*Result*: Research on the Configuration Path of Digital-Intelligent Enabled Urban Rainstorm Situation Awareness in Ternary Space.

*Against the backdrop of rapid urbanization and escalating risks posed by extreme rainstorms, the complexity of urban hydrological systems and limitations of fragmented data-driven approaches underscore the necessity of constructing integrated frameworks to enhance rainstorm situation awareness. Traditional methodologies typically rely on isolated physical monitoring, digital modeling, or social response mechanisms and fail to address the interdependencies among physical infrastructure, informational technologies, and social systems. This study aims to deepen our understanding of how digital and intelligent technologies can be configured across a physical-informational-social ternary space to achieve robust urban rainstorm governance by identifying context-specific empowerment paths and their applicability to diverse urban typologies. Guided by the theoretical framework of the physical-informational-social ternary space, this study employs a mixed-method approach combining fuzzy-set Qualitative Comparative Analysis (fsQCA) and Latent Dirichlet Allocation (LDA) modeling to investigate the pathways through which digital and intelligent tools empower urban rainstorm perception and to explore the disaster-affected characteristics of cities under different configurational paths. By tracking 35 typical Chinese cities, the fsQCA analysis reveals three differentiated empowerment configurations: (1) Balanced ternary space empowerment (G1), which achieves high-efficiency empowerment through three-dimensional collaboration among physical space data integration (including real-time sensor networks for hydrological monitoring), informational space intelligent analysis (including machine-learning-based risk prediction models), and social space emergency response (including interagency coordination systems), relying on dynamic interactions across the three domains. (2) Physically - socially dominant ternary space empowerment (G2): Grounded in core conditions of multisource data integration (combining meteorological, topographical, and citizen-generated data) and high disaster perception efficiency, this configuration incorporates peripheral conditions of server-side intelligence (including cloud-based data analytics) and user-side participation (including mobile application-driven hazard reporting), emphasizing data diversity and user-centric empowerment. (3) Physically - socially interactive binary space empowerment (G3): Empowerment is realized through the binary coupling of multisource data integration and high perception efficiency as the core conditions, prioritizing the technical synergy between physical monitoring and informational processing. Concurrently, a single-dimensional, low-empowerment configuration, which relies on isolated spatial data or technologies, is found to be insufficient for comprehensive disaster perception, thus empirically validating the necessity of ternary space configurational intersections. LDA topic modeling further demonstrates that different digital-intelligent empowerment patterns align with distinct disaster-sensitive city types: G3 suits hazard-sensitive cities (including Guangzhou), G2 matches vulnerable cities (including Xi'an), and G1 benefits exposure-sensitive megacities (including Beijing and Shanghai). Theoretical contributions of this study include constructing a "ternary space for urban rainstorm situation awareness" framework, which systematically analyzes the effects of digital-intelligent empowerment through the coupling mechanism of real-time physical space perception, intelligent informational space processing, and optimized social space decision-making--thereby transcending the limitations of traditional technological determinism. Methodologically, the research overcomes the constraints of single-method approaches by retaining fsQCA's strength in causal necessity analysis and integrating LDA's capability for semantic theme identification, forming a complete explanatory chain of "causal mechanisms-adaptive paths-type characteristics." At a practical level, this study proposes differentiated implementation strategies that provide both theoretical foundations and practical guidance for the digital and intelligent enhancement of urban rainstorm situation awareness. [ABSTRACT FROM AUTHOR]*