Exploration of artificial intelligence large model applications in digital twin water conservancy construction
Shu Quanying
Ma Yuan
Chen Liang
Li Lei
Guo Lei
Wu Jianbai
Abstract：Artificial intelligence(AI)large models can provide new momentum for enhancing the quality and efficiency of digital twin water conservancy construction.Following the approach of"positioning analysis,route exploration,needs assessment,implementation,and model promotion",this study analyzes the challenges in digital twin water conservancy,the development and industry applications of AI large models,and the necessity and feasibility of their application in this field.From the perspectives of technology,business,and management,the study explores the application of AI large models in digital twin water conservancy scenarios.Using the technical path of"scenario digitization,intelligent simulation,and precise decision-making",the study outlines key technologies such as dynamic digital scenario construction,intelligent simulation of complex systems,and precise human-machine collaborative decision-making.Based on a"2+N"business demand framework,the application routes and steps of AI large models are illustrated through specific scenarios,such as the"four pre"(forecasting,warning,rehearsal,and planning)flood control applications and network security protection.The study proposes a co-construction and sharing model for the application of AI large models in digital twin water conservancy,offering a"co-construction and sharing,unified and distributed,collaborative promotion"development approach.The findings provide references for the functional positioning and business scenario implementation of AI large models in digital twin water conservancy construction.
Keywords：digital twin water conservancyartificial intelligencelarge modelsintelligent simulationhuman-machine collaboration
Publication Date：2025-03-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：17( 14-30 )