水灾害现场透彻感知:理论框架、技术路径与关键科技问题

Theoretical framework and technological pathway for thorough perception of water disaster scenarios

  • 摘要: 针对水灾害现场环境极端、态势骤变、信息稀疏、风险链生与空间隐蔽等特征,本文厘清水灾害与水灾害现场的内涵;基于广义全链条认知范式,构建“感-知-融-馈”4层透彻感知理论框架,提出立体化韧性感知、智能融合认知、数字孪生推演、精准协同反馈四大核心技术路径。系统剖析自然驱动型与人为扰动型水灾害现场的底层科学问题,明确2类场景分别以“快”“深”为核心的差异化技术侧重,提炼出极端环境信息获取与传输、物理机理与数据驱动深度融合、复杂系统实时闭环调控三大共性关键科技瓶颈。该框架实现了从数据采集到行动落地的信息价值全转化,为水灾害现场全要素多尺度感知与快速应急响应提供系统性理论支撑。

     

    Abstract: Focusing on the core characteristics of water disaster scenes—extreme environments, rapid situational evolution, information sparsity, cascading risks, and spatial concealment—this study elucidates the essential connotations of water disasters and their on-site environments. Based on a generalized full-chain cognitive paradigm, a four-layer theoretical framework for thorough perception, "sensing-cognition-integration-feedback", is constructed. It involves four core technical pathways: multi-dimensional resilient sensing, intelligent fusion cognition, digital twin simulation, and precise collaborative feedback. The scientific issues underlying water disaster scenarios caused by naturally-driven and human factors are systematically examined. The two types of scenarios are distinguished by their respective technical emphases on "speed" and "depth." Three common key scientific and technological bottlenecks identified are information acquisition and transmission under extreme conditions, deep fusion of physics-based mechanisms with data-driven approaches, and real-time closed-loop regulation of complex systems. This framework achieves a full-cycle value transformation from data collection to operational action, providing systematic theoretical support for full-element, multiscale perception and rapid emergency response in water disaster scenarios.

     

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