined allocation of water resources in the Weihe River Basin. HIGHLIGHTS center dot A topological digital water network is introduced and implemented. center dot Bidirectionally coupled the hydrological cycle model with the water resource allocation model. center dot The water resource cloud model platform was constructed based on B/S architecture. center dot Integration of traditional water conservancy and watershed elements.