中国水利

基于数字孪生理论，从水网系统视角首次构建数字孪生灌区多维度认知体系，为复杂灌区系统数字化转型提供理论支撑。通过解构工程设施链、水资源系统网与管理主体群三维耦合关系，提出灌区水网具有层级复杂性、动态耦合性、功能复合性、区域差异性及业务协同性五大核心特性，并从特征维度、功能维度、协同维度三重维度解析数字孪生灌区内涵。研究突破传统灌区管理范式，以工程安全运行、水量科学调度、控制自动智能、管理协同高效、应急敏捷响应和服务主动便捷等业务目标为导向，构建“数字化场景—智慧化模拟—精准化决策—自动化控制—定量化评估”五阶闭环优化路径，形成以立体感知、墒情预报、动态评价、水量调度、远程控制为技术主线，以调水优化、输水仿真、智能控制、精准配水、高效用水为关键技术的数字孪生灌区智能体框架。该框架实现了灌区水网从“经验驱动”向“数据-机理-知识”驱动的范式转变，为数字孪生技术在复杂灌区系统中的深化应用提供可复制推广的实践范式，对保障国家粮食安全与水资源可持续利用具有重要战略价值。

Based on digital twin theory, a multidimensional cognitive framework for irrigation districts is constructed for the first time from the perspective of the water network system, providing theoretical support for the digital transformation of complex irrigation systems. By deconstructing the three-dimensional coupling relationship among the engineering facility chain, water resource system network, and management entities,five core characteristics of the irrigation water network are proposed: hierarchical complexity, dynamic coupling, functional integration, regional heterogeneity, and operational synergy. The connotation of digital twin irrigation districts is further analyzed from three dimensions: characteristics, functions, and collaboration.This study breaks through the traditional management paradigm of irrigation districts and, oriented toward business objectives such as safe operation of infrastructure, scientific water dispatching, automated and intelligent control, efficient collaborative management, agile emergency response, and proactive and convenient services, establishes a five-stage closed-loop optimization path: “digital scenarios → intelligent simulation →precise decision-making → automated control → quantitative evaluation”. An intelligent agent framework for digital twin irrigation districts is developed, with core technologies including three-dimensional sensing, soil moisture forecasting, dynamic assessment, water volume scheduling, and remote control, and key functions such as water transfer optimization, water conveyance simulation, intelligent control, precise water distribution,and efficient water use. This framework realizes a paradigm shift in irrigation water network management from “experience–driven” to “data–mechanism-knowledge-driven”, offering a replicable and scalable model for the application of digital twin technology in complex irrigation systems. It holds significant strategic value for ensuring national food security and the sustainable utilization of water resources.