Framework and key technologies of"cognitive digital twin basin"
TANG Hailin
FENG Jun
ZHOU Siyuan
Abstract：With the in-depth implementation of the"Digital China"strategy,the digital twin basin has become a critical infrastructure for modern water-resource governance.Significant progress has been made in the data foundation,model platforms,knowledge platforms,and"four pre"functions(forecast,early-warning,rehearsal and plan).However,existing digital twin systems exhibit notable deficiencies in higher-order cognitive capabilities,such as integrating expert knowledge,supporting autonomous learning,and enabling intelligent decision-making.This makes it difficult for them to meet the demands for scenario dynamization,business process automation,and decision-making intelligence.To overcome these challenges,this paper introduces cognitive intelligence and proposes the"cognitive digital twin basin"concept and its framework.Central to this paradigm is the cognitive intelligence layer,constructed upon three fundamental platforms:data,models,and knowledge.This layer is driven by a multi-agent system based on large language models(LLMs),which actively and intelligently coordinates and orchestrates the underlying platforms to deliver advanced cognitive capabilities,including dynamic modeling,intelligent simulation,and optimization-based decision-making.The objective is to transform the static and experience-driven processes within the"2+N"business to an automated and cognition-driven dynamic workflow.In terms of the technical system,the core technical paths are elaborated,including multi-agent collaboration,data and knowledge fusion-driven simulation,online parameter incremental learning,model state assimilation correction,and continuous optimization of expert preferences.Through a case study in the Tunxi River basin of Anhui Province,this paper demonstrates how the framework efficiently conducts flood forecasting and makes decisions,verifying the application value of cognitive intelligence in complex basin management.The paper discusses existing theoretical and engineering challenges and outlines future directions for the intelligent upgrading of data,models,and knowledge platforms.This work provides a theoretical and technical foundation for advancing digital twin basins in China toward higher-order cognitive intelligence.
Keywords：cognitive digital twin basinmulti-agent systemflood forecastingscheduling decision-makingcognitive intelligence layercognitive big modelTunxi River basin
Publication Date：2025-11-30
Online Publishing Date：2025-12-15(First online date of this platform, not the publication date of the document)
Pages：10( 37-46 )